Research on Efficient Dynamics Simulation Technology for Artillery Equipment

Abstract

In response to the efficiency bottleneck in the overall design phase of artillery, this paper proposes an agile design tool for artillery based on the RecurDyn solver, IAOD. This tool achieves rapid evaluation and optimization design of artillery dynamics simulation models through parametric modeling and integration of shooting test data. The IAOD system adopts a fully parameterized driven template model, combined with machine learning, parameter identification, and multi-level optimization algorithms, significantly improving the design efficiency of large caliber self-propelled artillery. The system innovatively applied a sparse single hidden layer neural network proxy model and a simulation parameter identification method based on test data, achieving multi-objective collaborative optimization. The effectiveness and practicality of the IAOD system have been verified through the practical application of a vehicle mounted artillery design case, demonstrating its potential for application in the field of artillery design. This study has significant military and defense value in improving the efficiency and quality of artillery equipment development.