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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reaction Evolution Flow Chart - The Critical Path to DDT [Slides]

Purpose (and limitations): The following flow-chart identifies and organizes a generalized, and simplified, sequence of necessary conditions for accidental ignition and reaction growth in a consolidated, polymer-bonded explosive (PBX) charge that has been insulted. A ‘yes’ answer to each question will lead down the critical path and produce violent, explosive reactions, up to and possibly including transition to detonation. Alternatively, any ‘no’ answer will serve as an off-ramp from the path resulting in less violent responses. It is important to note that this flow-chart is a high-level tool to flag potential operational vulnerabilities, but lacks the details needed to stand alone as a sole-source for risk determination. Each question represents a significant area of study and, therefore, the flow chart is intended to be supplemented by subject matter expert elicitations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

The antesonic condition for the explosion of core-collapse supernovae – II. Rotation and turbulence

In the problem of steady free fall on to a standing shockwave around a central mass, the ‘antesonic’ condition limits the regime of stable accretion to $c_T^2/v_\mathrm{esc}^2\le 3/16$, where cT is the isothermal sound speed in the subsonic post-shock flow, and vesc is the escape velocity at the shock radius. Above this limit, it is impossible to satisfy both the Euler equation and the shock jump conditions, and the system transitions to a wind. This physics explains the existence of a critical neutrino luminosity in steady-state models of accretion in the context of core-collapse supernovae. Here, we extend the antesonic condition to flows with rotation and turbulence using a simple one-dimensional formalism. Both effects decrease the critical post-shock sound speed required for explosion. While quite rapid rotation is required for a significant change to the critical condition, we show that the level of turbulence typically achieved in supernova simulations can greatly impact the critical value of $c_T^2/v_\mathrm{esc}^2$. A core angular velocity corresponding to a millisecond rotation period after contraction of the proto-neutron star results in only a ~5 percent reduction of the critical curve. In contrast, near-sonic turbulence with specific turbulent kinetic energy $K/c_T^2=0.5-1$, leads to a decrease in the critical value of $c_T^2/v_{\rm esc}^2$ by ~20 to 40 percent. This analysis provides a framework for understanding the role of post-shock turbulence in instigating explosions in models that would otherwise fail and helps explain why multidimensional simulations explode more easily than their one-dimensional counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Infrasonic directivity of monopole, dipole and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local (⁠<5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source (⁠<5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Infrasound↗
DOE OSTI2025

Analysis of Liquids Using the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER)

We developed a sensor called the Submerged Plasma for Isotopic Detection and Elemental Resolution (SPIDER) probe, which uses an atmospheric pressure glow discharge below the surface of liquids to excite species in the liquid. Through emission spectroscopy of molten salts, liquid metals, and heavy water, we demonstrated the SPIDER probe’s high resolution, accuracy, and versatility. We successfully identified trace concentrations of transition and rare-earth metals in molten salts and detected the isotopic shift of the H β → D β emission line. Our analysis revealed unconventional spectral alkali line shapes, indicating two competing excitation modes: film explosion and droplet vaporization. The film explosion mode, characterized by dense plasma, exhibited self-reversal and broadband continuum emission, while the droplet vaporization mode, associated with diffusive plasma, produced narrow-line emissions. Furthermore, by analyzing circuit transients alongside individual plasma events, we observed that film explosions generate higher currents, likely due to a shorter plasma length as the current preferentially flows through the thin liquid layer. Altogether, our results highlight the SPIDER probe’s efficacy and flexibility, making it well-suited for online material quantification of liquids in extreme environments.

AES↗
DOE OSTI2023

Improving manganin gauge measurements near radiographic fiducials

In dynamic experiments diagnosed with radiography and stress gauges, the gauges are often placed adjacent to radio-graphic fiducials, such as Ta foil, which perturbs the stress measurement. We conducted experiments to test the performance of different arrangements of manganin stress gauges and Ta foils. Three different gauge/foil configurations were tested, as well as a solitary gauge as control. Gauge/foil layers were placed between high-density polyethylene (HDPE) discs and impacted by a projectile in a gas gun, a simplification of a dynamic, high explosive experiment configuration. The stress measurements were minimally perturbed when a section of foil was removed near the active element of the gauge, as expected. In conclusion, a follow-up experiment showed that the modification to the foil has minimal impact on the radiographic measurement of the dynamic flow.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Semi-implicit method to solve compressible multiphase fluid flows without acoustic time step restrictions

A new 3D multiphase numerical capability is presented here for simulating multiphase flow regimes at all Mach numbers (M). The new method is a semi-implicit extension of the finite volume discrete equation method (DEM) of Chinnaya et al. (2004), which originally used explicit time-stepping. The capability is also developed to work with another extension of the DEM to moving grids for arbitrary Lagrangian-Eularian (ALE) methods detailed in Dunn (2011). Rather than solving all phase equations simultaneously, the DEM reduces the equations to a system of single-phase Riemann solves, where each phase has its own velocity and thermodynamic state. Exchanges between the phases are modeled through source terms accounting for the phase interactions. Furthermore, since the original multiphase scheme uses an explicit time-advancement scheme, it has time step restrictions dictated by the speed of sound, which limits the model's ability to simulate weakly compressible flows which typically need to be integrated for longer time periods. Here, we extend the current multiphase formulation by implementing a pressure-correcting step to enable implicit calculations and remove acoustic time step limitations. The new semi-implicit algorithm allows use of relatively large time steps compared to an explicit method. Validation and benefits of the new implicit time-step method are illustrated using several examples including weakly compressible flows and strong shock waves. The scheme presented here is general and may be used for a variety of applications which require capabilities for handling multiphase flow at a wide range of Mach numbers. However, the goal of this research is to simulate all stages of high energy explosions, including the shock formation (high Mach numbers) and evolution of the buoyant cloud (low Mach numbers).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Gas Transport in the Insensitive High Explosive PBX 9502

Small-scale laboratory experiments were performed to analyze gas transport mechanics in PBX 9502, an insensitive high explosive (IHE) composition. Two independent investigations are reported here. First, gas permeametry and dynamic pycnometry techniques were used to measure the molecular flow (Knudsen) coefficient and the internally interconnected void fraction of pristine and thermally damaged samples in two uniaxial pressing orientations. The permeability of PBX 9502 was found to be unmeasurably low (of the same order of magnitude as PTFE) with gas transport being diffusion-dominated. Secondly, a pressure vessel experiment was developed to measure quasi-static and dynamic gas generation as the explosive was heated to self-ignition (cookoff). The gas generation results and the permeability/diffusivity findings provide evidence that PBX 9502 remains impermeable until seconds prior to self-ignition. At ignition, internal void-pressure drives macro-scale cracking and the sample becomes uniformly incorporated in the following deconsolidating deflagration. These results are discussed within the context of previous observations of pressure-dependent cookoff behavior of PBX 9502 and provide a more complete description of thermal damage evolution in this explosive composition.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Material Model Parameters Optimization in Liquid Mercury Target Dynamics Simulation With Machine Learning Surrogates

A pulsed spallation target is subjected to very short (∼0.7μs) but intense loads (23.3 kJ) from repeated proton pulses, which knock away neutrons from the mercury atoms’ nuclei for a wide range application in physics, engineering, medicine, petroleum exploration, biology, chemistry, etc. The effect of this pulsed loading on the stainless-steel target module which contains the flowing mercury target material is difficult to predict not only due to its short but intense explosive-like physical reaction, but also the nonlinear material behavior of the liquid mercury in the structure. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at high power level stage. However, prediction of the resultant loading on the target is more difficult when helium gas is intentionally injected into the mercury. A 2-phase material model that incorporates the Rayleigh-Plesset (R-P) model is expected to address this complex multi-physics dynamics problem by including the bubble dynamics in the liquid mercury. A parameter sensitivity study was firstly employed to understand their impact on the simulation strains. The investigated parameters included E, μ, γ, σ, n, VFgas, and gas cumulative volume curve control parameters a and b. Verification and validation results from sparse polynomial expansions (SPE) method and directional Gaussian smoothing (DGS) optimization show that the surrogate model had training error of ∼7% and validation error of ∼15%, indicating that machine learning methods and surrogate models can help optimize the uncertain parameters in the complex 2-phase material model. This approach is expected to fill the knowledge gap between unknown liquid-gas mixture material model and measured vessel strain responses.

Lin, Lianshan↗
DOE OSTI2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

Classical problems in computational physics such as data-driven forecasting and signal reconstruction from sparse sensors have recently seen an explosion in deep neural network (DNN) based algorithmic approaches. However, most DNN models do not provide uncertainty estimates, which are crucial for establishing the trustworthiness of these techniques in downstream decision making tasks and scenarios. In recent years, ensemble-based methods have achieved significant success for the uncertainty quantification in DNNs on a number of benchmark problems. However, their performance on real-world applications remains under-explored. In this work, we present an automated approach to DNN discovery and demonstrate how this may also be utilized for ensemble-based uncertainty quantification. Specifically, we propose the use of a scalable neural and hyperparameter architecture search for discovering an ensemble of DNN models for complex dynamical systems. We highlight how the proposed method not only discovers high-performing neural network ensembles for our tasks, but also quantifies uncertainty seamlessly. This is achieved by using genetic algorithms and Bayesian optimization for sampling the search space of neural network architectures and hyperparameters. Subsequently, a model selection approach is used to identify candidate models for an ensemble set construction. Afterwards, a variance decomposition approach is used to estimate the uncertainty of the predictions from the ensemble. We demonstrate the feasibility of this framework for two tasks — forecasting from historical data and flow reconstruction from sparse sensors for the sea-surface temperature. In conclusion, we demonstrate superior performance from the ensemble in contrast with individual high-performing models and other benchmarks.

Deep ensembles↗
DOE OSTI2023

VIPIR: A High-Throughput Drop-Weight Impact Instrument for Imaging the Initiation and Propagation of Reactions in Energetic Materials

Characterizing the handling safety and sensitivity of explosives has been a challenging area of study for over 60 years. Historically one of the most accessible and widely utilized experiments has been the drop-weight impact test, which involves dropping a weight on a small sample sandwiched between two anvils. Because this experiment generally only utilizes sound thresholds to determine whether or not a sample reacted, the physical and chemical properties governing sensitivity remain convolved. Better understanding of chemical and material characteristics is needed to give the chemistry and engineering communities a predictive tool to determine the handling sensitivity of explosives prior to pursuing expensive and potentially hazardous synthesis and formulation operations. Here, we are developing a high throughput drop tower instrument capable of imaging the deformation and flow of energetic materials during impact and the resulting thermal ignition and propagation events. This instrument is based on previous designs but has been modified for higher throughput and tailorable modifications in the future. Herein, we present key design features that enable high-speed visible and thermal imaging of explosive initiation by sub-shock impacts, as well as preliminary results in which ignition sites were observed in an erythritol tetranitrate sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Non-Contact Vapor Detection of Illicit Drugs via Atmospheric Flow Tube-Mass Spectrometry

Real-time, non-contact detection of illicit drugs is a desirable goal for the interdiction of these controlled substances, but the relatively low vapor pressures of such species present a challenge for trace vapor detection technologies. The introduction of atmospheric flow tube-mass spectrometry (AFT-MS), which has previously been demonstrated to detect gas-phase analytes at low parts-per-quadrillion levels for explosives and organophosphorus compounds, also enables the potential for non-contact drug detection. With AFT-MS, direct vapor detection of cocaine and methamphetamine from ~5 µg residues at room temperature is demonstrated herein. Furthermore, thermal desorption of low- to sub-picogram levels of cocaine, methamphetamine, fentanyl, and heroin is observed via AFT-MS using a carrier flow rate of several L/min of air. These low levels can permit non-contact sampling through collection of vapor, effectively preconcentrating the analyte before desorption and analysis. Quantitative evaluation of the thermal desorption approach has yielded limits of detection (LODs) on order of 10 fg for cocaine and fentanyl, 100 fg for methamphetamine, and 1.6 pg for heroin. The LOD for heroin was lowered to 200 fg by using tributyl phosphate as a dopant to form a proton-bound heterodimer with heroin. When used with AFT-MS, the intentional formation of specific drug-dopant adducts has the potential to enhance detection limits and selectivity of additional drug species. Species that are prone to form adducts present a challenge to analysis, but that difficulty can be overcome by the intentional addition of a dopant. Molecules unlikely to form adducts will remain essentially unimpacted, but the adduct-forming species will interact with the dopant to compress the analyte signal into a single peak. This approach would be valuable in the application of non-contact screening for illicit substances via vapor collection followed by thermal desorption for analysis.

methamphetamine, cocaine, heroin, fentanyl, atmosp↗
DOE OSTI2022

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power flow equations can be successfully modeled using neural networks. These neural networks can be exactly transformed into mixed integer linear programs and embedded inside challenging optimization problems, thus replacing nonlinearities that are intractable for many applications with tractable piecewise linear approximations. Such approaches, though, suffer from an explosion of the number of binary variables needed to represent the neural network. Accordingly, this paper develops a technique for training an "optimally compact'' neural network, i.e., one that can represent the power flow equations with a sufficiently high degree of accuracy while still maintaining a tractable number of binary variables. We demonstrate the use of this neural network as an approximator of the nonlinear power flow equations by embedding it in the AC unit commitment problem, transforming the problem from a mixed integer nonlinear program into a more manageable mixed integer linear program. We use the 14-, 57-, and 89-bus networks as test cases and compare the AC-feasibility of commitment decisions resulting from the neural network, DC, and linearized power flow approximations. Our results show that the neural network model outperforms both the DC and linearized power flow approximations when embedded in the unit commitment problem. The neural network formulation most often selects a feasible unit commitment schedule, and furthermore, it only s

AC power flow↗
DOE OSTI2022

Effects of Model Uncertainties in Underground Chemical Explosions on Far-field Results

We used the CTH shock physics code to simulate the explosion of an 18-t chemical explosive at a depth of 250 m. We used the CTH in the two-dimensional axisymmetric (cylindrical) geometry (2DC) and most simulations included fully tamped explosions in wet tuff. Our study focused on parametric studies of three of the traditional strength models available in CTH, namely, geologic-yield, elastic perfectly-plastic von Mises, and Johnson-Cook strength (flow stress) models. We processed CTH results through a code that generates Reduced Displacement Potential (RDP) histories for each simulation. Since RDP is the solution of the linear wave equation in spherical coordinates, it is mainly valid at far-enough distance from the explosion the elastic radius. Among various parameters examined, we found the yield strength to have the greatest effect on the resulting RDP, where the peak RDP reduces almost linearly in log-log space as the yield strength increases. Moreover, an underground chemical explosion results in a cavity whose final diameter is inversely proportional to the material yield strength, i.e., as the material's yield strength increases the resulting final cavity radius decreases. Additionally, we found the choice of explosive material (COMP-C4 versus COMP-B) has minor effects on the peak RDP, where denser COMP-C4 shows higher peak RDP than the less dense COMP-B by a factor of ~1.1. In addition to wet tuff, we studied explosions in dry tuff, salt, and basalt, for a single strength model and yield strength value. We found wet tuff has the highest peak RDP value, followed by dry tuff, salt, and basalt. 2DC simulations of explosions in 11 m radius spherical, hemispherical, and cylindrical cavities showed the RDP signals have much lower magnitude than tamped explosions, where the cavity explosions mimicked nearly decoupled explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Magnetic reconnection in the era of exascale computing and multiscale experiments

Astrophysical plasmas have the remarkable ability to preserve magnetic topology, which inevitably gives rise to the accumulation of magnetic energy within stressed regions including current sheets. This stored energy is often released explosively through the process of magnetic reconnection, which produces a reconfiguration of the magnetic field, along with high-speed flows, thermal heating and nonthermal particle acceleration. Either collisional or kinetic dissipation mechanisms are required to overcome the topological constraints, both of which have been predicted by theory and validated with in situ spacecraft observations or laboratory experiments. However, major challenges remain in understanding magnetic reconnection in large systems, such as the solar corona, where the collisionality is weak and the kinetic scales are vanishingly small in comparison with macroscopic scales. The plasmoid instability or formation of multiple plasmoids in long, reconnecting current sheets is one possible multiscale solution for bridging this vast range of scales, and new laboratory experiments are poised to study these regimes. In conjunction with these efforts, we anticipate that the coming era of exascale computing, together with the next generation of observational capabilities, will enable new progress on a range of challenging problems, including the energy build-up and onset of reconnection, partially ionized regimes, the influence of magnetic turbulence and particle acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Direct observation of diamond formation in a shock-compressed high explosive

Understanding the formation timescale and structure of carbonaceous reaction products is critical for modeling the high-pressure equation-of-state of organic materials. We use the National Ignition Facility to shock-compress polycrystalline TATB (C 6 H 6 N 6 O 6 ) samples to ~70–130 GPa and ~4000–5500 K, employing in situ nanosecond X-ray diffraction to probe reaction products and velocimetry to measure transmitted compression wave profiles. Our diffraction data is consistent with the formation of diamond over timescales less than ~60 ns. This represents carbon condensation from a molecular explosive on timescales three times faster than previously reported and the earliest observation of diamond produced from reacting TATB. Reactive flow simulations with explicit chemistry reproduce the observed temporal structure within wave profiles to inform the distribution of P-T states. These findings provide direct evidence of ultrafast diamond formation in a reactive system at extreme conditions and provide new constraints for models of shock and detonation chemistry.

Clarke, Samantha M. [Lawrence Livermore National L↗
DOE OSTI2020

Multiphase representation of hotspot formation and growth

Multiphase reacting flow approach has been adopted for modeling of hotspot formation and growth on sub-zonal scale. Mechanical response of the high explosive (HE) is modeled by the Visco-Plastic SCRAM model which includes plastic work, crack growth, and frictional heating along the cracks. In this work a sub-zonal regions with high temperature, hotspots, are modeled as a new phase. Formation and growth of the hotspot phase from the cold phase is modeled as a phase change. Each phase has its own temperature and pressure. Chemical reactions also progress in both phases. The growth of hotspots are determined by the solution of the heat conduction equation with appropriate heat sources due to friction and plastic heating. Sample calculations using the BABBO code show successful detonation calculations with hotspot formation and growth.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks

Reacting astrophysical flows can be challenging to model, because of the difficulty in accurately coupling hydrodynamics and reactions. This can be particularly acute during explosive burning or at high temperatures where nuclear statistical equilibrium is established. We develop a new approach, based on the ideas of spectral deferred corrections (SDC) coupling of explicit hydrodynamics and stiff reaction sources as an alternative to operator splitting, that is simpler than the more comprehensive SDC approach we demonstrated previously. We apply the new method to a double-detonation problem with a moderately sized astrophysical nuclear reaction network and explore the time step size and reaction network tolerances, to show that the simplified-SDC approach provides improved coupling with decreased computational expense compared to traditional Strang operator splitting. This is all done in the framework of the Castro hydrodynamics code, and all algorithm implementations are freely available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Nonlinearities in Magnetic Confinement, Ionospheric Physics, and Population Explosion Leading to Profile Resilience Нелінійності в магнетному утриманні, фізиці іоносфери та процесі демографічного вибуху, які приводять до стійкості профілю

Nonlinearities play an important role in many fields. In the field of thermonuclear fusion, they are involved in questions such as profile resilience and fluid closure. A nonlinear phenomenon common to both fusion and astrophysical planets is the generation of zonal flows. These flows play a significant role in determining the level of turbulence and fluid closure in fusion. The effects of resonance broadening and nonlinearities are investigated, specifically focusing on the case of nonlinear instability that has appeared in drift waves. Similarities and differences between our systems are discussed, with population explosion and the dynamics of nonlinear systems for drift waves by different states in profile resilience described with great precision. The aim of our study is to put our fluid model for drift waves in tokamaks within the wider framework of statistical physics principles. This reinforces our belief in the broad application of our drift wave model, which encompasses current tokamaks, ITER, and the fusion pilot plant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗