Physics-informed machine learning model for prediction of ground reflected wave peak overpressure  

作　　者：Haoyu Zhang Yuxin Xu Lihan Xiao Canjie Zhen 

机构地区：[1]State Key Lab of Explosion Science and Technology,Beijing Institute of Technology,Beijing 100081,China [2]Chongqing Innovation Center,Beijing Institute of Technology,Chongqing 404100,China [3]Tangshan Research Institute,Beijing Institute of Technology,Tangshan 442000,China [4]Shandong Special Industry Group Co.Ltd.,Zibo 255000,China

出　　处：《Defence Technology（防务技术）》2024年第11期119-133,共15页Defence Technology

摘　　要：The accurate prediction of peak overpressure of explosion shockwaves is significant in fields such as explosion hazard assessment and structural protection, where explosion shockwaves serve as typical destructive elements. Aiming at the problem of insufficient accuracy of the existing physical models for predicting the peak overpressure of ground reflected waves, two physics-informed machine learning models are constructed. The results demonstrate that the machine learning models, which incorporate physical information by predicting the deviation between the physical model and actual values and adding a physical loss term in the loss function, can accurately predict both the training and out-oftraining dataset. Compared to existing physical models, the average relative error in the predicted training domain is reduced from 17.459%-48.588% to 2%, and the proportion of average relative error less than 20% increased from 0% to 59.4% to more than 99%. In addition, the relative average error outside the prediction training set range is reduced from 14.496%-29.389% to 5%, and the proportion of relative average error less than 20% increased from 0% to 71.39% to more than 99%. The inclusion of a physical loss term enforcing monotonicity in the loss function effectively improves the extrapolation performance of machine learning. The findings of this study provide valuable reference for explosion hazard assessment and anti-explosion structural design in various fields.

关 键 词：Blast shock wave Peak overpressure Machine learning Physics-informed machine learning 

分 类 号：TJ03[兵器科学与技术—兵器发射理论与技术]