The design optimization of thermal-driven actuators is a challenging task because the performance depends on multiple materials parameters,structural parameters,and working conditions.In this work,we adopted large scale finite element simulation together with machine leing algorithm to fulfill the on-demand design of thermal actuators.Finite element analysis was used to simulate the performance of thermal actuator with two-layer structure,which generated large amount of dataset by considering the variation of parameters including the moduli,thermal expansion coefficient,sample thickness and length,and temperature.Support vector regression (SVR) was adopted to establish the relationship between multiple input parameters and the resulting contact pressure.Thereafter,a simple interior point algorithm was used to achieve the on-demand design based on the SVR model.The contact pressures of thermal actuator constructed from the optimized parameters deviated less than 15％ of the target values.