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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Multicomponent Reactive Transport Model for Integrated Surface‐Subsurface Hydrology Problems

Abstract Despite the widespread use of integrated hydrology models in a variety of applications, consideration of multicomponent reactive transport is still not common. The implementation of these processes requires coupling transport at the surface‐subsurface interface and efficient solution of the non‐linear geochemical model that is consistent with the integrated hydrology solution. The Advanced Terrestrial Simulator provides a flexible multiphysics framework that facilitated this process. In this work, the integrated reactive transport process kernel (PK) was weakly coupled to the integrated hydrology PK. In turn, integrated transport and reactions were coupled using an operator splitting approach. This splitting enabled an explicit solution of the integrated transport problem, including a novel algorithm to calculate exchange fluxes across the surface‐subsurface interface and a point‐by‐point solution of the geochemical problem. Geochemical capabilities were added using well‐established external codes, but rather than using a custom interface to each, a generic interface was used that clearly specifies the variables and operations used by the chemistry PK. The implementation is demonstrated with two example simulations: transport of a tracer in a soil column as it saturates over time and water ponds on the surface and reactive transport in a hillslope driven by successive wet‐dry cycles that result in infiltration, runoff and exfiltration processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

HPC Network Simulation Tuning via Automatic Extraction of Hardware Parameters

Popular HPC network interconnection simulators such as SST/macro provide a variety of configurable parameters to explore the design space of hardware components such as network interface cards (NIC), switches, and links among them. While such knobs provide flexibility to explore design trade-offs for novel hardware, manually configuring simulations for matching configurations of the existing hardware to focus on topology exploration can be cumbersome and error-prone, leading to widely inaccurate simulations. This challenge is compounded when specifications of various (proprietary) technologies are not readily available or intentionally omitted. In this work, we propose a framework to autotune the multiple network models’ simulation configurations within SST/macro using Tree-structured Parzen Estimator-based Bayesian optimization to observe the effect on simulation accuracy across different message regimes. These regimes consist of small to large message sizes and latency to bandwidth-bound messages. We provide a detailed analysis of the simulation error for four representative HPC systems. Our Bayesian optimization based autotuning framework for network models achieves a maximum of 5x improvement in accuracy over best-effort manual configurations based on available hardware specifications.

Simulation, autotuning↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of the Four-Dimensional Ensemble-Variational Hybrid Data Assimilation with Self-Consistent Regional Background Error Covariance for Improved Hurricane Intensity Forecasts

The feasibility of a hurricane initialization framework based on the Gridpoint Statistical Interpolation (GSI)-based four-dimensional ensemble-variational (GSI-4DEnVar) hybrid data assimilation system for the Hurricane Weather Research and Forecasting model (HWRF) model is evaluated in this study. The system considers the temporal evolution of error covariances via the use of four-dimensional ensemble perturbations that are provided by high-resolution, self-consistent HWRF ensemble forecasts. It is different from the configuration of the GSI-based three-dimensional ensemble-variational (GSI-3DEnVar) hybrid data assimilation system, similar to that used in the operational HWRF, which employs background error covariances provided by coarser-resolution global ensembles from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) ensemble Kalman filtering data assimilation system. In addition, our proposed initialization framework discards the empirical intensity correction in the vortex initialization package that is employed by the GSI-3DEnVar initialization framework in operational HWRF. Data assimilation and numerical simulation experiments for Hurricanes Joaquin (2015), Patricia (2015), and Matthew (2016) are conducted during their intensity changes. The impacts of two initialization frameworks on the HWRF analyses and forecasts are compared. It is found that GSI-4DEnVar leads to a reduction in track, minimum sea level pressure (MSLP), and maximum surface wind (MSW) forecast errors in all of the HWRF simulations, compared with the GSI-3DEnVar initialization framework. With assimilating high-resolution observations within the hurricane inner-core region, GSI-4DEnVar can produce the initial hurricane intensity reasonably well without the empirical vortex intensity correction. Further diagnoses with Hurricane Joaquin indicate that GSI-4DEnVar can significantly alleviate the imbalances in the initial conditions and enhance the performance of the data assimilation and subsequent hurricane intensity and precipitation forecasts

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Simulating Electron Impact Ionization using a General Particle Tracer (GPT) Custom Element

A new C++ custom element has been developed with the framework of General Particle Tracer (GPT) to simulate electron impact ionization of residual gas molecules. The custom element uses Monte-Carlo routines to determine both the ion production rate and the secondary electron kinetic energy based on user-defined gas densities and theoretical values for the ionization cross section and the secondary electron differential cross section. It then uses relativistic kinematics to track the secondary electron, the scattered electron, and the newly formed ion after ionization. The ion production rate and the secondary electron energy distribution determined by the custom element have been benchmarked against theoretical calculations and against simulations made using the simulation package IBSimu. While the custom element was originally built for particle accelerator simulations, it is readily extensible to other applications. The custom element will be described in detail and examples of applications at the Thomas Jefferson National Accelerator Facility will be presented for ion production in a DC high voltage photo-gun.

Yoskowitz, J. T.↗
DOE OSTI2023

Magnetic potential based formulation for linear and non-linear 3D RF sheath simulation

Abstract This paper reports a new numerical scheme to simulate the radio-frequency (RF) induced RF sheath, which is suitable for a large 3D simulation. In the RF sheath boundary model, the tangential component of the electric field ( E t ) is given by the gradient of a scalar electric field potential. We introduce two additional scalar potentials for the tangential components of the magnetic field, which effectively impose the normal electric displacement ( D n ) on the plasma sheath boundary condition via in-homogeneous Neumann boundary condition and constrain the tangential electric field on the surface as curl-free ( ∇ × E t = 0 ). In our approach, the non-linear sheath impedance is formulated as a natural extension of the large thickness (or asymptotic) sheath limit ( D n = 0 ), allowing for handling both asymptotic and non-linear regimes seamlessly. The new scheme is implemented using the Petra-M finite element method analysis framework and is verified with simulations in the literature. The significance of non-linearity is discussed in various plasma conditions. An application of this scheme to asymptotic RF sheath simulation on the WEST ICRF antenna side limiters is also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Modeling Framework for Bulk Electric Grid Impacts from HEMP E1 and E3 Effects (Tasks 3.1 Final Report)

This report presents a framework to evaluate the impact of a high-altitude electromagnetic pulse (HEMP) event on a bulk electric power grid. This report limits itself to modeling the impact of EMP E1 and E3 components. The co-simulation of E1 and E3 is presented in detail, and the focus of the paper is on the framework rather than actual results. This approach is highly conservative as E1 and E3 are not maximized with the same event characteristics and may only slightly overlap. The actual results shown in this report are based on a synthetic grid with synthetic data and a limited exemplary EMP model. The framework presented can be leveraged and used to analyze the impact of other threat scenarios, both manmade and natural disasters. This report d escribes a Monte-Carlo based methodology to probabilistically quantify the transient response of the power grid to a HEMP event. The approach uses multiple fundamental steps to characterize the system response to HEMP events, focused on the E1 and E3 components of the event. 1) Obtain component failure data related to HEMP events testing of components and creating component failure models. Use the component failure model to create component failure conditional probability density function (PDF) that is a function of the HEMP induced terminal voltage. 2) Model HEMP scenarios and calculate the E1 coupled voltage profiles seen by all system components. Model the same HEMP scenarios and calculate the transformer reactive power consumption profiles due to E3. 3) Sample each component failure PDF to determine which grid components will fail, due to the E1 voltage spike, for each scenario. 4) Perform dynamic simulations that incorporate the predicted component failures from E1 and reactive power consumption at each transformer affected by E3. These simulations allow for secondary transients to affect the relays/protection remaining in service which can lead to cascading outages. 5) Identify the locations and amount of load lost for each scenario through grid dynamic simulation. This can be an indication of the immediate grid impacts from a HEMP event. In addition, perform more detailed analysis to determine critical nodes and system trends. 6) To help realize the longer-term impacts, a security constrained alternating current optimal power flow (ACOPF) is run to maximize critical load served. This report describes a modeling framework to assess the systemic grid impacts due to a HEMP event. This stochastic simulation framework generates a large amount of data for each Monte Carlo replication, including HEMP location and characteristics, relay and component failures, E3 GIC profiles, cascading dynamics including voltage and frequency over time, and final system state. This data can then be analyzed to identify trends, e.g., unique system behavior modes or critical components whose failure is more likely to cause serious systemic effects. The proposed analysis process is demonstrated on a representative system. In order to draw realistic conclusions of the impact of a HEMP event on the grid, a significant amount of work remains with respect to modeling the impact on various grid components.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks

Electroconvection is a multiphysics problem involving coupling of the flow field with the electric field as well as the cation and anion concentration fields. Here, we use electroconvection as a benchmark problem to put forward a new data assimilation framework, the DeepM&Mnet, for simulating multiphysics and multiscale problems at speeds much faster than standard numerical methods using pre-trained neural networks. We first pre-train DeepONets that can predict independently each field, given general inputs from the rest of the fields of the coupled system. DeepONets can approximate nonlinear operators and are composed of two sub-networks, a branch net for the input fields and a trunk net for the locations of the output field. DeepONets, which are extremely fast, are used as building blocks in the DeepM&Mnet and form constraints for the multiphysics solution along with some sparse available measurements of any of the fields. We demonstrate the new methodology and document the accuracy of each individual DeepONet, and subsequently we present two different DeepM&Mnet architectures that infer accurately and efficiently 2D electroconvection fields for unseen electric potentials. Furthermore, the DeepM&Mnet framework is general and can be applied for building any complex multiphysics and multiscale models based on very few measurements using pre-trained DeepONets in a “plug-and-play” mode.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation

Aggregation of electric vehicles (EVs) is a promising technique for providing secondary frequency regulation (SFR) in highly renewable energy-penetrated power systems. Equipped with energy storage devices, EV aggregation can provide reliable SFR. However, the main challenge is to guarantee reliable intra-interval SFR capacities and inter-interval delivery following the automatic generation control (AGC) signal. Furthermore, aggregated EV SFR provision will be further complicated by the EV charging time anxiety because SFR provision might extend EV's charging time. This paper proposes a deliverable EV SFR provision with a charging-time-constrained control strategy. First, a charging-time-constrained EV aggregation is proposed to address the uncertainty of EV capacity based on the state-space model considering the charging-time restriction of EV owners. Second, a real-time economic dispatch and time domain simulation (RTED-TDS) cosimulation framework is proposed to verify financial results and the dynamic performance of the EV SFR provision. Last, the proposed charging time-constrained EV aggregation is validated on the IEEE 39-bus system. In conclusion, the results demonstrate that with charging time-constrained EV aggregation, the dynamic performance of the system can be improved with a marginal increase in total cost. More importantly, the charging time constraint can be respected in the proposed SFR provision of the EV aggregation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Non-dimensional performance and safety parameters for heat pipes

The use of heat pipes in safety-critical systems such as nuclear microreactors dictates the development of generalized, practical, scalable performance and safety parameters. Traditional dimensional metrics, while informative, lack the universality required for comparative analysis across varying designs and operating regimes. Here, this work introduces a comprehensive set of non-dimensional parameters to characterize heat pipe performance and safety, including capillary performance, effective thermal conductivity, response time, exergetic efficiency, allowable temperature gradients, allowable rate of temperature change, priming coefficients, and factor of safety. A reference heat pipe design representative of microreactor applications was analyzed via the developed parameters using both traditional analytical models and Sockeye simulations under transient and steady-state conditions. Sodium, potassium, and water were evaluated as working fluids to demonstrate the applicability of the framework across a broad temperature range. The proposed non-dimensional parameters effectively captured key thermal-hydraulic behaviors and safety concerns, as was demonstrated via Sockeye simulations. This framework supports the development of design optimization strategies, operational protocols, and safety assurance practices for advanced reactor systems and other high-reliability applications.

42 - ENGINEERING↗
DOE OSTI2020

Whole cell simulator

A whole cell model (WCM) is a comprehensive multi-scale computational model representing all the known biochemical processes in a cell. It relies on a variety of intracellular pathway models and omics data. This computational framework enables seamless integration of diverse simulation methods used in WCM such as stochastic simulation algorithm (SSA), ordinary differential equations (ODE), flux balance analysis (FBA), and logic-based approaches. These methods run simultaneously, not only for whole pathways but also for subsets of reactions. Furthermore, we aim to enable dynamic switching between the methods when beneficial. Is

GEORGAKOUDIS, GIORGIS↗
DOE OSTI2023

Computational investigation of hysteresis and phase equilibria of n-alkanes in a metal-organic framework with both micropores and mesopores

Abstract Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions and phase equilibria in porous materials. In this work, adsorption isotherms for methane, ethane, propane, and n-hexane were calculated from atomistic grand canonical Monte Carlo (GCMC) simulations in a metal-organic framework having both micropores and mesopores to better understand hysteresis and phase equilibria between connected pores of different size and the external bulk fluid. At low temperatures, the calculated isotherms exhibit sharp steps accompanied by hysteresis. As a complementary simulation method, canonical (NVT) ensemble simulations with Widom test particle insertions are demonstrated to provide additional information about these systems. The NVT+Widom simulations provide the full van der Waals loop associated with the sharp steps and hysteresis, including the locations of the spinodal points and points within the metastable and unstable regions that are inaccessible to GCMC simulations. The simulations provide molecular-level insight into pore filling and equilibria between high- and low-density states within individual pores. The effect of framework flexibility on adsorption hysteresis is also investigated for methane in IRMOF-1.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Model of photoemission and framework for relating quantum efficiency to stoichiometry

Simulating the quantum efficiency (QE) from photocathodes used in accelerators and photoinjectors requires accounting for the properties of the photoemissive material, the optical properties, scattering coefficients, and doping concentrations of which are dependent upon the stoichiometry. We present a rapid and flexible optical model that can be used to investigate the consequences of changes in the dielectric properties and their impact on the QE through such factors as reflectivity and laser penetration depth. Differences in materials can then be characterized by changes to parameters used to evaluate the dielectric function in a Lorentz–Drude–Resonant model. A method to characterize data is motivated by the example of copper and vetted by application to an exact analytical model. The effects of changes in parameters describing the resonant terms, which aggregate in the visible and UV regions of the spectrum, are shown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Stringent σ8 constraints from small-scale galaxy clustering using a hybrid MCMC + emulator framework

ABSTRACT We present a novel simulation-based hybrid emulator approach that maximally derives cosmological and Halo Occupation Distribution (HOD) information from non-linear galaxy clustering, with sufficient precision for DESI Year 1 (Y1) analysis. Our hybrid approach first samples the HOD space on a fixed cosmological simulation grid to constrain the high-likelihood region of cosmology + HOD parameter space, and then constructs the emulator within this constrained region. This approach significantly reduces the parameter volume emulated over, thus achieving much smaller emulator errors with fixed number of training points. We demonstrate that this combined with state-of-the-art simulations result in tight emulator errors comparable to expected DESI Y1 LRG sample variance. We leverage the new abacussummit simulations and apply our hybrid approach to CMASS non-linear galaxy clustering data. We infer constraints on σ8 = 0.762 ± 0.024 and fσ8(zeff = 0.52) = 0.444 ± 0.016, the tightest among contemporary galaxy clustering studies. We also demonstrate that our fσ8 constraint is robust against secondary biases and other HOD model choices, a critical first step towards showcasing the robust cosmology information accessible in non-linear scales. We speculate that the additional statistical power of DESI Y1 should tighten the growth rate constraints by at least another 50–60 ${{\ \rm per\ cent}}$, significantly elucidating any potential tension with Planck. We also address the ‘lensing is low’ tension, which we find to be in the same direction as a potential tension in fσ8. We show that the combined effect of a lower fσ8 and environment-based bias accounts for approximately $50{{\ \rm per\ cent}}$ of the discrepancy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Hydrodynamic instabilities and heat transfer characteristics in the duct flow of a fluid in the supercritical thermodynamic regime

The behavior of fluids at supercritical thermodynamic conditions is inherently complex due to large variations in thermodynamic and transport properties. Recent numerical and experimental investigations illustrate ongoing interest for these fluids, especially supercritical CO 2 and supercritical water, for a variety of applications. For example, supercritical water reactors (SCWR) operate in this extreme condition of high-pressure and temperature, resulting in highly dynamic flow fields and unexpected heat transfer regimes. The potential heat transfer benefits in this regime are directly associated with the extreme variations in thermodynamic and transport properties, which occur at, and above, the critical point. This work characterizes the hydrodynamic instabilities that arise for fluids at supercritical thermodynamic conditions when buoyancy forces are significant. Two specific configurations are considered, a natural convection cavity flow, and a mixed convection, heated, horizontal channel flow. Natural convection flow in a cavity is a classical configuration with expected behavior below the critical point. This configuration aids in characterizing the effect of the variable properties in the supercritical thermodynamic regime. Further, limited studies in the existing literature have been conducted for low-Reynolds and intermediate-Rayleigh numbers, mixed-convection channel flows for supercritical water, which is the focus of the channel flow configuration. To investigate the thermally driven hydrodynamic instabilities in this regime, a high-order fully-implicit numerical method is used. Such strong variations in thermophysical properties (in particular, density) are difficult to simulate and an altogether compressible framework is needed. Therefore, the compressible Navier-Stokes equations are solved without any additional assumptions. The fully implicit, high-order in space and time, reconstructed discontinuous Galerkin method as implemented within the multi-physics code called ALE3D (Arbitrary Lagrangian and Eulerian in 2D and 3D), developed at Lawrence Livermore National Laboratory (LLNL), is used. This fully implicit, L-stable method accurately captures the compressible nature of the ow in the limit of very low Mach number. It has been widely accepted that above the critical point, only one phase is observed. However, recent research has indicated the existence of the distinct gas-like and liquid-like regions separated by the Widom line, the locus of the maxima of the specific heat. Along the Widom line, density decreases 6-fold, viscosity drops by a factor of 2, while specific heat spikes by an order of magnitude. These variations, specifically in density and viscosity, produce a thick pseudo-interface and flow dynamics behavior akin to film boiling. A pseudo-film at the heated wall of the cavity and the horizontal channel is observed where buoyancy forces induce mixing through the specific configurations. Further the local Rayleigh and Richardson numbers provide maps of the flow field and the buoyancy forces driving the microscopic mixing. In the first chapter, I describe a background of supercritical fluid and the various applications. The second chapter focuses on the mathematical model and numerical method used for simulations, where a description of the equation of state for supercritical water is described. The third chapter focuses on the natural convection cavity with a heated bottom wall. In this cavity a gas-like and a liquid-like flow within the supercritical thermodynamic regime are observed. The fourth chapter focuses on a forced convection, horizontal channel, distinguishing between the gas-like, liquid-like, and mixed flow regimes. Mixed convection flow, with the addition of gravitational forces in the horizontal channel show the influence of variable properties on the hydrodynamic development, heat transfer, and rising instabilities. The last chapter of this research focuses on characterizing the unstable hydrodynamics through time-averaging processes and analysis of the movement of energy through the developing plumes.

42 ENGINEERING↗
DOE OSTI2025

Enhanced MPM framework with multipatch isogeometric analysis for geotechnical applications

Achieving stable stress solutions at large strains using the Material Point Method (MPM) is challenging due to the accumulation of errors associated with geometry discretization, cell-crossing noise, and volumetric locking. Several simplified attempts exist in the literature to mitigate these errors, including higher-order frameworks. However, the stability of the MPM solution in such frameworks has been limited to simple geometries and the single-phase formulation (i.e., neglecting pore fluid). Although never explored, multipatch isogeometric analysis offers desirable qualities to simulate complex geometries while mitigating errors in the MPM. The degree of required high-order spatial integration has also never been investigated to infer a minimum limit for the stability of the stress solution in MPM. This paper presents a general-purpose numerical framework for simulating stable stresses in porous media, capturing both near incompressibility and multiphase interactions. First, the numerical framework is presented considering Non-Uniform Rational B-splines (NURBS) to perform isogeometric analysis (IGA) in MPM. Additionally, a volumetric strain smoothing algorithm is used to alleviate errors associated with volumetric locking. Second, the manifestation of cell-crossing errors is assessed via a series of problems with orders ranging from linear to cubic interpolation functions. Third, the use of NURBS is investigated and verified for problems with circular geometries. Finally, multipatch analysis is deployed to simulate plane strain and 3D penetration in soils, considering nearly incompressible elastoplastic (total stress) analysis and fully-coupled hydro-mechanical (effective stress) analysis. The stability of the solution is also analyzed for different constitutive models. From the results, it can be concluded that the framework using cubic interpolation functions with strain smoothing is the most convenient, presenting stable stress solutions for a broad range of multiphase geotechnical applications.

58 GEOSCIENCES↗