Review of multi‐scale mechanical behavior research on composite solid propellants based on data‐driven approach

Composite solid propellant is a kind of viscoelastic composite with high filling ratio and multi‐scale composition characteristics, and its macroscopic mechanical properties strongly depend on the microstructure of the propellant materia. However, with the increasing complexity of composition, structure and properties of composite solid propellants, the traditional research paradigm based on experimental observation, theoretical modeling and numerical simulation has encountered new scientific challenges and technical bottlenecks in the mechanical behavior analysis, charge design and manufacturing of composite solid propellants. Among them, the problems such as insufficient experimental observation, lack of theoretical model, limited numerical analysis and difficult verification of results restrict the development of composite solid propellants in future‐oriented engineering applications to a certain extent. The data‐driven computational mechanics method can directly establish complex relationships between variables from high‐dimensional and high‐throughput data, which can capture trends that are difficult to be found by traditional mechanics research methods, and has inherent advantages in the analysis, prediction and optimization of complex systems. This paper mainly reviews and evaluates the research of neural network based modeling, model‐free data‐driven calculation and data‐driven multi‐scale calculation, which provides the correct direction for the subsequent research of multi‐scale mechanical behavior of composite solid propellants based on data‐driven.