We present a data-driven blended equation of state (EOS) approach for condensed phase high explosive materials. We first calibrate four different high explosive materials (Nitromethane, HMX, PETN and TATB) using a single or blending multiple Fried Howard Gibbs (FHG) EOS by an ad hoc trial and error method that has been used in the past, and which leads to a predictive model that can be used in engineering calculations. This ad-hoc calibration is then re-calibrated based on Bayesian optimisation via Gaussian Process regression. The two calibrations are then compared qualitatively and quantitatively and are shown to be in good to excellent agreement.

我们针对凝结高爆炸性材料提出了一种数据驱动的混合状态方程（EOS）方法。我们首先通过过去使用的临时试验和错误方法，使用单一或混合多个Fried Howard Gibbs（FHG）EOS来校准四种不同的高爆炸性材料（硝基甲烷，HMX，PETN和TATB）。可在工程计算中使用的预测模型。然后，通过高斯过程回归，基于贝叶斯优化，对该临时校准进行重新校准。然后对这两个校准进行定性和定量比较，结果表明一致性良好。