Data-driven blended equations of state for condensed-phase explosives

Kibaek Lee, Alberto M. Hernández, D. Scott Stewart, Seungjoon Lee

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)413-435
Number of pages23
JournalCombustion Theory and Modelling
Issue number3
StatePublished - 2021
Externally publishedYes

ASJC Scopus subject areas

  • General Chemistry
  • General Chemical Engineering
  • Modeling and Simulation
  • Fuel Technology
  • Energy Engineering and Power Technology
  • General Physics and Astronomy


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