I. Introduction
Computer simulation technology is based on a variety of disciplines and theories, using computers and their corresponding software as tools, through a virtual test method to analyze and solve a comprehensive technology. Computer simulation (simulation), formerly known as the Monte Carlo method, is a method for solving random problems using random number experiments. The principle can be traced back to the physical experiment conducted by the French naturalist GLBBuffon in 1773 to estimate the pi value. According to the type of computer used in the simulation process, computer simulation has experienced three major stages: simulator simulation, analog-digital mixer simulation and digital machine simulation. In the 1950s, computer simulation mainly used simulators; after the 1960s, serial processing digital machines were gradually applied to simulation, but it was difficult to meet the simulation time limit requirements of large-scale complex systems such as aerospace and chemical industry; and analog-digital hybrids in the 1970s. The machine was once used in many high-tech research fields such as flight simulation, satellite simulation and nuclear reactor simulation. After the development of parallel processing technology in the 1980s, the digital machine finally became the mainstream of computer simulation. Nowadays, computer simulation technology has been widely used in the fields of machinery manufacturing, aerospace, transportation, ship engineering, economic management, engineering construction, military simulation and medical and health.
Second, the realization of computer simulation
For objects that need to be studied, computers are generally not directly recognizable and processed. This requires a mathematical model that reflects the essence of the object being studied and is easily processed by computers.
The mathematical model abstracts the essence of the research object, and the computer processes the abstract mathematical models and displays some of the characteristics of the research object by outputting the relevant data of the models. Of course, the representation can be three-dimensional. As the 3D display is more clear and intuitive, it has been adopted by more and more researchers. By analyzing these outputs, you can more clearly understand the research object. It can also be seen from this relationship that the accuracy of mathematical modeling is the most critical factor in determining the accuracy of computer simulation. From the perspective of the model, the implementation of computer simulation can be divided into three major steps: the establishment of the model, the transformation of the model and the simulation of the model.
1. Model establishment
For the object or problem to be studied, it is first necessary to abstract a certain system according to the purpose of the simulation, and to give the boundary conditions and constraints of the system. After that, it is necessary to use the knowledge of various related disciplines to describe the abstracted system with mathematical expressions. The content of the description is the so-called "mathematical model". This model is the core of computer simulation.
The mathematical model of the system can be divided into static model, continuous time dynamic model, discrete time dynamic model and mixed time dynamic model according to time relationship; it can be divided into continuous variable system model and discrete event system model according to the state description and change mode of the system. For some problems of mathematical modeling, Hu Feng et al. of Xi'an Jiaotong University have a detailed discussion in "Review of Dynamic System Computer Simulation Technology (I) - Simulation Model".
2. Model conversion
The so-called model transformation, that is, the mathematical expression abstracted from the previous step is transformed into a form that the computer can process through various appropriate algorithms and computer language. The content represented by this form is the so-called "simulation model". This model is the key to computer simulation. To achieve this process, you can either develop a new system yourself or use the simulation software already available on the market. For example, the MAGMAsoft software is used for simulation in the casting process.
3. Model simulation experiment
The simulation model obtained in the previous step is loaded into the computer, and the simulation model is run according to the preset experimental scheme to obtain a series of simulation results, which is called "model simulation experiment".
With the above conditions, simulation experiments are an easy task. But how should we evaluate the results of this simulation? This requires analysis of the reliability of the simulation experiment. Hu Feng et al. proposed two methods for verifying the reliability of simulation results in the article "Overview of Dynamic System Computer Simulation Technology (II) - Analysis of Simulation Results": Confidence Channel Method and Reverse Verification Method of Simulation Process, for Reference .
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