热力学参数及边界条件是影响混凝土温控仿真计算精度的重要因素之一,而通过室内试验的方式获得这些参数成本较高,且往往与工程实际不符。引入粒子群算法,根据现场的混凝土非绝热温升试块试验成果,进行反演计算和分析。结果表明,粒子群算法可以用于混凝土温度场的反问题研究中,且反演结果精度较高。 Thermodynamic parameters and boundary conditions are one of the important factors affecting the simulation accuracy of concrete temperature control. However, these parameters obtained through laboratory tests are expensive and often not in accordance with engineering practice. Particle swarm optimization (PSO) algorithm is introduced to calculate and analyze the test results according to the test results of non-adiabatic temperature rise test blocks in the field. The results show that particle swarm optimization can be used in the inverse problem of temperature field of concrete, and the inversion result is more accurate.