Prediction of Shock Wave Velocity Temporal Evolution Induced by Ms-Ns Combined Pulse Laser Based on Attention-LSTM

This study systematically examined shock wave velocity induced by millisecond–nanosecond combined-pulse laser (ms–ns CPL) at a fixed ns laser energy density of 6 J/cm2, exploring the effects of varying pulse delays of 0 to 3 ms and ms laser energy densities of 226.13 J/cm2, 301 J/cm2 and 376.89 J/cm2. The temporal evolution of shock wave velocity induced by varying laser parameters was predicted by an attention mechanism-based long short-term memory algorithm (Attention-LSTM). The dependence between laser parameters and the evolution of shock wave velocity was captured by the LSTM layer. An attention mechanism was utilized to adaptively increase the weights of important time points during the propagation of the shock wave, thereby improving prediction accuracy. The experimental data corresponding to ms laser energy densities of 226.13 J/cm2 and 301 J/cm2 were set as the training set. The ms laser energy density of 376.89 J/cm2 experimental data was set as test set to evaluate the generalization ability of the model under unknown ms laser energy. The results indicate that when ms laser energy density is 376.8 J/cm2, the pulse delay is 2.2 ms. The shock wave velocity induced by the CPL increased by 50.77% compared with that induced by a single ns laser. The proposed Attention-LSTM model effectively predicts the evolutionary characteristics of shock wave velocity. The mean absolute error (MAE), root mean square error (RMSE), mean bias error (MBE) and the correlation coefficient (R2) of the test set are 7.65, 9.01, 1.47 and 0.98, respectively. This study provides a new data-driven approach for predicting the shock wave behavior induced by combined laser parameters and provides valuable guidance for optimizing laser process parameter combinations.