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At least 73 records · Page 4

Fourier-like Thermal Relaxation of Nanoscale Explosive Hot Spots

Hot spots are local regions of high temperature that are widely considered to govern explosive initiation. Hot spot dynamics rests on a delicate balance between heat generation due to chemical reactions and heat loss through thermal conduction, making accurate determinations of the conductivity under extreme conditions a key component of predictive explosive models. We develop here an approach to directly determine the thermal transport properties of explosive hot spots with realistic initial structures through a combination of molecular dynamics (MD) and diffusive heat equation (HEq) modeling. Effective thermal conductivity values are determined by fitting HEq models to MD predictions of long timescale hot spot relaxation. The approach is applied to model hot spots in the molecular crystalline explosive 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) for a range of shock strengths and two limiting cases for impact orientation. Isotropic and anisotropic HEq models yield similar results, despite TATB exhibiting some of the largest and most anisotropic thermal conductivity values for explosive near normal conditions. The conductivity is found to be a strong function of density, which parametrically captures dependence on temperature, pressure, and material state. The associated root-mean-square errors of the fitted HEq models are approximately 5% of MD predicted final equilibrium temperatures. Here, the conductivity values determined here for TATB hot spots are considerably larger than those used in a prior hot spot criticality study, which may significantly impact predictions for critical hot spot sizes. The approach provides a convenient foundation for determining the effective thermal conductivity for hot spot problems in other explosives and directly yields information on reasonable approximations that might be taken in higher-level models for those materials.

36 MATERIALS SCIENCE↗

Demonstrating resonant ultrasound spectroscopy as a viable technique to characterize thermally conditioned high explosive materials

We present results of resonant ultrasound spectroscopy (RUS) measurements applied to granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. The material chosen in this study is a ubiquitously used explosive material known as pentaerythritol tetranitrate (PETN), which is used commercially in civil and defense applications both as a binderized plastic bonded explosive material and an unbinderized neat material. However, changes in granular PETN bulk elastic properties due to thermal conditioning, which could have implications for better understanding environmental aging-related effects, have not been well studied even though it is believed that elasticity may play an important role in explosive material initiation mechanisms. Furthermore, monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing non-destructive characterization tool that requires only dry point contact with the explosive material. To this end, we report the first study using RUS to quantify the elastic properties of binderized and neat PETN pressings as well as to quantify changes in elastic properties as a function of both thermal conditioning and bulk pressing density. Elastic stiffness coefficients, sometimes more commonly referred to as elastic constants, calculated from the RUS measurements on the different PETN-based materials show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings, different thermal exposure conditions, and even different neat PETN pressings of differing average crystal sizes and/or specific surface areas.

36 MATERIALS SCIENCE↗

Post-explosion Evolution of Core-collapse Supernovae

Here we investigate the post-explosion phase in core-collapse supernovae with 2D hydrodynamical simulations and a simple neutrino treatment. The latter allows us to perform 46 simulations and follow the evolution of the 32 explosion models during several seconds. We present a broad study based on three progenitors (11.2, 15, and 27 M ⊙ ), different neutrino heating efficiencies, and various rotation rates. We show that the first seconds after shock revival determine the final explosion energy, remnant mass, and properties of ejected matter. Our results suggest that a continued mass accretion increases the explosion energy even at late times. We link the late-time mass accretion to initial conditions such as rotation strength and shock deformation at explosion time. Only some of our simulations develop a neutrino-driven wind (NDW) that survives for several seconds. This indicates that NDWs are not a standard feature expected after every successful explosion. Even if our neutrino treatment is simple, we estimate the nucleosynthesis of the exploding models for the 15 M ⊙ progenitor after correcting the neutrino energies and luminosities to get a more realistic electron fraction.

79 ASTRONOMY AND ASTROPHYSICS↗

Joint Bayesian Inference for Near-Surface Explosion Yield and Height-of-Burst

Forensic capabilities to understand chemical and nuclear explosions are greatly aided by an accurate estimate of explosive yield with uncertainty. The relationship between explosive size and geophysical observations of seismic, acoustic, and optical waves can be exploited to provide an estimate of yield. Any near-surface yield estimate is complicated by the surface interaction, so an estimate for the explosion height-of-burst is necessarily included in the relationship. Additionally, the relationship dictates a trade-off between estimates of yield and height-of-burst. Fortunately, the surface interaction for each type of observation is different, which breaks the trade-off, and the inclusion of height-of-burst with multiple data types improves yield estimation. We define simple parametric forward models to relate seismoäcoustoöptic observations from a data set of known explosive yields and height-of-bursts. The parameters of the models and a prediction for the yield and height-of-burst of a new event can then be estimated given new observations via Bayesian inference. We report posterior distribution estimates of the parametric models using a Markov chain Monte Carlo sampling technique. These models are then used to predict the yield and height-of-burst of SUGAR, a historical near-surface nuclear explosion, using its reported historical observations. The reported yield of 1.2 ktonne Trinitrotoluene (TNT)-equivalent (Department of Energy, 2015) is within the estimated posterior. Yield uncertainty can be estimated from the spread of the posterior, which is between 0.9 and 2.1 ktonne TNT-equivalent. The posterior for height-of-burst has a wider range between 10 m below and 8 m above ground that includes the true height-of-burst of 1 m.

58 GEOSCIENCES↗

Halogenated PETN derivatives: interplay between physical and chemical factors in explosive sensitivity

Determining the factors that influence and can help predict energetic material sensitivity has long been a challenge in the explosives community. Decades of literature reports identify a multitude of factors both chemical and physical that influence explosive sensitivity; however no unifying theory has been observed. Recent work by our team has demonstrated that the kinetics of “trigger linkages” (i.e., the weakest bonds in the energetic material) showed strong correlations with experimental drop hammer impact sensitivity. These correlations suggest that the simple kinetics of the first bonds to break are good indicators for the reactivity observed in simple handling sensitivity tests. Herein we report the synthesis of derivatives of the explosive pentaerythritol tetranitrate (PETN) in which one, two or three of the nitrate ester functional groups are substituted with an inert group. Experimental and computational studies show that explosive sensitivity correlates well with Q (heat of explosion), due to the change in the number of trigger linkages removed from the starting material. In addition, this correlation appears more significant than other observed chemical or physical effects imparted on the material by different inert functional groups, such as heat of formation, heat of explosion, heat capacity, oxygen balance, and the crystal structure of the material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and modeling for a small-scale, rapidly heated high explosives initiation time (HEIT) experiment

Most small-scale assessments of explosive sensitivity, including the popular drop-weight impact test, convolute thermal and mechanical phenomena to the extent that it has been extremely challenging to decipher how an explosive ignites and propagates reactions. For instance, an impact generates heat through a range of dissipation mechanisms, which can in turn, depending on the reaction rates of the explosive, lead to chemical decomposition. To deconvolute the various contributions to the sub-shock initiation and propagation of explosive reactions, we describe the development and modeling of the High Explosives Initiation Time (HEIT) test - a new, small-scale, high-throughput experiment designed to rapidly heat milligram quantities of energetic materials confined within small diameter steel needles. Specifically, we have modeled and designed a 250 joule pulsed power system capable of rapidly delivering electrical current to the needles, resulting in rapid heat delivery to the sample. In conclusion, the energy deposition rate into the sample is controlled by different transmission line topologies. Modeling in COMSOL is performed to understand the energy required to heat up the explosive sample.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

All-Atom Simulation of 3D Hot Spot Formation in Shocked TATB Explosive

TATB is an insensitive high explosive (IHE) critical to the stockpile that is challenging to model at the continuum scale. Advanced detonation models in the Cheetah high explosive chemistry code require validation though subscale simulations. High explosive initiation is determined by micron-scale physics of hot spots formed a shock-collapsed pores. Pore sizes between 100 nm and 1 μm are believed to be the most important for determining the shock sensitivity of TATB. This range of pore sizes is difficult to access at the atomic scale through allatom molecular dynamics (MD) simulations, even with Sierra-class computers. Quasi-2D simulations are widely used and allow much larger pore sizes (up to 400 nm) to be studied, but the applicability of 2D simulations to the actual 3D pore response is not understood. Resolving these uncertainties through “full physics” MD modeling is key for generalizing, parameterizing, and validating the kinds of continuum models used to inform design, safety, and performance. This work was a continuation of FY20 efforts pushing simulations to full 3D with the largest-ever all-atom simulations of an explosive. These were the first all-atom full-3D simulations of large hot spots thought to govern explosive detonation and required over a billion atoms. Simulations were performed using LAMMPS, an open SNL science code. MD explosive models present unique challenges, even for established codes such as LAMMPS. Their model forms are more complex than typical models for metals, while simulating high temperature-pressure conditions is demanding and increases computational cost. Scaling problems in GPU-enabled MD algorithms initially limited simulations to <100 million atoms but were resolved through collaboration with SNL. An overall 24x speedup was obtained relative to CPU machines. Specialized analysis of these simulations required a bottom-up refactoring and algorithm parallelization of in-house codes and application of computer vision algorithms to extract meaningful information.

36 MATERIALS SCIENCE↗

LLNL Macroscopic Anisotropic Explosives Research At INL National Security Test Range: Shot Narrative

This series of experiments is exploring new frontiers in explosives science, technology, and engineering. The extensive list of experiment shots is necessary to sort out what works and what does not work in searching for an environment that supports anisotropic detonation properties in explosives. These experiments have been designed to serve as an economical and efficient first-cut determination as to whether there is any validity to an explosive analog to a series circuit of electrical diodes. That is, the detonation moves more easily in the “forward” direction than the “backward” direction. The basic data gleaned from these experiments will be used to design experiments that will be shot in the 10 kg tank at the High Explosives Application Facility (HEAF) at the Lawrence Livermore National Laboratory. In turn, those shots that will be heavy in diagostics and instrumentation, providing basic data that will be used by simulation code developers in creating high explosive models that account for air gap and oblique explosive surfaces undergoing sympathetic detonation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Low Temperature Time-to-Explosion Experiments on HMX in the LLNL's ODTX/P-ODTX System (FY 2020 Annual Report)

Over the last few decades, there has been a considerable research effort on the thermal decomposition and thermal explosion violence of energetic materials at elevated temperatures in different sample geometries and confinements. Thermal explosion studies on various energetic materials in two-dimensional geometry such as the Scaled-Thermal-Explosion-Experiment (STEX) system and the Sandia-Instrumented-Thermal-Ignition (SITI) system have been reported. The One-Dimensional Time to Explosion (ODTX) system, designed and built by LLNL, has been used since 1970s for thermal explosion studies. The system is attractive because of the one-dimensional geometry and minimal sample requirement. With the recent integration of a pressure monitoring element, the system can study pressure behavior of materials subjected to and during thermal exposure. Rapid pressure monitoring in µsec intervals allow for enhanced pressure determination in the time right before thermal explosion. The test data can be used for the validation of existing thermal models, particularly for introducing pressure terms. This report summarizes the efforts in performing small-scale safety tests, particle size measurements and conducting 7 ODTX/P-ODTX experiments on the Cl5 HMX material that Hunting uses for oil field applications.

36 MATERIALS SCIENCE↗

Sensitivity Effects of Hollow Glass Micro-Balloon Doping on RDX-Based Explosives

Sensitivity to initiation is an important characteristic of high explosives. Many chemical and physical properties are fine-tuned to deliver an energetic material that behaves according to the user’s specifications exactly. In some cases, it is advantageous to study the effects that non energetic additives have on the performance of an explosive material. Following on the promising results obtained in other experiments, a study is conducted on the effects of hollow glass micro-balloons (bubbles, spheres), or HGMB, on a material’s sensitivity. Threshold test data is compared between several formulations of explosives. The control formulation is an RDX-based explosive with a non-energetic binder, and the test formulations are identical in composition, but with the addition of HGMB, up to 6% by volume. Safety testing of the new HGMB-doped explosive formulations is conducted to ensure they can be produced and handled safely prior to intentional detonation. This experiment utilizes an attenuation card of varying thicknesses between the initiator and the test article to attenuate the shock imparted, and a witness plate is analyzed for each test article to determine a GO or NO GO result. The data collected and the conclusions of this study affect how additives like HGMB are utilized in future explosive sensitivity threshold experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid Analyses of Sparse Seismoacoustic Data Reveals the Timing and Size of the Accurate Energetic Systems Explosion

On 10 October 2025 an explosion occurred at a facility operated by Accurate Energetic Systems in Humphreys County, Tennessee. The incident resulted in 16 fatalities and created a debris field over several square kilometers. To address remaining questions about explosion timing and size, we collected about 20 seismic and 19 acoustic records of the blast from sensors up to hundreds of kilometers away. We then deployed 10 distinct physics-based, reduced order models (ROMs) that used validated geological structure and atmospheric conditions from the time of the event, along with observations of body- and surface-wave energy, as well as acoustic overpressure and phase duration. Each ROM predicted either timing, yield estimates, or both. We binned these estimates and their uncertainties according to each ROMs’ assumptions about confinement (aboveground, buried fully coupled, and buried partially coupled) and combined these estimates with other forensic data to conclude that the event occurred as a single, aboveground explosion on 10 December 2025 12:47:50.8 ±0.1 s with a yield equivalent to 11.8 [2.3,16.5] tons of Trinitrotoluene. Our estimates align with the Bureau of Alcohol, Tobacco, Firearms and Explosives inventory reports of 11–13 tons. This multimethod approach demonstrates the use of remotely observed geophysical data to rapidly aid conventional forensic investigations of accidental explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Quantifying the Potential of Argon Detection Capabilities for Nuclear Explosion Monitoring

Abstract Current noble gas detection systems for nuclear explosion monitoring are based on the detection of four radioxenon isotopes—Xe-131m, -133, -133m and -135. The data provided by radioxenon detection could be enhanced by other radionuclide signatures such as Ar-37. Activation of Ca-40 in rock by neutrons produces Ar-37, and monitoring for this additional nuclide could help distinguish detections of nuclear explosions from background sources, such as medical isotope production. This work studies the capabilities of a hypothetical argon detection network. A 10 kt explosion was modeled using MCNP and SCALE to determine the inventory of Ar-37 created in a representative granite rock layer, assuming either 0.1, 1 or 10% of the total inventory was released. The Ar-37 inventory was combined with atmospheric transport data from HYSPLIT compiled in a previous study, along with the detection limits of standard Ar-37 detection systems, to determine how many hypothetical monitoring stations would detect Ar-37 from an explosion. This method was repeated for 365 HYSPLIT data sets to create a year’s worth of hypothetical explosions, releases, and detections. The study quantified the average number of detections per release, the number of stations detecting Ar-37, and the possibility of detecting Ar-37 in coincidence with xenon.

37Ar↗

A comparison of explosively driven shock wave radius versus time scaling approaches

Abstract Explosively driven shock wave radius versus time profiles are frequently used to document energy release and relative explosive performance. Recently, two universal shock wave radius versus time profiles have been presented in the literature, which demonstrate the ability to represent explosively driven shock wave profiles for all explosive sources in any fluid environment. These two universal shock wave profiles are examined here relative to each other and relative to a commonly used nonlinear shock wave profile, which is fit to experimental data for individual explosive materials. The nonlinear profile, originally developed by Dewey, is examined here, and a universal non-dimensional form of the equation is proposed. The universal shock wave profiles are all found to be relatively similar, but with slight variations in a transition region of non-dimensional radii $$0.15\lesssim R^*\lesssim 2$$ 0.15 ≲ R ∗ ≲ 2 . The variations in this region result in different estimations of energy release or blast strength between the curve fits.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Explosive Byproduct Gas Transport Through Sorptive Geomedia

Current underground nuclear explosion (UNE) detection strategies rely heavily on atmospheric noble gas sampling of radioxenon. However, discriminating nuclear weapons testing programs from civilian sources is difficult due to highly variable atmospheric radioxenon backgrounds and processes affecting subsurface transport of parent radionuclides. Here, we aim to study the transport of gases produced by subsurface explosions as novel stable signatures for underground nuclear explosion (UNE) monitoring. These gases may be produced in large quantities with distinct molecular ratios, which will be impacted by subsurface transport processes. To demonstrate how ratios of gases produced by explosions can change during transport in geomaterials, we conducted laboratory benchtop experiments on the transport of carbon dioxide (CO 2 ) and hydrogen (H 2 ) gases through variably saturated zeolitic tuff, which is abundant at the historic US testing site. We observed that zeolitic tuff sorbs substantial quantities of CO 2 while allowing H 2 to transport more freely, leading to changes in the molecular ratios of the two gases along the transport pathway. Gas uptake in the dry zeolitic tuff core was 72.3% for CO 2 , compared with 53.4% for xenon and 7.6% for H 2 . The presence of 20% water saturation disrupted the CO 2 sorption process, though to a lesser extent than observed for noble gases, with a 36.7% drop in xenon sorption compared with a 21.9% drop for CO 2 . These results represent the first observations of zeolite sorption altering explosive gas ratios during transport through geomedia relevant to nuclear proliferation monitoring.

54 ENVIRONMENTAL SCIENCES↗

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is 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. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗

Prediction of impact sensitivity, heat of formation and heat of explosion using atomic connectivity

In these proceedings we revisit a large collection of explosives and explosive descriptors with the goal of predicting impact sensitivity using only local atomic environments that can be deciphered from molecular SMILES strings as descriptors without utilizing empirically measured values or computationally expensive electronic structure calculations. From the original database of nearly 500 descriptors, removing empirically measured and electronic structure values decreased the number of descriptors to 135, which we reduced to 18 the most important descriptors using Random Forests. The condensed model predicted impact sensitivity with essentially the same accuracy as the existing, more complex model (R 2 = 0.788 and RSME = 0.312), while remaining applicable to all types of explosives (Peroxides, azides, C-Nitros, Nitroamines, Nitrate Esters, etc.). In addition to impact sensitivity, we proposed similar models to accurately predict values heat of formation (ΔH f ) and heat of explosion (Q), with R 2 = 0.966 and 0.916, respectively. In conclusion, the work in these proceedings allows for prediction of explosive performance and sensitivity with only chemical structure information and an estimate of density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The effect of hardness on polymer-bonded pentaerythritol tetranitrate (PETN) explosive impact sensitivity

Handling sensitivity is an important property to assess when working with explosive samples and can be measured using a variety of tests, including drop-weight impact sensitivity. There exists a longstanding interest in the explosives community on the importance of measurable chemical, physical, and mechanical properties of explosives in impact sensitivity. However, most recent work in this area has explored chemical attributes rather than physical and mechanical properties of explosives. In this study, we measure hardness of explosive samples of pentaerythritol tetranitrate and Sylgard binder (XTX) during the curing process. The samples have been characterized for particle morphology through scanning electron microscopy and handling sensitivity through drop-weight impact testing. The relative importance of states of cure, methods of curing, morphology, and age of material are discussed. The data indicate that although there is a notable difference in morphology and mechanical properties for the samples as the polymer-bonded mixtures cure, the resulting changes to mechanical properties have a minimal effect on the sensitivity of the XTX.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fracture Network Influence on Rock Damage and Gas Transport following an Underground Explosion

Simulations of rock damage and gas transport following underground explosions that omit preexisting fracture networks in the subsurface cannot fully characterize the influence of geo-structural variability on gas transport. Previous studies do not consider the impact that fracture network structure and variability have on gas seepage. In this study, we develop a sequentially coupled, axi-symmetric model to look at the damage pattern and resulting gas breakthrough curves following an underground explosion given different fracture network realizations. We simulate 0.327 and 0.164 kT chemical explosives with burial depths of 100 m for 90 stochastically generated fracture networks. Gases quickly reach the surface in 30% of the higher yield simulations and 5% of the lower yield simulations. The fast breakthrough can be attributed to the formation of connected pathways between fractures to the surface. The formation of a connected damage pathway to the surface is not clearly correlated with the fracture intensity (P32) in our simulations. Breakthrough curves with slower transport are highly variable depending on the fracture network sample. The variability in the breakthrough behavior indicates that ignoring the influence of fracture networks on rock damage, which strongly influences the hydraulic properties following an underground explosion, will likely lead to a large underestimation of the uncertainty in the gas transport to the surface. This work highlights the need for incorporation of fracture networks into models for accurately predicting gas seepage following underground explosions.

58 GEOSCIENCES↗