# Dynamic Modeling and Simulation Analysis of Virtual Product Design and Creation Based on OSG Artificial Intelligence Platform

Authors: Xiaosong Zou; Tao Tao
Journal: Discrete Dynamics in Nature and Society
 (2022)

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## Abstract

The creation of Koji Pottery art is a creative act that has risen rapidly in recent years. The difference in the proportion of ingredients in the glaze directly affects the roughness, luster, and glaze of the glazed surface of the work. The curve of heating and cooling is also the key to the success or failure of the work. Therefore, taking the Koji tea bowl shape as a research example, a virtual reality simulation system and an OSG (OpenSceneGraph) artificial intelligence platform are used to construct a Koji tea bowl shape simulation model, and then the physical production is performed according to the model. After the design and production of the Koji tea bowl shape, the RTM (resin transfer molding) model is used to evaluate the process quality standard requirements of the Koji bowl shape. According to the RTM model test results, the homogeneity test results show that the result is much larger than 0.10, from which it can be inferred that the Koji tea bowl shape has reached the national process quality standard requirements. At the same time, the OSG artificial intelligence platform uses the iterative random sampling method to extract and display the abnormal data in the simulation model, which greatly improves the success rate of ceramic creation. In this paper, the creation and simulation of virtual ceramics based on OSG artificial intelligence platform are deeply studied and analyzed, and the related processes are improved, which reduces the difficulty of software operation and improves the creation efficiency.


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## Body

## 1. Introduction

In the past, only professionals engaged in the production of pottery art were able to create the size and shape of pottery art. In the process of their creation, they use the physical object for kneading. Although they will sketch the sketch before the molding, there is still no intuitive understanding of the pottery art when there is no specific kneading [1]. Through this traditional pottery art creation process, the creators will waste a long time and the design ideas are not clear enough. At the same time, because the three-dimensional effect of pottery art is not intuitively presented, pottery art belongs to one-time kneading molding, which leads to repeated kneading if the actual three-dimensional effect is not good, which will undoubtedly increase the material cost and time cost of pottery art production [2]. This process is not only a high demand for the mass pottery art lovers, but also a major challenge for the main players engaged in pottery art production. With the development of modern information technology and the advancement of computer technology, people rely on powerful computer computing capabilities to try to simulate pottery shapes through software. Using the excellent computing power of the computer, the three-dimensional model of the pottery art can be simulated, which breaks through the limitation of the traditional drawing composition and cannot directly convey the three-dimensional structure [3]. Let the pottery art creators know the three-dimensional structure when the pottery art is finished in the early stage of creation and design. Minimize the secondary production in the physical production process due to the inconspicuous stereo sensory, reducing the time cost and material cost. However, because such pottery’s production software is still an emerging product, there are still many imperfections, and the operations are still complicated. Pottery artists also have a lot of inconvenience [4].Although the software for pottery art creation and simulation has developed to the present, a large number of excellent works have been born, but the research on how to combine the OSG artificial intelligence platform for pottery art creation is still short, and there are many imperfections [5]. With the increasing demand for pottery in the society, how to remind the creative efficiency of pottery art is an urgent task. Only by comprehensively improving the efficiency of pottery art creation can the basic needs of the people be fundamentally satisfied. Therefore, this paper conducts in-depth research and analysis on the virtual pottery art creation and simulation of the base OSG artificial intelligence platform and improves the related processes to comprehensively improve the efficiency of the pottery art creation and the convenience of simulation.In this paper, the Koji tea bowl shape is used as a research example. WorldToolKit and OmegaSpace are used to build a virtual reality simulation system and OSG artificial intelligence platform to construct a Koji tea bowl shape simulation model, and the pottery art creation is based on the model data. The virtual reality simulation system provides more than 1,200 object-oriented functions for designers to call and write, including sound, brightness, and other environmental properties that can be called and set in the program. The numerical results calculated by the equation are imported into the Koji tea bowl shape model to make the properties conform to the actual characteristics in the environment, so that the simulation is more in line with the real situation. At the same time, the OSG artificial intelligence platform uses the iterative random sampling method to extract and display the abnormal data appearing in the simulation model, which greatly improves the success rate of pottery art creation.This paper mainly has the following innovations in several aspects: (1) the traditional virtual pottery art creation and simulation software contains a large number of professional parameters, which requires a large amount of professional knowledge to carry out smooth operation. However, as the number of people involved in the production of pottery has increased significantly, many people without relevant professional knowledge will not be able to smoothly simulate the creation of pottery art, which greatly reduces the efficiency of pottery art creation. In this paper, the virtual pottery art creation and simulation based on OSG artificial intelligence platform is deeply researched and analyzed, and the related processes are improved to reduce the difficulty of software operation and improve the creation efficiency. (2) The RTM model is used to evaluate the process quality standard requirements of the Koji tea bowl shape, and the actual effect of the theoretical model is verified by real data.The organizational structure of this paper is as follows: Section1 mainly describes the research background and the organizational structure of the article. Section 2 mainly describes the research status of OSG artificial intelligence platform in Koji Pottery art design. Section 3 mainly describes the design process of the algorithm model. Section 4 mainly describes the practical research in the creation and simulation of virtual pottery art in OSG artificial intelligence platform. Section 5 is mainly to summarize the research results.


## 2. Related Work

Virtual simulation technology was first born in the early 1980s. Liang proposed using computer technology to simulate human sensory feelings and simulate real vision and hearing through various means [6]. At the same time, the operator can further enhance the effect of virtual simulation by interacting with various simulated things in the virtual scene through the device. At the beginning of the birth, scholars proposed simulating the simulated planetary environment through this virtual technology. In this way, the simulated environment can be used to train the astronauts on various operations on the outer planet, which is conducive to the real landing of outer planets in the future [7]. Luo and Zhang proposed setting up multiple virtual simulation military training points, and connecting them through the network, so that unified operation management can be realized, and finally the force integration exercise system [8]. Ning proposed using custom professional data collection gloves to perform simulation modeling operations. Finally, virtual simulation modeling was implemented [9]. Jia proposed that the collector can be used to collect the human body motion data, and then the data is input into a specific robotic arm, so that the robot arm can perform the same limb movement as the collector. In this way, the machine can be remotely simulated [10]. According to the actual needs of virtual operations, Li et al. proposed a distributed system of DVS (Distributed Vibration Sensing) and used it as the underlying operating system. Based on this, a number of virtual environment operation technologies have been introduced, which greatly reduced the number of virtual environment operation technologies. The difficulty of virtual software development has greatly improved the simulation effect of virtual software [11]. Zhong and Tong proposed virtual reality dynamic system technology to further realize the dynamic tracking feedback of virtual simulation items, which made the virtual environment more authentic and enhanced the interaction with the virtual simulation system [12]. Wu et al. proposed adding simulated hand operation in the field of pottery space state and system dynamic simulation, in this way to achieve hand simulation control pottery modeling [13]. Guo suggested that although the simulation of hand operations, combined with 3D (three-dimensional) virtual software, can simulate the shaping of pottery’s, however, due to the inaccuracy of the simulation data, the pottery model was relatively rough, cannot be too fine control, or cannot meet the actual requirements of pottery art creation; it needed to be further optimized to improve the control ability of the simulated pottery model [14]. Yang et al. proposed combining graphic design software and 3D model software to further optimize the actual rendering effect of virtual pottery art and improve the decorative form of pottery art and the simulation effect of the kind (as shown in Figure 1) [15].Figure 1
The schematic diagram of the algorithm model.Through the analysis of the creation and simulation of virtual pottery art, it can be clearly understood that there are many research works carried out by various circles at present, and there are many research contents in both its theoretical basis and practical application [16, 17]. However, they are more concerned with the virtual pottery art creation and simulation itself, and combined with the OSG artificial intelligence platform, there is little involvement [18, 19]. Therefore, based on the virtual pottery art creation and simulation of OSG artificial intelligence platform, this paper conducts in-depth research and optimization, optimizes the operation of virtual pottery art creation and simulation, and enhances its creative efficiency (as shown in Figure 2).Figure 2
Network distance teaching based on streaming media technology has a wealth of research.


## 3. Algorithm Model Design

### 3.1. OSG Artificial Intelligence Platform

For now, the OSG artificial intelligence platform is mainly used in the processing of complex data models. It can be analyzed by process modeling during the research process [20]. There are two common modes: the fundamental model and the empirical model; the so-called fundamental model is based on the basic physics and chemical laws of the program. This model is often caused by internal mechanisms that are too complex, or where there are unknown or uncertain parameters that cause failure or unsatisfactory verification results [21]. Therefore, in order to establish an empirical model, the empirical model is to treat the program as a “Black Box” without knowing the program organization in question and only rely on the input and output data of the program. The model determined by mathematical skills is represented by artificial intelligence technology. The so-called artificial intelligence technology is a technique that mimics the establishment of human thinking and operation. It can also be divided into the artificial neural network, the genetic algorithm (genetic algorithms), and the fuzzy theory (fuzzy theorem). The OSG artificial intelligence platform mainly uses dynamic learning rules, genetic algorithms, and RANSAC data analysis algorithms to train different network architectures such as optimization neural network link weights through the common factors of factor analysis and is used to process abnormal data in virtual pottery art data model. The OSG artificial intelligence platform is a data calculus method that uses an iterative random sampling method to extract and screen abnormal data to obtain a mathematical model. The implementation principle is mainly based on two different data types that exist in the sample data: (1) normal data model; (2) noise and anomalous data model. The algorithm believes that the reason why it cannot adapt to the mathematical model is mainly because the abnormal data may be caused by wrong assumptions in the process of mathematical model calculation (as shown in Figure 3). However, these erroneous data often lack sufficient parameters to restore them. To this end, the algorithm restores its real data by multiple iterative screening methods. The basic implementation process is as follows.Figure 3
The healing of tendon injury was obtained by medical image analysis.Firstly, it is necessary to obtain the necessary data model data information. The means of obtaining is mainly to traverse the data through SPSS data statistics software (as shown in Figure4). Depending on the field of use, it can be divided into two types: airspace processing and frequency domain processing; the former is directly processed on the data model itself and the latter is to carry out various calculations and analysis on the data model after special processing. The airspace processing formula is as follows:(1)gx,y=EHfx,y.Figure 4
Local image information for the first derivative operator.
(a)(b)(c)(d)Among them,f⋅ is the data model before enhancement, and g⋅ is the enhanced data model, indicating enhanced operation.For a continuous functionfx,y, its gradient at position x,y can be expressed as(2)∇fx,y=Gx,y=GxGyT=∂f∂x∂f∂yT.A gradient is a vector whose amplitude and direction angle are(3)∇f=Gx,y=Gx2+Gy21/2,(4)ϕx,y=arctanGyGx.The approximate expression of the gradient is(5)Gx=fi,j+1−fi,j,(6)Gy=fi+1,j−fi,j.Usually, in order to reduce the amount of calculation, the absolute value is usually approximated by the gradient magnitude.(7)Gx,y=Gx+Gy.When analyzing a data model, the approximate value is usually calculated using a small area template tape measure (as shown in Figure5). One template is used for each of Gx and Gy, which requires two templates. According to the size of different templates, the calculation properties are different. Therefore, there are Roberts operators, Prewitt operators, and Sobel operators.Figure 5
The operator approximates the amplitude of the continuous gradient of the edge point.
(a)(b)(c)(d)The Roberts operator convolution template is(8)Gx=100−1,(9)Gy=01−10.The gradient templates in the horizontal and vertical directions of the Sobel operator are(10)Gx=−101−202−101,(11)Gy=121000−1−2−1.The gradient template in the two directions of the Prewitt operator is(12)Gx=−101−101−101,(13)Gy=111000−1−1−1.Then, the corner data extraction is performed on the content of the data model that has completed the preliminary processing. Suppose there are variablesIx and Iy that are used to represent the first-order partial derivatives of the data model in two different aspects of the Cartesian coordinate x-axis and y-axis. Then the function wx,y can be used to represent a two-dimensional Gaussian smoothing function on Cartesian coordinates. The calculation process of this function is shown in the following two formulas:(14)M=∑x,ywx,yIx2IxIyIxIyIy2,(15)R=detM−k⋅traceM2,k=0.04∼0.2.Solving equation (15) yields a specific number for each corner R on the data model. Then, using the corner points calculated by the normalization idea to match, the data model corner point value can be obtained. The matching calculation equation is as follows:(16)NCC=∑iI1xi,yi−u1I2xi,yi−u2∑iI1xi,yi−u12∑iI2xi,yi−u22.At the same time, the RANSAC data analysis algorithm can be used to purify the data model corner values (as shown in Figure6). In the process of purification, the data model needs to be purified according to the hierarchical channel mode, so there is the following linear algebraic formula:(17)R2G2B2=cr000cg000cb⋅R1G1B1+drdgdb.Figure 6
In the process of purification, the image should be considered separately according to the red, green, and blue color channels.
(a)(b)The variablesR2, G2, and B2 in the above formula represent three different levels of channels of the data model. The variable c,d is mainly used to represent the transformation parameters of the linear formula.This paper uses the R channel as an example to calculate. It is assumed that there are corner data of different data models of then groups, and the variable dn represents the absolute distance of the different data points R2,R1n to the straight line c,d. At this point, the purification is done by iterative summation as follows:(18)E=∑Tdn2.In the above formula, when the condition satisfiesdn2<Thre2, Tdn2=dn2. Otherwise Tdn2=Thre2. Filter the corners of the data model that meet the conditions and continue the iterative calculation. Until the value of E is not significantly changed, the entire purification process is completed (as shown in Figure 7).Figure 7
Image segmentation technique.After the data model is segmented, the similarity calculation is performed with the established data model in the database, and matching is performed according to the calculated result. The matching result of the data model is extremely characteristic. Use the following function to measure the similarity betweenT and f:(19)SEx,y=∑i=1N∑j=1Nfx−i,y−j−Ti,j2.Among them, the size of the data model isN×N, and the above formula provides a measure for the degree of matching between the data model T and f at the x,y coordinate data model. Expand the above formula to calculate its matching result:(20)SEx,y=∑i=1N∑j=1Nf2x−i,y−j−2∑i=1N∑j=1Nfx−i,y−jTi,j+∑i=1N∑j=1NT2i,j.


### 3.2. Koji Pottery Creation Skills

Koji Pottery is a low-temperature glazed soft pottery that combines painting, sculpture, glaze, and pottery. Tracing back to the source, it is a long-standing and long-lasting pottery art from Fujian and Guangdong. The production process is as follows: (1) soil selection. The clay used in modern times is about half-porcelain, Japanese scorpion, Chinese black soil, Golden Gate white clay, and Miaoli soil used to blend head and hand color. In order to make the clay plasticity good, the raw material selection of the clay should be proportional, and the shrinkage ratio is preferably about 10%, and the relationship of the gem glaze is a light glaze. After the rough body is mixed, it is better to be white when it is bisque firing, because the white color of the rough body can more accurately display the bright glaze. (2) Modeling. Form a work style that is greatly different from modern and early traditions. Modern Koji Pottery has more molding moldings than traditional ones. Mass production has become the trend of modern Koji Pottery. Molding of compacting blanks is a modern skill. Parts of larger pieces or high-complexity pieces are separately produced and combined to complete shaping (as shown in Figure8).Figure 8
Can accept messages sent by other nodes that are not participating.(3) Rough body. It is almost similar to traditional techniques. The difference is that the early traditional blanks have no front and back; that is, there is no rough shell behind; generally only the left and right sides can see the rough body, while the back is empty. The modern rough body is multidimensional, and the back is not empty. The rough body is hollowed out from below or another suitable place, and then the bottom or back is sealed, leaving only a vent for the kiln to burn. (4) Dry. Craftsmanship is similar to tradition. (5) Bisque firing. Rough body bisque firing refers to the direct kiln firing of the unglazed body, referred to as bisque firing. Rough body should be placed in the kiln to pay attention to the way of kiln, how to stack, and how to burn evenly. When the kiln is burned, it is necessary to pay attention to the temperature rise slowly, especially the preheating baking before the kiln is burned. It takes at least 20 hours or more; when the temperature rises by 4°C, the kiln door can be closed. In order to find the hardness of the rough body, it usually burns to 800°C. Today, it is usually burnt twice: the first is bisque firing rough body, and the second is glaze burning (as shown in Figure9).Figure 9
Multicast is the sending of data packets to a host group represented by a unique IP address.
(a)(b)


## 3.1. OSG Artificial Intelligence Platform

For now, the OSG artificial intelligence platform is mainly used in the processing of complex data models. It can be analyzed by process modeling during the research process [20]. There are two common modes: the fundamental model and the empirical model; the so-called fundamental model is based on the basic physics and chemical laws of the program. This model is often caused by internal mechanisms that are too complex, or where there are unknown or uncertain parameters that cause failure or unsatisfactory verification results [21]. Therefore, in order to establish an empirical model, the empirical model is to treat the program as a “Black Box” without knowing the program organization in question and only rely on the input and output data of the program. The model determined by mathematical skills is represented by artificial intelligence technology. The so-called artificial intelligence technology is a technique that mimics the establishment of human thinking and operation. It can also be divided into the artificial neural network, the genetic algorithm (genetic algorithms), and the fuzzy theory (fuzzy theorem). The OSG artificial intelligence platform mainly uses dynamic learning rules, genetic algorithms, and RANSAC data analysis algorithms to train different network architectures such as optimization neural network link weights through the common factors of factor analysis and is used to process abnormal data in virtual pottery art data model. The OSG artificial intelligence platform is a data calculus method that uses an iterative random sampling method to extract and screen abnormal data to obtain a mathematical model. The implementation principle is mainly based on two different data types that exist in the sample data: (1) normal data model; (2) noise and anomalous data model. The algorithm believes that the reason why it cannot adapt to the mathematical model is mainly because the abnormal data may be caused by wrong assumptions in the process of mathematical model calculation (as shown in Figure 3). However, these erroneous data often lack sufficient parameters to restore them. To this end, the algorithm restores its real data by multiple iterative screening methods. The basic implementation process is as follows.Figure 3
The healing of tendon injury was obtained by medical image analysis.Firstly, it is necessary to obtain the necessary data model data information. The means of obtaining is mainly to traverse the data through SPSS data statistics software (as shown in Figure4). Depending on the field of use, it can be divided into two types: airspace processing and frequency domain processing; the former is directly processed on the data model itself and the latter is to carry out various calculations and analysis on the data model after special processing. The airspace processing formula is as follows:(1)gx,y=EHfx,y.Figure 4
Local image information for the first derivative operator.
(a)(b)(c)(d)Among them,f⋅ is the data model before enhancement, and g⋅ is the enhanced data model, indicating enhanced operation.For a continuous functionfx,y, its gradient at position x,y can be expressed as(2)∇fx,y=Gx,y=GxGyT=∂f∂x∂f∂yT.A gradient is a vector whose amplitude and direction angle are(3)∇f=Gx,y=Gx2+Gy21/2,(4)ϕx,y=arctanGyGx.The approximate expression of the gradient is(5)Gx=fi,j+1−fi,j,(6)Gy=fi+1,j−fi,j.Usually, in order to reduce the amount of calculation, the absolute value is usually approximated by the gradient magnitude.(7)Gx,y=Gx+Gy.When analyzing a data model, the approximate value is usually calculated using a small area template tape measure (as shown in Figure5). One template is used for each of Gx and Gy, which requires two templates. According to the size of different templates, the calculation properties are different. Therefore, there are Roberts operators, Prewitt operators, and Sobel operators.Figure 5
The operator approximates the amplitude of the continuous gradient of the edge point.
(a)(b)(c)(d)The Roberts operator convolution template is(8)Gx=100−1,(9)Gy=01−10.The gradient templates in the horizontal and vertical directions of the Sobel operator are(10)Gx=−101−202−101,(11)Gy=121000−1−2−1.The gradient template in the two directions of the Prewitt operator is(12)Gx=−101−101−101,(13)Gy=111000−1−1−1.Then, the corner data extraction is performed on the content of the data model that has completed the preliminary processing. Suppose there are variablesIx and Iy that are used to represent the first-order partial derivatives of the data model in two different aspects of the Cartesian coordinate x-axis and y-axis. Then the function wx,y can be used to represent a two-dimensional Gaussian smoothing function on Cartesian coordinates. The calculation process of this function is shown in the following two formulas:(14)M=∑x,ywx,yIx2IxIyIxIyIy2,(15)R=detM−k⋅traceM2,k=0.04∼0.2.Solving equation (15) yields a specific number for each corner R on the data model. Then, using the corner points calculated by the normalization idea to match, the data model corner point value can be obtained. The matching calculation equation is as follows:(16)NCC=∑iI1xi,yi−u1I2xi,yi−u2∑iI1xi,yi−u12∑iI2xi,yi−u22.At the same time, the RANSAC data analysis algorithm can be used to purify the data model corner values (as shown in Figure6). In the process of purification, the data model needs to be purified according to the hierarchical channel mode, so there is the following linear algebraic formula:(17)R2G2B2=cr000cg000cb⋅R1G1B1+drdgdb.Figure 6
In the process of purification, the image should be considered separately according to the red, green, and blue color channels.
(a)(b)The variablesR2, G2, and B2 in the above formula represent three different levels of channels of the data model. The variable c,d is mainly used to represent the transformation parameters of the linear formula.This paper uses the R channel as an example to calculate. It is assumed that there are corner data of different data models of then groups, and the variable dn represents the absolute distance of the different data points R2,R1n to the straight line c,d. At this point, the purification is done by iterative summation as follows:(18)E=∑Tdn2.In the above formula, when the condition satisfiesdn2<Thre2, Tdn2=dn2. Otherwise Tdn2=Thre2. Filter the corners of the data model that meet the conditions and continue the iterative calculation. Until the value of E is not significantly changed, the entire purification process is completed (as shown in Figure 7).Figure 7
Image segmentation technique.After the data model is segmented, the similarity calculation is performed with the established data model in the database, and matching is performed according to the calculated result. The matching result of the data model is extremely characteristic. Use the following function to measure the similarity betweenT and f:(19)SEx,y=∑i=1N∑j=1Nfx−i,y−j−Ti,j2.Among them, the size of the data model isN×N, and the above formula provides a measure for the degree of matching between the data model T and f at the x,y coordinate data model. Expand the above formula to calculate its matching result:(20)SEx,y=∑i=1N∑j=1Nf2x−i,y−j−2∑i=1N∑j=1Nfx−i,y−jTi,j+∑i=1N∑j=1NT2i,j.


## 3.2. Koji Pottery Creation Skills

Koji Pottery is a low-temperature glazed soft pottery that combines painting, sculpture, glaze, and pottery. Tracing back to the source, it is a long-standing and long-lasting pottery art from Fujian and Guangdong. The production process is as follows: (1) soil selection. The clay used in modern times is about half-porcelain, Japanese scorpion, Chinese black soil, Golden Gate white clay, and Miaoli soil used to blend head and hand color. In order to make the clay plasticity good, the raw material selection of the clay should be proportional, and the shrinkage ratio is preferably about 10%, and the relationship of the gem glaze is a light glaze. After the rough body is mixed, it is better to be white when it is bisque firing, because the white color of the rough body can more accurately display the bright glaze. (2) Modeling. Form a work style that is greatly different from modern and early traditions. Modern Koji Pottery has more molding moldings than traditional ones. Mass production has become the trend of modern Koji Pottery. Molding of compacting blanks is a modern skill. Parts of larger pieces or high-complexity pieces are separately produced and combined to complete shaping (as shown in Figure8).Figure 8
Can accept messages sent by other nodes that are not participating.(3) Rough body. It is almost similar to traditional techniques. The difference is that the early traditional blanks have no front and back; that is, there is no rough shell behind; generally only the left and right sides can see the rough body, while the back is empty. The modern rough body is multidimensional, and the back is not empty. The rough body is hollowed out from below or another suitable place, and then the bottom or back is sealed, leaving only a vent for the kiln to burn. (4) Dry. Craftsmanship is similar to tradition. (5) Bisque firing. Rough body bisque firing refers to the direct kiln firing of the unglazed body, referred to as bisque firing. Rough body should be placed in the kiln to pay attention to the way of kiln, how to stack, and how to burn evenly. When the kiln is burned, it is necessary to pay attention to the temperature rise slowly, especially the preheating baking before the kiln is burned. It takes at least 20 hours or more; when the temperature rises by 4°C, the kiln door can be closed. In order to find the hardness of the rough body, it usually burns to 800°C. Today, it is usually burnt twice: the first is bisque firing rough body, and the second is glaze burning (as shown in Figure9).Figure 9
Multicast is the sending of data packets to a host group represented by a unique IP address.
(a)(b)


## 4. Practical Application

### 4.1. Experimental Overview

Pottery is a profound knowledge. It consists of the understanding and blending of sifting soil, cultivating soil, shaping, and glaze properties, to the firing curve of bisque firing and glaze burning. Each method has its skills and knowledge. The glaze pharmacy is a subject that has changed thousands of times. The difference in the proportion of ingredients in the glaze directly affects the roughness, luster, and glaze of the glazed surface of the work. In particular, in the firing process, in order to reduce the firing temperature and change the firing atmosphere, the rough body component and the glaze component are adjusted several times, and the temperature rise and fall curves are also the key to determining the success or failure of the work (Figure10). Therefore, taking the Koji tea bowl shape as a research example, the virtual reality simulation system and the OSG artificial intelligence platform were used to construct the Koji tea bowl shape simulation model, in order to provide a data foundation for the real Koji tea bowl shape creation, and improve the success rate of Pottery art creation.Figure 10
The expert model of building energy intelligent management is applied to the energy management of the building garden.


### 4.2. Experimental Simulation

Tianmu teacup has a long history, elegant black rabbit cups, and lined with fresh white tea, so the color contrast is distinct, in line with the Song Dynasty literati pursuit of pure and simple aesthetic philosophy. The most representative of the Tianmu tea bowl shape is the Jianyao teacup. In this series of tea bowls, the tea bowl shape is shaped like a kiln cup. The rough body is made of three clays, such as Yuli Y-202 clay, Japanese purple clay, and American black clay, used alone or in combination. Qu tea bowl is made of clay and shaped like a pile of cups. The lips are short and outward without obvious distortion. The belly is round, and the overall shape is hemispherical, and the pier is short and round. The rough body is blended with Japanese purple clay and American black clay. The glazing method is single-hung immersion method, and after glazing, it is oxidized and fired at 123 degrees Celsius. Therefore, WorldToolKit and OmegaSpace are used to build a virtual reality simulation system to create Koji tea bowl shape. WTK is a set of virtual reality software. Strictly speaking, it is just a set of functions that use Visual C++ as the main program. It provides more than 1,200 object-oriented functions for designers to call and write. Various environmental attributes, such as sound, brightness, etc., can be called and set in the program. The numerical results calculated by the equation are imported into the Koji tea bowl shape model to make the properties conform to the actual characteristics in the environment, so that the simulation is more in line with the real situation. The system program first sets the data of all global variables first, such as Viewing Volume, Viewpoint, Input Sensor, and Scene Graph Hierarchies. Then execute WTuniverse_go() to enter the simulation loop until WTuniverse_stop() is called; the system leaves the loop, clears the occupied resources, and ends the program. OmegaSpace is a software package with a windowed interface and can be directly transferred to the model via Visual C++ as a numerical model calculation tool and via network transmission or RS-232C. OmegaSpace’s settings for sound, brightness, and collision detection are set directly on the interface, and you do not need to write complex program code yourself like WTK. After the construction of the Koji tea bowl shape simulation model is completed, the artwork is created according to the model data (as shown in Figure11).Figure 11
Actively issue abnormal energy consumption and alert to reduce wrong energy consumption.


### 4.3. Experimental Evaluation

RTM resin transfer molding is a material manufacturing method with low pressure and closed container. Without additional pressure, all the original materials can be vacuumized in the non-open-space and closely combined by injecting resin at the same time to complete the fabrication of composites.After the design and production of the Koji tea bowl shape, the RTM model was used to evaluate the process quality standards of the Koji tea bowl. The execution steps are as follows: find different evaluation indexes of the evaluated objects and establish an evaluation weight matrix R, calculate the product of each row element of the judgment matrix R, and obtain the actual weight value of the different indicators of the evaluated object. The evaluation score can be calculated by calculating the weight value and the evaluation content data. The evaluation results can be obtained by calculating the data information recorded during the experiment according to the above calculation method (as shown in Figure12). The data in the figure shows that the homogeneity test results of the Koji tea bowl shape designed in this paper are P=0.662>0.10. Since the result is much larger than 0.10, it can be inferred that the Koji tea bowl shape has reached the national process quality standard requirements.Figure 12
Precision instrument of watt-hour meter tester with fault in transmission system.The evaluation data show that the test results of the uniformity of the shape of the designed curved tea bowl are correct. Since the result is far greater than 0.10, it can be inferred that the shape of cross toe bowl has reached the national process quality standard. To sum up, the iterative random sampling method is used to extract the abnormal data in the simulation model. The implementation principle is mainly based on two different data types in the sample data: (1) normal data model; (2) noise and abnormal data model. The algorithm believes that the data that cannot adapt to the mathematical model is mainly due to the abnormal data caused by the wrong assumptions in the calculation process of the mathematical model. However, these error data usually lack sufficient parameters to recover them. Therefore, the algorithm restores its real data through a variety of iterative filtering methods. After the design and production of the curved bowl shape, the RTM model is used to evaluate the process quality standard of the curved bowl. This greatly reduces the efficiency of ceramic art creation. This paper improves the relevant process and reduces the difficulty of software operation.


## 4.1. Experimental Overview

Pottery is a profound knowledge. It consists of the understanding and blending of sifting soil, cultivating soil, shaping, and glaze properties, to the firing curve of bisque firing and glaze burning. Each method has its skills and knowledge. The glaze pharmacy is a subject that has changed thousands of times. The difference in the proportion of ingredients in the glaze directly affects the roughness, luster, and glaze of the glazed surface of the work. In particular, in the firing process, in order to reduce the firing temperature and change the firing atmosphere, the rough body component and the glaze component are adjusted several times, and the temperature rise and fall curves are also the key to determining the success or failure of the work (Figure10). Therefore, taking the Koji tea bowl shape as a research example, the virtual reality simulation system and the OSG artificial intelligence platform were used to construct the Koji tea bowl shape simulation model, in order to provide a data foundation for the real Koji tea bowl shape creation, and improve the success rate of Pottery art creation.Figure 10
The expert model of building energy intelligent management is applied to the energy management of the building garden.


## 4.2. Experimental Simulation

Tianmu teacup has a long history, elegant black rabbit cups, and lined with fresh white tea, so the color contrast is distinct, in line with the Song Dynasty literati pursuit of pure and simple aesthetic philosophy. The most representative of the Tianmu tea bowl shape is the Jianyao teacup. In this series of tea bowls, the tea bowl shape is shaped like a kiln cup. The rough body is made of three clays, such as Yuli Y-202 clay, Japanese purple clay, and American black clay, used alone or in combination. Qu tea bowl is made of clay and shaped like a pile of cups. The lips are short and outward without obvious distortion. The belly is round, and the overall shape is hemispherical, and the pier is short and round. The rough body is blended with Japanese purple clay and American black clay. The glazing method is single-hung immersion method, and after glazing, it is oxidized and fired at 123 degrees Celsius. Therefore, WorldToolKit and OmegaSpace are used to build a virtual reality simulation system to create Koji tea bowl shape. WTK is a set of virtual reality software. Strictly speaking, it is just a set of functions that use Visual C++ as the main program. It provides more than 1,200 object-oriented functions for designers to call and write. Various environmental attributes, such as sound, brightness, etc., can be called and set in the program. The numerical results calculated by the equation are imported into the Koji tea bowl shape model to make the properties conform to the actual characteristics in the environment, so that the simulation is more in line with the real situation. The system program first sets the data of all global variables first, such as Viewing Volume, Viewpoint, Input Sensor, and Scene Graph Hierarchies. Then execute WTuniverse_go() to enter the simulation loop until WTuniverse_stop() is called; the system leaves the loop, clears the occupied resources, and ends the program. OmegaSpace is a software package with a windowed interface and can be directly transferred to the model via Visual C++ as a numerical model calculation tool and via network transmission or RS-232C. OmegaSpace’s settings for sound, brightness, and collision detection are set directly on the interface, and you do not need to write complex program code yourself like WTK. After the construction of the Koji tea bowl shape simulation model is completed, the artwork is created according to the model data (as shown in Figure11).Figure 11
Actively issue abnormal energy consumption and alert to reduce wrong energy consumption.


## 4.3. Experimental Evaluation

RTM resin transfer molding is a material manufacturing method with low pressure and closed container. Without additional pressure, all the original materials can be vacuumized in the non-open-space and closely combined by injecting resin at the same time to complete the fabrication of composites.After the design and production of the Koji tea bowl shape, the RTM model was used to evaluate the process quality standards of the Koji tea bowl. The execution steps are as follows: find different evaluation indexes of the evaluated objects and establish an evaluation weight matrix R, calculate the product of each row element of the judgment matrix R, and obtain the actual weight value of the different indicators of the evaluated object. The evaluation score can be calculated by calculating the weight value and the evaluation content data. The evaluation results can be obtained by calculating the data information recorded during the experiment according to the above calculation method (as shown in Figure12). The data in the figure shows that the homogeneity test results of the Koji tea bowl shape designed in this paper are P=0.662>0.10. Since the result is much larger than 0.10, it can be inferred that the Koji tea bowl shape has reached the national process quality standard requirements.Figure 12
Precision instrument of watt-hour meter tester with fault in transmission system.The evaluation data show that the test results of the uniformity of the shape of the designed curved tea bowl are correct. Since the result is far greater than 0.10, it can be inferred that the shape of cross toe bowl has reached the national process quality standard. To sum up, the iterative random sampling method is used to extract the abnormal data in the simulation model. The implementation principle is mainly based on two different data types in the sample data: (1) normal data model; (2) noise and abnormal data model. The algorithm believes that the data that cannot adapt to the mathematical model is mainly due to the abnormal data caused by the wrong assumptions in the calculation process of the mathematical model. However, these error data usually lack sufficient parameters to recover them. Therefore, the algorithm restores its real data through a variety of iterative filtering methods. After the design and production of the curved bowl shape, the RTM model is used to evaluate the process quality standard of the curved bowl. This greatly reduces the efficiency of ceramic art creation. This paper improves the relevant process and reduces the difficulty of software operation.


## 5. Conclusion

The virtual reality simulation system and the OSG artificial intelligence platform were used to create Koji tea bowl pottery. Due to the difference in the proportion of ingredients in the enamel of the roasted toe bowl, it directly affects the roughness, gloss, and glaze of the glazed surface of the work. In particular, in the firing process, in order to lower the firing temperature and change the firing atmosphere, the green body component and the glaze component are adjusted several times, and the temperature rise and temperature drop curves are also the key to determining the success or failure of the work. Therefore, WorldToolKit and OmegaSpace are used to build a virtual reality simulation system to simulate the Koji tea bowl shape. The virtual reality simulation system provides more than 1,200 object-oriented functions for designers to call and write, including sound, brightness, and other environmental properties that can be called and set in the program. The numerical results calculated by the equation are imported into the Koji tea bowl shape model to make the properties conform to the actual characteristics in the environment, so that the simulation is more in line with the real situation. At the same time, the OSG artificial intelligence platform is used to extract the abnormal data appearing in the simulation model by using iterative random sampling. The implementation principle is mainly based on two different data types that exist in the sample data: (1) normal data model; (2) noise and anomalous data model. The algorithm believes that the data that cannot adapt to the mathematical model is mainly because the abnormal data may be caused by wrong assumptions in the process of mathematical model calculation. However, these erroneous data often lack sufficient parameters to restore them. Therefore, the algorithm restores its real data by multiple iterative screening methods. After the design and production of the Koji bowl shape, the RTM model is used to evaluate the process quality standards of the Koji bowl. The evaluation data shows that the homogeneity test results of the designed Koji tea bowl shape areP=0.662>0.10. Since the result is much larger than 0.10, it can be inferred that the cross-toe bowl shape has reached the national process quality standard. However, the OSG artificial intelligence platform used in this paper has certain design flaws in the anomaly data screening, which is not conducive to popularization and application. Therefore, in future research, the defects in this aspect will be improved.



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*Source: 6214097-2022-01-17.xml*