In addition, the Virtual Fabricator, similar to that in the desktop-based system, is created with the Virtools Dev for digital fabrication of multi-material prototypes, as in Figure 11. When the fabrication completes, designers can fully immerse in the CAVE virtual environment for stereoscopic visualisation and quality analysis of the resulting multimaterial virtual prototype. This full-immersive environment blocks out most disturbances and hence enhances the efficiency of the design review and improvement process.

It can be seen that the PC cluster-based CAVE system above is relatively convenient and flexible, making full-immersive VR a versatile and affordable tool for small-and-medium sized companies to develop products.

Virtual Prototyping for Rapid Product Development 217

Front View Side View

Top View Isometric View

Fig. 12. A colour STL model of an infrared thermometer casing

Fig. 13. Digital fabrication of the thermometer casing

Fig. 11. Digital fabrication of a multi-material toy assembly in a CAVE VR environment

### **4. Case studies**

### **4.1 A thermometer casing**

Figure 12 shows an infrared thermometer commonly fabricated by a manufacturer in Hong Kong. Such products have become very popular as a result of heightened awareness of personal hygiene due to recent outbreaks of infectious diseases. The thermometer is assembled with several components of different materials. Using the MMVP system, multitoolpaths can be efficiently planned to fabricate a digital prototype of the thermometer casing. Subsequently, the prototype quality can be evaluated by stereoscopic visualisation and superimposition of the prototype on its STL model.

Figure 13 shows the complete multi-material digital prototype, while Figure 14a superimposes it on the STL model for visual analysis. It can be seen that there are excessive materials on the prototype. The overall accuracy of the prototype was evaluated by calculating the average and maximum cusp heights, which are 0.027mm and 0.060mm, respectively. In Figure 14b, green pins and red pins are used to highlight unacceptable deviations exceeding 0.055mm and the maximum deviations, respectively. Therefore, using the MMVP system, the MMLM process may be conveniently iterated with new sets of process parameters without incurring much extra cost. Hence, an optimal combination of process parameters can be obtained for subsequent fabrication of physical prototypes of satisfactory quality.

Fig. 11. Digital fabrication of a multi-material toy assembly in a CAVE VR environment

Figure 12 shows an infrared thermometer commonly fabricated by a manufacturer in Hong Kong. Such products have become very popular as a result of heightened awareness of personal hygiene due to recent outbreaks of infectious diseases. The thermometer is assembled with several components of different materials. Using the MMVP system, multitoolpaths can be efficiently planned to fabricate a digital prototype of the thermometer casing. Subsequently, the prototype quality can be evaluated by stereoscopic visualisation

Figure 13 shows the complete multi-material digital prototype, while Figure 14a superimposes it on the STL model for visual analysis. It can be seen that there are excessive materials on the prototype. The overall accuracy of the prototype was evaluated by calculating the average and maximum cusp heights, which are 0.027mm and 0.060mm, respectively. In Figure 14b, green pins and red pins are used to highlight unacceptable deviations exceeding 0.055mm and the maximum deviations, respectively. Therefore, using the MMVP system, the MMLM process may be conveniently iterated with new sets of process parameters without incurring much extra cost. Hence, an optimal combination of process parameters can be obtained for subsequent fabrication of physical prototypes of

**4. Case studies**

satisfactory quality.

**4.1 A thermometer casing**

and superimposition of the prototype on its STL model.

Top View Isometric View

Fig. 13. Digital fabrication of the thermometer casing

Virtual Prototyping for Rapid Product Development 219

digital multi-material prototypes to help improve designs and shorten development cycles of jewellery products at competitive costs. Designers can view and evaluate their designs with digital prototypes instead of physical ones, at minimal costs and time possible. Furthermore, digital prototypes may be conveniently transmitted over the Internet to

Figure 15 shows an example of a fashion necklace, and the MMVP system is used to produce digital prototypes of such products. Figure 16 shows the digital fabrication process and the complete multi-material digital prototype, which can be stereoscopically visualised for quality analysis, as in Figure 17a. The necklace prototype can also be superimposed on its STL model to highlight the excessive materials, as shown in Figures 17b and 17c. The average and maximum cusp heights of the prototype, which are 0.260mm and 0.554mm, respectively, are calculated for evaluation of the overall accuracy of the prototype. In Figure

Isometric view

Front view Side view

facilitate global manufacturing.

Fig. 15. A multi-material necklace

Top view

Fig. 14a. Digital multi-material thermometer casing and superimposition on its STL model

Fig. 14b. Areas of the thermometer casing with dimensional deviation beyond design limits

### **4.2 A jewellery product – a necklace**

Hong Kong is a leading exporter of jewellery products. As such products get more fashionoriented, innovative designs become more important. Local jewellery manufacturers have realised that they should not only rely on the skills of individual craftsmen. Some have recently adopted LM technology to develop high value-added jewellery items. Hence, the proposed multi-material virtual prototyping system will be particularly useful for building

Excessive materials

Fig. 14a. Digital multi-material thermometer casing and superimposition on its STL model

deviations

Green pins showing unacceptable

Fig. 14b. Areas of the thermometer casing with dimensional deviation beyond design limits

Hong Kong is a leading exporter of jewellery products. As such products get more fashionoriented, innovative designs become more important. Local jewellery manufacturers have realised that they should not only rely on the skills of individual craftsmen. Some have recently adopted LM technology to develop high value-added jewellery items. Hence, the proposed multi-material virtual prototyping system will be particularly useful for building

**4.2 A jewellery product – a necklace**

deviations

Red pins showing maximum

digital multi-material prototypes to help improve designs and shorten development cycles of jewellery products at competitive costs. Designers can view and evaluate their designs with digital prototypes instead of physical ones, at minimal costs and time possible. Furthermore, digital prototypes may be conveniently transmitted over the Internet to facilitate global manufacturing.

### Fig. 15. A multi-material necklace

Figure 15 shows an example of a fashion necklace, and the MMVP system is used to produce digital prototypes of such products. Figure 16 shows the digital fabrication process and the complete multi-material digital prototype, which can be stereoscopically visualised for quality analysis, as in Figure 17a. The necklace prototype can also be superimposed on its STL model to highlight the excessive materials, as shown in Figures 17b and 17c. The average and maximum cusp heights of the prototype, which are 0.260mm and 0.554mm, respectively, are calculated for evaluation of the overall accuracy of the prototype. In Figure

Virtual Prototyping for Rapid Product Development 221

Fig. 17a. Stereoscopic view for visualisation of the necklace prototype

Excessive materials

Stereoscopic view

Fig. 17b. Superimposition of the necklace prototype and on its STL model

17c, green pins and red pins are used to highlight unacceptable deviations exceeding 0.550mm and the maximum deviations, respectively. Therefore, using the MMVP system, the designers can conveniently perform quality analysis and iterate the MMLM processes. Thus, an optimal combination of process parameters such as, the build direction, layer thickness, and hatch space can be obtained for subsequent fabrication of physical prototypes.

Fig. 16. Digital fabrication process of a multi-material prototype of the necklace

17c, green pins and red pins are used to highlight unacceptable deviations exceeding 0.550mm and the maximum deviations, respectively. Therefore, using the MMVP system, the designers can conveniently perform quality analysis and iterate the MMLM processes. Thus, an optimal combination of process parameters such as, the build direction, layer thickness, and hatch space can be obtained for subsequent fabrication of physical

Fig. 16. Digital fabrication process of a multi-material prototype of the necklace

the necklace

A complete multi-material virtual prototype of

prototypes.

Fig. 17a. Stereoscopic view for visualisation of the necklace prototype

Fig. 17b. Superimposition of the necklace prototype and on its STL model

Virtual Prototyping for Rapid Product Development 223

Choi, S.H. & Chan, A.M.M. (2002). A dexel-based virtual prototyping system for product

Choi, S.H. & Cheung, H.H. (2005a). A multi-material virtual prototyping system. *Computer-*

Choi, S.H. & Cheung, H.H. (2005b). A multi-material virtual prototyping system for product

Choi, S.H. & Cheung, H.H. (2006). A topological hierarchy-based approach to toolpath

Choi, S.H. & Cheung, H.H. (2007). Multi-material virtual prototyping for product development and biomedical. *Computers In Industry*, Vol.58, No.5, 438-452. Choi, S.H. & Kwok, K.T. (2002). A tolerant slicing algorithm for layered manufacturing.

Choi, S.H. & Kwok, K.T. (2004). A topological hierarchy-sorting algorithm for layered

Choi, S.H. & Samavedam, S. (2001). Visualisation of rapid prototyping. *Rapid Prototyping*

Choi, S.H. & Samavedam, S. (2003). Modelling and optimisation of rapid prototyping.

Gomes de Sá, A. & Zachmann, G. (1999). Virtual reality as a tool for verification of assembly and maintenance processes. *Computers & Graphics*, Vol.23, No.3, 389-403. Kerttula, M. & Tokkonen, T. (2001). Virtual design of multiengineering electronics systems.

Kim, H.T., Lee, J.K., Park, J.H., Park, B.J. & Jang, D.S. (2002). Applying digital manufacturing

Lopez, S.M. & Wright, P.K. (2002). The role of rapid prototyping in the product

Mujber, T.S., Szecsi, T. & Hashmi, M.S.J. (2004). Virtual reality applications in

Object, (2011b). http://www.objetblog.com/2011/05/23/objet-to-demonstrate-unique-

Patel, H., Sharples, S., Letourneur, S., Johansson, E., Hoffmann, H., Lorisson, L., Saluaar, D.

technology to ship production and the maritime environment. *Integrated*

development process: a case study on the ergonomic factors of handheld video

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manufacturing. *Rapid Prototyping Journal*, Vol.10, No.2, 98-113.

development. *Rapid Prototyping Journal*, Vol.8, No.5, 300-314.

October, 1998. p. 250-1253.

Vol.2, No.1-4, 329-338.

*Journal*, Vol.7, No.2, 99–114.

No.2, 143-156.

156:1834-1838.

No.3, 267-279.

*Aided Design*, Vol.37, No.1, 123-136.

*Rapid Prototyping Journal*, Vol.8, No.3, 161-179.

*Computers in Industry*, Vol.47, No.1, 39-53.

*IEEE Computer*, Vol.34, No.11, 71-79.

*Manufacturing Systems*, 13(5):295-305.

games. *Rapid Prototyping Journal*, Vol.8, No.2, 116-125.

Object, (2011a). http://www.objet.com/3D-Printer/Objet\_connex500/.

multi-material-3d-printing-applications-at-rapid/.

and Cybernetics, Hyatt Regency La Jolla, San Diego, California, USA, 11-14

development and biomedical engineering. *Computer-Aided Design and Applications*,

planning for multi-material layered manufacturing. *Computer-Aided Design*, Vol.38,

Red pins showing maximum deviations

Green pins showing unacceptable deviations

Fig. 17c. Areas of necklace prototype with dimensional deviations beyond design limits

### **5. Conclusion**

This chapter proposes a VP system which integrates the good features of semi- and fullimmersive VR to enhance the versatility and effectiveness of virtual simulation for product design and digital fabrication of multi-material prototypes at affordable cost.

The VP system comprises mainly a suite of software packages for simulation of MMLM processes, including multi-toolpath planning, build-time estimation, and accuracy analysis. It can drive a desktop-based VR system with either a monitor or a large non-depolarising screen to generate a semi-immersive VR environment, which is cost-effective, portable, and easy to operate, for review and improvement of product designs. To minimise disturbances and to enhance the level of immersion, the VP system can control a PC cluster-based CAVE system to create a full-immersive VR environment that enhances collaboration and communication of a design team working on product development. It is indeed an effective and versatile tool for rapid product development to meet ever-increasing diversities of customer demands, stringent cost control, and complexity of new products.

### **6. Acknowledgements**

The authors would like to acknowledge the Research Grant Council of the Hong Kong SAR Government and the CRCG of the University of Hong Kong for their financial support for this project.

### **7. References**

Bochenek, G.M. & Ragusa, J.M. (1998). Study results: the use of virtual environments for product design. In: Proceedings of IEEE International Conference on Systems, Man,

Red pins showing maximum deviations

Fig. 17c. Areas of necklace prototype with dimensional deviations beyond design limits

design and digital fabrication of multi-material prototypes at affordable cost.

Green pins showing unacceptable deviations

customer demands, stringent cost control, and complexity of new products.

This chapter proposes a VP system which integrates the good features of semi- and fullimmersive VR to enhance the versatility and effectiveness of virtual simulation for product

The VP system comprises mainly a suite of software packages for simulation of MMLM processes, including multi-toolpath planning, build-time estimation, and accuracy analysis. It can drive a desktop-based VR system with either a monitor or a large non-depolarising screen to generate a semi-immersive VR environment, which is cost-effective, portable, and easy to operate, for review and improvement of product designs. To minimise disturbances and to enhance the level of immersion, the VP system can control a PC cluster-based CAVE system to create a full-immersive VR environment that enhances collaboration and communication of a design team working on product development. It is indeed an effective and versatile tool for rapid product development to meet ever-increasing diversities of

The authors would like to acknowledge the Research Grant Council of the Hong Kong SAR Government and the CRCG of the University of Hong Kong for their financial support for

Bochenek, G.M. & Ragusa, J.M. (1998). Study results: the use of virtual environments for

product design. In: Proceedings of IEEE International Conference on Systems, Man,

**5. Conclusion**

**6. Acknowledgements**

this project.

**7. References**

and Cybernetics, Hyatt Regency La Jolla, San Diego, California, USA, 11-14 October, 1998. p. 250-1253.

**10**

**Oriented Multi-Body System Virtual Prototyping**

*Institute of Advanced Design & Manufacturing, School of Mechanical Engineering,*

In recent years, knowledge-based new product competition has become the mainstream of manufacturing competitiveness. As an important way to simulate various problems of complex mechanical systems, virtual prototyping technology is being widely used. It supports concurrent engineering and emphasizes the overall product performance, and strives to simulate the product function and behavior. Based on considering the overall product performance in three-dimensional CAD and its following function modules, virtual prototyping does the innovative design and informs a digital prototyping which do not

Virtual Prototyping (VP) is a new product design method generated in the recent 20 years. Based on computer simulation, VP embodies not only the product's innovative design but also the product's risk-free digital test, especially suiting for high cost trial production of complex mechanical system development. The main elements of VP are: virtual prototype model - virtual test analysis - virtual prototype evaluation (qualitative and quantitative). VP embodies the global optimization process which is based on computer simulation and aims to get more realistic products. It supports "Top-to-Down" design approach. The main techniques of VP ---- CAX, multi-body system modeling and analysis, simulation, optimization, visualization and VR technology are used to get a digital prototype with optimized performance, thereby the development costs and the reliance on physical prototypes are reduced, product qualities are improved, and time-to-market is accelerated. Railway vehicle system which belongs to complex mechanical system areas is composed of mechanical, electrical, active control and drive systems (power distributed EMU), and its main part is mechanical systems. The quality of vehicle performances is the key problem of the vehicle product development. Based on the railway vehicle product design, especially the design results of the whole product machine, the performances include: dynamic performance, operational safety, aerodynamics, air-condition, strength and fatigue reliability. Therefore, it is inevitable to research and develop the railway vehicle virtual

It is also inevitable to research the railway vehicle virtual prototyping technique for the railway transportation equipment, especially for the high-speed, heavy haul train. The past

**1. Introduction**

**1.1 Railway vehicle virtual prototyping**

depends on the physical prototype.

prototyping for advanced manufacturing technology.

railway vehicle product development mainly takes the following forms:

**Technology for Railway Vehicle**

*Southwest Jiaotong University, People's Republic of China*

Guofu Ding, Yisheng Zou, Kaiyin Yan and Meiwei Jia

### **Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle**

Guofu Ding, Yisheng Zou, Kaiyin Yan and Meiwei Jia *Institute of Advanced Design & Manufacturing, School of Mechanical Engineering, Southwest Jiaotong University, People's Republic of China*

### **1. Introduction**

224 Modeling and Simulation in Engineering

Tennyson, S., McCain, G., Hatten, S. & Eggert, R. (2006). Case study: promoting design

Weyrich, M. & Drews, P. (1999). An interactive environment for virtual manufacturing: the

Wöhlke, G. & Schiller, E. (2005). Digital planning validation in automotive industry.

virtual workbench. *Computers in Industry*, Vol.38, No.1, 5-15.

*Computers in Industry*, Vol.56, No.4, 393-405.

309.

Virtools, (2006). http://www.virtools.com.

automation by rural manufacturers. *Rapid Prototyping Journal*, Vol.12, No.5, 304-

### **1.1 Railway vehicle virtual prototyping**

In recent years, knowledge-based new product competition has become the mainstream of manufacturing competitiveness. As an important way to simulate various problems of complex mechanical systems, virtual prototyping technology is being widely used. It supports concurrent engineering and emphasizes the overall product performance, and strives to simulate the product function and behavior. Based on considering the overall product performance in three-dimensional CAD and its following function modules, virtual prototyping does the innovative design and informs a digital prototyping which do not depends on the physical prototype.

Virtual Prototyping (VP) is a new product design method generated in the recent 20 years. Based on computer simulation, VP embodies not only the product's innovative design but also the product's risk-free digital test, especially suiting for high cost trial production of complex mechanical system development. The main elements of VP are: virtual prototype model - virtual test analysis - virtual prototype evaluation (qualitative and quantitative). VP embodies the global optimization process which is based on computer simulation and aims to get more realistic products. It supports "Top-to-Down" design approach. The main techniques of VP ---- CAX, multi-body system modeling and analysis, simulation, optimization, visualization and VR technology are used to get a digital prototype with

optimized performance, thereby the development costs and the reliance on physical prototypes are reduced, product qualities are improved, and time-to-market is accelerated.

Railway vehicle system which belongs to complex mechanical system areas is composed of mechanical, electrical, active control and drive systems (power distributed EMU), and its main part is mechanical systems. The quality of vehicle performances is the key problem of the vehicle product development. Based on the railway vehicle product design, especially the design results of the whole product machine, the performances include: dynamic performance, operational safety, aerodynamics, air-condition, strength and fatigue reliability. Therefore, it is inevitable to research and develop the railway vehicle virtual prototyping for advanced manufacturing technology.

It is also inevitable to research the railway vehicle virtual prototyping technique for the railway transportation equipment, especially for the high-speed, heavy haul train. The past railway vehicle product development mainly takes the following forms:

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 227

can make scheme decision and be easy to deal with three-dimensional CAX / DFX intelligent optimization design, a variety of integrated performance analysis (vehicle dynamics, aerodynamics, strength, fatigue reliability, etc.) and l dynamic running simulation of mutual behaviours. In the end, So it can enhance the innovative design for

At present, there are two levels in the virtual prototyping study. The first level is the development and manufacturing of the virtual prototype platform, i.e. the development of various software. There are three software development modes. First is the development of various functional modules software, such as Pro-E, Solidwork, Catia, UG, CAXA, etc; railway vehicle dynamics software: ADAMS/Rail, SIMPACK, NUCARS, VAMPIRE, DADS/Rail, etc; strength and fatigue analysis software: Ideas, ABAQUS, ANSYS, Fatigue, etc; fluid analysis software: FLUENT, StarCD etc; the work mainly depends on software companies to develop. The second is integrating various modeling and analysis software based on PDM, through the interfaces and PDM management (such as using collaborative management platform of Pro-E) to realize the concept of virtual prototyping-based software process, and design the experience and knowledge library, prototype library, model library, physical experimental data and analysis data repository. There has been some work on the re-development of existing software, but the analysis software itself has not been studied. The third level is developing a truly virtual prototyping platform to complete design and analysis in one software that does not need data transmission and conversion which is seamless connectivity. Such as Virtual-Lab from LMS company which co-operates with physical design software of Catia, mergers dynamics software of DADS, is seamlessly connected with ABAQUS, ANSYS (only finite element solver), and finally joins the advantages of fatigue and acoustic computing from LMS's own company to achieve a

According to these studies, three main virtual prototyping platforms at present are as

2. The core is CAX/DFX which is combined with other virtual prototyping platform analysis software, typically for Virtual-Lab from LMS which is a more versatile

3. According to the industry needs and the concept of the virtual prototype, various analysis software were integrated based on PDM; some re-developments for acquiring

Complying with virtual prototyping technology, railway vehicle virtual prototyping intends to establish a digital development platform for railway vehicle products. According to the

1. Establish the railway vehicle product digital model. Based on three-dimensional CAD,

1. Virtual prototype platform architecture research based on simulation framework,

the product solution are done. There are many such systems.

railway vehicle characteristics, the following factors should be considered:

establish the innovative design platform for railway vehicle products.

**2. Layout of railway vehicle virtual prototyping**

high-speed railway vehicle to a new level.

complete virtual prototype platform.

platform for virtual prototyping.

mainly for spacecraft.

follows:

**2.1 Overall plan**

**1.2 Research status of the railway vehicle virtual prototyping**

Improving the speed of railway transport will not only bring issues such as safety, comfort, economy and environmental protection, but also result in a number of major scientific and technological problems. The most typical scientific and technical issues with speed are as follows:

With the increasing railway vehicle speed, safety, comfort, economy and environmental protection for high-speed railway vehicle are more and more important. Building the virtual prototype high-speed railway vehicle platform will provide strong technical support for researches arising from high speed.

Therefore, based on comprehensive analysis of related research fields, railway vehicle virtual prototype engineering research is carried out; the development and testing platform of railway vehicle virtual prototyping is established. Combined with the existing railway vehicle rolling test experiment bench, a hardware and software platform is formed which can make scheme decision and be easy to deal with three-dimensional CAX / DFX intelligent optimization design, a variety of integrated performance analysis (vehicle dynamics, aerodynamics, strength, fatigue reliability, etc.) and l dynamic running simulation of mutual behaviours. In the end, So it can enhance the innovative design for high-speed railway vehicle to a new level.

### **1.2 Research status of the railway vehicle virtual prototyping**

At present, there are two levels in the virtual prototyping study. The first level is the development and manufacturing of the virtual prototype platform, i.e. the development of various software. There are three software development modes. First is the development of various functional modules software, such as Pro-E, Solidwork, Catia, UG, CAXA, etc; railway vehicle dynamics software: ADAMS/Rail, SIMPACK, NUCARS, VAMPIRE, DADS/Rail, etc; strength and fatigue analysis software: Ideas, ABAQUS, ANSYS, Fatigue, etc; fluid analysis software: FLUENT, StarCD etc; the work mainly depends on software companies to develop. The second is integrating various modeling and analysis software based on PDM, through the interfaces and PDM management (such as using collaborative management platform of Pro-E) to realize the concept of virtual prototyping-based software process, and design the experience and knowledge library, prototype library, model library, physical experimental data and analysis data repository. There has been some work on the re-development of existing software, but the analysis software itself has not been studied. The third level is developing a truly virtual prototyping platform to complete design and analysis in one software that does not need data transmission and conversion which is seamless connectivity. Such as Virtual-Lab from LMS company which co-operates with physical design software of Catia, mergers dynamics software of DADS, is seamlessly connected with ABAQUS, ANSYS (only finite element solver), and finally joins the advantages of fatigue and acoustic computing from LMS's own company to achieve a complete virtual prototype platform.

According to these studies, three main virtual prototyping platforms at present are as follows:

### **2. Layout of railway vehicle virtual prototyping**

### **2.1 Overall plan**

226 Modeling and Simulation in Engineering

1. For the research methods, the traditional design embodies the serial, over-reliance on physical prototypes and over-focuses on local optimization of product characteristics, over-emphasizes on the structure itself, less stresses on the whole design features. As the increasing of railway vehicle speeds, these traditional design methods can not meet the performance requirements of high-speed vehicle, so a new performance design concept must be adopted which particularly emphasizes on the overall performance

2. For the research process, the traditional design methods do not form a complete innovative product development system. Different railway vehicle models were designed by different research institutes, followed by the related performance analysis carried out by other different research units, then they were produced by relevant companies and tested to form the product at last. This has led to no systematicness in the product development process and a serious gap between design, performance analysis, manufacturing and testing. And analysis platforms and analysis models which impact the product performance are different. For example, the structural strength analysis did not use dynamic load spectrum from dynamics study to fatigue strength analysis for key components and structure, and did not consider the impact of railway vehicle movement and structure vibration from the air flow disturbance, and so on. So there are differences between research results and actual operating conditions which lead to railway vehicle running accidents. According to this situation, based on improving the various functional softwares of railway vehicles to establish integrated and intelligent performance design software platform, and form a unified computing methods and standards, combing traditional mechanical design, part strength analysis and product performance analysis in a design analysis platform to do visual design and

Improving the speed of railway transport will not only bring issues such as safety, comfort, economy and environmental protection, but also result in a number of major scientific and technological problems. The most typical scientific and technical issues with speed are as

 Air resistance problem - in the dense atmosphere, the aerodynamic drag is the cubic relationship to the rate of growth, so there is a reasonable speed value in terms of the track on the ground. Then, how to break this resistance barrier to further improve the ground speed of rail transport? Under the high-speed conditions, there are serious basic scientific problems to be solved, such as railway vehicle and air-coupled dynamic

 Running noise problem - the main problem of high-speed railway vehicle is noise. Both the wheel-rail noise and aerodynamic noise need to be explored from the noise generation mechanism to the transmission mechanism. Vibration and noise reduction

With the increasing railway vehicle speed, safety, comfort, economy and environmental protection for high-speed railway vehicle are more and more important. Building the virtual prototype high-speed railway vehicle platform will provide strong technical support for

Therefore, based on comprehensive analysis of related research fields, railway vehicle virtual prototype engineering research is carried out; the development and testing platform of railway vehicle virtual prototyping is established. Combined with the existing railway vehicle rolling test experiment bench, a hardware and software platform is formed which

problem, air compressibility characteristics problem, and so on.

requirements under the high-speed conditions.

overall performance design is very urgent.

are the eternal scientific and technical issues.

researches arising from high speed.

follows:

Complying with virtual prototyping technology, railway vehicle virtual prototyping intends to establish a digital development platform for railway vehicle products. According to the railway vehicle characteristics, the following factors should be considered:

1. Establish the railway vehicle product digital model. Based on three-dimensional CAD, establish the innovative design platform for railway vehicle products.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 229

In accordance with the above ideas, the concept of the platform for railway vehicle virtual prototype is shown in Fig. 2-2. Structure of this part is divided into four main sections:

This part is composed of distributed network running software and hardware, virtual prototype concurrent design and simulation systems, distributed database servers,

Around the mainstream 3D CAD software, a railway vehicle product innovation design

This model is the basis for subsequent design and analysis. This section includes: product scheme design, design automation, serialization and modularization and

Interface the following performance and simulation, establish the interconnected

This section is mainly designed for cost, assembly, processing techniques and other manufacturing characteristics. Evaluate the economy, manufacturability, assembly ability of products according to a comprehensive perspective to reduce the risk of trial and trial times for the final product optimization services. This section mainly

This part mainly completes the integration management of the design and analysis

Based on the above product digital description, mainly simulate the function, behavior and running environment of the products: railway vehicle multi-body dynamics analysis, multi-field coupling dynamic analysis and simulation, strength and fatigue reliability analysis of key parts, analysis and simulation of railway vehicle structural vibration noise, simulation of mode, brake and shock response, analysis and simulation

Combining with the digital model and various performance analysis results, the mixed digital simulation of the railway vehicle dynamic, which is a multi-domain environment coupled simulation, includes: railway vehicle running simulation and etc

Those four parts above form a more complete railway vehicle virtual prototype development platform. On this platform, PDM, concurrent simulation tools and platform are the linkage to achieve these functions. Fig. 2-3 is the data flow analysis for railway

The part with thin red line means that exchange data is needed before data processing. From this it can be seen that the three-dimensional model is the entire data center of the system. The key processes of this part are: establish a reasonable railway vehicle database model and the database structure of the whole vehicle model, open the system to all data format; establish the database coordinating relationship between various databases; deal with

concurrency control and collaboration issues between various database.

of aerodynamics and air noise, co-simulation of multi-field coupling and etc.

1. Product digital design and simulation basis system

platform which includes four major parts is built:

b. Product modeling based on physical properties

a. Model design of product digitization

c. Design oriented manufacturing

d. Product data management (PDM)

4. Railway vehicle running simulation

based on virtual reality technical.

vehicle virtual prototyping engineering.

2. Product innovation design system based on three-dimensional CAD

includes: virtual assembly and virtual manufacturing;

of manufacturing data from database server. 3. Digital prototyping-oriented performance analysis

optimization design, different model library for railway vehicles;

middleware of CAD and CAE platform to achieve the model unity;

clusters computer group and etc.

According to the specific case of railway vehicle virtual prototype, the program of establishing the "railway vehicle virtual prototype research and development platform" is shown in Fig. 2- 1. The core part of the whole project should be achieved in high-speed local area network platform which supports concurrent engineering methodology and is composed of highperformance PC. The platform should be the overall situation to solve problems related to the global system. Considering the relationship of various parts of the virtual prototype, it can regulate and coordinate the running of various sub-systems, and share the information and resources to achieve the overall goal of railway vehicle virtual prototype.

Different constrained work is carried out concurrently on the basis of the management platform. There are mainly five major modules according to the product development process: PDM module, product research module, product performance analysis module, product virtual manufacture modules and product running simulation module, as shown in Fig. 2-1.

Fig. 2-1. Digitization process of the product research and manufacturing

2. Integrate multi-domain prototype model. Based on three-dimensional CAD model, consider basic data of various characteristics of railway vehicle, such as physical

3. Take into account the integrality of the prototype model. Integrate seamlessly the multibody dynamics environment and integrated model based on CAD, make dynamic automatic modeling and solving according to the CAD model, and build railway vehicle multi-body system with nonlinear dynamics simulation and computation. 4. Take into account the integrality of the prototype mode. Integrate seamlessly the integrated model and CAE analysis environment; analyze and simulate the structures, fatigue and the reliability performance for railway vehicle; simulate and calculate the

5. Combine the virtual reality technology and build a virtual prototype test platform. Considering the simulation of human factor and hardware in the loop, the assessment

6. Build the design platform of key components for railway vehicle, comprehensively evaluate the manufacturability to achieve the aim of railway vehicle virtual prototype based on CAX / DFX and optimize the design of railway vehicle virtual prototype. 7. In accordance with PDM principle, establish the data management platform of the entire system to build the system simulation management platform, and make the

According to the specific case of railway vehicle virtual prototype, the program of establishing the "railway vehicle virtual prototype research and development platform" is shown in Fig. 2- 1. The core part of the whole project should be achieved in high-speed local area network platform which supports concurrent engineering methodology and is composed of highperformance PC. The platform should be the overall situation to solve problems related to the global system. Considering the relationship of various parts of the virtual prototype, it can regulate and coordinate the running of various sub-systems, and share the information and

Different constrained work is carried out concurrently on the basis of the management platform. There are mainly five major modules according to the product development process: PDM module, product research module, product performance analysis module, product virtual manufacture modules and product running simulation module, as shown in Fig. 2-1.

model of airflow field and temperature field outside and inside the train.

analysis of railway vehicle virtual prototype should be built

resources to achieve the overall goal of railway vehicle virtual prototype.

Fig. 2-1. Digitization process of the product research and manufacturing

information, assembly information, etc.

system an organic whole.

In accordance with the above ideas, the concept of the platform for railway vehicle virtual prototype is shown in Fig. 2-2. Structure of this part is divided into four main sections:

	- a. Model design of product digitization This model is the basis for subsequent design and analysis. This section includes: product scheme design, design automation, serialization and modularization and optimization design, different model library for railway vehicles;
	- b. Product modeling based on physical properties Interface the following performance and simulation, establish the interconnected middleware of CAD and CAE platform to achieve the model unity;
	- c. Design oriented manufacturing This section is mainly designed for cost, assembly, processing techniques and other manufacturing characteristics. Evaluate the economy, manufacturability, assembly ability of products according to a comprehensive perspective to reduce the risk of trial and trial times for the final product optimization services. This section mainly includes: virtual assembly and virtual manufacturing;
	- d. Product data management (PDM) This part mainly completes the integration management of the design and analysis of manufacturing data from database server.

Those four parts above form a more complete railway vehicle virtual prototype development platform. On this platform, PDM, concurrent simulation tools and platform are the linkage to achieve these functions. Fig. 2-3 is the data flow analysis for railway vehicle virtual prototyping engineering.

The part with thin red line means that exchange data is needed before data processing. From this it can be seen that the three-dimensional model is the entire data center of the system. The key processes of this part are: establish a reasonable railway vehicle database model and the database structure of the whole vehicle model, open the system to all data format; establish the database coordinating relationship between various databases; deal with concurrency control and collaboration issues between various database.

Fig. 2-2. Innovation system of railway vehicle virtual prototype

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 231

Fig. 2-3. Data flow analysis for railway vehicle virtual prototyping engineering

From Fig. 2-4, it can be seen that establishing a reasonable, reliable and adequate information model is the core of the entire system data processing. The model database is a complete virtual prototype model. The work will be done by the product design platform. This section can rely on the function of three-dimensional solid modeling such as CAXA to

2. Generate the physical model and simplified model (simplified according to the requirements of the mechanical model) corresponding with three-dimensional solid model; plan the model according to the actual performance including materials, quality, mass center, surface area, volume, inertia moment, mechanical properties curve function, stiffness, composite calculation of main/sub-section and etc; classify the entities with performance characteristics in accordance with the similar principle. 3. Have the part assembly function, it is design for assembly (DFA) ,and can be combined in accordance with the model tree to generate a separate entity model, so that it has its

**2.2 Innovative design platform for railway vehicle virtual prototyping**

1. Have all functions of generating three-dimensional solid model;

improve itself, the specific functional requirements are:

Fig. 2-2. Innovation system of railway vehicle virtual prototype

Fig. 2-3. Data flow analysis for railway vehicle virtual prototyping engineering

### **2.2 Innovative design platform for railway vehicle virtual prototyping**

From Fig. 2-4, it can be seen that establishing a reasonable, reliable and adequate information model is the core of the entire system data processing. The model database is a complete virtual prototype model. The work will be done by the product design platform. This section can rely on the function of three-dimensional solid modeling such as CAXA to improve itself, the specific functional requirements are:

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 233

**Strenth computation**

**Strenth analysis Lift prediction**

This platform integrates the railway vehicle parametric design and vehicle dynamics computation. Based on the railway vehicle dynamics simulation software, using multi-body system dynamics computation method and model database from entity CAD design, settle the model first, which includes error checking, feature and parameter identification and extraction to form the dynamic computation model. According to the simulation run line conditions, do simulation solution and analyze the three elements(safety, stability, comfortability) of the railway vehicle to obtain the critical instability speed, ride comfort, dynamic wheel-rail forces and other targets. The dynamic load and dynamic stress from simulation can be used for strength and fatigue reliability analysis. Send the result database is transferred to optimization design module to do parameters and structure optimization.

**3-D CAD entity design**

**Meshing**

**Model type Physical property Assembly property**

**Fulid analysis**

**Aerodynamics Vehicle HAVC analysis**

The dynamic computational platform for railway vehicle is shown in Fig. 2-6.

Fig. 2-6. Dynamic computational platform for railway vehicle

Fig. 2-5. Main ways to analyze railway vehicle

**TPLDYNA/VSDS Dynamics computation**

> **Rigid body Elastic body**

own physical property performance, for example: the change of the mass center, surface area, volume, inertia moment, materials composition and etc.

The architecture and data flow of this platform is shown in Fig. 2-4.

Fig. 2-4. 3-D design platform for railway vehicle oriented virtual prototyping

### **2.3 Performance analysis platform for railway vehicle virtual prototyping**

Railway vehicle performance analysis is mainly composed by dynamics, intensity and fluid analysis, with the core dynamics based on meshing analysis. They are established on the basis of three-dimensional CAD digital model. The main ways to analyze railway vehicle are shown in Fig. 2-5.

Fig. 2-5. Main ways to analyze railway vehicle

4. Establish constraint models of all kinds of components in accordance with the constraints. It should have the function of kinematics analysis which be able to detect

5. Have parametric function which has both features and structural parametric characteristic to generate the parts automatically, and can modify the entity parameter

6. Geometric model must support the STEP standard and support design for

7. Have the management function for all model databases and the whole vehicle database. Each component has a physical (including the simplified model) and geometric model sub-database. All model databases should be opened to all, and should have the

8. All geometric and physical models must support the conversion with kinds of software

area, volume, inertia moment, materials composition and etc.

manually or automatically according to the optimized result.

manufacturing (DFM) to expand the virtual manufacturing;

interface and a strong re-development based on VC interface; The architecture and data flow of this platform is shown in Fig. 2-4.

Fig. 2-4. 3-D design platform for railway vehicle oriented virtual prototyping

**2.3 Performance analysis platform for railway vehicle virtual prototyping**

Railway vehicle performance analysis is mainly composed by dynamics, intensity and fluid analysis, with the core dynamics based on meshing analysis. They are established on the basis of three-dimensional CAD digital model. The main ways to analyze railway vehicle

function of automatic indexing.

are shown in Fig. 2-5.

interference, moreover can simulate the deformed elastic components.

own physical property performance, for example: the change of the mass center, surface

This platform integrates the railway vehicle parametric design and vehicle dynamics computation. Based on the railway vehicle dynamics simulation software, using multi-body system dynamics computation method and model database from entity CAD design, settle the model first, which includes error checking, feature and parameter identification and extraction to form the dynamic computation model. According to the simulation run line conditions, do simulation solution and analyze the three elements(safety, stability, comfortability) of the railway vehicle to obtain the critical instability speed, ride comfort, dynamic wheel-rail forces and other targets. The dynamic load and dynamic stress from simulation can be used for strength and fatigue reliability analysis. Send the result database is transferred to optimization design module to do parameters and structure optimization. The dynamic computational platform for railway vehicle is shown in Fig. 2-6.

Fig. 2-6. Dynamic computational platform for railway vehicle

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 235

In the virtual prototyping, the first is to get the virtual prototype model which must rely on three-dimensional CAD software. How to get the virtual prototype model fast and accurately is the basic part for speeding up product design. According to the parts that can be parameterized, prototype model automated design ideas and methods are proposed. Take the bogie design for an example, this approach is detail studied. The following process

Around the bogie design automation, its implementation framework is shown in Figure 3-1. In object-oriented development environment, the automatic design of the bogie parts with user-friendly interface is completed, the data management library is established, and the changes and assembly of the bogie vehicle model (mainly for the wheelset and spring components) are implemented. At the same time, the extraction of bogie performance attribute parameters is completed, generated bogie model is saved as sel-definied file automatically, and the bogie component model and corresponding data are reproduced in the file browser. Thus, the data for dynamics calculation platform and finite element

Since there are many parts in the bogey, the secondary stiff spring is taken here for an example. First, the basic design flow is obtained according to the design requirement. According to the design results, based on the technical support of COM component interface, API, CAD environment and database under three-dimensional CAD redevelopment environment, drive 3D rendering engine and draw out different specification three-dimensional model of the secondary stiffness spring to get the virtual model. The

With the same process, other parts of the bogie can also be designed. 3-D figure of the wheelset and wheel axle which was obtained from automatic design is shown in Fig. 3-3 and

**3. Design model of the railway vehicle digital prototype-take bogie for an**

**example**

of this method is shown in Fig. 2-9.

analysis platform are subsequently provided.

Fig. 3-1. Structure graph of the system framework

design results are shown in Fig. 3-2.

3-4.

The key of this part is the extraction of the whole vehicle model database including entities simplification, combination, extraction of the physical properties, and extraction of coordinate location of the component and etc, with the requirement of using all data from the model database; In addition, data visualization and classification of the results also need interface development. This is the main context of this chapter.

### **2.4 Running simulation of the railway vehicle**

The platform does the final integrated simulation of comprehensive test and evaluation to virtual prototype. Related tools are used to produce various effects, and the main task is to simulate various operating conditions of the vehicle to make clear people's understanding and awareness of the vehicle in the simulation loop. In other words, it means to regard people as an intelligent individual to do all performance testing of the virtual prototype, including: safety, comfortability, stability and so on. The core of this platform is virtual environment which has the following contents: vehicle LOD models, various result data form performance simulation computation, vehicle kinematics model, virtual reality interface device, a variety of effects tools (all kinds of dynamic simulation tools, brake tools, control simulation tools, etc.), virtual scene (bridges, tunnels, rail, the distance light scenes, etc.), control mathematical model, traction model, braking model and etc.

The key of this part is how to integrate these multi-dimensional information as a whole and simulate various properties of the railway vehicle virtual prototype, saving the dynamic test database as a certain prototype database ultimately. Running simulation of the railway vehicle is shown in Fig. 2-9.

Fig. 2-9. Running simulation of the railway vehicle (virtual test)

The key of this part is the extraction of the whole vehicle model database including entities simplification, combination, extraction of the physical properties, and extraction of coordinate location of the component and etc, with the requirement of using all data from the model database; In addition, data visualization and classification of the results also need

The platform does the final integrated simulation of comprehensive test and evaluation to virtual prototype. Related tools are used to produce various effects, and the main task is to simulate various operating conditions of the vehicle to make clear people's understanding and awareness of the vehicle in the simulation loop. In other words, it means to regard people as an intelligent individual to do all performance testing of the virtual prototype, including: safety, comfortability, stability and so on. The core of this platform is virtual environment which has the following contents: vehicle LOD models, various result data form performance simulation computation, vehicle kinematics model, virtual reality interface device, a variety of effects tools (all kinds of dynamic simulation tools, brake tools, control simulation tools, etc.), virtual scene (bridges, tunnels, rail, the distance light scenes, etc.), control mathematical model, traction model, braking model

The key of this part is how to integrate these multi-dimensional information as a whole and simulate various properties of the railway vehicle virtual prototype, saving the dynamic test database as a certain prototype database ultimately. Running simulation of the railway

interface development. This is the main context of this chapter.

Fig. 2-9. Running simulation of the railway vehicle (virtual test)

**2.4 Running simulation of the railway vehicle**

and etc.

vehicle is shown in Fig. 2-9.

### **3. Design model of the railway vehicle digital prototype-take bogie for an example**

In the virtual prototyping, the first is to get the virtual prototype model which must rely on three-dimensional CAD software. How to get the virtual prototype model fast and accurately is the basic part for speeding up product design. According to the parts that can be parameterized, prototype model automated design ideas and methods are proposed. Take the bogie design for an example, this approach is detail studied. The following process of this method is shown in Fig. 2-9.

Around the bogie design automation, its implementation framework is shown in Figure 3-1. In object-oriented development environment, the automatic design of the bogie parts with user-friendly interface is completed, the data management library is established, and the changes and assembly of the bogie vehicle model (mainly for the wheelset and spring components) are implemented. At the same time, the extraction of bogie performance attribute parameters is completed, generated bogie model is saved as sel-definied file automatically, and the bogie component model and corresponding data are reproduced in the file browser. Thus, the data for dynamics calculation platform and finite element analysis platform are subsequently provided.

Fig. 3-1. Structure graph of the system framework

Since there are many parts in the bogey, the secondary stiff spring is taken here for an example. First, the basic design flow is obtained according to the design requirement. According to the design results, based on the technical support of COM component interface, API, CAD environment and database under three-dimensional CAD redevelopment environment, drive 3D rendering engine and draw out different specification three-dimensional model of the secondary stiffness spring to get the virtual model. The design results are shown in Fig. 3-2.

With the same process, other parts of the bogie can also be designed. 3-D figure of the wheelset and wheel axle which was obtained from automatic design is shown in Fig. 3-3 and 3-4.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 237

**4. Performance extraction of railway vehicle digital prototype oriented multi-**

Existed CAD software has been able to get a very complete product configuration and can get the relationship between the product and components in its design space, but it is mainly designed for manufacturing. Therefore, functionality and output data provided by CAD rarely faces to the subsequent performance analysis which has been confirmed in the analysis of many product cases. In the subsequent product performance analysis which includes multi-body dynamic analysis, strength and reliability analysis and other performance analysis, CAD still only provides a preliminary physical model which can not get its own performance properties from the entity itself. So the attribute data of product components need to be obtained by physical experiment. The difficulties of data collection, the investment of testing equipment and the cost of product development are enlarged. Moreover, with the perspective of practical effect, in the following process of passing the performance analysis function, due to precision, algorithm, solving model and other reasons, CAD models will lose some information that may lead to too much human intervention and waste a lot of human and material resources. Even a small mistake can result in the fact that the prototype analysis can not keep going normally. So, a lot of virtual prototype analysis at present still do their own studies. CAD is only responsible for the design. The model is re-modeled after being simplified according to the product function in dynamic analysis. The model is carried out according to the initial design scheme in finite element analysis. So these lead to serious gap between analysis software and CAD, also lead to no unification of the analytical results from different analysis software. Enterprise even does not know which algorithm is correct, so they still choose the conservative design approach such as raising the safety factor and so on. This makes people misunderstand the

Fig. 3-5. Automatic assembly process of the bogie

**body system 4.1 Method**

virtual prototyping technology.

The automatic assembly process of the bogie is shown in Fig.3-5 (some small parts omitted). Through this automatic process, it only takes less than one minute to complete bogie assembly in SolidWorks. With the parameters of the previous parts, a different type of bogie can be designed easily which speeds up the design rate and efficiency.

Fig. 3-2. Design automation of the secondary stiffness spring

Fig. 3-3. Design automation of the axle

Fig. 3-4. Design automation of the wheelset

Fig. 3-5. Automatic assembly process of the bogie

### **4. Performance extraction of railway vehicle digital prototype oriented multibody system**

### **4.1 Method**

236 Modeling and Simulation in Engineering

The automatic assembly process of the bogie is shown in Fig.3-5 (some small parts omitted). Through this automatic process, it only takes less than one minute to complete bogie assembly in SolidWorks. With the parameters of the previous parts, a different type of bogie

can be designed easily which speeds up the design rate and efficiency.

Fig. 3-2. Design automation of the secondary stiffness spring

Fig. 3-3. Design automation of the axle

Fig. 3-4. Design automation of the wheelset

Existed CAD software has been able to get a very complete product configuration and can get the relationship between the product and components in its design space, but it is mainly designed for manufacturing. Therefore, functionality and output data provided by CAD rarely faces to the subsequent performance analysis which has been confirmed in the analysis of many product cases. In the subsequent product performance analysis which includes multi-body dynamic analysis, strength and reliability analysis and other performance analysis, CAD still only provides a preliminary physical model which can not get its own performance properties from the entity itself. So the attribute data of product components need to be obtained by physical experiment. The difficulties of data collection, the investment of testing equipment and the cost of product development are enlarged. Moreover, with the perspective of practical effect, in the following process of passing the performance analysis function, due to precision, algorithm, solving model and other reasons, CAD models will lose some information that may lead to too much human intervention and waste a lot of human and material resources. Even a small mistake can result in the fact that the prototype analysis can not keep going normally. So, a lot of virtual prototype analysis at present still do their own studies. CAD is only responsible for the design. The model is re-modeled after being simplified according to the product function in dynamic analysis. The model is carried out according to the initial design scheme in finite element analysis. So these lead to serious gap between analysis software and CAD, also lead to no unification of the analytical results from different analysis software. Enterprise even does not know which algorithm is correct, so they still choose the conservative design approach such as raising the safety factor and so on. This makes people misunderstand the virtual prototyping technology.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 239

For the elastic body: identification number, quality, geometry shape, mass center, moment of inertia, location coordinates, freedom, material density, modulus of elasticity, mode,

For element force: serial number, coordinate position which connects two rigid bodies (location of the up and down points), physical definition of the force element type (stiffness,

The data are given by their own characteristics of the product components such as quality, geometry shape, mass, inertia, density, modulus of elasticity, stiffness, damping, etc. Some are obtained from product assembly relationship and space movement characteristics such as: position, location, connection relationship of hinge and multi-body, position coordinates. Many of these properties can be extracted from the CAD model, but all current CAD systems do not provide this function. So the building of an abstraction layer between CAD and prototype performance analysis is proposed to obtain a satisfactory virtual prototype

In theory, the second defined data is directly from the CAD design model. It should be more accurate and more reasonable, but the difficulty of CAD may increase. If taken as a separate function layer designed by design and analysis staff, this difficulty can be simplified. In the first approach, manufacturing are mainly considered after the CAD model is designed, without considering the definition of products and component attributes. Most are obtained

From Fig. 4-1 (b), in order to achieve the aim of extraction from CAD directly or attributes definition, higher requirements are needed on CAD functions. However, the current CAD can not meet this requirement obviously, so its function should be extended. For a variety of CAD software, they have re-development functions, such as ToolKit of Pro-E, SDK API (Application Programming Interface) of SolidWork, SDK (Software Development Kit) of

Prototyping can be obtained from three-dimensional solid model design, Extend Data Object (EDO), internal and extended Catalogs (a pixel classification function of CAXA software) and the second development. The model attribute definitions can be defined through an external interface or SDK development of CAXA platform to obtain an extended IGES file. The so-called extensible IGES files are to keep the original model data interface and format unchanged, increase the special format data in the end of the file system which is mainly used to define the properties of the model data. This file can interface the common application software and can be used for the system which has both specialization and generality. Therefore, the obtained data are data blocks based on IGES that can describe model properties. Those data blocks form the whole data model are for

Obviously, the prototype model is actually a combination of a space abstracted physical prototype and the entity model. Entity model is obtained from the CAD design and attached to the physically abstracted model. The abstracted model not only defines the properties of the product components, but also maps to the graph-like model structure according to their functions and relationships, reducing the functionality according to the follow-up requirement. In order to overcome the model data consistency, several key issues must be solved, and they are: define and extract the data directly in the solid

by analyzing the functions supplied by analysis tests tools to do re-modeling.

**4.3 Virtual prototype performance design solutions based on CAD**

CAXA. This study is based on three-dimensional CAD of CAXA.

damping, etc.

the platform.

damping, friction and other characteristics).

model as shown in Fig. 3-6.

The real reason for this misunderstanding is only considering the geometric modeling in the CAD, but not considering modeling of product components and the full machine. By putting the extraction of the product model's performance data in performance analysis module artificially, the integrity of the CAD model itself is ignored. In fact, the product CAD model provides geometric model and physical properties of the products and components simultaneously, so the physical properties should be modeled in CAD and property definition should be considered in CAD design to provide a complete integrated model for the following performance analysis which will unify the model. These two ideas are summarized in Fig. 4-1.

Fig. 4-1. Two different methods to definite the property

The proposed method provides an abstraction layer between CAD and prototype performance analysis in order to obtain a satisfactory virtual prototype model.

### **4.2 The requirements of virtual prototype model for product performance analysis under multi-body system**

The ultimate virtual prototype not only depends on the completeness of the design, but also depends on the correctness of prototype analysis, which will replace the product physical prototypes to achieve product performance analysis, testing and evaluation. For mechanical system virtual prototyping, the main performance analysis tools are: strength analysis, life prediction, multi-body dynamics, fluid analysis (gas, fluid dynamics) and so on.

The basic data of the analysis are from the three-dimensional CAD design itself. Take multibody systems analysis for example, the following performance data should be provided by the system:

For rigid body: identification number, quality, geometry shape, mass center, moment of inertia, location coordinates, position coordinates, degree of freedom, material density, etc.

For kinematic pair: identity, type, location of hinge points and associated two rigid, position coordinates of the hinge point, location coordinates of the hinge point, the number of degrees of freedom. In general, kinematic set are: rotating set, sliding set, planar joint, cylindric pair, cardan joint, spherical pair, gear pair, etc.

The real reason for this misunderstanding is only considering the geometric modeling in the CAD, but not considering modeling of product components and the full machine. By putting the extraction of the product model's performance data in performance analysis module artificially, the integrity of the CAD model itself is ignored. In fact, the product CAD model provides geometric model and physical properties of the products and components simultaneously, so the physical properties should be modeled in CAD and property definition should be considered in CAD design to provide a complete integrated model for the following performance analysis which will unify the model. These two ideas

(a) Traditional method (b) Method of this research

The proposed method provides an abstraction layer between CAD and prototype

The ultimate virtual prototype not only depends on the completeness of the design, but also depends on the correctness of prototype analysis, which will replace the product physical prototypes to achieve product performance analysis, testing and evaluation. For mechanical system virtual prototyping, the main performance analysis tools are: strength analysis, life

The basic data of the analysis are from the three-dimensional CAD design itself. Take multibody systems analysis for example, the following performance data should be provided by

For rigid body: identification number, quality, geometry shape, mass center, moment of inertia, location coordinates, position coordinates, degree of freedom, material density, etc. For kinematic pair: identity, type, location of hinge points and associated two rigid, position coordinates of the hinge point, location coordinates of the hinge point, the number of degrees of freedom. In general, kinematic set are: rotating set, sliding set, planar joint,

**4.2 The requirements of virtual prototype model for product performance analysis**

performance analysis in order to obtain a satisfactory virtual prototype model.

prediction, multi-body dynamics, fluid analysis (gas, fluid dynamics) and so on.

Fig. 4-1. Two different methods to definite the property

cylindric pair, cardan joint, spherical pair, gear pair, etc.

are summarized in Fig. 4-1.

**under multi-body system**

the system:

For the elastic body: identification number, quality, geometry shape, mass center, moment of inertia, location coordinates, freedom, material density, modulus of elasticity, mode, damping, etc.

For element force: serial number, coordinate position which connects two rigid bodies (location of the up and down points), physical definition of the force element type (stiffness, damping, friction and other characteristics).

The data are given by their own characteristics of the product components such as quality, geometry shape, mass, inertia, density, modulus of elasticity, stiffness, damping, etc. Some are obtained from product assembly relationship and space movement characteristics such as: position, location, connection relationship of hinge and multi-body, position coordinates. Many of these properties can be extracted from the CAD model, but all current CAD systems do not provide this function. So the building of an abstraction layer between CAD and prototype performance analysis is proposed to obtain a satisfactory virtual prototype model as shown in Fig. 3-6.

In theory, the second defined data is directly from the CAD design model. It should be more accurate and more reasonable, but the difficulty of CAD may increase. If taken as a separate function layer designed by design and analysis staff, this difficulty can be simplified. In the first approach, manufacturing are mainly considered after the CAD model is designed, without considering the definition of products and component attributes. Most are obtained by analyzing the functions supplied by analysis tests tools to do re-modeling.

### **4.3 Virtual prototype performance design solutions based on CAD**

From Fig. 4-1 (b), in order to achieve the aim of extraction from CAD directly or attributes definition, higher requirements are needed on CAD functions. However, the current CAD can not meet this requirement obviously, so its function should be extended. For a variety of CAD software, they have re-development functions, such as ToolKit of Pro-E, SDK API (Application Programming Interface) of SolidWork, SDK (Software Development Kit) of CAXA. This study is based on three-dimensional CAD of CAXA.

Prototyping can be obtained from three-dimensional solid model design, Extend Data Object (EDO), internal and extended Catalogs (a pixel classification function of CAXA software) and the second development. The model attribute definitions can be defined through an external interface or SDK development of CAXA platform to obtain an extended IGES file. The so-called extensible IGES files are to keep the original model data interface and format unchanged, increase the special format data in the end of the file system which is mainly used to define the properties of the model data. This file can interface the common application software and can be used for the system which has both specialization and generality. Therefore, the obtained data are data blocks based on IGES that can describe model properties. Those data blocks form the whole data model are for the platform.

Obviously, the prototype model is actually a combination of a space abstracted physical prototype and the entity model. Entity model is obtained from the CAD design and attached to the physically abstracted model. The abstracted model not only defines the properties of the product components, but also maps to the graph-like model structure according to their functions and relationships, reducing the functionality according to the follow-up requirement. In order to overcome the model data consistency, several key issues must be solved, and they are: define and extract the data directly in the solid

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 241

Fig. 4-6. Property extraction of the multi-body system based on CAXA

Catalog, AttributeSet, embedded database and etc.

In the extracted process, coordinate transformation of design space, assembly space and feature space of the part is used in CAXA. Various properties of abstract defined bodies based on the geometric topological core are obtained. For unabstracted properties, the rich re-development interface function is used for extension, more suitable methods are: EDO,

model, mesh finite element in the solid model automatically in accordance with the requirements of FEA, extract model directly to do visualization of functional analysis subsequently and so on. The relationship of the model and performance analysis based on CAXA is shown in Fig. 4-2.

Fig. 4-2. Relationship of the model and performance analysis based on CAXA

Property definition for the performance analysis can be achieved by several redevelopments such as EDO, API, Catalog and so on.

### **4.4 Extraction of the virtual prototype performance attribute based on CAXA**

Railway vehicle system is a typical complex mechanical system. in the view of multi-body dynamics, this system is a complex system which interacts with a multi-body system. It can be simplified as: rigid body (soft body), hinge, force element, force, and etc. It can be defined as following:

For the body in the mechanical systems virtual prototyping, the most important is to describe its geometric and physical relationship in space. The architecture process of the performance and attributes obtained system for the entire multi-body system is shown in Fig. 4-6.

model, mesh finite element in the solid model automatically in accordance with the requirements of FEA, extract model directly to do visualization of functional analysis subsequently and so on. The relationship of the model and performance analysis based on

Fig. 4-2. Relationship of the model and performance analysis based on CAXA

**4.4 Extraction of the virtual prototype performance attribute based on CAXA**

3. Define the force and force couple of the rigid body as the external force.

developments such as EDO, API, Catalog and so on.

2. Define the suspension as force element;

as following:

Fig. 4-6.

flexibility.

Property definition for the performance analysis can be achieved by several re-

Railway vehicle system is a typical complex mechanical system. in the view of multi-body dynamics, this system is a complex system which interacts with a multi-body system. It can be simplified as: rigid body (soft body), hinge, force element, force, and etc. It can be defined

1. Relative to the suspension system, the stiffness of the car, bogie, wheelset and other qualities is much great, so they can be defined as rigid body without considering their

For the body in the mechanical systems virtual prototyping, the most important is to describe its geometric and physical relationship in space. The architecture process of the performance and attributes obtained system for the entire multi-body system is shown in

CAXA is shown in Fig. 4-2.

Fig. 4-6. Property extraction of the multi-body system based on CAXA

In the extracted process, coordinate transformation of design space, assembly space and feature space of the part is used in CAXA. Various properties of abstract defined bodies based on the geometric topological core are obtained. For unabstracted properties, the rich re-development interface function is used for extension, more suitable methods are: EDO, Catalog, AttributeSet, embedded database and etc.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 243

Decode the neutral file first. Obtain the rigid body, marker body, constraint, element force, applied force and etc according to established formats. Resume the space topology of the multi-body system according to the defined property. For example, rigid body a, b, c, has marker i, j, k, and force d, e, f, respectively, and the associated relationships ii, jj, kk, ee have been defined. The space topology structure can be resumed which is shown in

Although the physical models based on multi-body system are obtained, it has not been attached to the geometric solid model. In order to obtain a visual model, it needs to output the neutral file model in CAXA. In accordance with the decoded format, it can be IGES, STL, OBJ, 3DS, etc. In this study, 3DS model is adopted. The way to obtain the geometric model

Fig. 5-1.

Fig. 5-1. Rebuild multi-body system structure

of the prototype is shown in Fig. 5-2.

Once the model is defined and extracted, the virtual prototype based on CAD with unified regulations and property definition can be obtained, and pass to the performance analysis module.

Physical abstracted model corresponds with entity model through the marker and serial number. It strictly reflects the space topology construct relationship between various bodies. Their mapping forms an integrated digital model which has CAD features and physical features of product components to the following performance analysis.

Property extraction in CAXA is shown in Fig. 4-8.

Fig. 4-8. Property extracted in CAXA

### **5. Topology construction of railway vehicle virtual prototype oriented to multi-body system --physical model abstraction**

### **5.1 Transition of design prototype model to multi-body system analysis model based on virtual prototype-- the establishment of topology structure**

Mapa topology structure of multi-body system in CAD environment through property modeling, and store it in a neutral file format. This format retains the defined topology of the multi-body system including assembly location relationship, position and orientation relationship of the space coordinate, constraint relations and constraint definitions between bodies and etc. Output a corresponding geometric model simultaneously which strictly corresponds to the part or assembly in the neutral file. The initial data for multi-body system modeling abstracted from the CAD modeling are obtained. The transition from virtual prototype model to the multi-body analysis model is achieved.

Once the model is defined and extracted, the virtual prototype based on CAD with unified regulations and property definition can be obtained, and pass to the performance analysis

Physical abstracted model corresponds with entity model through the marker and serial number. It strictly reflects the space topology construct relationship between various bodies. Their mapping forms an integrated digital model which has CAD features and physical

**5. Topology construction of railway vehicle virtual prototype oriented to**

**5.1 Transition of design prototype model to multi-body system analysis model based**

Mapa topology structure of multi-body system in CAD environment through property modeling, and store it in a neutral file format. This format retains the defined topology of the multi-body system including assembly location relationship, position and orientation relationship of the space coordinate, constraint relations and constraint definitions between bodies and etc. Output a corresponding geometric model simultaneously which strictly corresponds to the part or assembly in the neutral file. The initial data for multi-body system modeling abstracted from the CAD modeling are obtained. The transition from

features of product components to the following performance analysis.

Property extraction in CAXA is shown in Fig. 4-8.

Fig. 4-8. Property extracted in CAXA

**multi-body system --physical model abstraction**

**on virtual prototype-- the establishment of topology structure**

virtual prototype model to the multi-body analysis model is achieved.

module.

Decode the neutral file first. Obtain the rigid body, marker body, constraint, element force, applied force and etc according to established formats. Resume the space topology of the multi-body system according to the defined property. For example, rigid body a, b, c, has marker i, j, k, and force d, e, f, respectively, and the associated relationships ii, jj, kk, ee have been defined. The space topology structure can be resumed which is shown in Fig. 5-1.

### Fig. 5-1. Rebuild multi-body system structure

Although the physical models based on multi-body system are obtained, it has not been attached to the geometric solid model. In order to obtain a visual model, it needs to output the neutral file model in CAXA. In accordance with the decoded format, it can be IGES, STL, OBJ, 3DS, etc. In this study, 3DS model is adopted. The way to obtain the geometric model of the prototype is shown in Fig. 5-2.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 245

In accordance with the virtual prototype form CAD, describe them as objects with multibody meaning using object-oriented idea, map them into 5 linear chains, and form a space topology model of visualized multi-body system. This model is also built on the principle of framework based on OpenGL and object oriented graphics. The existed relationship of this

model in three-dimensional visualized space is shown in Fig.5-3.

Fig. 5-3. Existed relationship of this model in three-dimensional visualized space

The above visual model suits for not only mechanical multi-body system, but also railway vehicle. Considering the particularity of the railway vehicle multi-body system solution, according to the given multi-body system analysis software, the special object is established as shown in Fig. 5-4. The visualized model can be defined in the system or imported form

These objects include: Car, Bogie, Wheelset, Track, Damper, Rod, Spring and Friction plate, which complete vehicle component modeling, simulate for vehicle model running, and

Create the solid model according to the associated sign of the given two ends. If the relative marker position changes, the shape and position or orientation of the model can be adjusted.

Four categories have their own "dynamic" property pages. Every category has its corresponding variable receiving and data transformation which prepare initial data for

**5.2 Topology construction of the railway vehicle multi-body system**

the CAD model directly.

dynamics solver.

prepare for the dynamic calculation.

It has basic functions of three-dimensional simulation.

Fig. 5-2. Transition of virtual prototype of analysis model

From the figure above, multi-body description of the physical model corresponds to the objects given by geometric entities exactly. These objects determine to give which solid through classifying the point, line and surface. According to the assembly sequence of virtual prototype in CAD and marker body of the neutral file, their position relation is mapped. Properties such as transformation relation between the fixed coordinate system and the inertial coordinate system, transformation relation between the marker coordinate system and the fixed coordinate system, Euler angle corresponded to the rigid body, position and orientation of the marker coordinate system, the relationship of the defined constraints (restriction of the degree freedom), position and orientation corresponded to the force, have been strictly defined in the neutral file. Finally it is located by mapping the coordinate system of virtual prototype and space coordinate system of the visualization module to obtain the satisfactory model of multi-body system.

Fig. 5-2. Transition of virtual prototype of analysis model

module to obtain the satisfactory model of multi-body system.

From the figure above, multi-body description of the physical model corresponds to the objects given by geometric entities exactly. These objects determine to give which solid through classifying the point, line and surface. According to the assembly sequence of virtual prototype in CAD and marker body of the neutral file, their position relation is mapped. Properties such as transformation relation between the fixed coordinate system and the inertial coordinate system, transformation relation between the marker coordinate system and the fixed coordinate system, Euler angle corresponded to the rigid body, position and orientation of the marker coordinate system, the relationship of the defined constraints (restriction of the degree freedom), position and orientation corresponded to the force, have been strictly defined in the neutral file. Finally it is located by mapping the coordinate system of virtual prototype and space coordinate system of the visualization In accordance with the virtual prototype form CAD, describe them as objects with multibody meaning using object-oriented idea, map them into 5 linear chains, and form a space topology model of visualized multi-body system. This model is also built on the principle of framework based on OpenGL and object oriented graphics. The existed relationship of this model in three-dimensional visualized space is shown in Fig.5-3.

Fig. 5-3. Existed relationship of this model in three-dimensional visualized space

### **5.2 Topology construction of the railway vehicle multi-body system**

The above visual model suits for not only mechanical multi-body system, but also railway vehicle. Considering the particularity of the railway vehicle multi-body system solution, according to the given multi-body system analysis software, the special object is established as shown in Fig. 5-4. The visualized model can be defined in the system or imported form the CAD model directly.

These objects include: Car, Bogie, Wheelset, Track, Damper, Rod, Spring and Friction plate, which complete vehicle component modeling, simulate for vehicle model running, and prepare for the dynamic calculation.

Create the solid model according to the associated sign of the given two ends. If the relative marker position changes, the shape and position or orientation of the model can be adjusted. It has basic functions of three-dimensional simulation.

Four categories have their own "dynamic" property pages. Every category has its corresponding variable receiving and data transformation which prepare initial data for dynamics solver.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 247

Fig. 5-6. Model the railway vehicle (simplified model, import model)

Fig. 5-7. Model the railway vehicle (obtained from the design drawing, import the model

with 1:1)

Components of four categories are stress-carrying parts and are built by inheriting the CForceElement in the virtual prototype system. In order to facilitate the unified management of data, four categories created by this module are added to the CForceElementList chain, and also to the ObjectList chain for the visualization need.

Fig. 5-4. Define railway vehicle model

Associated structure layers are shown in Fig. 5-5.

Fig. 5-5. Associated structure of the railway vehicle

A railway vehicle multi-body system model can be generated rapidly according to the above description. The defined model is shown in Fig. 5-6, which is a simplified model. Fig. 5-7 shows that import models from the design.

Components of four categories are stress-carrying parts and are built by inheriting the CForceElement in the virtual prototype system. In order to facilitate the unified management of data, four categories created by this module are added to the

CForceElementList chain, and also to the ObjectList chain for the visualization need.

Fig. 5-4. Define railway vehicle model

Associated structure layers are shown in Fig. 5-5.

Fig. 5-5. Associated structure of the railway vehicle

shows that import models from the design.

A railway vehicle multi-body system model can be generated rapidly according to the above description. The defined model is shown in Fig. 5-6, which is a simplified model. Fig. 5-7

Fig. 5-6. Model the railway vehicle (simplified model, import model)

Fig. 5-7. Model the railway vehicle (obtained from the design drawing, import the model with 1:1)

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 249

Render various independent parts of the model with difference colours, output

them as 3DS format.

Build the virtual prototype model in CAXA

Add EDO to the model to extract the properties, define it as rigid body, marker, force, force element

Fig. 6-2. Analysis flow of the railway vehicle virtual prototype

dynamic calculation

Assemble the whole model, select the whole vehicle model, update the database, output the property file

necessary.

product optimization process and intelligent design process.

achieved.

**6.2 A case process study of railway vehicle virtual prototype**

The process is actually obtained directly from the virtual prototype → properties extraction of the multi-body system model →transition of geometrical and physical model of multibody systems → multi-body systems visualization modeling and mathematical modeling building → kinematics and dynamics solving of the multi-body system. This process is like mechanical system product development process, reflecting the integrated process from design model to analysis model, then to solve model, and reflecting the cycle iteration in product design process. This process supplies a theoretical and practical basis for study of

Import CAXA model, read geometry model data and

Modify the model property necessary

Dynamic calculation

Visualization of the simulation and

property data simultaneously.

Since the system is more complex, in order to obtain more significant technical route, the railway vehicle design model is simplified. The railway vehicle virtual prototype process is

### **5.3 Multi-body system analysis**

The model established includes variety data for analysis of multi-body systems. After transiting to analysis model, multi-body analysis will be done by analysis module. Since the universality of the model and plug-in nature of the multi-body analysis module, many solvers can be used to compute for common mechanical multi-body system, such as Adams, Simpack, etc. For railway vehicle multi-body system, because of the field specialization, a specialized analysis module is needed to do analysis, such as Adams / Rail, railway vehicle part of Simpack. A software system is self-developed such as TPLdyna, VSDS. TPLdyna is developed by State Key Laboratory of Power Traction of Southwest Jiaotong Universtiy. VSDS is developed by Dr. Jue Wang of SWJTU. They both have multi-body system features but have different solvers. This study supplies the model interface to them. Here especially supports Dr. Jue Wang'VSDS, see Fig.6.10-14.

### **6. A case study of railway vehicle virtual prototype oriented to the multi-body system**

### **6.1 Analysis idea**

According to the modeling method above, space topology structure of the railway vehicle is shown in Fig. 6-1. B1 is car, B2 and B3 are frameworks, B4-B7 are wheelsets, B8 is track, FE1- FE6 are force elements, F1-F4 are wheel-track contact forces. Defining the force element, hinge and external force as directional has two aims: First, defining one of two adjacent objects as a reference object is to describe the relative movement of another. Second, it aims to define the positive direction of applied force and reacted force between the adjacent objects.

Fig. 6-1. Topology description of the railway vehicle multi-body system

To accomplish the railway vehicle virtual prototype analysis, take multi-body system analysis as an example, the processing description is shown in Fig. 6-2.

The model established includes variety data for analysis of multi-body systems. After transiting to analysis model, multi-body analysis will be done by analysis module. Since the universality of the model and plug-in nature of the multi-body analysis module, many solvers can be used to compute for common mechanical multi-body system, such as Adams, Simpack, etc. For railway vehicle multi-body system, because of the field specialization, a specialized analysis module is needed to do analysis, such as Adams / Rail, railway vehicle part of Simpack. A software system is self-developed such as TPLdyna, VSDS. TPLdyna is developed by State Key Laboratory of Power Traction of Southwest Jiaotong Universtiy. VSDS is developed by Dr. Jue Wang of SWJTU. They both have multi-body system features but have different solvers. This study supplies the model interface to them. Here especially

**6. A case study of railway vehicle virtual prototype oriented to the multi-body**

According to the modeling method above, space topology structure of the railway vehicle is shown in Fig. 6-1. B1 is car, B2 and B3 are frameworks, B4-B7 are wheelsets, B8 is track, FE1- FE6 are force elements, F1-F4 are wheel-track contact forces. Defining the force element, hinge and external force as directional has two aims: First, defining one of two adjacent objects as a reference object is to describe the relative movement of another. Second, it aims to define the positive direction of applied force and reacted force between the adjacent

Fig. 6-1. Topology description of the railway vehicle multi-body system

analysis as an example, the processing description is shown in Fig. 6-2.

To accomplish the railway vehicle virtual prototype analysis, take multi-body system

**5.3 Multi-body system analysis**

supports Dr. Jue Wang'VSDS, see Fig.6.10-14.

**system**

objects.

**6.1 Analysis idea**

Fig. 6-2. Analysis flow of the railway vehicle virtual prototype

The process is actually obtained directly from the virtual prototype → properties extraction of the multi-body system model →transition of geometrical and physical model of multibody systems → multi-body systems visualization modeling and mathematical modeling building → kinematics and dynamics solving of the multi-body system. This process is like mechanical system product development process, reflecting the integrated process from design model to analysis model, then to solve model, and reflecting the cycle iteration in product design process. This process supplies a theoretical and practical basis for study of product optimization process and intelligent design process.

### **6.2 A case process study of railway vehicle virtual prototype**

Since the system is more complex, in order to obtain more significant technical route, the railway vehicle design model is simplified. The railway vehicle virtual prototype process is achieved.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 251

4. For marker, the extracted information includes components, location and relative coordinate transformation matrix of the component coordinate system. Achievement of

extraction is shown in Fig.6-5.

Fig. 6-5. Physical property extraction

Fig. 6-6. Obtain the marker information

the marker information is shown in Fig. 6-6.

displacement, velocity, etc. it should be entered manually. The physical property

1. Build the railway vehicle virtual prototype model in CAXA as shown in Fig. 6-3 and Fig. 6-4.

Fig. 6-3. Design model in CAXA

Fig. 6-4. COM interface added design model

displacement, velocity, etc. it should be entered manually. The physical property extraction is shown in Fig.6-5.

Fig. 6-5. Physical property extraction

250 Modeling and Simulation in Engineering

1. Build the railway vehicle virtual prototype model in CAXA as shown in Fig. 6-3 and

Fig. 6-4.

Fig. 6-3. Design model in CAXA

Fig. 6-4. COM interface added design model

"physical property output", to view or add properties.

2. Add EDO on the model to extract the model property. Then click the right key

3. For components, it is required to extract attribute mass, inertia, coordinate transformation matrix, space location and etc. For initial state such as initial 4. For marker, the extracted information includes components, location and relative coordinate transformation matrix of the component coordinate system. Achievement of the marker information is shown in Fig. 6-6.

Fig. 6-6. Obtain the marker information

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 253

9. Check the accuracy of the data imported, perfect some incomplete information. Test results show that the model is resumed completely and property data is right. The data meets the dynamics and simulation requirements. Then transition of model to

10. Load the track, set the measure variables and simulation parameters, and prepare for the dynamics calculation and simulation. Post-processing of the analysis module is

Fig. 6-8. Model resuming and checking in analysis view

performance analysis module is shown in Fig.6-9.

Fig. 6-9. Transition of model to performance analysis module

shown in Fig.6-10.

5. For force element (spring, damper, friction plate and rod), extracted information includes connected components and marker point which is to fix the position and orientation of the component. Multi-body topology relation from design model is shown in Fig. 6-7.

Fig. 6-7. Multi-body topology relation from design model

	- a. Render various independent parts of the model with difference colors.
	- b. Output files as 3DS format! file name and path should be the same with property data.

By operations above, model in CAXA and property extraction has been finished.

8. Import the CAXA model and property data. The model can be recovered in VirtualMBS, and it maps the multi-body system topology relationship of railway vehicle. The catalog tree in the left clearly expresses space layer structure and mutual dependence of multi-body system. The model resuming and checking in analysis view is shown in Fig. 6-8.

5. For force element (spring, damper, friction plate and rod), extracted information includes connected components and marker point which is to fix the position and orientation of the component. Multi-body topology relation from design model is

6. Output the property database. The extracted property has been written into the database after the operation above. The subsequent job is to assemble the whole prototype, clicking to update the database, then clicking to output the property

b. Output files as 3DS format! file name and path should be the same with property

8. Import the CAXA model and property data. The model can be recovered in VirtualMBS, and it maps the multi-body system topology relationship of railway vehicle. The catalog tree in the left clearly expresses space layer structure and mutual dependence of multi-body system. The model resuming and checking in analysis view

shown in Fig. 6-7.

Fig. 6-7. Multi-body topology relation from design model

7. Output the geometric model. Two points should be paid attention to:

a. Render various independent parts of the model with difference colors.

By operations above, model in CAXA and property extraction has been finished.

data to the certain position.

data.

is shown in Fig. 6-8.

Fig. 6-8. Model resuming and checking in analysis view

9. Check the accuracy of the data imported, perfect some incomplete information. Test results show that the model is resumed completely and property data is right. The data meets the dynamics and simulation requirements. Then transition of model to performance analysis module is shown in Fig.6-9.

Fig. 6-9. Transition of model to performance analysis module

10. Load the track, set the measure variables and simulation parameters, and prepare for the dynamics calculation and simulation. Post-processing of the analysis module is shown in Fig.6-10.

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 255

11. Dynamics calculation results and simulation. Given speed is 65km/h and straight length is 30.78m, when the simulation period is 0.389s, vehicle enters the curve segment, and runs stably. Realtime simulation of the railway vehicle dynamics based

Fig. 6-11. Realtime simulation of the railway vehicle dynamics based on 3-D visualization During the process the tension and pressure fz of the measured variable Spring0 and the

total wheel force Tz0 are shown in Fig. 6-12. The red is for fz, the green is for Tz0.

on 3-D visualization is shown in Fig.6-11.

Fig. 6-12. Calculation results

 a) Post-processing module definition of the analysis module (two-dimensional data visualization)

of the analysis module

Fig. 6-10. Post-processing of the analysis module

 a) Post-processing module definition of the analysis module (two-dimensional data visualization)

> b) Simulation parameter definition of the analysis module

Fig. 6-10. Post-processing of the analysis module

11. Dynamics calculation results and simulation. Given speed is 65km/h and straight length is 30.78m, when the simulation period is 0.389s, vehicle enters the curve segment, and runs stably. Realtime simulation of the railway vehicle dynamics based on 3-D visualization is shown in Fig.6-11.

Fig. 6-11. Realtime simulation of the railway vehicle dynamics based on 3-D visualization

During the process the tension and pressure fz of the measured variable Spring0 and the total wheel force Tz0 are shown in Fig. 6-12. The red is for fz, the green is for Tz0.

Fig. 6-12. Calculation results

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 257

Fig. 6-15. Partial view

Fig. 6-16. Model with coordinate system

Other visualized results of this system are as follows:

Fig. 6-13. Wheel-track force of left wheel of the wheelset 2

Fig. 6-14. Analysis space scene

Fig. 6-15. Partial view

Other visualized results of this system are as follows:

Fig. 6-13. Wheel-track force of left wheel of the wheelset 2

Fig. 6-14. Analysis space scene

Fig. 6-16. Model with coordinate system

Oriented Multi-Body System Virtual Prototyping Technology for Railway Vehicle 259

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### **7. Summary**

According to the study above, the technology from virtual prototype design-prototype property extraction-analysis model established based on the multi-body system-transition from multi-body system design model to multi-body system analysis model, analysis solution of multi-body system-data visualization, is initially proved, which embodies the product design process. It can be promoted to other CAE analysis module, and it supplies detailed basic research theory and techniques for railway vehicle virtual prototype platform independent researches.

### **8. Acknowledgment**

This work is supported by the National Natural Science Foundation of China (NSFC) under Grant 50975240 and by the Youth Fund of Sichuan Province under Grant 09ZQ026-003 and the Fundamental Research Funds for the Central Universities under Grant SWJTU09ZT06, and New Century Excellence Plan Grand NCET-09-0665. In this works, VSDS computation module is used for testify the procedure, which is developed by Dr. Jue Wang. Thanks for his work.

### **9. References**

1. Through analyzing the current virtual prototyping patterns, the framework of railway

2. The follow-up property extraction of analysis module is put into the three-dimensional CAD environment to ensure the uniformity of analysis model and prototype model. 3. The whole process of transition form prototype model to analysis model for virtual

4. In order to check the series theory proposed, take a certain railway vehicle model design as an example, a case study is done in the developed software to check the

According to the study above, the technology from virtual prototype design-prototype property extraction-analysis model established based on the multi-body system-transition from multi-body system design model to multi-body system analysis model, analysis solution of multi-body system-data visualization, is initially proved, which embodies the product design process. It can be promoted to other CAE analysis module, and it supplies detailed basic research theory and techniques for railway vehicle virtual prototype platform

This work is supported by the National Natural Science Foundation of China (NSFC) under Grant 50975240 and by the Youth Fund of Sichuan Province under Grant 09ZQ026-003 and the Fundamental Research Funds for the Central Universities under Grant SWJTU09ZT06, and New Century Excellence Plan Grand NCET-09-0665. In this works, VSDS computation module is used for testify the procedure, which is developed by Dr. Jue Wang. Thanks for

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**8. Acknowledgment**

his work.

**9. References**

**7. Summary**

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**0**

**11**

*Germany*

**Enabling and Analyzing Natural Interaction with**

Functional validations of virtual prototypes are a promising application area of immersive Virtual Reality (Moehring & Froehlich, 2011). Through the interactive simulation of operating procedures such analyses aim at providing insight about virtual prototypes, e. g. concerning visibility aspects, reachability of control elements, and ergonomics. A key requirement is the enabling of *natural interaction* defined by Zachmann as *"interaction which imitates that same interaction in the real world as close as possible"* (Zachmann & Rettig, 2001). In immersive VR,

However, a challenging task remains in the modeling and simulation of interactions with dynamic control elements such as sliders, switches etc. (Moehring & Fröhlich, 2010). We have devised and implemented a framework that not only aims at simplifying the specification of such *control actuators* for interactive virtual environments but also facilitates the recording, automated classification, and analysis of natural interactions with such control actuators. The presented approach builds on the European Standard EN 894-3 (DIN894-3, 2006) and covers all types of control actuators defined therein. This standard defines systematic guidelines for

A characterizing feature of control actuators in the real world is given by their function: Controlling the behavior of machines and other appliances. In order to model the triggering of changes of environment objects in the simulation, our framework allows to associate control actuators with *interaction events*. Interaction events may be fired continuously, e. g. during movement of sliders, or when discrete states are reached, e. g. switches. Besides making interactive simulations more realistic, interaction events can also be recorded to allow later playback and analysis of the interaction. For this, detailed timing information is stored in the interaction events. For example, interaction events may be used for the animation of virtual

Contributions of our research include an XML-based modeling language for control actuators that can be seen as both an abstraction layer and an extension to lower-level rigid body physics modeling capabilities provided e. g. by Collada (Khronos Group, 2008) and X3D (International Organization for Standardization, 2008). Further, we produce a reference implementation of control actuators with direct object manipulation, an interaction database for analyzing interaction events including recognizing basic interactions and grasp classification, and a powerful graphical analysis tool. Through this, the process of adding

natural interaction can be realized through data gloves and motion tracking devices.

the choice and configuration of control actuators to ergonomically design machinery.

humans that imitate the user interactions when operating virtual prototypes.

interactive elements to virtual prototypes can be drastically simplified.

**1. Introduction**

**Functional Virtual Prototypes**

Matthias Lenk and Arnd Vitzthum *Technical University Bergakademie Freiberg*

Frank Gommlich, Guido Heumer, Bernhard Jung,

Vehicle Simulators for Prototyping, Training and Ergonomics. *Proceedings of the Computer Graphics International*.

Ronald, D. Williams & Robert, H. Klenke. (2003). Teaching Computer Design Using Virtual Prototyping. *IEEE Transactions on education*, Vol. 46, No. 2.

### **Enabling and Analyzing Natural Interaction with Functional Virtual Prototypes**

Frank Gommlich, Guido Heumer, Bernhard Jung, Matthias Lenk and Arnd Vitzthum *Technical University Bergakademie Freiberg Germany*

### **1. Introduction**

260 Modeling and Simulation in Engineering

Ronald, D. Williams & Robert, H. Klenke. (2003). Teaching Computer Design Using Virtual

Prototyping. *IEEE Transactions on education*, Vol. 46, No. 2.

*Computer Graphics International*.

Vehicle Simulators for Prototyping, Training and Ergonomics. *Proceedings of the*

Functional validations of virtual prototypes are a promising application area of immersive Virtual Reality (Moehring & Froehlich, 2011). Through the interactive simulation of operating procedures such analyses aim at providing insight about virtual prototypes, e. g. concerning visibility aspects, reachability of control elements, and ergonomics. A key requirement is the enabling of *natural interaction* defined by Zachmann as *"interaction which imitates that same interaction in the real world as close as possible"* (Zachmann & Rettig, 2001). In immersive VR, natural interaction can be realized through data gloves and motion tracking devices.

However, a challenging task remains in the modeling and simulation of interactions with dynamic control elements such as sliders, switches etc. (Moehring & Fröhlich, 2010). We have devised and implemented a framework that not only aims at simplifying the specification of such *control actuators* for interactive virtual environments but also facilitates the recording, automated classification, and analysis of natural interactions with such control actuators. The presented approach builds on the European Standard EN 894-3 (DIN894-3, 2006) and covers all types of control actuators defined therein. This standard defines systematic guidelines for the choice and configuration of control actuators to ergonomically design machinery.

A characterizing feature of control actuators in the real world is given by their function: Controlling the behavior of machines and other appliances. In order to model the triggering of changes of environment objects in the simulation, our framework allows to associate control actuators with *interaction events*. Interaction events may be fired continuously, e. g. during movement of sliders, or when discrete states are reached, e. g. switches. Besides making interactive simulations more realistic, interaction events can also be recorded to allow later playback and analysis of the interaction. For this, detailed timing information is stored in the interaction events. For example, interaction events may be used for the animation of virtual humans that imitate the user interactions when operating virtual prototypes.

Contributions of our research include an XML-based modeling language for control actuators that can be seen as both an abstraction layer and an extension to lower-level rigid body physics modeling capabilities provided e. g. by Collada (Khronos Group, 2008) and X3D (International Organization for Standardization, 2008). Further, we produce a reference implementation of control actuators with direct object manipulation, an interaction database for analyzing interaction events including recognizing basic interactions and grasp classification, and a powerful graphical analysis tool. Through this, the process of adding interactive elements to virtual prototypes can be drastically simplified.

(a) Fitting (b) Actuator (c) Control Actuator

Enabling and Analyzing Natural Interaction with Functional Virtual Prototypes 263

Fig. 2. Composition of a control actuator. Each control actuator consists of a fitting and at

Fig. 3. The XML schema for annotated objects within our framework.

The element *physics* and its subelement *joint* (see figure 3) contains the major characteristics of control actuators regarding their representation in the dynamics simulation. The fitting references one or more actuators with the *children* element. These actuators are also annotated objects with the difference that they have specified information about *joint*s and their constraints. A joint definition contains at least the joint type (e. g. DoubleAxisHinge for a joystick, or Slider for a volume control), the specification of the DOF axes and the constraints

In case of discrete actuators it is necessary to define at least one discrete state which is represented by an angular or translational offset from the neutral position. Additional it is possible to specify unsteady intermediate states. When a control actuator reaches an unsteady state, it will automatically move to a defined successor state. This is useful for realizing complex actuator movements, e. g. a gear shift. Figure 4 shows the gears of a car with steady gear states and intermediate discrete states. States A and B are unsteady with 5 as the successor state. Listing 1 shows an example for discrete states of an actuator definition. It proved possible to implement all presented control actuators in the European standard EN 894-3 with at most two DOFs for either translation or rotation. A combination or mixture of

least one actuator.

along these axes.

Fig. 1. Selection of control actuators defined in the European standard EN 894-3.

### **2. Control actuators**

This subchapter introduces the concept of control actuators, our XML based modeling language and a reference implementation of control actuators. An easy way to include different control actuators into a dynamic environment is to use an extended version of annotated objects (Weber et al., 2006). They are declared and managed in an XML-based representation structure, which combines all information about types of scene objects in a common database. Such information includes graphical model, type, component references, physical parameters, joint definitions, etc. Annotated objects are similar to the concept of smart objects (Kallmann & Thalmann, 1999). In contrast to smart objects, they do not contain any form of behavior description, neither for object nor for actor behavior. The object behavior of annotated objects is totally dependent on their physical simulation.

### **2.1 Concept**

Structurally, control actuators are compound objects where a movable part can change its position or orientation w.r.t. a static part, the fitting. The relative movement is constrained by the degrees of freedom (DOFs) of a joint connecting the static and the movable part. Here, the composition of both is called control actuator. In Figure 2 an emergency button is shown. In this example the button takes the role of the actuator. Multiple actuators with the same fitting are also conceivable and are used, e. g., in the case of cockpit instruments, keyboards or other operational controls. Thus, control actuators share many similarities with rigid bodies from the Collada and X3D specifications. However, the definition of control actuators requires additional capabilities not available in basic Collada or X3D. In particular, many types of control actuators such as switches and gear shifts exhibit lock states which correspond to discrete values along a continuous DOF of joints. A control actuator will snap to a discrete state when no further force is exerted on the actuator.

Our concept of control actuators covers all types of control actuators and guidelines defined in the European standard EN 894-3 (see fig. 1).

### **2.2 Declaration**

Annotated objects with their attributes are represented in a compact and easy to use XML structure. To check the correct syntax of annotated objects and their actuators there is an XML schema. To ensure extensibility of the format, all object attributes are denoted by an all-purpose parameter format consisting of name, type and value, represented by the *param* element.

2 Will-be-set-by-IN-TECH

Fig. 1. Selection of control actuators defined in the European standard EN 894-3.

of annotated objects is totally dependent on their physical simulation.

state when no further force is exerted on the actuator.

in the European standard EN 894-3 (see fig. 1).

This subchapter introduces the concept of control actuators, our XML based modeling language and a reference implementation of control actuators. An easy way to include different control actuators into a dynamic environment is to use an extended version of annotated objects (Weber et al., 2006). They are declared and managed in an XML-based representation structure, which combines all information about types of scene objects in a common database. Such information includes graphical model, type, component references, physical parameters, joint definitions, etc. Annotated objects are similar to the concept of smart objects (Kallmann & Thalmann, 1999). In contrast to smart objects, they do not contain any form of behavior description, neither for object nor for actor behavior. The object behavior

Structurally, control actuators are compound objects where a movable part can change its position or orientation w.r.t. a static part, the fitting. The relative movement is constrained by the degrees of freedom (DOFs) of a joint connecting the static and the movable part. Here, the composition of both is called control actuator. In Figure 2 an emergency button is shown. In this example the button takes the role of the actuator. Multiple actuators with the same fitting are also conceivable and are used, e. g., in the case of cockpit instruments, keyboards or other operational controls. Thus, control actuators share many similarities with rigid bodies from the Collada and X3D specifications. However, the definition of control actuators requires additional capabilities not available in basic Collada or X3D. In particular, many types of control actuators such as switches and gear shifts exhibit lock states which correspond to discrete values along a continuous DOF of joints. A control actuator will snap to a discrete

Our concept of control actuators covers all types of control actuators and guidelines defined

Annotated objects with their attributes are represented in a compact and easy to use XML structure. To check the correct syntax of annotated objects and their actuators there is an XML schema. To ensure extensibility of the format, all object attributes are denoted by an all-purpose parameter format consisting of name, type and value, represented by the *param*

**2. Control actuators**

**2.1 Concept**

**2.2 Declaration**

element.

Fig. 2. Composition of a control actuator. Each control actuator consists of a fitting and at least one actuator.

Fig. 3. The XML schema for annotated objects within our framework.

The element *physics* and its subelement *joint* (see figure 3) contains the major characteristics of control actuators regarding their representation in the dynamics simulation. The fitting references one or more actuators with the *children* element. These actuators are also annotated objects with the difference that they have specified information about *joint*s and their constraints. A joint definition contains at least the joint type (e. g. DoubleAxisHinge for a joystick, or Slider for a volume control), the specification of the DOF axes and the constraints along these axes.

In case of discrete actuators it is necessary to define at least one discrete state which is represented by an angular or translational offset from the neutral position. Additional it is possible to specify unsteady intermediate states. When a control actuator reaches an unsteady state, it will automatically move to a defined successor state. This is useful for realizing complex actuator movements, e. g. a gear shift. Figure 4 shows the gears of a car with steady gear states and intermediate discrete states. States A and B are unsteady with 5 as the successor state. Listing 1 shows an example for discrete states of an actuator definition.

It proved possible to implement all presented control actuators in the European standard EN 894-3 with at most two DOFs for either translation or rotation. A combination or mixture of

Listing 1. XML code example of an emergency button, shown in figure 2.

Enabling and Analyzing Natural Interaction with Functional Virtual Prototypes 5

Enabling and Analyzing Natural Interaction with Functional Virtual Prototypes 265

<param name="jointtype" type="string">slider</param> <param name="pinDir" type="array3">0 0 -1</param> <param name="minValue" type="double">0</param> <param name="maxValue" type="double">0.1</param>

<param name="name" type="string">deactivated</param>

<param name="name" type="string">activated</param> <param name="value" type="double">0.05</param>

<param name="value" type="double">0</param>

<child type="string">emergencyActuator</child>

<annotatedobject>

<children>

</children> </annotatedobject> <annotatedobject>

> <physics> <joint>