*Article* **Effect of Interior Space and Window Geometry on Daylighting Performance for Terrace Classrooms of Universities in Severe Cold Regions: A Case Study of Shenyang, China**

**Yingjie Jia, Zheming Liu \*, Yaoxuan Fang, Huiying Zhang, Caiyi Zhao and Xuqiang Cai**

Jangho Architecture College, Northeastern University, Shenyang 110819, China **\*** Correspondence<EMAIL_ADDRESS>
**Abstract:** Good daylighting performance positively affects students' physical and mental health, learning efficiency, and the building's energy-saving capability. Due to the terrace classroom having ample space, large capacity, the ability to avoid obstructing sight, and the ability to meet various use needs, it is the most important place in university buildings. However, research on the daylighting performance of university terrace classrooms is limited, leading to a lack of quantitative guidance in early design stages. This study aims to explore the effects of interior space and window geometry of terrace classrooms in universities in severe cold regions on daylighting performance. This research took Shenyang as an example; spatial daylight autonomy (sDA300,50%) and useful daylight illuminance (UDI100–2000) were selected as daylighting performance evaluation indices. Based on the Grasshopper parametric platform, the simulation was carried out using Ladybug and Honeybee plugins. Correlation and regression analyses revealed the relationship between interior space and window geometry parameters and the evaluation indices. The results showed the following: window-to-floor ratio (WFR), classroom height (Htc), window height (Hw), window-to-wall ratio (WWR), classroom width (Wtc), and window width (Ww) have positive effects on improving the daylight sufficiency of the terrace classrooms facing each orientation, and the degree of the effect decreases in order. To ensure the overall daylighting performance, the Wtc can be maximized. The width of walls between windows for south-facing and west-facing classrooms should be 0.9 m. The WWR and WFR for south-facing classrooms should be 0.3–0.5 and 0.11–0.14, respectively. The WWR and WFR for north-facing classrooms should be 0.6–0.7 and 0.14–0.20, respectively. Prediction models are established for the sDA300,50% and UDI100–2000 of the terrace classrooms facing each orientation.

**Keywords:** daylighting performance; terrace classrooms; interior space geometry; window geometry; severe cold regions


**Author details**

Sie Long Kek1\*, Kok Lay Teo2 and Mohd Ismail Abd Aziz3

\*Address all correspondence to<EMAIL_ADDRESS>
1 Center for Research in Computational Mathematics, Universiti Tun Hussein Onn Malaysia, Parit Raja, Malaysia

2 Department of Mathematics and Statistics, Curtin University of Technology, Perth, WA, Australia

3 Department of Mathematical Sciences, Universiti Teknologi Malaysia, UTM, Skudai, Ma‐ laysia

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#### **Design, Analysis, and Applications of Iterative Methods for Solving Nonlinear Systems Design, Analysis, and Applications of Iterative Methods for Solving Nonlinear Systems Design, Analysis, and Applications of Iterative Methods for Solving Nonlinear Systems**

Alicia Cordero, Juan R. Torregrosa and Maria P. Vassileva Alicia Cordero, Juan R. Torregrosa and Alicia Cordero, Juan R. Torregrosa and Maria P. Vassileva

Additional information is available at the end of the chapter Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/64106

#### **Abstract**

In this chapter, we present an overview of some multipoint iterative methods for solving nonlinear systems obtained by using different techniques such as composition of known methods, weight function procedure, and pseudo-composition, etc. The dynamical study of these iterative schemes provides us valuable information about their stability and reliability. A numerical test on a specific problem coming from chemistry is performed to compare the described methods with classical ones and to confirm the theoretical results.

**Keywords:** system of nonlinear equations, iterative methods, order of convergence, weight function procedure, stability, basin of attraction


*4.2. Data Collection*

The procedure for the case selection was as follows: Korea's rebar production plant in Anseong, Gyeonggi-do, was chosen for model development, and a visit there was planned. With over 100 building sites in its delivery history, this plant can be considered to have a solid process. We then described the machine. The elements appropriate for the underconsideration situation were found among the different machine-specific characteristics of the rebar fabrication process described in the preceding section. Table 3 provides a summary of the characteristics of the hoists, cutters, and benders employed as resources in the simulation. The machine characteristics that have an impact on the processing times and loss rates were configured as parameters and applied to the simulation model. By adjusting the settings in accordance with the characteristics of each piece of machine, the loss rate and necessary time were discovered. The varieties of rebar required at various places were then identified. Table 4 provides a summary of the information introduced in the simulation of the rebar fabrication process based on the data of the real rebar length and number of cuts.

#### **Table 3.** Machine features.

**Table 4.** Rebar types for each site.