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At least 1,189 records · Page 66

Simulation and analysis of the 3D double shock-induced recompression of spall using a hybrid PAGOSA with FLIP+MPM

In this work, an innovative hybrid algorithm PAGOSA with FLIP + MPM is first presented by coupling PAGOSA with the particle FLIP + MPM, and applied to systematically exploring the 3D recompression of spall induced by double-shock waves in ductile materials as the few existing studies are currently limited to the pure longitudinal recompression of spall, and ignore the 3D effects. This algorithm solves the difficulties the grid-based methods encounter when applied to capturing the fracture in material. We first validate the capabilities of PAGOSA with FLIP + MPM to predict different fracture/fragmentation cases by solving two benchmark problems and comparing with the analytical solutions or the experiment results. The convergences and the infinity-norm errors are also investigated. Subsequently, the 3D effects are demonstrated by simulating the spallation in material using PAGOSA with FLIP + MPM and comparing with those in the longitudinal cases. Additionally, some factors that affect the spallation with 3D effects are also discussed. Finally, the recompressions of spall in material with/without 3D effects are systematically simulated and analyzed. The recompression of spall driven by a high explosive is also simulated to show the ability of PAGOSA with FLIP + MPM to handle this kind of problem. The conditions that can lead to a recompression of spall are explored. Also, numerical results show that PAGOSA with FLIP + MPM can accurately predict different fracture cases, that the 3D effects play an important role in fracture/fragmentation, and the recompression of spall is very sensitive to the occurrence conditions, shows great differences when considering 3D effects in real applications. Moreover, the present hybrid method can be easily extended to other grid-based techniques employed for fracture in materials.

3D effects↗

IMS observations of infrasound and acoustic-gravity waves produced by the January 2022 volcanic eruption of Hunga, Tonga: A global analysis

The 15 January 2022 Hunga, Tonga, volcano's explosive eruption produced the most powerful blast recorded in the last century, with an estimated equivalent TNT yield of 100–200 megatons. The blast energy was propagated through the atmosphere as various wave types. The most prominent wave was a long-period (>2000 s) surface-guided Lamb wave with energy comparable to that of the 1883 Krakatoa Lamb wave; both were clearly observed by pressure sensors (barometers) worldwide. Internal gravity, acoustic-gravity, and infrasound waves were captured in great detail by the entire infrasound component of the International Monitoring System (IMS). For instance, infrasound waves (<300 s period) were seen to circumnavigate Earth up to eight times. Atmospheric waves captured by the IMS infrasound network and selected barometers near the source provide insight on Earth's impulse response at planetary scales.

58 GEOSCIENCES↗

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↗

Examination of entrainment, combustibility, and heat transfer due to cell venting inside simplified battery energy storage enclosures

Battery energy storage systems (ESS) assembled of modules containing lithium-ion batteries can pose fire and explosion hazards during thermal runaway because vented gases may accumulate, combust, or escape enclosures. Here, we propose a prototypical configuration composed of the main components of an ESS rack, where modules are represented as rectangles within an enclosure and vent gas is injected steadily through the top of a module. This idealized geometry allows for exploration of how rack-level characteristics can influence smaller single-cell or module-level scales. Through this geometry, we conduct numerical simulations to understand how variations in the vent velocity, temperature, and vertical location affect entrainment rates, fraction of uncombusted fuel, rich-gas coverage, and heat flux to other modules. At lower vent velocities and vertical positions, buoyancy drives enough entrainment and mixing to react with most of the vent gases on the converging plenum. As jet momentum increases and/or buoyancy decreases via higher vent position in the rack, vent gases can propagate into and burn in the divergence plenum. Heat flux to the impinged module scales strongly with vent momentum and temperature, while heat transfer to upper modules peaks when flames in the diverging plenum reach the surface and declines when combustion is suppressed.

Computational fluid dynamics↗

A review of coal heating value correlations with application to coal char, tar, and other fuels

Accurately measuring a fuel’s heating value is one of the first steps in the classification of a new fuel. Heating values are widely used in coal combustion research and are becoming more useful in other fuel types as well. Many different empirical correlations to predict heating values based on primary organic (CHONS) elemental composition are found in the literature, many of which were originally created to predict heating values of parent coal, and some of which have been extended for biomass. However, no correlations exist for heating values of coal chars and tars. Thirteen literature heating value correlations (10 model forms with 13 unique sets of coefficients) were evaluated for their predictive accuracy of a wide variety of fuel types, including 353 coals. This comparative analysis showed that the predictive capabilities of many of these literature models are very similar for coal-based fuels, with good correlation of coal char heating values. Correlation of coal tar heating values was hampered by the lack of heating value data. The choice of which model to use becomes more important for biomass fuels as well as for more unique fuel types like propellants and explosives, municipal solid waste, etc. Finally, the best model forms for each fuel type are suggested based on several statistical measures of fit.

01 COAL, LIGNITE, AND PEAT↗

Experimental and theoretical analysis of carbon driven detonation waves in a heterogeneously premixed Rotating Detonation Engine

Coal dust explosions can be hazardous; however, they can also generate a significant rise in stagnation pressure if adequately harnessed. Rotating detonation combustors seek to take advantage of the stagnation pressure rise phenomenon in a more sustained and controlled manner via confinement to a physical annulus, leading to increased overall thermodynamic efficiency. Here this investigation presents an analysis of detonations fueled by Carbon Black, a solid particulate consisting of virtually pure carbon molecules and lean Hydrogen-Air mixtures. It is realized that with the addition of Carbon Black, an increase of lean mixture detonability and detonation velocities extending the operating limit over that of a pure hydrogen-air mixture is experienced. For all testing conditions, the total equivalence ratio is held at φ = 1, while the fuel mixture's carbon mass fraction is increased from 0 to 0.7 while the hydrogen is decreased. Detonation wave velocities are extracted from high-speed imaging through applying a Discrete Fourier Transform algorithm to determine changes to the wave speed as Carbon Black particles are introduced. As a result, due to the addition of Carbon Black as an auxiliary fuel source, detonations were formed instead of deflagrations in operating conditions where one would expect deflagrations at the same hydrogen-air equivalence ratios without Carbon Black addition. The detonation formation provides evidence that the coal particles are reacting within the detonation wave in a large enough capacity to support a detonation wave within the annulus. Furthermore, the wave speed is shown to increase with the additional of carbon particles. At a constant global equivalence ratio, the detonation wave velocities were found to decrease with hydrogen's incremental replacement with coal particles. Whereby, through a theoretical comparison of the heat of combustion as computed from the experimentally derived detonation wave velocities, a linear relationship of the two was shown to exist. Therefore, the heat of combustion has the potential to describe an operational limit to sustaining a detonation wave.

42 ENGINEERING↗

A tool and a methodology to use macros for abstracting variations in code for different computational demands

Scientific software used on high-performance computing platforms is in a phase of transformation because of the combined increase in the heterogeneity and complexity of models and hardware platforms. Having separate implementations for different platforms can easily lead to combinatorial explosions; therefore, the computational science community has been looking for mechanisms to express code through abstractions that can be specialized for different platforms. Most existing approaches use template meta-programming in C++, and are, therefore language specific. Here, we have developed a tool that uses customized expansion of macros to mimic some of C++ behavior in other languages. It enables unification of any code variants that may be necessary to run efficiently on different target architectures and different computational environments through use of macros with multiple alternative definitions and ability to arbitrate on definition selection for expansion. Combined with two other tools, a custom runtime, and a user specified recipe translator, our custom macroprocessor becomes a part of an overall performance portability solution that does not depend on any specific programming language. We also use macros as code-shorthand that lets code snippets become building blocks that allow variations in control flow to explore performance options. We demonstrate use of macros in Flash-X, a multiphysics multicomponent code with many Fortran legacy components derived from an earlier community code FLASH.

Heterogenous computing↗

DTLMod: A simulation framework for in situ workflow optimization

In situ processing workflows have become essential for coping with the explosion in data volume and velocity in large-scale scientific computing, providing domain scientists with early insights at runtime. Multiple frameworks implement this paradigm through a data transport layer (DTL), offering different data access modes and deployment schemes, but researchers currently lack the appropriate tools to assess design and deployment options before committing to costly real experiments. We introduce DTLMod, an open-source simulated DTL that enables performance evaluation of in situ workflow configurations at scale. Built on SimGrid, it links into any SimGrid-based simulator and is available in C++ and Python. We evaluate DTLMod along four axes: scalability (tens of thousands of simulated processes across interconnected clusters in seconds, with linear memory scaling), versatility (three implementation variants trading fidelity for speed), accuracy (simulated times faithfully reflecting real behavior), and practical utility (two use cases demonstrating evidence-based workflow design decisions).

Suter, Fred [ORNL] (ORCID:0000000319021955)↗

Lithium and boron isotopic compositions of olivine in chondrules from carbonaceous and ordinary chondrite meteorites: Implications for the origin of solar 11 B/ 10 B ratio

We report the origin of solar 11 B/ 10 B ratio ~4 remains an open question. It has been thought that a significant portion of boron in the Solar System was derived from continuous spallation nucleosynthesis during interactions between Galactic Cosmic Rays and C—N—O nuclei in the interstellar medium. However, because GCR-produced boron is characterized by 11 B/ 10 B ~2.5, an endmember with 11 B/ 10 B > 4 is required to account for the solar 11 B/ 10 B ratio. Two leading hypotheses for the sources of 11 B-rich components include low energy spallation in the Sun’s parental molecular cloud and the neutrino process during the supernova explosions. In this study, lithium and boron elemental and isotopic compositions of seven porphyritic olivine chondrules and one isolated olivine crystal from four meteorites (Allende, Yamato 81020, Asuka 12236, and QUE 97008) were determined in-situ to help constrain which of the two nucleosynthetic mechanisms has most likely supplied the forming Solar System with extra 11 B. Apparent isotopic variations in Li/Si, B/Si, δ 7 Li and δ 11 B were found in chondrule olivine crystals, but only three chondrules exhibit statistically resolved δ 11 B heterogeneities. Using these three chondrules as a basis for discussion, we evaluated the processes that could potentially cause elemental and isotopic variations of Li and B. We argue that the data can be best understood in the context of condensation of lithium-boron-rich material onto chondrule precursors in (an) initially heterogeneous gaseous reservoir(s), which could be realized if the Solar System derived 11 B-rich components from a supernova or supernovae.

58 GEOSCIENCES↗

Modeling the dynamic response of rock masses with multiple compliant fluid saturated joint sets - Part II: Continuum modeling

Part I of this two-part paper describes enhancements of a mesoscale model to include: many non-persistent fluid saturated joints with finite area, normal compliance with hysteresis and the weakening effects of angular deviation in the joint sets and of fluid pressure in the joints. The objective of this Part II is to use the results of the mesoscale model as simulated data to inspire functional forms in a continuum model for rock masses with multiple compliant fluid saturated joint sets which include these enhancements. Also, an algorithm is proposed for reducing the number of joint sets being modeled. Examples are presented here which show that the continuum model can predict similar anisotropic response to that observed in mesoscale simulations. In contrast with the mesoscale model, the continuum model can be used for large scale simulations of real applications, smoothly transitioning from coupled inelastic thermomechanical response near an explosive source to orthotropic elastic response far from the source.

58 GEOSCIENCES↗

Reducing ion diffusion at atmospheric pressure through intermingled positive and negative ions

Increasing ion molecule reaction times for ambient ionization techniques can increase sensitivity of detection. Longer reaction times result in an increase in analyte signal relative to the reactant ion signal, however with a subsequent decrease in the total ion intensity. This loss in the total number of ions reaching the detector limits the extent to which increased reaction time can improve detection in practical applications. In this study ion loss was measured using either electric fields or gas flow to control ion transit time. Ion transit times ranged from 40 ms to 8s, which resulted in ion densities ranging from 5 x 10 6 to 2 x 10 4 ions/cm 3 , respectively. These results provide insights into practical reaction time limitations or experimental boundaries when exploring sensitivity enhancements in ambient ionization. When exploring longer reaction times with an atmospheric flow tube coupled to a mass spectrometer (AFT-MS), an additional corona discharge ionization source of the same polarity was added in an attempt to increase total ion signal, but no improvement in signal was observed. This observation suggested that there was a maximum ion density being reached by the corona discharge that could not be increased by adding more of the same polarity ions. A hypothesis was that intermingling both polarities of ions would reduce ion loss and increase the measured ion signal. When two corona discharge sources—one each of positive and negative polarity—were used simultaneously in an AFT-MS, the total ion signal of either polarity measured by the MS was approximately double the current from a single corona discharge source. An increase in the negative ion signal was also observed when ~10 parts-per-trillion vapor levels of an explosive (RDX) were introduced. In this case both the nitrate reactant ions and the RDX signal more than doubled with the addition of a corona discharge source producing positive ions. When intermingling positive and negative ions, an increase in ion current was also observed when the AFT was coupled directly to a Faraday detector or to an ion mobility spectrometer. This was the first demonstration of interfacing the AFT to an IMS. The observations and developments from this work will help in creating more portable instruments with improved sensitivity for detection of chemicals.

47 OTHER INSTRUMENTATION↗

Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness

The original Tepla (TEnsile PLAsticity) ductile damage model, based on the Gurson yield surface, has long been used to model damage evolution and material failure under dynamic loading. Unfortunately, Tepla suffered from mesh sensitivity, numerical instability, and limited predictive capability. Here, we theoretically reformulate Tepla to address these issues. We especially focus on the prediction of porosity, which is the key state variable used for modeling ductile damage, as compared to more easily measured surface velocities, which are at best an indirect measure of damage. Key model changes include separating the viscosity during volumetric void growth from underlying shear strength behavior and switching to an iterative bisection solver. The new Tepla is then calibrated on incipient spall experiments on half-hard copper and tantalum, which demonstrate its ability to simultaneously fit the model to recovered porosity distributions and measured surface velocities, a stringent test. Improved numerical behavior, such as greatly reduced mesh sensitivity, is also shown in those simulations. Finally, the new Tepla model is applied to several high-explosive loaded, sweeping wave experiments, showing the ability of the model to predict behavior on tests with significantly different loading conditions and histories than the calibration data.

36 MATERIALS SCIENCE↗

Unveiling the nature of Ga-based chalcogenides for electrical switching selectors

Three-dimensional phase-change memory with stackable crossbar architecture is a promising technology to meet the urgent demands for high-density storage and rapid information processing in the era of explosive data growth. The performance depends strongly on the properties of ovonic threshold switching (OTS) selectors, which control the on/off states of memory units. Amorphous GaS serves as an outstanding OTS material, distinguished by its sizable mobility gap and high crystallization temperature, while the underlying mechanism continues to be inadequately comprehended. Here, in this work, we systematically studied the structural and electronic properties of amorphous Ga-X (X = S/Se/Te) using first-principles calculations. The results show that Ga atoms adopt tetrahedral motifs, while S/Se/Te atoms predominantly exhibit the structure of a distorted triangular pyramid. This structural arrangement is ascribed to the substantial dative bonds formed by the lone-pair electrons of the anions and the vacant sp3 orbitals around Ga atoms. Large mobility gaps (e.g., GaS: 2.43 eV, GaSe: 1.76 eV, GaTe: 1.26 eV) and distinct mid-gap states (e.g., ∼0.66 eV above valence band tail) ensure that these three chalcogenide glasses can be switched on under an external electric field while effectively suppressing leakage current without a bias, and the defect electronic states originate from short, robust Ga-Ga bonds due to the formation of distorted chain-like local structures. Our research elucidates the mechanisms of amorphous Ga-X as OTS materials, enriching the spectrum of electrical switching selectors by incorporating III-VI chalcogenides. This inclusion offers novel opportunities for the refinement and optimization of high-density integrated memory systems.

36 MATERIALS SCIENCE↗

Bubbles in US gasoline prices: Assessing the role of hurricanes and anti–price gouging laws

This paper examines the presence of bubbles — price changes that cannot be attributed to market fundamentals — in weekly US retail gasoline prices for ten US cities, and whether these bubbles are affected by hurricane events and anti–price gouging laws. Rolling-window, right-tailed unit root tests were used to identify and date bubbles. The analysis found 6 to 22 bubbles, lasting 4 weeks or longer, in city-level retail gasoline prices between 2000 and 2017. A linear regression model of the adjustment speed coefficients from the bubble identification step found that hurricane events increase the rate of price explosivity (or slow the rate of return to equilibrium) following a shock. Furthermore, the regression estimates also imply that state anti–price gouging laws can counteract these effects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗

The life and accomplishments of Alex Chernov

We report in the last two decades, crystal growth science has experienced explosive expansion. The primary driver has been the vast range of natural and engineered materials whose understanding and optimization require in-depth knowledge of how molecules cooperate to erect perfect three dimensional translationally-symmetric arrays - the miracle that we call crystallization. These huge fundamental and applied advances were possible only because we, the current generation of researchers, stand on the shoulders of our giant forefathers. Alex Chernov is among the tallest of the crystal growth giants.

99 GENERAL AND MISCELLANEOUS↗

Effects of natural zeolites on field-scale geologic noble gas transport

Improving predictive models for noble gas transport through natural materials at the field-scale is an essential component of improving US nuclear monitoring capabilities. Several field-scale experiments with a gas transport component have been conducted at the Nevada National Security Site (Non-Proliferation Experiment, Underground Nuclear Explosion Signatures Experiment). However, the models associated with these experiments have not treated zeolite minerals as gas adsorbing phases. This is significant as zeolites are a common alteration mineral with a high abundance at these field sites and are shown here to significantly fractionate noble gases during field-scale transport. This fractionation and associated retardation can complicate gas transport predictions by reducing the signal-to-noise ratio to the detector (e.g. mass spectrometers or radiation detectors) enough to mask the signal or make the data difficult to interpret. Omitting adsorption-related retardation data of noble gases in predictive gas transport models therefore results in systematic errors in model predictions where zeolites are present.Herein is presented noble gas adsorption data collected on zeolitized and non-zeolitized tuff. Experimental results were obtained using a unique piezometric adsorption system designed and built for this study. Data collected were then related to pure-phase mineral analyses conducted on clinoptilolite, mordenite, and quartz. These results quantify the adsorption capacity of materials present in field-scale systems, enabling the modeling of low-permeability rocks as significant sorption reservoirs vital to bulk transport predictions.

58 GEOSCIENCES↗

Background Concentrations of Argon-39 in Shallow Soil Gas

While radioisotopes of noble gases are known to be indicators of underground nuclear explosions (UNE), McIntyre et al. (2017) was the first to report the presence of 39Ar in shallow soil gas in association with a decades old UNE. While this finding hinted at the potential application of 39Ar to be used as an indicator of an UNE, doing so would also require an understanding of the natural concentrations of 39Ar present in soil gas. Without knowing the expected range and variability of naturally occurring concentrations of 39Ar, it is difficult to determine what measured concentrations would be indicative of an elevated concentration. This paper presents results from 16 soil gas samples and three atmospheric air samples collected from various locations across the western United States. Shallow soil gas samples were collected into self-contained underwater breathing apparatus (SCUBA) tanks using a custom-built soil gas sampling system and then processed and analyzed for 39Ar. The measured concentrations of 39Ar varied from atmospheric air concentrations to about 3.5 times atmospheric air concentrations. The variation in concentration was primarily attributed to the latitude the sample was collected at, which was consistent with previous work (Johnson et al. 2015). The results presented here represent the first measurements of natural background 39Ar concentrations in shallow soil gas. This data will be necessary if 39Ar is to be used as an indicator of UNE.

Fritz, Brad G.↗