The High Explosives and Affected Targets (HEAT) Dataset

arXiv cs.LG / 4/22/2026

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Key Points

The HEAT dataset is proposed to fill a gap in public training and validation data for AI surrogate models of high-explosive-driven, multi-material shock dynamics.
It provides physics-rich, 2D cylindrically symmetric simulation data generated with an Eulerian multi-material shock-propagation code from Los Alamos National Laboratory.
HEAT is split into two simulation partitions—CYL (expanding shock-cylinder, with varying materials including metals, polymers, water, gases, and a detonator) and PLI (perturbed layered interfaces with fixed materials).
Each dataset entry includes time-series thermodynamic fields (e.g., pressure, density, temperature), kinematic fields (position, velocity), and continuum quantities such as stress.
By capturing phenomena like shock propagation, momentum transfer, plastic deformation, thermal effects, and detonation physics via reactive materials, HEAT aims to serve as a benchmark for AI/ML models in multi-material shock physics.

Abstract

Artificial Intelligence (AI) surrogate models provide a computationally efficient alternative to full-physics simulations, but no public datasets currently exist for training and validating models of high-explosive-driven, multi-material shock dynamics. Simulating shock propagation is challenging due to the need for material-specific equations of state (EOS) and models of plasticity, phase change, damage, fluid instabilities, and multi-material interactions. Explosive-driven shocks further require reactive material models to capture detonation physics. To address this gap, we introduce the High-Explosives and Affected Targets (HEAT) dataset, a physics-rich collection of two-dimensional, cylindrically symmetric simulations generated using an Eulerian multi-material shock-propagation code developed at Los Alamos National Laboratory. HEAT consists of two partitions: expanding shock-cylinder (CYL) simulations and Perturbed Layered Interface (PLI) simulations. Each entry includes time series of thermodynamic fields (pressure, density, temperature), kinematic fields (position, velocity), and continuum quantities such as stress. The CYL partition spans a range of materials, including metals (aluminum, copper, depleted uranium, stainless steel, tantalum), a polymer, water, gases (air, nitrogen), and a detonating material. The PLI partition explores varied geometries with fixed materials: copper, aluminum, stainless steel, polymer, and high explosive. HEAT captures key phenomena such as shock propagation, momentum transfer, plastic deformation, and thermal effects, providing a benchmark dataset for AI/ML models of multi-material shock physics.