Heterogeneous Energetic Materials Research Articles

Effects of micrometer-scale cavities on the shock-to-detonation transition in a heterogeneous LX-17 energetic material

Cavities and other fracture structures within energetic materials may have significant impact on their performance. The mechanism on how hot spots induced by cavity collapse affect the detonation initiation process is still not fully understood. In this work, two-dimensional simulations are conducted for heterogeneous LX-17 energetic material containing array-distributed cavities to investigate the detonation initiation process induced by the impaction of the incident shock wave (ISW), and the impacts of cavity size and volume fraction on the shock-to-detonation transition (SDT) are also evaluated. First, we fix the cavity radius to be 40 μm and the cavity volume fraction to be 12.57%, and compare the detonation initiation processes for neat and heterogeneous LX-17 energetic materials. The results indicate that cavities within LX-17 can accelerate the detonation initiation, i.e., shortening the initiation distance and time. Then, the flow characteristics and incident shock wave evolutions during the cavity collapse process are analyzed. The results show that the interaction between the cavity and the incident shock wave results in the local hot spots and causes LX-17 reactant to auto-ignite, so as to accelerate the shock-to-detonation transition. Finally, the influence of the cavity size and volume fraction on the detonation initiation process is assessed. It is found that as the cavity volume fraction increases, the detonation initiation distance and time increase and even become larger than the results predicted of the neat case, i.e., the acceleration effect of cavities on the detonation initiation weakens and the cavities even inhibits the shock-to-detonation transition. When the cavity volume fraction is fixed, it is found cases of small-size cavity predict longer initiation distance and time than cases of large-size cavity. The analysis indicates that increasing cavity volume fraction corresponds to smaller density of LX-17 reactant, and the hot spot duration time is shorter for cases of small-size cavity than cases of large-size cavity. Therefore, the detonation initiation distance and time increase as the cavity volume fraction increases and the cavity size decreases.

Physically evocative meso-informed sub-grid source term for energy localization in shocked heterogeneous energetic materials

Reactive burn models for heterogeneous energetic materials (EMs) must account for chemistry as well as microstructure to predict shock-to-detonation transition (SDT). Upon shock loading, the collapse of individual voids leads to ignition of hotspots, which then grow and interact to consume the surrounding material. The sub-grid dynamics of shock-void interactions and hotspot development are transmitted to macro-scale SDT calculations in the form of a global reactive “burn model.” This paper presents a physically evocative model, called meso-informed sub-grid source terms for energy localization (MISSEL), to close the macro-scale governing equations for calculating SDT. The model parameters are explicitly related to four measurable physical quantities: two depending on the microstructure (the porosity ϕ and average pore size D¯void), one depending on shock–microstructure interaction (the fraction of critical voids ξcr), and the other depending on the chemistry (the burn front velocity Vhs). These quantities are individually quantifiable using a small number of rather inexpensive meso-scale simulations. As constructed, the model overcomes the following problems that hinder the development of meso-informed burn models: (1) the opacity of more sophisticated surrogate/machine-learning approaches for bridging meso- and macro-scales, (2) the rather large number of high-resolution mesoscale simulations necessary to train machine-learning algorithms, and (3) the need for calibration of many free parameters that appear in phenomenological burn models. The model is tested against experimental data on James curves for a specific class of pressed 1,3,5,7-tetranitro-1,3,5,7-tetrazoctane materials. The simple, evocative, and fast-to-construct MISSEL model suggests a route to develop frameworks for physics-informed, simulation-derived meso-informed burn models.

A Physics‐Aware Deep Learning Model for Energy Localization in Multiscale Shock‐To‐Detonation Simulations of Heterogeneous Energetic Materials

AbstractPredictive simulations of the shock‐to‐detonation transition (SDT) in heterogeneous energetic materials (EM) are vital to the design and control of their energy release and sensitivity. Due to the complexity of the thermo‐mechanics of EM during the SDT, both macro‐scale response and sub‐grid mesoscale energy localization must be captured accurately. This work proposes an efficient and accurate multiscale framework for SDT simulations of EM. We introduce a new approach for SDT simulation by using deep learning to model the mesoscale energy localization of shock‐initiated EM microstructures. The proposed multiscale modeling framework is divided into two stages. First, a physics‐aware recurrent convolutional neural network (PARC) is used to model the mesoscale energy localization of shock‐initiated heterogeneous EM microstructures. PARC is trained using direct numerical simulations (DNS) of hotspot ignition and growth within microstructures of pressed HMX material subjected to different input shock strengths. After training, PARC is employed to supply hotspot ignition and growth rates for macroscale SDT simulations. We show that PARC can play the role of a surrogate model in a multiscale simulation framework, while drastically reducing the computation cost and providing improved representations of the sub‐grid physics. The proposed multiscale modeling approach will provide a new tool for material scientists in designing high‐performance and safer energetic materials.

Preparation of quasi-core/shell structured composite energetic materials to improve combustion performance.

Composite explosives with fast reaction rate, high energy release efficiency, and remarkable combustion performance can be obtained by the interaction between homogeneous energetic materials and heterogeneous energetic materials and have broad application prospects. However, ordinary physical mixtures can easily cause separation between the components in the preparation process, which is not conducive to reflecting the advantages of composite materials. In this study, high-energy composite structured explosives with RDX modified by polydopamine as the core and PTFE/Al as the shell were prepared using a simple ultrasonic method. The study of morphology, thermal decomposition, heat release, and combustion performance demonstrated that the quasi-core/shell structured samples have higher exothermic energy, faster combustion rate, more stable combustion characteristics, and lower mechanical sensitivity than the physical mixture.

Domain partitioning material point method for simulating shock in polycrystalline energetic materials

Heterogeneous energetic materials (EMs) subjected to mechanical shock loading exhibit complex thermo-mechanical processes which are driven by the high temperature, pressure, and strain rate behind the shock. These lead to spatial energy localization in the microstructure, colloquially known as “hotspots” where chemistry may commence and possibly culminating in detonation. Shock-induced pore collapse is one of the dominant mechanisms by which localization occurs. In order to physically predict the shock sensitivity of energetic materials under these extreme conditions, we formulate a multiplicative crystal plasticity model with key features inferred from molecular dynamics (MD) simulations. Within the framework of thermodynamics, we incorporate the pressure dependence of both monoclinic elasticity and critical resolved shear stress into the crystal plasticity formulation. Other fundamental mechanisms, such as strain hardening and pressure-dependent melting curves, are all inferred from atomic-scale computations performed across relevant intervals of pressure and temperature. To handle the extremely large deformation and the evolving geometry of the self-contact due to pore collapse, we leverage the capabilities of the Material Point Method (MPM) to track the interface via the Lagrangian motion of material points and the Eulerian residual update to avoid the mesh distortion issue. This combination of features enables us to simulate the shock-induced pore collapse and associated hotspot evolution with a more comprehensive physical underpinning, which we apply to the monoclinic crystal β-HMX. Treating MD predictions of the pore collapse as ground truth,head-to-head validation comparisons between MD and MPM predictions are made for samples with identical sample geometry and similar boundary conditions for reverse-ballistic impact speeds ranging from 0.5kms−1 to 2.0kms−1. Comparative studies are performed to reveal the importance of incorporating a frictional contact algorithm, pressure-dependent elastic stiffness, and non-Schmid critical resolved shear stress in the mesoscale model.

Mechanisms of shock-induced initiation at micro-scale defects in energetic crystal-binder systems

Crystals of energetic materials, such as HMX, embedded in plastic binders are the building blocks of plastic-bonded explosives. Such heterogeneous energetic materials contain microstructural features such as sharp corners, interfaces between crystal and binder, intra- and extra-granular voids, and other defects. Energy localization or hotspots arise during shock interaction with the microstructural heterogeneities, leading to the initiation of PBXs. In this paper, high-resolution numerical simulations are performed to elucidate the mechanistic details of shock-induced initiation in a PBX; we examine four different mechanisms: Shock-focusing at sharp corners or edges and its dependency on the shape of the crystal, and the strength of the applied shock; debonding between crystal and binder interfaces; collapse of voids in the binder located near an HMX crystal; and the collapse of voids within HMX crystals. Insights are obtained into the relative contributions of these mechanisms to the ignition and growth of hotspots. Understanding these mechanisms of energy localization and their relative importance for hotspot formation and initiation sensitivity of PBXs will aid in the design of energetic material-driven systems with controlled sensitivity, to prevent accidental initiation and ensure reliable performance.

Multi-scale modeling of shock initiation of a pressed energetic material. II. Effect of void–void interactions on energy localization

Heterogeneous energetic materials (EMs) contain microstructural defects such as voids, cracks, interfaces, and delaminated zones. Under shock loading, these defects offer potential sites for energy localization, i.e., hotspot formation. In a porous EM, the collapse of one void can generate propagating blast waves and hotspots that can influence the hotspot phenomena at neighboring voids. Such void–void interactions must be accounted for in predictive multi-scale models for the reactive response of a porous EM. To infuse such meso-scale phenomena into a multi-scale framework, a meso-informed ignition and growth model (MES-IG) has been developed, where the influence of void–void interactions is incorporated into the overall reaction rate through a function, fv−v. Previously, MES-IG was applied to predict the sensitivity and reactive response of EM, where fv−v was assumed to be a function of the overall sample porosity alone. This paper performs a deeper analysis to model the strong dependency of fv−v on other factors, such as void size and shock strength. The improved model for void–void interactions produces good agreement with direct numerical simulations of the HE microstructures and, thus, advances the predictive capability of multi-scale models of the shock response and sensitivity of EM.

Effect of void positioning on the detonation sensitivity of a heterogeneous energetic material

Although it is well-established that voids profoundly influence the initiation and reaction behaviors of heterogeneous energetic materials such as polymer-bonded explosives (PBX) and propellants, there has been little study of how void location in different constituents in the microstructures of such materials affect the macroscale behavior. Here, we use three-dimensional (3D) mesoscale simulations to study how void placement within the reactive grains vs the polymer binder influences the shock-to-detonation transition in a polymer-bonded explosive. The material studied here has a microstructure comprised of 75% PETN (pentaerythritol tetranitrate) grains and 25% hydroxyl-terminated polybutadiene polymer binder by volume. Porosities up to 10% in the form of spherical voids distributed in both the grains and polymer are considered. An Arrhenius reactive burn relation is used to model the chemical kinetics of the PETN grains under shock loading, thereby resolving the heterogeneous detonation behavior of the PBX. The influence of void location on the shock initiation sensitivity of the material is quantitatively ranked by comparing the predicted run distance to detonation (RDD) for each sample. The analysis includes inherent quantification of uncertainties arising from the stochastic variations in the microstructure morphologies and void distributions by using statistically equivalent microstructure sample sets, leading to probabilistic formulations for the RDD as a function of shock pressure. The calculations reveal that the location of voids in the composite microstructure significantly affects the RDD. Specifically, voids exclusively within the grains cause the PBX to be more sensitive (having shorter RDD) than voids in the polymer binder. Unique probabilistic relationships are derived to map the probability of observing RDD for each void location material case, allowing for prediction of initiation behavior anywhere in the shock pressure–RDD space. These findings agree with trends reported in the literature.

Meso-scale simulation of energetic materials. I. A method for generating synthetic microstructures using deep feature representations

The response of a wide class of heterogeneous energetic materials (HEs) to loads is determined by dynamics at the meso-scale, i.e., by physicochemical processes in their underlying microstructure. Structure–property–performance (S–P–P) linkages for such materials can be developed in a multi-scale framework, connecting the physics and thermophysical properties at the meso-scale to response at the macro-scale. Due to the inherent stochasticity of the microstructure, ensembles of microstructures are required to conduct meso-scale simulations to establish S–P–P linkages. Here, a deep neural network-based method called deep feature representation is applied to generate a range of material microstructures from heterogeneous energetic materials to metal foams and metallic mixtures. The method allows for the generation of stochastic microstructures using a single real microstructure as the input and is not limited to low packing density or topological complexity of solids. In its application to pressed energetic materials, we show that qualitative and quantitative features of real (i.e., imaged) microstructures are captured in the synthetic microstructures. Therefore, a stochastic ensemble of synthetic microstructures can be created for use in reactive meso-scale simulations to relate the microstructures of HEs to their performance. While the focus is on pressed HE microstructures, we also show that the method is general and useful for generating microstructures for in silico experiments for a wide range of composite/multiphase materials, which can be used to establish S–P–P linkages.

Multi-scale modeling of shock initiation of a pressed energetic material I: The effect of void shapes on energy localization

Accurate simulations of the shock response of heterogeneous energetic (HE) materials require closure models, which account for energy localization in the micro-structure. In a multi-scale framework, closure is provided by reaction rate models that account for ignition and growth of hotspots, allowing for prediction of the overall macro-scale sensitivity of a HE material. In the present meso-informed ignition and growth (MES-IG) model, the reaction rate is expressed as a function of shock pressure and morphology of the void field in a pressed energetic material. In MES-IG, the void morphology is quantified in terms of a limited number of parameters: viz., overall porosity, void size, and shape (aspect ratio and orientation). In this paper, we quantify the effects of arbitrary variations in void shapes on meso-scale energy deposition rates. A collection of voids of arbitrary shapes is extracted from scanning electron microscope (SEM) images of real, pressed HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine) samples and classified into groups based on their similarity in shapes. Direct numerical simulations (DNS) are performed on the highly contorted “real” void shapes, and the calculated hotspot ignition and growth rates are compared with values predicted by the MES-IG. It is found that while the parameterization of complex void morphologies in terms of orientation and aspect ratio gives fairly good agreement between DNS and MES-IG reaction rates, the intricate details of highly complex void shapes impact hotspot characteristics to a significant extent. This work suggests possible improvements for the prediction of reaction rate in the energetic microstructure by adopting a more detailed description of shapes.

Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

The sensitivity of heterogeneous energetic (HE) materials (propellants, explosives, and pyrotechnics) is critically dependent on their microstructure. Initiation of chemical reactions occurs at hot spots due to energy localization at sites of porosities and other defects. Emerging multi-scale predictive models of HE response to loads account for the physics at the meso-scale, i.e. at the scale of statistically representative clusters of particles and other features in the microstructure. Meso-scale physics is infused in machine-learned closure models informed by resolved meso-scale simulations. Since microstructures are stochastic, ensembles of meso-scale simulations are required to quantify hot spot ignition and growth and to develop models for microstructure-dependent energy deposition rates. We propose utilizing generative adversarial networks (GAN) to spawn ensembles of synthetic heterogeneous energetic material microstructures. The method generates qualitatively and quantitatively realistic microstructures by learning from images of HE microstructures. We show that the proposed GAN method also permits the generation of new morphologies, where the porosity distribution can be controlled and spatially manipulated. Such control paves the way for the design of novel microstructures to engineer HE materials for targeted performance in a materials-by-design framework.

Evaluation of reaction kinetics models for meso-scale simulations of hotspot initiation and growth in HMX

Meso-scale modeling of heterogeneous energetic materials requires accurate description of the chemical reaction model that governs the decomposition of solid energetic crystals to gaseous products. For HMX, various 1-step and multi-step Arrhenius based chemical kinetic models are available; these chemical kinetics models for HMX have been calibrated against macro-scale experimental data under different ranges of pressure and temperature conditions, which may lie outside the ranges that arise during void collapse. Therefore, depending on the reaction model, the predicted meso-scale hotspot initiation and growth behavior can vary. Here, we examine the effects of five global HMX reaction kinetics models on predictions of void collapse induced hotspots, viz. the Henson-Smilowitz 1-step (HS1), Menikoff 1-step (M1), Tarver-Nichols 3-step (TN3), Henson-Smilowitz 9-step (HS9) and a 7-step extended Brill-Yetter model (BYS7). Variations in the hotspot behavior predicted using the different models are observed to be significant. A detailed examination of the individual reaction mechanisms of each of these global chemistry models is undertaken to provide insights and understanding of the reaction steps that lead to the differences in the predicted hotspot behavior. For the temperature regime relevant to the void collapse generated hotspots, the differences in the hotspot behavior are attributed to the orders of magnitude variations in the reaction rates that govern the maximum energy release during HMX decomposition. The paper shows that the issue of a suitable kinetics model, even for the commonly used HMX material, remains unsettled.

Unified Approach for Meso-Informed Burn Models in Shocked Energetic Materials

Reactive hydrocode calculations of shock-to-detonation transition in heterogeneous energetic (HE) materials need to be closed with burn models. One requirement of burn models is to supply a macroscale control volume with an energy release rate due to chemical reactions that reflects the subgrid physics of hotspot ignition and growth. Energy localization at hotspots delivers chemical energy at a rate , where is the heat of reaction and is a meso-scale energy localization time scale. This energy deposition rate is much larger than nominal Arrhenius-form chemical energy deposition rates in a homogeneous sample subjected to the same shock loading. To develop meso-informed energy deposition rate models, this paper identifies a meso-scale energy release time scale that is common to burn models based on the hotspot ignition and growth concept. The identification of a common time scale allows for a unified microstructure-aware, physics-based reactive burn model; high-fidelity meso-scale numerical simulations are used to construct a surrogate model for . The surrogate model is shown to capture the effects of microstructural parameters on and can be used for meso–macro coupling in a multiscale model to predict the sensitivity of HE materials.

Formation of heterogeneous energetic materials to regulate sensitivity of TATB by 2D materials

The exploration of relationship between energetic density and stability is essential for the development of high energy density materials. Using the first-principles calculations, we investigate the electronic structures and effective masses of TATB/2D (graphene, MoS2, MoTe2, WS2) heterogeneous energetic materials. We find that the main contribution to the band gap decrease is due to the energy bands moving towards lower energy levels. The decreased effective mass with the increasing pressure is the same as the change of band gap, meaning that the decreased effective mass after heterogeneity is good for sensitization of energetic materials. The introduction of 2D materials into insensitive high explosives is a promising way to make controlled explosives.

Prediction of Probabilistic Detonation Threshold via Millimeter‐Scale Microstructure‐Explicit and Void‐Explicit Simulations

AbstractWe present an approach and relevant models for predicting the probabilistic shock‐to‐detonation transition (SDT) behavior and Pop plot (PP) of heterogeneous energetic materials (HEM) via mesoscopic microstructure‐explicit (ME) and void explicit (VE) simulations at the millimeter (mm) sample size scale. Although the framework here is general, the particular material considered in this paper is pressed Octahydro‐1,3,5,7‐tetranitro‐1,2,3,5‐tetrazocine (HMX). To systematically delineate the effects of material heterogeneities, four material cases are considered. These cases are homogeneous material, material with granular microstructure but no voids, homogeneous material with voids, and material with both granular microstructure and voids. Statistically equivalent microstructure sample sets (SEMSS) are generated and used. Eulerian hydrocode simulations explicitly resolve the material heterogeneities, voids, and the coupled mechanical‐thermal‐chemical processes. In particular, it is found that both microstructure and voids strongly influence the SDT behavior and PP. The effects of different combinations of microstructure heterogeneity and voids on the SDT process and PP are quantified and rank‐ordered. The overall framework uses the Mie–Grüneisen equation of state and a history variable reactive burn model (HVRB). A novel probabilistic representation for quantifying the PP is developed, allowing the calculation of (1) the probability of observing SDT at a given combination of shock pressure and run distance, (2) the run‐distance to detonation under a given combination of shock pressure and prescribed probability, and (3) the shock pressure required for achieving SDT at a given run distance with a prescribed probability. The results are in agreement with general trends in experimental data in the literature.

Effects of parametric uncertainty on multi-scale model predictions of shock response of a pressed energetic material

Predictive simulations of shock-to-detonation transitions (SDTs) of energetic materials must contend with uncertainties in the material properties, reactive models, and the microstructures of the material. In this work, we analyze the effects of uncertainties in the run-to-detonation distance h of a pressed energetic (HMX) material due to variabilities in the thermomechanical properties of HMX. The run distances are computed using a recently developed machine-learning based multiscale modeling framework, viz., the Meso-informed Ignition and Growth (MES-IG) model. The input uncertainties are first used in the MES-IG model to quantify the variabilities in the hotspot dynamics at the mesoscale. A Kriging-based Monte Carlo method is used to construct probability density functions (pdfs) for the mesoscale reaction-product formation rates; these are used to propagate the mesoscale uncertainties to the macroscale reaction-progress variables to construct pdfs for the run-to-detonation distance h. We evaluate uncertainties in h due to variabilities in six material properties, viz., specific heat, Grüneisen parameter, bulk modulus, yield strength, thermal expansion coefficient, and the thermal conductivity of the material. Among these six properties, h is found to be most sensitive to the variabilities in the specific heat of the material; the uncertainties in the specific heat amplify exponentially across scales and result in logarithmic pdfs for h. Thus, the paper not only quantifies and propagates uncertainties in material properties across scales in a multiscale model of SDT, but also ranks the properties with respect to the sensitivity of the SDT response of heterogeneous energetic materials on each property.

Void collapse generated meso-scale energy localization in shocked energetic materials: Non-dimensional parameters, regimes, and criticality of hotspots

The formation of hotspots due to collapse of voids leads to enhanced sensitivity of heterogeneous energetic (HE) materials. Several mechanisms of void collapse have been identified, but the regimes in which these mechanisms dominate have not been clearly delineated using scaling arguments and dimensionless parameters. This paper examines void collapse in cyclotetramethylene-tetranitramine (HMX) to demarcate regimes where plastic collapse and hydrodynamic jetting play dominant roles in influencing hotspot related sensitivity. Using scaling arguments, a criticality envelope for HMX is derived in the form Σcr=∑(Ps,Dvoid), i.e., as a function of shock pressure Ps and void size Dvoid, which are controllable design parameters. Once a critical hotspot forms, its subsequent growth displays a complex relationship to Ps and Dvoid. These complexities are explained with scaling arguments that clarify the physical mechanisms that predominate in various regimes of hotspot formation. The insights and scaling laws obtained can be useful in the design of HE materials.

Multi-scale shock-to-detonation simulation of pressed energetic material: A meso-informed ignition and growth model

This work presents a multiscale modeling framework for predictive simulations of shock-to-detonation transition (SDT) in pressed energetic (HMX) materials. The macro-scale computations of SDT are performed using an ignition and growth (IG) model. However, unlike in the traditional semi-empirical ignition-and-growth model, which relies on empirical fits, in this work meso-scale void collapse simulations are used to supply the ignition and growth rates. This results in a macro-scale model which is sensitive to the meso-structure of the energetic material. Energy localization at the meso-scale due to hotspot ignition and growth is reflected in the shock response of the energetic material via surrogate models for ignition and growth rates. Ensembles of meso-scale reactive void collapse simulations are used to train the surrogate model using a Bayesian Kriging approach. This meso-informed Ignition and Growth (MES-IG) model is applied to perform SDT simulations of pressed HMXs with different porosity and void diameters. The computations are successfully validated against experimental pop-plots. Additionally, the critical energy for SDT is computed and the experimentally observed Ps2τs=constant relations are recovered using the MES-IG model. While the multiscale framework in this paper is applied in the context of an ignition-and-growth model, the overall surrogate model-based multiscale approach can be adapted to any macro-scale model for predicting SDT in heterogeneous energetic materials.

Microstructures and Reaction Properties of Ti/Ni, Ti/Al and Ni/Al Multilayer Films

Reactive multilayer thin films are well-defined heterogeneous nanostructured energetic materials which can release chemical energy through a self-sustainable reaction. They have attracted intense interests due to potential applications in diverse fields such as joining, igniters, and high energy density power sources. In this paper, Ti/Ni, Ti/Al and Ni/Al multilayer films were prepared by magnetron sputtering. The reaction kinetics, microstructure and phase variation of these free-standing films are comparatively investigated. During slow heat reaction, the reaction products of reactive multilayer Ti/Ni nanofoils change from B2-TiNi austenite phase into TiNi3, illustrating an evolution of the phase transformation during reaction. These intermediate phases are also identified by slow heating and quenching. The fast speed imaging exhibits that the front speed is 0.47m/s, 0.8m/s and 3m/s respectively for as-deposited Ti/Ni, Ti/Al, and Ni/Al films. Differential thermal analysis yields that the corresponding releasing heat is 551.44 J/g, 434.18 J/g, and 562.5 J/g for these three composites. The theoretical minimum multilayer thickness for melting a tin solder layer has been calculated on the base of these characterizations, which proved the application potential of joining using the as-deposited film.

Shock interactions with heterogeneous energetic materials

The complex physical phenomenon of shock wave interaction with material heterogeneities has significant importance and nevertheless remains little understood. In many materials, the observed macroscale response to shock loading is governed by characteristics of the microstructure. Yet, the majority of computational studies aimed at predicting phenomena affected by these processes, such as the initiation and propagation of detonation waves in explosives or shock propagation in geological materials, employ continuum material and reactive burn model treatment. In an effort to highlight the grain-scale processes that underlie the observable effects in an energetic system, a grain-scale model for hexanitrostilbene (HNS) has been developed. The measured microstructures were used to produce synthetic computational representations of the pore structure, and a density functional theory molecular dynamics derived equation of state (EOS) was used for the fully dense HNS matrix. The explicit inclusion of the microstructure along with a fully dense EOS resulted in close agreement with historical shock compression experiments. More recent experiments on the dynamic reaction threshold were also reproduced by inclusion of a global kinetics model. The complete model was shown to reproduce accurately the expected response of this heterogeneous material to shock loading. Mesoscale simulations were shown to provide a clear insight into the nature of threshold behavior and are a way to understand complex physical phenomena.