基于ANSYS和MATLAB智能算法的电石热物性参数反演

电石是一种重要的化工基础原料，其冷凝、降温过程对电石出炉系统设计和生产流程控制有着重要影响，因此研究电石的冷却过程有着重要的意义。由于无法通过实验手段测量电石内部温度，需要通过软件仿真获得电石冷却过程中的温度场分布。而目前国内在材料热物性参数方面的数据和研究较少，缺少电石导热系数值。基于ANSYS热仿真和MATLAB智能算法，利用神经网络和遗传算法进行参数反演，得到了电石的热传导系数随温度变化的值。结果表明这种方法有效可行，对电石出炉系统设计和生产流程控制起到了重要的指导作用，并为研究物质的热物性参数提供了一种新思路。

Thermal Parameter Inversion of Calcium Carbide Based on ANSYS and MATLAB Intelligent Algorithm

Calcium carbide is a kind of important fundamental raw material in chemical industry , its con-densation and cooling process has important influence on the design of Calcium Carbide tapping system and control of production process .For it is impossible to measure its inner temperature by experimental means , need to simulate its temperature field in the cooling process with software .However, research and data on thermophysical property of ma-terial is rare in domestic , and the coefficient of heat tronsmission simulation is lack of data .This article is based on ANSYS thermal analysis and MATLAB intelligent algorithm , and get the thermal conductivity of Calcium Carbide which varies with the temperature through parameter inversion with neural network and genetic algorithm .The Result shows that this method is effective and feasible , it provides important guidance in the design of Calcium Carbide tap-ping system and process control , and offers a new method to research on thermophysical parameter of materials .