改进粒子群算法求解具有复杂结构的瞬态非线性热传导反问题

Improved Particle Swarm Optimization for Solving Transient Nonlinear Inverse Heat Conduction Problem in Complex Structure

精确求解具有复杂结构的瞬态热传导反问题对于为耦合传热问题建模和结构优化设计提供关键参数具有重要意义。本文采用ABAQUS软件中的有限元法计算瞬态非线性热传导正问题,提出的改进粒子群算法(Particle swarm optimization,PSO)用于求解瞬态非线性热传导反问题;以具有再生冷却系统的超燃冲压发动机燃烧室不可接触表面的边界条件作为反向辨识参数,文中给出了一些数值测试用于检验该算法的性能。结果表明,新方法可以精确且有效地反向辨识具有可再生冷却系统的超燃冲压发动机燃烧室边界条件。通过求解瞬态非线性反问题,验证了改进例子群算法对求解具有复杂结构的瞬态非线性热传导反问题的有效性。

Accurately solving transient nonlinear inverse heat conduction problems in complex structures is of great importance to provide key parameters for modeling coupled heat transfer process and the structure’s optimization design.The finite element method in ABAQUS is employed to solve the direct transient nonlinear heat conduction problem.Improved particle swarm optimization(PSO)method is developed and used to solve the transient nonlinear inverse problem.To investigate the inverse performances,some numerical tests are provided.Boundary conditions at inaccessible surfaces of a scramjet combustor with the regenerative cooling system are inversely identified.The results show that the new methodology can accurately and efficiently determine the boundary conditions in the scramjet combustor with the regenerative cooling system.By solving the transient nonlinear inverse problem,the improved particle swarm optimization for solving the transient nonlinear inverse heat conduction problem in a complex structure is verified.