A Simple Reactive-Flow Model for Corner-Turning in Insensitive High Explosives, Including Failure and Dead Zones. I. The Model

TL;DR

This paper introduces a simple, physically grounded reactive-flow model that effectively captures corner-turning, failure, and dead zones in insensitive high explosives, providing a computationally efficient alternative to existing complex models.

Contribution

The paper presents a novel, minimal-parameter reactive-flow model specifically designed for corner-turning in insensitive high explosives, improving computational efficiency and stability.

Findings

Model reproduces corner-turning in tests

Captures failure and dead zones accurately

More efficient than previous models

Abstract

I report on a novel simple reactive-flow model that captures corner-turning behaviour, including failure and the creation of dead zones, in insensitive solid heterogeneous high explosives. The model is fast, has a minimum of free parameters, and is physically grounded in the underlying initiation and burn phenomena. The focus of the model is explosives based on triaminotrinitrobenzene (TATB), although the model is quite general. I initially developed the model and integrated it into a branch of a Lawrence Livermore National Laboratory (LLNL) arbitrary Lagrangian-Eulerian (ALE) code concurrently with other modelling efforts of mine, but I subsequently adopted it to study corner-turning behavior in the TATB-based high explosive PBX 9502 when two other available models suggested to me proved inadequate, being either prohibitively computationally expensive or numerically unstable. An early version of the model reproduces corner-turning behavior in two different double-cylinder tests and a mushroom-type corner turning test. The model was informed and influenced by other reactive-flow models applicable to shock initiation or corner-turning, most especially including JWL++ Tarantula 2011 and an in-house piecewise-linear CHEETAH-based model that exhibits corner-turning behaviour, but also, to a degree, by Ignition & Growth (I&G), CREST, and the Statistical Hot-Spot Model. The model also shares some similarities to SURF models. In this paper, I describe the model and its theoretical development as I originally conceived it, as well as subsequent improvements.