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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Emergence of Diverse Failure Patterns in Weathering‐Induced Landslides: Insights From Particle Finite Element Simulations

Weathering is a fundamental driver of landslide evolution over geological timescales. Despite its ubiquity and importance, quantifying how weathering drives the progressive destabilization of rock slopes remains challenging. In this work, we develop a unified computational framework based on the particle finite element method to investigate the evolution of weathering‐induced landslides, from long‐term weathering to short‐term slope failure and runout dynamics. The framework integrates key processes, including weathering front propagation, time‐dependent strength degradation, rupture surface development, and post‐failure runout dynamics. Through numerical simulation experiments, we elucidate how interactions among weathering characteristics (type, intensity, and rate law), bedrock strength, fracture distribution, and slope geometry govern the failure modes and kinematics of weathering‐induced landslides. Simulations show that matrix‐dominated weathering leads to shallow translational failures, whereas fracture‐dominated weathering produces deep‐seated rotational and compound landslides. Pre‐existing fractures and slope morphology also strongly influence the movement of destabilized landmasses, affecting the failure pattern (e.g., kinematic mode and rupture surface geometry) and post‐failure behavior (e.g., runout velocity). We further demonstrate that the failure time and volume of weathered slopes are governed by the competition between gravitational driving forces and cohesive resisting forces during progressive destabilization. These findings provide new insights into the fundamental mechanisms that drive the emergence of diverse failure patterns of weathering‐induced landslides with important implications for landslide hazard assessment.

Wang, Liang [Eidgenoessische Technische Hochschule↗
DOE OSTI2025

Particle-in-cell simulations of burning inertial confinement fusion capsule implosions

Anomalies observed in the neutron spectral shift of high-yield shots at the National Ignition Facility (NIF) suggest the presence of suprathermal ions [E. P. Hartouni et al., Nat. Phys. 19, 72 (2023)], implying that kinetic effects play a significant role in burning inertial confinement fusion (ICF) plasmas. Furthermore, recent measurements of reaction-in-flight (RIF) neutrons offer a direct probe of the stopping power in the burning fuel region of high-energy alpha particles and up-scattered fuel ions. We have developed the particle-in-cell code PICNIC, an exactly energy-conserving particle-in-cell Monte-Carlo collision (PIC-MCC) code to simulate the burn stage in ICF. We present results from 1D spherical simulations of NIF shot N210808, which was the first to exceed the Lawson criterion for laser fusion. We find that the suprathermal ions generated by large-angle Rutherford and nuclear elastic scattering (NES) with fusion alphas produce an alpha knock-on neutron (AKN) signal consistent with the extent and relative yield of the AKN spectrum identified in ignition experiments at the NIF. Furthermore, we also find that the inclusion of large-angle scattering physics does not explain the anomalously large spectral shift observed in the experiment.

High-energy-density plasmas↗
DOE OSTI2023

Quantum simulation of fundamental particles and forces

Key static and dynamic properties of matter — from creation in the Big Bang to evolution into subatomic and astrophysical environments — arise from the underlying fundamental quantum fields of the standard model and their effective descriptions. However, the simulation of these properties lies beyond the capabilities of classical computation alone. Advances in quantum technologies have improved control over quantum entanglement and coherence to the point at which robust simulations of quantum fields are anticipated in the foreseeable future. In this Perspective article, we discuss the emerging area of quantum simulations of standard-model physics, outlining the challenges and opportunities for progress in the context of nuclear and high-energy physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

An explicit scheme to enforce charge conservation in transient Particle-in-Cell simulations with Maxwell-Boltzmann electrons

The Maxwell-Boltzmann electron model is a very popular approximation of the electronic behavior in electrostatic plasmas, adopted in all cases where the electron dynamics is governed only by a balance between electric and pressure forces. In such a model, the electron dynamics is reduced to solving for a nonlinear Poisson problem together with an additional expression enforcing charge conservation. In this work we derive an expression of charge conservation which can be conveniently applied to explicit schemes to update the reference Boltzmann density, particularly useful when simulating plasma sheaths. The scheme can be equally applied to both steady-state and transient problems. Two examples are shown, a steady-state plasma sheath, and a radio-frequency magnetic presheath. Our proposed scheme allows to enforce global charge conservation locally in time, and can thus be applied to the simulation of transient phenomena.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

How sheath properties change with gas pressure: modeling and simulation

Abstract Particle-in-cell simulations are used to study how neutral pressure influences plasma properties at the sheath edge. The high rate of ion–neutral collisions at pressures above several mTorr are found to cause a decrease in the ion velocity at the sheath edge (collisional Bohm criterion), a decrease in the edge-to-center density ratio ( h l factor), and an increase in the sheath width and sheath potential drop. A comparison with existing analytic models generally indicates favorable agreement, but with some distinctions. One is that models for the h l factor need to be made consistent with the collisional Bohm criterion. With this and similar corrections, a comprehensive fluid-based model of the plasma boundary transition is constructed that compares well with the simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Nonlinear δf particle in cell gyrokinetic simulations of the microtearing mode

Nonlinear simulations are carried out for the microtearing mode using particle-based δf gyrokinetic simulations for parameters relevant to spherical tokamaks. The present study finds that the microtearing mode can generate significant electron heat flux, which is predominantly carried out by the electromagnetic component of the heat flux with a negligible contribution from the electrostatic component. The mode sustains without the electrostatic component. We observe that the electron heat flux increases with the electron temperature gradient. The heat flux exhibits a very weak dependence on the collisions. It increases with electron β initially; however, at very high β, the electron heat flux is reduced.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Scaling the training of particle classification on simulated MicroBooNE events to multiple GPUs

Measurements in Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors, such as the MicroBooNE detector at Fermilab, feature large, high fidelity event images. Deep learning techniques have been extremely successful in classification tasks of photographs, but their application to LArTPC event images is challenging, due to the large size of the events. Events in these detectors are typically two orders of magnitude larger than images found in classical challenges, like recognition of handwritten digits contained in the MNIST database or object recognition in the ImageNet database. Ideally, training would occur on many instances of the entire event data, instead of many instances of cropped regions of interest from the event data. However, such efforts lead to extremely long training cycles, which slow down the exploration of new network architectures and hyperparameter scans to improve the classification performance. We present studies of scaling a LArTPC classification problem on multiple architectures, spanning multiple nodes. The studies are carried out on simulated events in the MicroBooNE detector. We emphasize that it is beyond the scope of this study to optimize networks or extract the physics from any results here. Institutional computing at Pacific Northwest National Laboratory and the SummitDev machine at Oak Ridge National Laboratory’s Leadership Computing Facility have been used. To our knowledge, this is the first use of state-of-the-art Convolutional Neural Networks for particle physics and their attendant compute techniques onto the DOE Leadership Class Facilities. We expect benefits to accrue particularly to the Deep Underground Neutrino Experiment (DUNE) LArTPC program, the flagship US High Energy Physics (HEP) program for the coming decades.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Simulating single-particle dynamics in magnetized plasmas: The RMF code

The RMF (Rotating Magnetic Field) code is designed to calculate the motion of a charged particle in a given electromagnetic field. It integrates Hamilton’s equations in cylindrical coordinates using an adaptive predictor-corrector double-precision variable-coefficient ordinary differential equation solver for speed and accuracy. RMF has multiple capabilities for the field. Particle motion is initialized by specifying the position and velocity vectors. Here, the six-dimensional state vector and derived quantities are saved as functions of time. A post-processing graphics code, XDRAW, is used on the stored output to plot up to 12 windows of any two quantities using different colors to denote successive time intervals. Multiple cases of RMF may be run in parallel and perform data mining on the results. Recent features are a synthetic diagnostic for simulating the observations of charge-exchange-neutral energy distributions and RF grids to explore a Fermi acceleration parallel to static magnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Long-term variability in immersion-mode marine ice-nucleating particles from climate model simulations and observations

Abstract. Ice-nucleating particles (INPs) in the Southern Ocean (SO) atmosphere have significant impacts on cloud radiative and microphysical properties. Yet, INP prediction skill in climate models remains poorly understood, in part because of the lack of long-term measurements. Here we show, for the first time, how model-simulated INP concentrations compare with year-round INP measurements during the Macquarie Island Cloud Radiation Experiment (MICRE) campaign from 2017–2018. We simulate immersion-mode INP concentrations using the Energy Exascale Earth System Model version 1 (E3SMv1) by combining simulated aerosols with recently developed deterministic INP parameterizations and the native classical nucleation theory (CNT) for mineral dust in E3SMv1. Because MICRE did not collect aerosol measurements of super-micron particles, which are more effective ice nucleators, we evaluate the model's aerosol fields at other high-latitude sites using long-term in situ observations of dust and sea spray aerosol. We find that the model underestimates dust and overestimates sea spray aerosol concentrations by 1 to 2 orders of magnitude for most of the high-latitude sites in the Southern Hemisphere. We next compare predicted INP concentrations with concentrations of INPs collected on filter samples (typically for 2 or 3 d) and processed offline using the Colorado State University ice spectrometer (IS) in immersion freezing mode. We find that when deterministic parameterizations for both dust and sea spray INPs are used, simulated INPs are within a factor of 10 of observed INPs more than 60 % of the time during summer. Our results also indicate that the E3SM's current treatment of mineral dust immersion freezing in the SO is impacted by compensating biases – an underprediction of dust amount was compensated by an overprediction of its effectiveness as INPs. We also perform idealized droplet freezing experiments to quantify the implications of the time-dependent behavior assumed by the E3SM's CNT-parameterization and compare with the ice spectrometer observations. We find that the E3SM CNT 10 s diagnostic used in this study is a reasonable approximation of the exact formulation of CNT, when applied to ice spectrometer measurements in low-INP conditions similar to Macquarie Island. However, the linearized 10 s diagnostic underestimates the exact formula by an order of magnitude or more in places with high-INP conditions like the Sahara. Overall, our findings suggest that it is important to correct the biases in E3SM's simulated dust life cycle and update E3SM's INP parameterizations. INP prediction errors of 2 to 3 orders of magnitude can have considerable impacts on the simulated cloud and radiative properties in global climate models. On comparing INP concentrations during MICRE against ship-based campaigns, Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) and Antarctic Circumnavigation Expedition (ACE), we find that INPs from the latter are significantly higher only in regions closer to Macquarie Island. This alludes to the fact that physical, chemical and biological processes affecting INP concentrations as stimulated by the island could be partly responsible for the high INP concentrations observed at Macquarie Island during the MICRE campaign. Therefore, improvements to both aerosol simulation and INP parameterizations are required to adequately simulate INPs and their cloud impacts in E3SM. It will be helpful to include a parallel measurement of the size-resolved aerosol composition and explore opportunities for long-term measurement platforms in future field campaigns studying INP sources in remote marine regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

MADLens, a python package for fast and differentiable non-Gaussian lensing simulations

Here, we present MADLens a python package for producing non-Gaussian lensing convergence maps at arbitrary source redshifts with unprecedented precision. MADLens is designed to achieve high accuracy while keeping computational costs as low as possible. A MADLens simulation with only particles produces convergence maps whose power agrees with theoretical lensing power spectra up to within the accuracy limits of HaloFit. This is made possible by a combination of a highly parallelizable particle-mesh algorithm, a sub-evolution scheme in the lensing projection, and a machine-learning inspired sharpening step. Further, MADLens is fully differentiable with respect to the initial conditions of the underlying particle-mesh simulations and a number of cosmological parameters. These properties allow MADLens to be used as a forward model in Bayesian inference algorithms that require optimization or derivative-aided sampling. Another use case for MADLens is the production of large, high resolution simulation sets as they are required for training novel deep-learning-based lensing analysis tools. We make the MADLens package publicly available under a Creative Commons License

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Fraction of Free-Base Nicotine in Simulated Vaping Aerosol Particles Determined by X-ray Spectroscopies

A new generation of electronic cigarettes is exacerbating the youth vaping epidemic by incorporating additives that increase the acidity of generated aerosols, which facilitate uptake of high nicotine levels. We need to better understand the chemical speciation of vaping aerosols to assess the impact of acidification. Here we used X-ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe the acid-base equilibria of nicotine in hydrated vaping aerosols. Here we show that, unlike the behavior observed in bulk water, nicotine in the core of aqueous particles was partially protonated when the pH of the nebulized solution was 10.4, with a fraction of free-base nicotine (α FB ) of 0.34. Nicotine was further protonated by acidification with equimolar addition of benzoic acid (α FB = 0.17 at pH 6.2). By contrast, the degree of nicotine protonation at the particle surface was significantly lower, with 0.72 < α FB < 0.80 in the same pH range. The presence of propylene glycol and glycerol completely eliminated protonation of nicotine at the surface (α FB = 1) while not affecting significantly its acid-base equilibrium in the particle core. These results provide a better understanding of the role of acidifying additives in vaping aerosols, supporting public health policy interventions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗