*2.1. Materials*

Two types of alumina ceramic samples were fabricated. The first type, dense ceramic specimens, investigated how the hot isostatic pressure sintering application affects ceramic surface roughness. Then, the dense ceramic specimens were treated with the silane coupling agent and measurements of the contact angle, and shear tests of adhesive joints were carried out. In the second type of sample, porous ceramic preforms were applied to ceramic– elastomer composites fabrication and then was analyzed how the coupling agent affected their microstructure, residual porosity, and compressive strength as well as stress at the plateau. Moreover, porous ceramic preforms were tested using X-ray tomography and a strength testing machine. All the material fabrication processes carried out are shown schematically in Figure 1.

The dense alumina ceramic samples were prepared by the three-step or four-step methods. First, the pre-compaction process of Granulox NM9922 (Nabaltec AG, Schwandorf, Germany) alumina granulate in steel molds by uniaxial pressing at a working pressure of 200 MPa was conducted. Secondly, the samples were densified into green bodies by cold isostatic pressing (CIP) under a pressure of 200 MPa for 1 min. Next, the free sintering process (pressureless sintering) was carried out in a Nabertherm HT 08/18 electric chamber furnace (Nabertherm, Lilienthal, Germany). An air inert atmosphere was used. After reaching 1600 ◦C, the samples were heated for 2 h to get rid of organic binders contained in the pressed shape. The samples produced by the three-step method were designated

Al2O3-SS. A part of the samples marked Al2O3-HIP200 was additionally treated by HIP process under a pressure of 200 MPa in an argon atmosphere at 1600 ◦C for 1 h.

**Figure 1.** Scheme of materials fabrication processes: (**a**) dense ceramics fabrication, (**b**) porous ceramics preform production, (**c**) composite fabrication, respectively.

The urea–urethane elastomers (PU2.5) were synthesized by a one-shot method from 4,4-methylenebis(phenylisocyanate) (MDI), poly(ethylene adipate) PEA, and dicyandiamide (DCDA). The molar ratio of MDI to (PEA + DCDA) substrates was equal to 2.5 (which means a hard to soft segments ratio equal to 1.50).

The porous ceramic preforms applied for the infiltration process were fabricated using the same methods as dense ceramic samples. However, to obtain open porous preforms, the alumina powders supplied by the P.P.U.H.KOS company were mixed with 10–15 wt% of Granulox NM9922 (Nabaltec AG, Schwandorf, Germany) high-temperature ceramic binder and 7 wt% of dextrin solution as pore structure forming agent. Two different sizes of alumina powders were used to fabricate ceramic preforms with different values of porosity. As a result of an application of alumina powder with 300–100 μm and 1200–1000 μm size, preforms with 20% and 40% porosities were produced, respectively. After the preparation of two types of ceramic mixtures, they were inserted into steel forms and molded by uniaxial pressing at a working pressure of 100 MPa. In the next step, the pre-sintering of semi-finished preforms was performed using an electric chamber furnace. Finally, to enhance mechanical properties and increase the density of ceramic preforms, hot isostatic pressing was conducted under 200 MPa pressure in argon at 1600 ◦C temperature for 1 h.

The ceramic–elastomer composites were made by the infiltration of the ceramic preforms with 20 vol% and 40 vol% porosity by a reactive mixture of urea–urethane elastomers in the liquid form. The infiltration was carried out under subatmospheric pressure.

The coupling agents can be used in two ways. In general, the surface of ceramics before infiltration by a polymer is covered by the solution of the coupling agents [11,14]. It was claimed that the most satisfying results were achieved when the agents were dissolved

in benzene, toluene, and alcohol in an amount of not more than 10% by weight. In the case of ceramic–polymer composites, to cover the pore surfaces thoroughly, it is recommended to apply pressure pre-infiltration of the ceramic preforms by a coupling agent. Then, the process of drying the preform is used. This type of sample preparation is characterized by high durability and resistance during storage. The disadvantage of this method is the need to introduce into the fabrication process an additional step consisting of coating the ceramic preform with a coupling agent. Another way of applying the coupling agent is by adding it to the reactive mixture of polymer before filling the ceramic pores. During infiltration, the coupling agent migrates to the phase boundaries, acting as an adhesion promoter. The advantage of this method is the ease of implementation. However, there are several problems regarding the stability of the agent and the durability of its conjunction with the polymer, due to the presence of moisture in the system. Moreover, it was observed that a higher amount of coupling agent should be used, because a significant part of it does not reach the interface and remains in the "mass" of the polymer [10].

In this work, a Unisilan U-15 silane coupling agent (UNISIL Company, Tarnów, Poland) was applied. The U-15 Unisilan with the chemical name N-2-aminoethyl-3aminopropyltrimethoxysilane is mainly used as a coupling agent to inorganic fillers in composites based on acrylic polymer, epoxy resin, vinyl polymer, and polyamide, polyether, polyurethane, silicone. A U-15 silane coupling agent was applied directly to the ceramic surface. Dense ceramic samples, as well as porous ceramic preforms, were immersed in the solution of 1 wt% and 5 wt% U-15 agent in toluene for 5 s. Next, the samples were placed in an oven for 2 h at 120 ± 5 ◦C under a vacuum to evaporate the toluene. Next, the temperature was reduced to about 80 ◦C and the samples were heated for another 18 h.


D.N. (2008). Nutrition in clinical practice - the refeeding syndrome**:** illustrative cases and guidelines for prevention and treatment. *Eur J Clin Nutr,* 62: 687-94. Tonoike, T., Takahashi, T., Watanabe, H., Kimura, H., Suwa, M., Akaho. & Itaku, Y. (2004).

Treatment with intravenous hyperalimentation for severely anorectic patients and

voluntary nasogastric tube feeding in female inpatients with anorexia nervosa.

### *Edited by Ignacio Jáuregui-Lobera*

Eating disorders are common, frequently severe, and often devastating pathologies. Biological, psychological, and social factors are usually involved in these disorders in both the aetiopathogeny and the course of disease. The interaction among these factors might better explain the problem of the development of each particular eating disorder, its specific expression, and the course and outcome. This book includes different studies about the core concepts of eating disorders, from general topics to some different modalities of treatment. Epidemiology, the key variables in the development of eating disorders, the role of some psychosocial factors, as well as the role of some biological influences, some clinical and therapeutic issues from both psychosocial and biological points of view, and the nutritional evaluation and nutritional treatment, are clearly presented by the authors of the corresponding chapters. Professionals such as psychologists, nurses, doctors, and nutritionists, among others, may be interested in this book.

Photo by Foxys\_forest\_manufacture / iStock

Relevant topics in Eating Disorders

Relevant topics in

Eating Disorders

*Edited by Ignacio Jáuregui-Lobera*


**Yang Li 1,2,\* and Xuewei Chao 1**

Received: 13 April 2020; Accepted: 15 May 2020; Published: 18 May 2020

**Abstract:** In the area of plant protection and precision farming, timely detection and classification of plant diseases and crop pests play crucial roles in the management and decision-making. Recently, there have been many artificial neural network (ANN) methods used in agricultural classification tasks, which are task specific and require big datasets. These two characteristics are quite different from how humans learn intelligently. Undoubtedly, it would be exciting if the models can accumulate knowledge to handle continual tasks. Towards this goal, we propose an ANN-based continual classification method via memory storage and retrieval, with two clear advantages: Few data and high flexibility. This proposed ANN-based model combines a convolutional neural network (CNN) and generative adversarial network (GAN). Through learning of the similarity between input paired data, the CNN part only requires few raw data to achieve a good performance, suitable for a classification task. The GAN part is used to extract important information from old tasks and generate abstracted images as memory for the future task. Experimental results show that the regular CNN model performs poorly on the continual tasks (pest and plant classification), due to the forgetting problem. However, our proposed method can distinguish all the categories from new and old tasks with good performance, owing to its ability of accumulating knowledge and alleviating forgetting. There are so many possible applications of this proposed approach in the agricultural field, for instance, the intelligent fruit picking robots, which can recognize and pick different kinds of fruits; the plant protection is achieved by automatic identification of diseases and pests, which can continuously improve the detection range. Thus, this work also provides a reference for other studies towards more intelligent and flexible applications in agriculture.

**Keywords:** similarity; metric; memory; deep learning


**1. Introduction**

After carbon dioxide (CO2), ethanol and glycerol are the most abundant compounds produced during alcoholic fermentation. The levels of ethanol and glycerol in wine depend upon many factors, such as seasonal events affecting the concentration of grape sugar, and winemaking decisions, including fermentation conditions and fermenting yeasts [1].

At a commercial scale, inoculations with *Saccharomyces cerevisiae* strains are often preferred over those with non-*Saccharomyces* or *S.* non-*cerevisiae* yeasts, because the latter is considered responsible for incomplete fermentations (and consequently high levels of residual sugar in wine), and they produce high concentrations of acetic acid and ethyl acetate [2,3]. Nevertheless, non-*Saccharomyces* or *S.* non-*cerevisiae* yeasts are important to winemakers, particularly to those who target wines with unique sensory characters that are popularly recognised as typical of their geographical origin or variety [4–7]. These yeasts are also popular among winemakers who choose to produce less alcoholic wines [8].

Although non-*Saccharomyces* and *S.* non-*cerevisiae* yeasts are sought after for their specific oenological characteristics, it is a challenge for some of these yeasts to conduct a complete fermentation

to a desired level of dryness. This is very important to winemakers, in part because finished wines with higher levels of residual sugars above 0.5 g/L require high doses of sulfur dioxide (SO2) to ensure their microbial stability to prevent wine spoilage. Therefore, inoculations of non-*Saccharomyces*/*S.* non-*cerevisiae* in mixed cultures with *S. cerevisiae* strains, which have higher fermentation rates, have been studied to ensure complete fermentation.

The strategy of using selected mixed cultures for alcoholic fermentation is believed to be the key to produce wines with desirable characteristics that meet changing market demands with less ethanol but still with flavours comparable to standard wines [9]. This strategy is carried out by two different methods of inoculation: (1) co-inoculation, which involves concurrent inoculations of non-*Saccharomyces*/*S.* non-*cerevisiae* yeasts at high cell concentration (e.g., 107 cell/mL) with *S. cerevisiae*; and/or (2) sequential inoculation, which involves inoculating non-*Saccharomyces*/*S.* non-*cerevisiae* yeasts to start the fermentation and continue for a determined amount of time alone, and inoculating *S. cerevisiae* to take over and complete the fermentation [9,10]. The time period before carrying out the sequential *S. cerevisiae* inoculation and the *Saccharomyces*/non-*Saccharomyces* or *Saccharomyces* non-*cerevisiae* inoculum ratio are both important parameters that affect the fermentation kinetics and oenological outcomes, and the former generally varies between 1 and 3 days [11–14].

Many reviews have studied different perspectives of non-*Saccharomyces*/*S.* non-*cerevisiae* yeasts for modern winemaking practices, including their influence on different wine quality parameters with an emphasis on traits such as the primary (or varietal) and secondary (or fermentative) aromas of wines, acidity, freshness, as well as specific styles of wines (such as traditional method sparkling wines and red table wines) [3,9,15–21].

The aim of this review is to highlight those studies that have shown a direct link between the use of non-*Saccharomyces* or *S.* non-*cerevisiae* and the concentration of ethanol and glycerol in wine or synthetic media. The first part of this review provides an overview of ethanol and glycerol as contributors to wine sensory characteristics, and a general overview of non-*S. cerevisiae* or *S.* non-*cerevisiae* yeasts. The second part of this review provides more specific details of individual non-*S. cerevisiae* or *S.* non-*cerevisiae* species that are relevant to the wine industry. We conclude this review by suggesting what additional research might help winemakers have greater control over wine quality outcomes.

## **2. Ethanol Reduction**

Ethanol is produced by yeast during the alcoholic fermentation and is generally found in the range of 11.5–15% *v*/*v* in wines. It is an important wine component that directly effects organoleptic properties, aging, and wine stability [22]. The impact of ethanol on the sensory profile of wines and other alcoholic beverages has been recently reviewed [23]. Ethanol influences taste and mouthfeel sensations, alters the sensation of sweetness, increases bitterness, decreases sourness, and contributes to the hotness sensation and body of the wine [24–27]. Ethanol can also decrease the volatility of aroma compounds by increasing their solubility in the wine [28], making small compounds such as fruity-driven ethyl esters and acetates less recognisable by human senses.

According to the International Organisation of Vine and Wine (OIV), the alcohol strength of wines must be a minimum of 8.5% *v*/*v*, although in cool climate wine regions, this value can be lowered to 7% *v*/*v* [29]. Over the past two decades, ethanol content in wines has been noticeably increasing in some regions by 0.1–1% per year [30,31]. Apart from hotter climates leading to higher sugar berry levels at harvest and therefore, higher alcohol contents in wine [32], one of the main reasons behind this progressive increase is consumer demand for specific wine styles, which are described as rich, well-structured, with a flavour profile dominated by dark, ripe fruits [33]. This style requires optimal grape maturity and higher sugar content of 240 g/L or more [34].

Nonetheless, an increasing trend for reduced alcohol in beverages (broadly defined as containing 9% to 13% *v*/*v* ethanol), and low-alcohol (0.5–2% *v*/*v*) wines by consumers has been recently observed [35,36]. Increasing health and safety consciousness and global initiatives towards moderating alcohol consumption are reasons for producing lower alcohol wines that appeal to wine drinkers [37]. Wines may also be subjected to higher taxation depending on their alcohol content, which increases the final cost of wines to the consumer [38]. Since ethanol is the main source of caloric content in wine, there is also a risk of a negative impact on wine export to countries where health labeling of foods and beverages served at restaurants is voluntary or mandatory [39].

During winemaking, high sugar and therefore ethanol can cause sluggish and stuck alcoholic fermentations and can be challenging for successful malolactic fermentations [40,41]. As a means to address these issues, methods have been studied that include lowering the final ethanol content of wine using a wide selection of interventions. These can be grouped into (1) pre- (e.g., viticultural, juice dilution, and fermentation of early harvest fruit); (2) concurrent (e.g., non-*Saccharomyces* yeasts, modified yeasts, and arrested fermentation) [42,43]; and (3) post-fermentation (e.g., non-membrane and membrane ethanol removal) [43–45]. The use of microbiological approaches such as inoculation with non-*Saccharomyces* yeasts for producing wines with less ethanol is a promising alternative to the removal of ethanol by membrane based-approaches [11,46–48]. The advantages associated with the use of low-ethanol/high-glycerol yielding yeasts include their relatively easy application and lower costs when compared to more expensive and less eco-friendly approaches, such as membrane contactors, nanofiltration, or the spinning cone column [49,50]. However, it is important to acknowledge that low-ethanol/high-glycerol yielding yeasts are much less e ffective than the membrane-based processes in terms of ethanol reductions [44], and they are perhaps only suitable when winemakers want to achieve a reduction in ethanol content by up to 3.0% *v*/*v* [49].

Inoculations with non-*Saccharomyces* yeasts can be used as a strategy to produce lower alcohol wines due to the yeasts di fferent sugar utilisation pathways, including respiration, alcoholic fermentation, and glycerol–pyruvic metabolisms, and di fferent regulatory mechanisms, in comparison to *S. cerevisiae* [51]. While the theoretical sugar-to-ethanol yield for a complete fermentation by *S. cerevisiae* generally ranges from 90% to 95%, the residual sugar is consumed via alternative metabolic pathways and biomass biosynthesis [52]. On the other hand, ethanol yield and the by-products formed vary immensely amongst non-*Saccharomyces* yeasts [23]. For example, due to the Crabtree e ffect, *S. cerevisiae* prefers fermentation metabolism rather than respiration when the sugar amount exceeds 10 g/L [40]. In contrast, among non-*Saccharomyces* yeasts, there are strains and species that can consume sugar with aerobic respiration regardless of sugar concentration [53,54] without contributing significantly to the final ethanol level of the wine. Therefore, non-*Saccharomyces* yeasts have been studied under partial and controlled aeration strategies during fermentation to achieve lower ethanol by allowing part of the sugar to be consumed via respiration rather than alcoholic fermentation [47,55]. However, an increase in undesirable volatile compounds, such as acetic acid and ethyl acetate, are the main limiting factors of the aeration strategies that require the application of a proper aeration regime [55–57].

As a response to interest in reduced alcohol levels in wines, researchers studied non-*S. cerevisiae* and *S.* non-*cerevisiae* yeast species [49,56,58–60] (Table 1). Several non-*Saccharomyces* yeast strains were identified, including *Metschnikowia pulcherrima,* and two species of *Kluyveromyces,* which have the capacity to decrease ethanol yields by respiration [59]. *M. pulcherrima* AWRI 1149 was identified as a potential yeast to produce wine with a reduced ethanol concentration, having been identified following the evaluation of 50 non-*Saccharomyces* isolates under limited aeration conditions, and in sequential inoculations with *S. cerevisiae* [49]. A similar study with 48 non-*Saccharomyces* yeast isolates identified *Torulaspora delbrueckii* AWRI 1152 and *Zygosaccharomyces bailii* AWRI 1578 yeasts as suitable for reducing ethanol [56]. More recently, the respiratory, fermentative, and physiological characteristics of 114 non-*Saccharomyces* yeasts were evaluated [60]. Taking into account their ability to reduce ethanol content *Hanseniaspora uvarum* BHu9 and BHu11, *Hanseniaspora osmophila* BHo51, *Starmerella bacillaris* (synonym. *Candida zemplinina*) BSb55, and *Candida membranaefaciens* BCm71 were selected as candidates for co-fermentations.


**5. Effect of the CDH on SH Diurnal Variation**

Previous studies [38] have pointed out that the uncertainty in the estimate of SH over the TP can be strongly attributed to the heat transfer coefficient CDH. CDH is affected by ground roughness and atmospheric stratification stability and has obvious seasonal and diurnal variations [39]. In order to address whether CDH is the dominant factor giving rise to the bias between calculated SH and observed SH, here the diurnal variation characteristics of the heat transfer coefficient (CDH-O hereafter) derived with the observed SH according to Equation (1) is examined (Figure 8). Due to the limitation of observational data, only the CDH-O at NAMORS can be obtained.

**Figure 8.** Seasonal mean of the diurnal variation in the derived heat transfer coefficient (CDH-O), observed SH (Obs\_SH, unit: W m−2) and calculated SH (Cal\_SH, unit: W m−2) at NAMORS in (**a**) spring, (**b**) summer, (**c**) autumn, and (**d**) winter. The two horizontal dashed lines indicate zero SH and 0.004 CDH-O, respectively.

As shown in Figure 8, the value of CDH-O in summer is the largest, followed by spring and autumn, and the smallest is in winter. This may be due to the unstable atmospheric stratification in summer over the TP and the greater roughness of the underlying surface vegetation, resulting in a larger CDH-O in summer. In general, the CDH-O values in all seasons are basically larger and stable in the day but fluctuate significantly at night, especially during the time from 00:00 to 10:00. Because the surface roughness at the fixed station has almost no diurnal variation, the CDH-O should be mainly considered to be affected by the stability of atmospheric stratification.

For the calculated SH, the CDH is set as 4 × 10−3, which is the average value often used in previous studies. However, the derived transfer coefficient CDH-O is much lower than 4 × 10−3 throughout the day (Figure 8), which suggests that the calculation of SH by choosing a fixed value of 4 × 10−3 will be overestimated, and also be biased in the diurnal variation. Clearly, the difference in diurnal variation between the calculated SH and the observed SH is the largest in spring, followed by summer, winter, and autumn, and the deviation can be up to 69.53 W m−2 and 194.46 W m−2 in autumn and spring, respectively. Therefore, the value of CDH is very important, which will bring a certain uncertainty to the SH calculation and its diurnal variation.

A more reasonable value of the heat transfer coefficient is urgently needed to reduce the uncertainty and obtain a more accurately calculated SH. Usually, the TP is a strong heat source in spring and summer, and most studies on SH also focused on these two seasons. Therefore, by further calculations, the seasonal mean CDH-O values in spring and summer at NAMORS are about 2.24 × 10−3 and 2.78 × 10−3, respectively, and the new SH in these two seasons is obtained by using these new CDH. Here, Figure 9 shows the relationships between the originally calculated SH, the new SH, and the observed SH. Obviously, the new SH is much closer to the observations on a diurnal scale, especially in spring, with a maximum deviation of 27.89 W m−2, only being 12.7% of the maximum deviation between the originally calculated SH and the observed SH. Moreover, the new SH shows interannual variations comparable with the observed SH (Figure 10). Of note is that, during the spring of 2006–2012, the change of the new SH is completely consistent with the observed SH, and the relative deviation of the new SH is only 13.1%, while that of the calculated SH is 101.9%. Considering the scarcity of directly observed flux data over the TP region, it is inevitable to calculate SH for the research involving TP SH. Therefore, the new and better heat transfer coefficient (2.24 × 10−3 in spring and 2.78 × 10−3 in summer) presented here is conducive to calculating SH more accurately in the future.

**Figure 9.** The relationship between the originally calculated SH and observed SH (blue lines, unit: W m−2), and between the new SH and observed SH (red lines, unit: W m−2) in the seasonal mean of the diurnal variation in (**a**) spring and (**b**) summer at NAMORS. RMSE1 and RMSE2 denote the root mean squared error of the originally calculated SH and the new SH, respectively.

**Figure 10.** Time series of the annual mean in observed SH (Obs\_SH, units: W m−2), originally calculated SH (Cal\_SH, units: W m−2), and new SH (New SH, units: W m−2) in (**a**) spring and (**b**) summer at NAMORS during the period 2006–2016.

#### **6. Conclusions and Discussion**

Obvious diurnal variation exists in SH over the TP. Here we adopted the hourly observational SH from the Tibetan Plateau Scientific Data Center to deeply understand the characteristics of the SH diurnal variation over the TP. In addition, the differences between the observed and calculated SH are also examined. The main conclusions are as follows:

Research related to turbulent flux has always been the core issue of land–atmosphere interaction [40], and an in-depth understanding of diurnal variation characteristics in SH over the TP can help us to understand the key land surface processes. Due to the uneven distribution of observations in high mountain regions [28], especially over the TP, the model performance is still poor [41], so various parameterization schemes and numerical models for SH are usually developed. An in-depth understanding of the diurnal variation characteristics of SH over the TP can help to improve and calibrate the numerical modes. Moreover, the new CDH obtained by comparing the calculated SH and observed SH on a diurnal scale can boost the accuracy of SH calculations. However, the impact of the diurnal variation in TP SH on the weather has not been mentioned in this study, and it therefore needs further exploration in the future. It is also worth noting that the suggested new CDH is obtained only from NAMORS due to data limitations, so there is still a certain one-sidedness.

**Author Contributions:** Conceptualization, M.W.; formal analysis, Z.Z.; writing—original draft, Z.Z.; writing—review and editing, M.W., J.W., X.M., J.L. and X.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was sponsored by the National Natural Science Foundation of China (42030605), the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (2019QZKK0105), the National Natural Science Foundation of China (41605039, 41807434, 42030611), the Natural Science Foundation of Jiangsu Province, China (grant no. BK20221449), Meteorological soft science of China Meteorological Administration (2022ZDIANXM28), and the open project of Key Laboratory of Meteorological Disaster (KLME), Ministry of Education & Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology (grant no. KLME202203).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** The data presented in this study are openly available in [National Tibetan Plateau Data Center] at [https://doi.org/10.11888/Meteoro.tpdc.270910], reference number [27].

**Conflicts of Interest:** The authors declare no conflict of interest.


**Abstract**

This chapter examined the theoretical background of the use of a screw working body in front of the planner bucket and conducting experiments in laboratory conditions with the proposed working body. This work supports the practical solution of using a screw working particle in the current field planning. Significance of the work reducing traction resistance to soil movement up to 20% enables the tractor unit to work at higher speeds of translational motion; the latter contributes to increased productivity, improved planning quality and reduced cash costs per unit of work performed. The chapter was prepared under results of research in the Mechanics Laboratory of Bukhara Engineering Technological Institute.

**Keywords:** productivity of the screw working body, translational speed of the planning unit, screw pitch, screw diameter, drawing prisms

#### **1. Introduction**

Further development of agriculture in modern conditions determines the introduction of new advanced technologies and machines for their implementation.

As we know, for increase of volume agricultural products, it is need to intensification of agricultural production, one of the means of which is wide land reclamation, which provides, as one of the most important measures, the planning of the irrigated land surface. Alignment of the surface of the fields by the long-base planners is of great importance in the range of planning works, and research work to improve these planners is carried out both in Uzbekistan and abroad.

The analysis of the state of the issue showed the need to improve the quality of planning work, increase the productivity of long-base planners and increase the levelling ability of the latter [1, 2].

### **2. Literature review**

By world and domestic farming practices, it has been proved that planning or levelling the surface of the fields is the main land reclamation measure designed

to eliminate irregularities on the field under sowing in the form of various rise and falls.

Many domestic and foreign scientific works [3–6] have been published on the need for field planning, authors of which have been examined the issue from different perspectives and pointed out the advantages of this operation. Moreover, there are many advantages, whether it is capital and operational planning or micro alignment. Experiments have established that under conditions of turbulent terrain, crop losses amount to 40% of the potential crop. Cotton grown on mounds and lowlands gives raw cotton of lower quality: fibre strength, grade, ripeness, etc. are reduced.

In areas with saline soil, a high-quality planning prevents the formation of saline spots (areas) and thereby ensures sustainable yields of all types of crops [6, 7]. Flushing saline lands without planning are ineffective.

According to Ref. [6], it was established that uniform soil moisture is achieved on the planned field, and the irrigation water consumption is significantly reduced.

In the United States, great importance is given to the planning of the surface of irrigated areas. Annually, in this country, approximately more than half of the irrigated areas are subject to planning [3, 6, 7]. Americans do not spare the cost of land planning, as this increases income from irrigated land and reduces the cost of production.

To ensure the high quality of the technological processes, including irrigation, it is necessary to pay special attention to the capital planning and the mandatory periodic implementation of the field operational planning.

#### **3. Research methods**

It is known that the magnitude and the nature of the change in the angular speed of a material particle determine the productivity and energy indicators for conveying the material with a screw [2, 8].

Let us consider the movement of a material particle of mass dm located at point O of an inclined cylindrical screw at a distance *r* from the axis of the screw (**Figures 1** and **2**) and moving along the trajectory of the absolute movement AB; the axes *τ, b* and *n* are, respectively, tangent, binormal and normal to the trajectory of absolute motion [9]. The *n* axis is directed towards the centre of curvature and

> coincides with the *y* axis. The Z axis is parallel to the axis of the screw, and the *x* and *y* axes are located on tangent and normal in plane PP of the screw, perpendicular to

*Material particle of mass dm located at point O of an inclined cylindrical screw at a distance* r*.*

*Study of the Parameters of the Planner with a Screw Working Body*

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

The following forces impact on the soil particle: particle gravity Gr = gdm, which

, acting along the tangent to the trajectory of the absolute motion of the

particle on a blade casing Fk1 (along the *τ* axis), and friction force on a helical surface Fш (at an angle of inclination of the helix *αr* to the *х* axis); tangential inertial

particle (*τ* axis) and directed opposite to the particle's absolute speed vector *V* (**Figure 3**); normal inertial force directed to the centre of curvature of the trajectory (along the *n* axis); and normal reaction of the adjacent layer Fк*II*(along the *n* axis) and the helical surface Fш*I* (at an angle *аr* to the *z* axis). *βш* is the angle of inclination of the screw to the horizon; and *ε* is the current angle of rotation of the particle, measured from the projection of the О2 particle on the PP plane. The resultant F*л* of

= Gr.sin βш (along the *z* axis), radial

2 � *μ* � *d* � *m* (along the *y* axis), friction force of a

III = Gr.cosβш�sin*ε* (along the *x*

its axis ШШ; GG horizontal plane.

*Particle's absolute speed vector V.*

axis); centrifugal force *Fц* ¼ *ωr*

Gr

**125**

**Figure 2.**

**Figure 3.**

force, *Fu*

*t*

can be divided into three components, axial GrI

II = Gr.cos βш cosε (along the *y* axis) and tangent Gr

**Figure 1.** *Movement of a material particle of mass dm located at point O.*

*Study of the Parameters of the Planner with a Screw Working Body DOI: http://dx.doi.org/10.5772/intechopen.93308*

to eliminate irregularities on the field under sowing in the form of various rise

need for field planning, authors of which have been examined the issue from different perspectives and pointed out the advantages of this operation. Moreover, there are many advantages, whether it is capital and operational planning or micro alignment. Experiments have established that under conditions of turbulent terrain, crop losses amount to 40% of the potential crop. Cotton grown on mounds and lowlands gives raw cotton of lower quality: fibre strength, grade, ripeness, etc. are

Many domestic and foreign scientific works [3–6] have been published on the

In areas with saline soil, a high-quality planning prevents the formation of saline

According to Ref. [6], it was established that uniform soil moisture is achieved on the planned field, and the irrigation water consumption is significantly reduced. In the United States, great importance is given to the planning of the surface of

To ensure the high quality of the technological processes, including irrigation, it

It is known that the magnitude and the nature of the change in the angular speed

Let us consider the movement of a material particle of mass dm located at point

spots (areas) and thereby ensures sustainable yields of all types of crops [6, 7].

irrigated areas. Annually, in this country, approximately more than half of the irrigated areas are subject to planning [3, 6, 7]. Americans do not spare the cost of land planning, as this increases income from irrigated land and reduces the cost of

is necessary to pay special attention to the capital planning and the mandatory

of a material particle determine the productivity and energy indicators for

O of an inclined cylindrical screw at a distance *r* from the axis of the screw (**Figures 1** and **2**) and moving along the trajectory of the absolute movement AB; the axes *τ, b* and *n* are, respectively, tangent, binormal and normal to the trajectory of absolute motion [9]. The *n* axis is directed towards the centre of curvature and

Flushing saline lands without planning are ineffective.

*Direct Torque Control Strategies of Electrical Machines*

periodic implementation of the field operational planning.

and falls.

reduced.

production.

**Figure 1.**

**124**

**3. Research methods**

conveying the material with a screw [2, 8].

*Movement of a material particle of mass dm located at point O.*

**Figure 2.** *Material particle of mass dm located at point O of an inclined cylindrical screw at a distance* r*.*

**Figure 3.** *Particle's absolute speed vector V.*

coincides with the *y* axis. The Z axis is parallel to the axis of the screw, and the *x* and *y* axes are located on tangent and normal in plane PP of the screw, perpendicular to its axis ШШ; GG horizontal plane.

The following forces impact on the soil particle: particle gravity Gr = gdm, which can be divided into three components, axial GrI = Gr.sin βш (along the *z* axis), radial Gr II = Gr.cos βш cosε (along the *y* axis) and tangent Gr III = Gr.cosβш�sin*ε* (along the *x* axis); centrifugal force *Fц* ¼ *ωr* 2 � *μ* � *d* � *m* (along the *y* axis), friction force of a particle on a blade casing Fk1 (along the *τ* axis), and friction force on a helical surface Fш (at an angle of inclination of the helix *αr* to the *х* axis); tangential inertial force, *Fu t* , acting along the tangent to the trajectory of the absolute motion of the particle (*τ* axis) and directed opposite to the particle's absolute speed vector *V* (**Figure 3**); normal inertial force directed to the centre of curvature of the trajectory (along the *n* axis); and normal reaction of the adjacent layer Fк*II*(along the *n* axis) and the helical surface Fш*I* (at an angle *аr* to the *z* axis). *βш* is the angle of inclination of the screw to the horizon; and *ε* is the current angle of rotation of the particle, measured from the projection of the О2 particle on the PP plane. The resultant F*л* of

#### *Direct Torque Control Strategies of Electrical Machines*

the normal reaction of the helical surface *F*ш*I* and the friction force against the helical surface *Fш* ¼ *fFш*1 is deviated from the normal and the helical surface by the angle of friction *ϕ* ¼ *arctgf*, where *f* is the coefficient of friction of the soil over the screw metal. If we consider that the loosened soil before the bucket of the planner is clay, then the value of this coefficient is 0.6 ... 0.7. [8]

The friction force of a particle on a bucket caused by the combined action of forces Fц and GII r is equal to:

$$F\_{k\_1} = f\_r \left( F\_\eta + G\_r^{\llcorner \Pi} \right) = f\_r \left( a\_r^{\llcorner 2} \cdot r + \mathfrak{g} \cos \beta\_w \cdot \cos \varepsilon \right) \cdot dm,$$

where *fr* and *f*, respectively, are the friction coefficients of the particle on the bucket and the adjacent layer of material and the helical surface.

Absolute particle speed:

$$\mathfrak{G} = \sqrt{\mathfrak{G}\_t^2 + \mathfrak{G}\_o}^2 = r\sqrt{\alpha\_r^2 + \left(\alpha - \alpha\_r\right)^2 \cdot \mathfrak{g}^2 a\_r} \tag{1}$$

elementary angle of rotation along the arc О1, О2 (**Figure 1**) of the particle

*sin*ð½ Þ *ar* þ *ϕ ωr* þ cosð Þ� *ar* þ *ϕ tgar*ð Þ *ω* � *ωr* cosð Þ *ar* þ *ϕ ωr* � sin ð Þ *ar* þ *ϕ tgar*ð Þ *ω* � *ωr*

! *g* � sin *βш* � *ωr* � *g* � cos *βш* sin *ε* � *tgar*ð Þ *ω* � *ωr* � ��

*Study of the Parameters of the Planner with a Screw Working Body*

! �*g* � sin *βш* � *tgar*ð Þ� *ω* � *ωr g* � cos *βш* sin *ε* � *ωr* ð Þ *ω* � *ωr r ωr* � ð Þ *ω* � *ωr tg*2*ar* ½ �

ð *ε*¼ð Þ 2*k*þ1 *π*

*ε*¼2*kπ*

dependence of *ωr* on *ε* for screws with different parameters.

! �*fr ωr* ð Þ 2 þ *g* � cos *βш* � cos *ε x*

ð Þ *ω* � *ωr r ωr* � ð Þ *ω* � *ωr tg*2*ar* ½ � !

*ωr*

By integrating Eq. (8) by the Euler method [3], we can obtain the curves of the

In the inclined screw, there is a periodically steady motion of the material

(*k*) is any number. In order to simplification for inclined screws, it is possible to take the average value of the angular speed in the area of periodically steady motion:

�*ωrdε* ffi *ωr*

Eq. (8), equating the right side to zero at *ε* ¼ 2*kπ* and *ε* ¼ ð Þ 2*k* þ 1 *π*. However, for practical purposes, the angular speed of a soil particle at the periphery of the screw

> for vertical screws, 0, 4*ω*<*ωrш* < 0, 5*ω*, for steeply inclined screws, *βш* ≥30*o* ð Þ *0*, *3ω*< *ωrш* <*0*, *4ω*,

where *ωrш* is the particle angular speed at the periphery of the screw, sec�1

The study of Eq. (8) showed that in a certain zone limited by the cylindrical contour of the soil shaft, soil particles relatively quickly acquire the angular speed of the screw and their lifting stops [8]. The value of the so-called critical radius *rкр* depends on the initial conditions and is determined from Eq. (8) after substituting

In the horizontal *(βш < 30*°*)* screw, during the period of steady motion, the angular speed of the particle is zero. The angle of rotation of the particle ε, at which the steady motion begins, depends on the initial conditions and can be found from

Maximum productivity on loosened soil, determined by the throughput between

*ε* ¼ *arctg f r* sin ð Þ *ar* þ *ϕ* cos �1

ð Þ *ω* � *ωr r ωr* � ð Þ *ω* � *ωr tg*2*ar* ½ � !

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

2 þ ð Þ *ω* � *ωr* 2 � *tg*2*ar*

max is on the plot with the values of the angle

ð Þ 2*k*þ1 *π*

min can be found by progressive approximation from

ð Þ *ar* þ *ϕ* � � (10)

2 (9)

2*kπ* þ *ωr*

min is in the zone 2ð Þ *k* þ 1 *π* > *ε*>2*kπ*, where

�

(8)

.

ð Þ *ω* � *ωr r ωr* � ð Þ *ω* � *ωr tg*2*ar* ½ � !

q

*dε* ¼ ð Þ *ω* � *ωr dt*, we obtain:

�

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

particle. The maximum value of *ω*r

The values of *ω*r

can be taken as:

*ωr = ω* at *dω*r*/dε = 0*.

the upper turns of the screw will be:

Eq. (8):

**127**

2*kπ* > *ε*>ð Þ 2*k* � 1 *π*, and the value of *ω*r

*ωr cp* ¼

maх and *ω*r

*dωr dε* ¼

where *ϑ*t is tangential particle speed at the radius *r* from the axis of the screw, *ϑt* ¼ *ωr* � *r*; *ϑ*о is the axial speed of the particle at a radius *r* from the axis of the screw, *ϑо* ¼ ð Þ *ω* � *ωr tgar*; *ω* is screw angular speed; and *аr* is the angle of inclination of the helix of the screw on the radius *r* (**Figure 2**).

The tangent force of inertia is defined as follows:

$$F\_u{}^t = \frac{d\theta}{dt}dm = \frac{r[\alpha\_r - (\alpha - \alpha\_r)t\mathbf{g}^2 a\_r]}{\sqrt{\alpha\_r^2 + (\alpha - \alpha\_r)^2 t\mathbf{g}^2 a\_r}} \cdot \frac{d\alpha\_r}{dt}dm\tag{2}$$

Normal inertial force:

$$F\_u{}^{\
u} = \mathfrak{G}^2 \cdot r\_a{}^{-1} \cdot dm = r^2 \left[ \alpha\_r{}^2 + (\alpha - \alpha\_r)^2 \cdot \mathfrak{g}^2 a\_r \right] \cdot \left[ r \left( \mathfrak{1} + \mathfrak{g}^2 \theta \right) \right]^{-1},\tag{3}$$

where r*a* is the radius of curvature of the trajectory at the selected point, *ra* ¼ *r* 1 þ *tg*2 ð Þ*θ* ; and *θ* is the angle of inclination of the helix of the particle trajectory to the axis Х (**Figure 2**)

$$\text{tg}\,\theta = \text{tg}\,a\_w(w - a\_r)a\_r^{-1},\tag{4}$$

where *a*ш is screw helix angle at the periphery.

According to the D'Alembert's principle [8], the equation of dynamic equilibrium of a material particle in the projections on the axis of the natural trihedral of the trajectory ð Þ *τ*, *b*, *n* (**Figure 2**) will be

$$\begin{split} \sum \boldsymbol{\pi} &= \left[ \boldsymbol{F}\_{\boldsymbol{x}} \sin \left( \boldsymbol{a}\_{r} + \boldsymbol{\theta} + \boldsymbol{\phi} \right) - \boldsymbol{G}\_{r}^{\boldsymbol{\Pi}\mathcal{I}} \cos \boldsymbol{\theta} - \boldsymbol{F}\_{\boldsymbol{k}\_{1}} - \boldsymbol{F}\_{\boldsymbol{u}}^{\boldsymbol{\epsilon}} - \boldsymbol{G}\_{r}^{\boldsymbol{1}} \sin \boldsymbol{\theta} \right] \cdot \cos \boldsymbol{\varepsilon} - \\ &- \left( \boldsymbol{F}\_{\boldsymbol{u}} + \boldsymbol{G}\_{r}^{\boldsymbol{H}} - \boldsymbol{F}\_{\boldsymbol{u}}^{\boldsymbol{H}} - \boldsymbol{F}\_{\boldsymbol{k}^{\boldsymbol{H}}} \right) \cdot \sin \boldsymbol{\varepsilon} = \boldsymbol{O}, \end{split} \tag{5}$$

$$\sum b = \pm F\_{\pi} \cdot \cos(a\_r + \theta - \phi) + G\_r^{\text{III}} \cdot \sin \theta - G\_r^{-1} \cdot \cos \theta = 0,\tag{6}$$

$$\begin{split} \sum \boldsymbol{n} &= \left( \boldsymbol{F\_{u}} + \boldsymbol{G\_{r}}^{\operatorname{II}} + \boldsymbol{F\_{u}}^{\operatorname{II}} - \boldsymbol{F\_{k\_{\hat{u}}}} \right) \cdot \cos \boldsymbol{\varepsilon} + \left[ \boldsymbol{F\_{r}} \sin \left( \boldsymbol{a\_{r}} + \boldsymbol{\theta} + \boldsymbol{\phi} \right) - \boldsymbol{\varepsilon} \right] \\ &- \boldsymbol{G\_{r}}^{\operatorname{III}} \cdot \cos \boldsymbol{\theta} - \boldsymbol{F\_{k1}} - \boldsymbol{F\_{u}}^{\operatorname{I}} - \boldsymbol{G\_{r}}^{\operatorname{I}} \sin \boldsymbol{\theta} \right] \cdot \sin \boldsymbol{\varepsilon} \end{split} \tag{7}$$

Solving these equations jointly, excluding the force F*л* from them, after the corresponding transformation of the exception and time by expressing the

the normal reaction of the helical surface *F*ш*I* and the friction force against the helical surface *Fш* ¼ *fFш*1 is deviated from the normal and the helical surface by the angle of friction *ϕ* ¼ *arctgf*, where *f* is the coefficient of friction of the soil over the screw metal. If we consider that the loosened soil before the bucket of the planner is

The friction force of a particle on a bucket caused by the combined action of

where *fr* and *f*, respectively, are the friction coefficients of the particle on the

*ωr*

where *ϑ*t is tangential particle speed at the radius *r* from the axis of the screw, *ϑt* ¼ *ωr* � *r*; *ϑ*о is the axial speed of the particle at a radius *r* from the axis of the screw, *ϑо* ¼ ð Þ *ω* � *ωr tgar*; *ω* is screw angular speed; and *аr* is the angle of inclination

q

*dt dm* ¼ *r ωr* � ð Þ *ω* � *ωr tg*2*ar* ½ �

*ωr*

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

q �

2 þ ð Þ *ω* � *ωr* 2

2 þ ð Þ *ω* � *ωr* 2 � *tg*2

where r*a* is the radius of curvature of the trajectory at the selected point, *ra* ¼ *r* 1 þ *tg*2 ð Þ*θ* ; and *θ* is the angle of inclination of the helix of the particle trajectory to

*tgθ* ¼ *tgaш*ð Þ *ω* � *ωr ωr*

According to the D'Alembert's principle [8], the equation of dynamic equilibrium of a material particle in the projections on the axis of the natural trihedral of

*III* cos *θ* � *Fk*1 � *Fu*

� � � sin *ε* ¼ *O*, (5)

*III* � sin *θ* � *Gr*

1 sin *θ* � � � cos *ε*�

� � � cos *ε* þ ½*Fл* sin ð Þ� *ar* þ *θ* þ *ϕ*

*t* � *Gr*

Solving these equations jointly, excluding the force F*л* from them, after the corresponding transformation of the exception and time by expressing the

h i

2 � *r* þ *g* cos *βш* � cos *ε* � � � *dm*,

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

2 þ ð Þ *ω* � *ωr* 2 � *tg*2*ar*

*tg*2*ar*

*ar*

�1

*t* � *Gr*

*dωr*

� *r* 1 þ *tg*2 *θ* � � � � �1

*dt dm* (2)

, (4)

1 � cos *θ* ¼ 0, (6)

1 sin *θ*� � sin *ε* (7)

, (3)

(1)

clay, then the value of this coefficient is 0.6 ... 0.7. [8]

*II* � � ¼ *fr ωr*

bucket and the adjacent layer of material and the helical surface.

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi *ϑt* 2 þ *ϑo* 2

¼ *r*

r is equal to:

*Direct Torque Control Strategies of Electrical Machines*

*Fk*1 ¼ *fr Fц* þ *Gr*

*ϑ* ¼

*Fu t* ¼ *dϑ*

Normal inertial force:

*н* ¼ *ϑ*2 � *ra*

the axis Х (**Figure 2**)

*Fu*

q

of the helix of the screw on the radius *r* (**Figure 2**). The tangent force of inertia is defined as follows:

�1 � *dm* ¼ *r*

where *a*ш is screw helix angle at the periphery.

 (8)

$$\rightarrow \frac{-\mathbf{g} \cdot \sin \beta\_{\rm un} \cdot \mathbf{t} \mathbf{g} a\_r (a - a r\_r) - \mathbf{g} \cdot \cos \beta\_{\rm un} \sin \varepsilon \cdot a\_r}{(a - a r\_r) r [a\_r - (a - a r\_r) \mathbf{t} \mathbf{g}^2 a\_r]}$$

By integrating Eq. (8) by the Euler method [3], we can obtain the curves of the dependence of *ωr* on *ε* for screws with different parameters.

In the inclined screw, there is a periodically steady motion of the material particle. The maximum value of *ω*r max is on the plot with the values of the angle 2*kπ* > *ε*>ð Þ 2*k* � 1 *π*, and the value of *ω*r min is in the zone 2ð Þ *k* þ 1 *π* > *ε*>2*kπ*, where (*k*) is any number. In order to simplification for inclined screws, it is possible to take the average value of the angular speed in the area of periodically steady motion:

$$\rho\_r^{cp} = \int\_{\varepsilon = 2k\pi}^{\varepsilon = (2k+1)\pi} \cdot \rho\_r d\varepsilon \cong \frac{\rho\_r^{2k\pi} + \rho\_r^{(2k+1)\pi}}{2} \tag{9}$$

The values of *ω*r maх and *ω*r min can be found by progressive approximation from Eq. (8), equating the right side to zero at *ε* ¼ 2*kπ* and *ε* ¼ ð Þ 2*k* þ 1 *π*. However, for practical purposes, the angular speed of a soil particle at the periphery of the screw can be taken as:

> for vertical screws, 0, 4*ω*<*ωrш* < 0, 5*ω*, for steeply inclined screws, *βш* ≥30*o* ð Þ *0*, *3ω*< *ωrш* <*0*, *4ω*,

where *ωrш* is the particle angular speed at the periphery of the screw, sec�1 .

The study of Eq. (8) showed that in a certain zone limited by the cylindrical contour of the soil shaft, soil particles relatively quickly acquire the angular speed of the screw and their lifting stops [8]. The value of the so-called critical radius *rкр* depends on the initial conditions and is determined from Eq. (8) after substituting *ωr = ω* at *dω*r*/dε = 0*.

In the horizontal *(βш < 30*°*)* screw, during the period of steady motion, the angular speed of the particle is zero. The angle of rotation of the particle ε, at which the steady motion begins, depends on the initial conditions and can be found from Eq. (8):

$$\boldsymbol{\varepsilon} = \operatorname{arctg}\left[ \, \boldsymbol{f}\_r \sin \left( \boldsymbol{a}\_r + \phi \right) \cos^{-1} \left( \boldsymbol{a}\_r + \phi \right) \right] \tag{10}$$

Maximum productivity on loosened soil, determined by the throughput between the upper turns of the screw will be:

$$
\Pi = \int\_{r\_{\rm sp}}^{r\_{\rm u}} \mathfrak{g}\_r dS,\tag{11}
$$

In horizontal and gently dipping screws at inclination angle *βш* ≤ *30*°, the angular

1

where *dш, dв*, respectively, are the diameters of the screw and shaft, m; *Кн* is the screw filling coefficient, for our case we can take equal to *Кн = 0,2 … 0,4;* and *Кβ* is the coefficient taking into account the angle of inclination of the screw to the

The main parameters of working elements of the screw include the length of the conveying part—*lш*, the length of the cutting part—*lр*, the diameter of the screw—

The length of the conveying and cutting parts of the screw is taken construc-

The diameter of the screw *dш* with a horizontal working body at the given

1 = Пт can be determined from formula (14) after some

1 � *Кр* 900*ϑокр* � *KaKн* � *Kβ*

*1*

For a horizontal screw, operating speed (*ϑ*п) of movement is (m/s):

*ϑП* ¼ *ПT* � *lp*

cutting length of the planner's knife, m; and hр is the thickness of the cut soil

where Пт is the efficiency of the planning unit on cut of soil, m3

taken depending on the inclination of the cutting edge of the screw. For our case,

The working speed of the soil movement with the screw should be equal to the speed of filling the planner bucket with soil. The latter depends on the forward speed of movement of the planner. For our case, with a certain accuracy, we can take *ϑгр = ϑков = ϑ*п, where *ϑгр* is the speed of the soil movement with the screw, *ϑков* is the speed of filling the planner bucket with soil and *ϑ*п is the forward speed of the

The working speed of the planner's movement can also be determined from the conditions for ensuring a given efficiency on a cut of soil with the planner's bucket.

Based on the analysis of the above theoretical background in the determination of the efficiency of the screw working body, it is suggested that with the increase in

�1 � *hp* �1

where *ϑ*окр is the peripheral speed on the cutting edge of the screw, *ϑ*окр = 1.5 … 3 m/seс; and К*а* is the coefficient taking into account the inclination of the cutting

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

� ��1 þ *d*2

*ш/dш = 0,7 … 1,0.* Other designations see from the

*1*

*ш* is taken equal to *l*

*в*

*ω* � *KHKβ* � *Kр*

�1

/h), we can

, (14)

*1*

, (15)

*ш = Каdш*, the value of *Ка* is

, (16)

/seс; *l*р is the

*ш* and the

speed of the material particle is *ωсрrш* = 0. To calculate the capacity (m3

**3.1 Selection and justification of the main parameters of the screw**

*dш*, peripheral speed on the cutting edge—*ϑокр*, the pitch of the screw—*l*

tively, based on the type of screw and the parameters of the medium being processed. For preliminary calculations, we can take the length of the conveying part of the horizontally located screw *lш = lp = (0,7 … 0,8) вп*, where *в*n is the width

2 � *db* 2 � �*lш*

*ПТ* ¼ 450 *dш*

*Study of the Parameters of the Planner with a Screw Working Body*

use [1] the following formula:

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

horizon *βш, Кβ = 1,0 … 0,8* [8].

working speed of movement—*ϑр*.

*dш* ≥

The step of the horizontal screw *l*

*ПT*

q

of the planner scoop.

transformations, m;

edge of the screw, *Кa = l1*

we can take *Ка* equal to 0.85.

productivity Пт

formula (14).

planner, m/s.

layer, m.

**129**

where *rш* is the outer radius of the screw; *ϑ*r is the ground sliding speed on the helical surface of the screw (relative speed); and dS is the elementary crosssectional area of the soil located between the upper turns in a plane perpendicular to the relative speed vector.

The screw capacity in a dense body will be:

$$
\Pi\_T = \frac{1}{K\_p} \int\_{\kappa\_{\rm sp}}^{r\_w} \mathfrak{d}\_r \cdot d\mathbf{S}^I,\tag{12}
$$

where кр is soil loosening coefficient; for our case, кр = 1.14 … 1.28 [8].

Soil in the cross section of the screw by a plane, passing through the axis of the screw, occupies an area bounded from below by a straight-line perpendicular to the axis of the screw (**Figure 4**). Then in the cross section, we get a rectangle of length *l* II, which can be taken equal to the pitch of the screw *l* II = *l* I ш.

The elementary area of soil cross-section at a distance *r* from the screw axis will be equal to:

$$d\mathbf{S} = d\mathbf{S}\_1 \cdot \cos a\_r = l^1\_{\ \ u} d\_r \cos a\_r = 2\pi l^1\_{\ \ u} \left(\sqrt{4\pi^2 \cdot r^2 + \left(l^1\_{\ \ u}\right)^2}\right)^{-1} \cdot r d\_r,\tag{13}$$

where *dS1* is the elementary area of soil in axial cross-section (**Figure 4**).

**Figure 4.** *Position of soil area in the cross section of the screw.*

*Study of the Parameters of the Planner with a Screw Working Body DOI: http://dx.doi.org/10.5772/intechopen.93308*

*П* ¼

helical surface of the screw (relative speed); and dS is the elementary cross-

*ПT* ¼ 1 *Кр*

the relative speed vector.

*l*

be equal to:

**Figure 4.**

**128**

*Position of soil area in the cross section of the screw.*

*dS* ¼ *dS*1 � cos *ar* ¼ *l*

The screw capacity in a dense body will be:

*Direct Torque Control Strategies of Electrical Machines*

II, which can be taken equal to the pitch of the screw *l*

*шdr* cos *ar* ¼ 2*πl*

1

*r* ð*ш*

*rкр*

where *rш* is the outer radius of the screw; *ϑ*r is the ground sliding speed on the

sectional area of the soil located between the upper turns in a plane perpendicular to

*r* ð*ш*

*ккр*

Soil in the cross section of the screw by a plane, passing through the axis of the screw, occupies an area bounded from below by a straight-line perpendicular to the axis of the screw (**Figure 4**). Then in the cross section, we get a rectangle of length

The elementary area of soil cross-section at a distance *r* from the screw axis will

1 *ш*

where *dS1* is the elementary area of soil in axial cross-section (**Figure 4**).

where кр is soil loosening coefficient; for our case, кр = 1.14 … 1.28 [8].

*ϑr* � *dSI*

*ϑrdS*, (11)

, (12)

� *rdr*, (13)

II = *l* I ш.

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 4*π*2 � *r*2 þ *l*

� � q �1

1 *ш* � �2

In horizontal and gently dipping screws at inclination angle *βш* ≤ *30*°, the angular speed of the material particle is *ωсрrш* = 0. To calculate the capacity (m3 /h), we can use [1] the following formula:

$$
\Pi\_T = 4\mathsf{50} \left( d\_{\textit{u}} \,^2 - d\_{\textit{b}} \,^2 \right) l\_{\textit{u}} \,^1 \boldsymbol{\alpha} \cdot \boldsymbol{K}\_H \boldsymbol{K}\_{\boldsymbol{\beta}} \cdot \boldsymbol{K}\_p \,^{-1}, \tag{14}
$$

where *dш, dв*, respectively, are the diameters of the screw and shaft, m; *Кн* is the screw filling coefficient, for our case we can take equal to *Кн = 0,2 … 0,4;* and *Кβ* is the coefficient taking into account the angle of inclination of the screw to the horizon *βш, Кβ = 1,0 … 0,8* [8].

#### **3.1 Selection and justification of the main parameters of the screw**

The main parameters of working elements of the screw include the length of the conveying part—*lш*, the length of the cutting part—*lр*, the diameter of the screw *dш*, peripheral speed on the cutting edge—*ϑокр*, the pitch of the screw—*l 1 ш* and the working speed of movement—*ϑр*.

The length of the conveying and cutting parts of the screw is taken constructively, based on the type of screw and the parameters of the medium being processed. For preliminary calculations, we can take the length of the conveying part of the horizontally located screw *lш = lp = (0,7 … 0,8) вп*, where *в*n is the width of the planner scoop.

The diameter of the screw *dш* with a horizontal working body at the given productivity Пт 1 = Пт can be determined from formula (14) after some transformations, m;

$$d\_{\rm un} \ge \sqrt{\boldsymbol{\Pi}\_T^{-1} \cdot \boldsymbol{K}\_p \left(\boldsymbol{\Theta}\boldsymbol{\Pi}\boldsymbol{\Theta}\_{\rm opp} \cdot \boldsymbol{K}\_d \boldsymbol{K}\_n \cdot \boldsymbol{K}\_\beta\right)^{-1} + d\_{\rm o}^2},\tag{15}$$

where *ϑ*окр is the peripheral speed on the cutting edge of the screw, *ϑ*окр = 1.5 … 3 m/seс; and К*а* is the coefficient taking into account the inclination of the cutting edge of the screw, *Кa = l1 ш/dш = 0,7 … 1,0.* Other designations see from the formula (14).

The step of the horizontal screw *l 1 ш* is taken equal to *l 1 ш = Каdш*, the value of *Ка* is taken depending on the inclination of the cutting edge of the screw. For our case, we can take *Ка* equal to 0.85.

The working speed of the soil movement with the screw should be equal to the speed of filling the planner bucket with soil. The latter depends on the forward speed of movement of the planner. For our case, with a certain accuracy, we can take *ϑгр = ϑков = ϑ*п, where *ϑгр* is the speed of the soil movement with the screw, *ϑков* is the speed of filling the planner bucket with soil and *ϑ*п is the forward speed of the planner, m/s.

The working speed of the planner's movement can also be determined from the conditions for ensuring a given efficiency on a cut of soil with the planner's bucket. For a horizontal screw, operating speed (*ϑ*п) of movement is (m/s):

$$\mathfrak{G}\_{\rm II} = \boldsymbol{\Pi}\_{\rm T} \cdot \boldsymbol{l}\_{\rm p}^{-1} \cdot \boldsymbol{h}\_{\rm p}^{-1},\tag{16}$$

where Пт is the efficiency of the planning unit on cut of soil, m3 /seс; *l*р is the cutting length of the planner's knife, m; and hр is the thickness of the cut soil layer, m.

Based on the analysis of the above theoretical background in the determination of the efficiency of the screw working body, it is suggested that with the increase in the speed of rotation and in diameters of the screw, the productivity of the screw working body increases. The screw pitch is also of great importance, with an increase in which the volume of soil moved to the sidewalls of the planner bucket increases, which in turn contributes to an even distribution of the soil of the drawing prism along the width of the planner passage. With an increase in the speed of forward movement of the planner increases the working capacity of the screw working body, that is screws move a large volume of soil to the sides relative to each other. However, such an improvement in the work of working element of the screw for our case, as shown by selective experiments with the experimental sample of a mini-planner, occurs up to a speed of 2 m/s of the forward movement of the unit. Above this speed, the screws begin to become clogged with soil, and the technological process of the screw working body is violated.

We derived the equation of traction resistance of the planner, which has the following form:

$$\begin{split} P &= f\_n G\_n + \frac{\left[\sin\beta(1-f^2)2f\cos\beta\right]\tau \cdot S}{\sin\left(\beta+\theta\right)(1-\mu f) + \cos\left(\beta+\theta\right)(\mu+f)} + \frac{1}{3}\lambda\_b l^3 \text{tg}^2\rho\_0 \text{tg}^2\left(45 - \frac{\beta}{2}\right)f + \frac{\beta}{2} \\ &+ G\_{\eta p} \left(f\cos^2\beta + \text{tg}\rho + \frac{2V^2\sin^2\frac{\beta}{2}}{K\rho cm \cdot \text{g}}\right) \end{split} \tag{17}$$

where *f n*� planner rolling resistance coefficient; *Gn*� mass of the planner; *β*� cutting angle; *f*, *μ*� coefficients of friction of soil on steel and soil on soil; *τ*� shear stress; *S*� shear area; *θ*� shear angle; *λv*� volumetric mass of soil as in the function of movement speed; *l*� bucket side length; *φ*0� angle of slope of the soil roller during movement; *Gnp*� mass of the soil roller; *V*� unit movement speed; and *Kycm*� coefficient taking into account the design of the rear wall of the bucket [10].

#### **4. Results and discussion**

From the analysis and conclusions we can see that with the increase in the rotation speed and diameter of the screw, the productivity of the screw working element increases. The screw pitch is also of great importance, with an increase in which increases the amount of soil movement to the sidewalls of the planner bucket, which in turn contributes to uniform distribution of the soil of the drawing prism along the width of the planner. With the increase in the speed of translational movement of the planner increases the functionality of the screw working element, that is the screws move a large volume of soil to the sides relative to each other. Below in **Figure 5**, the location of the screws in the bucket of the planner is shown.

Below are the curves (**Figures 7**–**9**) of the change in productivity of the screw working element of the planner depending on the rotation speed, diameter and

*Scheme of the location of the screws in the bucket of the planner (1—rear wall of the bucket, 2—tank walls,*

*Study of the Parameters of the Planner with a Screw Working Body*

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

As we can see from the graph (**Figure 7**), with the increase in screw rotation, the screw productivity is directly proportional to screw rotation. At a screw rotation of

The change in the performance of the screw in the function (Ds) of the diameter

six times. This increase in productivity approximately corresponds to the desired

Analysing this graph, we can say that the change in productivity along its diameter has curvilinear nature. Moreover, part of the curve to the point

corresponding to Ds = 180 mm is a power-law nature, and then the curve changes linearly. Further increase in the diameter of the screw (Ds) leads to the increase in its productivity so that the planner will not be able to provide the screws with soil for their normal operation. In addition, the increase in the given productivity of the

/h, and at screw rotation of 240 rpm, the screw

/h. That is, the productivity of the screw increases by

pitch of the screw.

**Figure 6.**

**131**

**Figure 5.**

*3—knife of the rear wall and 4—screws).*

40 rpm, the screw capacity is 2.56 m3

*General view of the experimental prototype of the mini planner.*

performance of the planning unit.

of the screw is shown in **Figure 8**.

capacity increases to 15.38 m3

However, such improvement in the work of the screw working element for our case, as shown by selective experiments with the experimental sample of a miniplanner, occurs up to the speed of 2 m/s of translational movement of the unit. Above this speed, the screws begin to be clogged with soil, and the technological process of the screw working body is violated. Below in **Figure 6**, experimental sample of a mini-planner with a screw working body is shown.

The above analysis requires investigating the productivity of the screw working body, depending on the rotation speed, diameter and pitch of the screw. Therein, the translational speed of the planning unit is also of significant importance. Because, the volume of the planner's bucket filled with soil per unit of time should be equal to the volume of the processed soil by the screws.

*Study of the Parameters of the Planner with a Screw Working Body DOI: http://dx.doi.org/10.5772/intechopen.93308*

#### **Figure 5.**

the speed of rotation and in diameters of the screw, the productivity of the screw working body increases. The screw pitch is also of great importance, with an increase in which the volume of soil moved to the sidewalls of the planner bucket increases, which in turn contributes to an even distribution of the soil of the drawing prism along the width of the planner passage. With an increase in the speed of forward movement of the planner increases the working capacity of the screw working body, that is screws move a large volume of soil to the sides relative to each other. However, such an improvement in the work of working element of the screw for our case, as shown by selective experiments with the experimental sample of a mini-planner, occurs up to a speed of 2 m/s of the forward movement of the unit. Above this speed, the screws begin to become clogged with soil, and the technolog-

We derived the equation of traction resistance of the planner, which has the

1 3 *λvl* 3 *tg*2

*φ*0*tg*2 45 � *β*

2 � �

*f*þ

(17)

ical process of the screw working body is violated.

*Direct Torque Control Strategies of Electrical Machines*

sin *β* 1 � *f*

*β* þ *tgρ* þ

2 � �2*f* cos *β* � �*τ* � *S* sin ð Þ *β* þ *θ* ð Þþ 1 � *μf* cosð Þ *β* þ *θ* ð Þ *μ* þ *f* þ

2*V*2 sin 2 *β*

*Kycm* � *g*

2

1

CA

where *f n*� planner rolling resistance coefficient; *Gn*� mass of the planner; *β*� cutting angle; *f*, *μ*� coefficients of friction of soil on steel and soil on soil; *τ*� shear stress; *S*� shear area; *θ*� shear angle; *λv*� volumetric mass of soil as in the function of movement speed; *l*� bucket side length; *φ*0� angle of slope of the soil roller during movement; *Gnp*� mass of the soil roller; *V*� unit movement speed; and *Kycm*� coefficient taking into account the design of the rear wall of the bucket [10].

From the analysis and conclusions we can see that with the increase in the rotation speed and diameter of the screw, the productivity of the screw working element increases. The screw pitch is also of great importance, with an increase in which increases the amount of soil movement to the sidewalls of the planner bucket, which in turn contributes to uniform distribution of the soil of the drawing prism along the width of the planner. With the increase in the speed of translational movement of the planner increases the functionality of the screw working element, that is the screws move a large volume of soil to the sides relative to each other. Below in **Figure 5**, the location of the screws in the bucket of the planner is shown. However, such improvement in the work of the screw working element for our case, as shown by selective experiments with the experimental sample of a miniplanner, occurs up to the speed of 2 m/s of translational movement of the unit. Above this speed, the screws begin to be clogged with soil, and the technological process of the screw working body is violated. Below in **Figure 6**, experimental

The above analysis requires investigating the productivity of the screw working body, depending on the rotation speed, diameter and pitch of the screw. Therein, the translational speed of the planning unit is also of significant importance. Because, the volume of the planner's bucket filled with soil per unit of time should

sample of a mini-planner with a screw working body is shown.

be equal to the volume of the processed soil by the screws.

following form:

*P* ¼ *f nGn* þ

þ*Gnp f* cos 2

**4. Results and discussion**

**130**

B@

0

*Scheme of the location of the screws in the bucket of the planner (1—rear wall of the bucket, 2—tank walls, 3—knife of the rear wall and 4—screws).*

**Figure 6.** *General view of the experimental prototype of the mini planner.*

Below are the curves (**Figures 7**–**9**) of the change in productivity of the screw working element of the planner depending on the rotation speed, diameter and pitch of the screw.

As we can see from the graph (**Figure 7**), with the increase in screw rotation, the screw productivity is directly proportional to screw rotation.  That is, the productivity of the screw increases by six times. This increase in productivity approximately corresponds to the desired performance of the planning unit.

The change in the performance of the screw in the function (Ds) of the diameter of the screw is shown in **Figure 8**.

Analysing this graph, we can say that the change in productivity along its diameter has curvilinear nature. Moreover, part of the curve to the point corresponding to Ds = 180 mm is a power-law nature, and then the curve changes linearly. Further increase in the diameter of the screw (Ds) leads to the increase in its productivity so that the planner will not be able to provide the screws with soil for their normal operation. In addition, the increase in the given productivity of the

*Change of the productivity of the screw working element depending on the speed of rotation of the screws (at Dp = 0.18 m, Sp = 0.15 m and Kн = 0.28—bucket filling ratio).*

working element could be obtained with a further increase in its diameter (Ds). But it is known that the increase in the diameter (Ds) of the screw is accompanied by greater energy consumption during its operation compared to the increase in the pitch of the screw. Therefore, a theoretical study of the work of the screw working element in the bucket of the planner allows us to conclude that for a given productivity of the planning unit, it is advantageous and advisable to use the screw parameters: Ds = 180 mm, ns = 240 rpm and screw pitch Ss = 180 mm.

*Change in the productivity of the screw working element depending on the pitch (Ss) of the screw*

*Study of the Parameters of the Planner with a Screw Working Body*

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

Increase in the productivity of the screw working element due to the increase in

corresponding material costs in comparison with the increase in the diameter (Ds) of the screw. In addition, further increase in the diameter of the screw causes

Using the methodology for conducting scientific research and processing the obtained data [2, 10], we derived empirical equations (formulas) of dependencies *y* ¼ *f n*ð Þ *ш* , *y* ¼ *f D*ð Þ *ш* and *y* ¼ *f S*ð Þ *ш* . For the graphs of **Figures 7**–**9**, respectively,

The screw working body surface was geometrically modelled by corresponding author and the offered geometric models give possibility to control engineering and technological parameters by optimization of geometric parameters of working surface, which may use this possibility in designing the working body of screw plan-

; and *y*3 ¼ 102, 5*X*, the curve of which is consistent with

the pitch of the screw reduces the metal consumption of the screw and the

difficulties in their layout in the bucket of the planner.

ners through exporting CAD models to CAE system [9, 11–15].

*y*1 ¼ 0, 064*X*; *y*2 ¼ 474, 7*X*2

**133**

**Figure 9.**

the curves shown in **Figures 7**–**9**.

*(at Ds = 0.18 m, ns = 240 rpm and Kн = 0.28).*

#### **Figure 8.**

*Change in productivity of the screw working element depending on the diameter (Ds) of the screw (at Ss = 0.15 m, ns = 240 rpm and Kн = 0.28).*

scheduler, which is accompanied by the increase in the translational speed of the movement of the unit above 7.5 km/h, leads to a disruption of the technological process of planning and the decrease in the quality indicators of field levelness [3].

The graph of the performance of the screw working element depending on the pitch (Sm) of the screw is shown in **Figure 9**.

As we can see from the graph, with the increase in the pitch of the screw (Ss), its productivity changes in direct proportion to the changes in the pitch (Ss), that is the functional change in the curve is linear. If with a screw pitch of 30 mm, the screw capacity is 3.07 m3 /h, then with a screw pitch of 180 mm, the productivity increases to 18.45 m3 /h, that is it increases six times.

Analysis of the graph (**Figure 9**) shows that increasing the screw pitch to 180 mm increases the capacity to 18.45 m3 /h, which is almost to 3 m3 more than at the screw pitch Ss = 150 mm. Such an increase in the productivity of the screw

*Study of the Parameters of the Planner with a Screw Working Body DOI: http://dx.doi.org/10.5772/intechopen.93308*

#### **Figure 9.**

*Change in the productivity of the screw working element depending on the pitch (Ss) of the screw (at Ds = 0.18 m, ns = 240 rpm and Kн = 0.28).*

working element could be obtained with a further increase in its diameter (Ds). But it is known that the increase in the diameter (Ds) of the screw is accompanied by greater energy consumption during its operation compared to the increase in the pitch of the screw. Therefore, a theoretical study of the work of the screw working element in the bucket of the planner allows us to conclude that for a given productivity of the planning unit, it is advantageous and advisable to use the screw parameters: Ds = 180 mm, ns = 240 rpm and screw pitch Ss = 180 mm.

Increase in the productivity of the screw working element due to the increase in the pitch of the screw reduces the metal consumption of the screw and the corresponding material costs in comparison with the increase in the diameter (Ds) of the screw. In addition, further increase in the diameter of the screw causes difficulties in their layout in the bucket of the planner.

Using the methodology for conducting scientific research and processing the obtained data [2, 10], we derived empirical equations (formulas) of dependencies *y* ¼ *f n*ð Þ *ш* , *y* ¼ *f D*ð Þ *ш* and *y* ¼ *f S*ð Þ *ш* . For the graphs of **Figures 7**–**9**, respectively, *y*1 ¼ 0, 064*X*; *y*2 ¼ 474, 7*X*2 ; and *y*3 ¼ 102, 5*X*, the curve of which is consistent with the curves shown in **Figures 7**–**9**.

The screw working body surface was geometrically modelled by corresponding author and the offered geometric models give possibility to control engineering and technological parameters by optimization of geometric parameters of working surface, which may use this possibility in designing the working body of screw planners through exporting CAD models to CAE system [9, 11–15].

scheduler, which is accompanied by the increase in the translational speed of the movement of the unit above 7.5 km/h, leads to a disruption of the technological process of planning and the decrease in the quality indicators of field levelness [3]. The graph of the performance of the screw working element depending on the

*Change in productivity of the screw working element depending on the diameter (Ds) of the screw*

*Change of the productivity of the screw working element depending on the speed of rotation of the screws*

*(at Dp = 0.18 m, Sp = 0.15 m and Kн = 0.28—bucket filling ratio).*

*Direct Torque Control Strategies of Electrical Machines*

Analysis of the graph (**Figure 9**) shows that increasing the screw pitch to

the screw pitch Ss = 150 mm. Such an increase in the productivity of the screw

As we can see from the graph, with the increase in the pitch of the screw (Ss), its productivity changes in direct proportion to the changes in the pitch (Ss), that is the functional change in the curve is linear. If with a screw pitch of 30 mm, the screw

/h, then with a screw pitch of 180 mm, the productivity increases

/h, which is almost to 3 m3 more than at

pitch (Sm) of the screw is shown in **Figure 9**.

*(at Ss = 0.15 m, ns = 240 rpm and Kн = 0.28).*

180 mm increases the capacity to 18.45 m3

/h, that is it increases six times.

capacity is 3.07 m3

to 18.45 m3

**132**

**Figure 8.**

**Figure 7.**

**References**

(69):41–44

Abrorov-51.pdf

nirovka\_0.pdf

[1] Khasanov IS, Norov SN. Theoretical

*DOI: http://dx.doi.org/10.5772/intechopen.93308*

*Study of the Parameters of the Planner with a Screw Working Body*

parameters of the screw working jointly with the planner bucket. Agrarian Science Journal, Moscow, 2015;**6**

[9] Juraev TK. Design the working surface based on the particle trajectory. In: Proceeding Outs of Conference "AVIA-2013". Kiev: NAU; 2013. pp. 21– 23. Available from: https://scholar.goog

7986884450713291378&hl=en&oi=sch

[10] Norov SN. Theoretical background for research of tractive effort of the planner. In: Collected papers of XXII International Scientific-Practical conference "Russian Science in the Modern World". Moscow. 2019. Available from: http://xn–80aa3afkg vdfe5he.xn–p1ai/RNSM-22\_originalma

[11] Juraev TK. Decision maintenance management problems in agriculture Engineering by Constructive Geometric Modeling Methods. Maintenance Management. Edited by Fausto Pedro García Márquez and Mayorkinos Papaelias. London, United Kingdom. 2020. pp. 23-37. https://mts.intechopen. com/storage/books/8623/authors\_book/.

[12] Juraev T.Kh, Murodov N.M, Naimov S.T. Application the Geometric Modeling Methods and Systems in Design Engineering and Manufacturing on Example of Agriculture Engineering. /Design and Manufacturing. /Edited by Evren Yasa, Mohsen Mhadhbi and Eleonora Santecchia. First published in London, United Kingdom, 2020 by IntechOpen, 211-231 p. http://dx.doi. org/10.5772/intechopen.83290.

[13] Juraev TK. Creating the geometric

Conference on Information Science and Communications Technologies ICISCT

database for product lifecycle management system in agricultural engineering. In: International

le.com/scholar?cluster=

olarr

ket\_N-1.pdf

experiments on the use of screw before

[2] Norov SN, Hamraeva MF. Analytical research of determining the maximum efficiency of planning machines. International Journal of Advanced Research in Science, Engineering and Technology. 2019:**6**(6):361-362.

Available from: http://www.ijarset.com/

Development of a Machine System for Complex Mechanization of Precultival Treatment of Agricultural Conditions in the Bukhara Region. Deutschland, Germany: LAP LAMBERT Academic Publishing; 2019. p. 65. Available from: https://www.lap-publishing.com/

[4] Efremov AN. Laser Planning of Irrigated Lands. Moscow. 2016.

[5] Antonov EV. Development of technological process of planning rice drafts using the multifunctional planning machine [Dissertation for the degree of candidate of technical

sciences]. Russia. 2008

Machinery. 2016;**3**:37

**135**

Available from: https://www.ya-fermer. ru/sites/default/files/lasernayapla

[6] Efremov AN, Yu NS. Machines and technologies of capital planning of rice drafts. Tractors and Agricultural

calculating the operational efficiency of

[8] Khasanov IS, Norov SN. Theoretical background for determining some

[7] Efremov AN. The method of

levers. Construction and Road Machines. 2015;**5**:42-46

upload/2019/june/37-IJARSET-

[3] Norov SN. Research and

background of the results of

the planner bucket. Universum: Technical Sciences Moscow. 2019;**12**