TY - JOUR
T1 - Data-driven blended equations of state for condensed-phase explosives
AU - Lee, Kibaek
AU - Hernández, Alberto M.
AU - Stewart, D. Scott
AU - Lee, Seungjoon
N1 - Funding Information:
D.S.S. (at University of Florida) is supported by the Office of Naval Research (ONR), Navy N00014-19-1-2084, and the Air Force Office of Scientific Research (AFOSR), FA9550-19-1-0204. K.L. and D.S.S. efforts recorded here have been recently supported at the University of Illinois by ONR grant, N00014-16-1-2057 and AFOSR grant AF FA9550-17-1-0223. S.L. is supported by the San José State University.
Publisher Copyright:
© 2021 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
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U2 - 10.1080/13647830.2021.1887524
DO - 10.1080/13647830.2021.1887524
M3 - Article
AN - SCOPUS:85101031674
SN - 1364-7830
VL - 25
SP - 413
EP - 435
JO - Combustion Theory and Modelling
JF - Combustion Theory and Modelling
IS - 3
ER -