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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The Umbra Simulation and Integration Framework Applied to Emergency Response Training

The Mine Emergency Response Interactive Training Simulation (MERITS) is intended to prepare personnel to manage an emergency in an underground coal mine. The creation of an effective training environment required realistic emergent behavior in response to simulation events and trainee interventions, exploratory modification of miner behavior rules, realistic physics, and incorporation of legacy code. It also required the ability to add rich media to the simulation without conflicting with normal desktop security settings. Our Umbra Simulation and Integration Framework facilitated agent-based modeling of miners and rescuers and made it possible to work with subject matter experts to quickly adjust behavior through script editing, rather than through lengthy programming and recompilation. Integration of Umbra code with the WebKit browser engine allowed the use of JavaScript-enabled local web pages for media support. This project greatly extended the capabilities of Umbra in support of training simulations and has implications for simulations that combine human behavior, physics, and rich media.

Hamilton, Paul Lawrence↗
DOE OSTI2020

Optimal Sizing of Resilience Solutions for the U.S. Army Reserve

Power or water outages in buildings threaten the ability of the military to support surrounding communities during natural disasters. Outages can last for days, weeks or months. Typical solutions include very expensive batteries and onsite generation that are sized based on historical power needs. The U.S. Army Reserve (USAR) has teamed up with the Pacific Northwest National Laboratory (PNNL) to develop a simulation framework that optimizes future power needs to reduce the cost of resilience solutions. The approach starts with the building. Power needs during an emergency event are simulated at the building end-use level, then loads are reduced through the selection of life cycle cost-effective building-level technology improvements. These new optimized loads are then fed into a microgrid sizing tool that dynamically constructs many different combinations of solar photovoltaic, battery storage, and generator resources to meet the load for hundreds of statistically generated outage scenarios. Six site assessments completed by USAR and PNNL in 2019 have resulted in a 1-14% reduction in overall investment when optimizing the buildings first before determining the generation requirements. This approach helps the Army secure critical missions and provide a 14 day-minimum supply of necessary energy and water in the most efficient manner.

buidlings, efficiency, resilience, FEDS, MCOR↗
DOE OSTI2022

Towards Low-Overhead Resilience for Data Parallel Deep Learning

Data parallel techniques have been widely adopted both in academia and industry as a tool to enable scalable training of deep learning models. At scale, DL training jobs can fail due to software or hardware bugs, may need to be preempted or terminated due to unexpected events, or may perform suboptimally because they were misconfigured. Under such circumstances, there is a need to recover and/or reconfigure data-parallel DL training jobs on-the-fly, while minimizing the impact on the accuracy of the DNN model and the runtime overhead. In this regard, state-of-art techniques adopted by the HPC community mostly rely on checkpoint-restart, which inevitably leads to loss of progress, thus increasing the runtime overhead. In this paper we explore alternative techniques that exploit the properties of modern deep learning frameworks (overlapping of gradient averaging and weight updates with local gradient computations through pipeline parallelism) to reduce the overhead of resilience/elasticity. To this end we introduce a failure simulation framework and two resilience strategies (immediate mini-batch rollback and lossy forward recovery), which we study compared with checkpoint-restart approaches in a variety of settings in order to understand the trade-offs between the accuracy loss of the DNN model and the runtime overhead.

data-parallel training↗
DOE OSTI2024

Validation of Phasor-Domain Transmission and Distribution Co-simulation Against Electromagnetic Transient Simulation

The rapid deployment of renewable energy resources has led to the widespread use of power electronics in modern power systems. As these systems transition from being dominated by large synchronous machines to increasingly incorporating inverter-based resources (IBRs), traditional methods are becoming inadequate. Addressing this challenge, this paper introduces a scalable phasor-domain T\&D co-simulation framework based on open-source software. It focuses on the framework's validation against the PSCAD Electromagnetic Transient (EMT) analysis tool. The validation results demonstrate the framework's high-fidelity and a computational time speed-up of 60 to 100 times, marking a pioneering validation effort in T\&D co-simulation research.

Inverter-based resources, co-simulation, Electroma↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2024

Machine learning-enhanced model-based scenario optimization for DIII-D

Abstract Scenario development in tokamaks is an open area of investigation that can be approached in a variety of different ways. Experimental trial and error has been the traditional method, but this required a massive amount of experimental time and resources. As high fidelity predictive models have become available, offline development and testing of proposed scenarios has become an option to reduce the required experimental resources. The use of predictive models also offers the possibility of using a numerical optimization process to find the controllable inputs that most closely achieve the desired plasma state. However, this type of optimization can require as many as hundreds or thousands of predictive simulation cases to converge to a solution; many of the commonly used high fidelity models have high computational burdens, so it is only reasonable to run a handful of predictive simulations. In order to make use of numerical optimization approaches, a compromise needs to be found between model fidelity and computational burden. This compromise can be achieved using neural networks surrogates of high fidelity models that retain nearly the same level of accuracy as the models they are trained to replicate while reducing the computation time by orders of magnitude. In this work, a model-based numerical optimization tool for scenario development is described. The predictive model used by the optimizer includes neural network surrogate models integrated into the fast Control-Oriented Transport simulation framework. This optimization scheme is able to converge to the optimal values of the controllable inputs that produce the target plasma scenario by running thousands of predictive simulations in under an hour without sacrificing too much prediction accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2021

ATM TestBed 2021 Simulating & Testing for the Future of Flight

TestBed is a NASA facility that not only connects geographically distributed tools without having to worry about obsolescence, but it is also a comprehensive one-stop-access simulation framework that allows researchers to develop and test solutions to current and future challenges more quickly by addressing development pain points, while also facilitating the connection of simulators and new tools to a variety of organizations, allowing for faster testing and development. Specifically, TestBed enables one to better characterize the impact of a new technology under development and to communicate its impact to stakeholders.

Air Traffic Management↗
NASA NTRSDate not supplied

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗
DOE OSTI2020

Validation of finite element analysis strategy to investigate acoustic levitation in a two-axis acoustic levitator

A two-axis acoustic levitator can be used to generate a standing pressure wave capable of levitating solid and liquid particles at appropriate input conditions. This work proposes a simulation framework to investigate the two-axis levitation particle stability using a commercial, computational fluid dynamics software based on the harmonic solution to the acoustic wave equation. The simulation produced predictions of the standing wave that include a strong "+" shaped pattern of nodes and anti-nodes that are aligned with the levitator axes. To verify the simulation, a levitator was built and used to generate the standing wave. The field was probed with a microphone and a motorized-scanning system. After scaling the simulated pressure to the measured pressure, the magnitudes of the sound pressure level at corresponding high-pressure locations were different by no more than 5%. This is the first time a measurement of a two-axis levitator standing pressure wave has been presented and shown to verify simulations. Furthermore, as an additional verification, the authors consulted high speed camera measurements of a reference-levitator transducer, which was found to have a maximum peak-to-peak displacement of 50 +/- 5 mu m. The reference-levitator is known to levitate water at 160 dB. The system for this work was simulated to match the operation of the reference-levitator so that it produced sound pressure levels of 160 dB. This pressure was achieved when the transducer maximum peak-to-peak displacement was 50.8 mu m. The agreement between the two levitators' displacements provides good justification that the modeling approach presented here produces reliable results.

2 axis levitator↗
DOE OSTI2024

Resolved photons in S HERPA

We present the first complete simulation framework, in the SHERPA event generator, for resolved photon interactions at next-to leading order accuracy. It includes photon spectra obtained through the equivalent-photon approximation, parton distribution functions to parametrize the hadronic structure of quasi-real photons, the matching of the parton shower to next-to leading order QCD calculations for resolved photon cross sections, and the modelling of multiple-parton interactions. We validate our framework against a wide range of photo-production data from LEP and HERPA experiments, observing good overall agreement. We identify important future steps relevant for high-quality simulations at the planned Electron–Ion Collider.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Situational Awareness of Grid Anomalies (SAGA)

The modern power industry becomes more vulnerable to cyber events due to the growing interconnectivity, interdependence, and complexity of the electric power grid. High-fidelity modeling and simulation tools that support the preventative risk analysis on potential cyber-relevant events is essential for ensuring the situational awareness of the system operator as it provides an inexpensive and risk-free environment to test the system responses under various cyber-relevant events and hereby can support research on cyber anomaly detection, optimal protective resource allocation, and mitigation measures. In this webinar, we will share NREL's cybersecurity research capabilities by highlighting the development of a scalable cyber-physical event test bed and demonstration with real hardware in the loop. The developed cyber-physical event test bed is backboned by an integrated transmission, distribution, and communication dynamic co-simulation framework and a plug-and-play cyber event generation module. It is designed to be modular and compatible with parallel computing, and thereby supports large-scale system simulations at an affordable computation cost. The test bed can capture millisecond-to-minutes dynamic frequency and voltage responses under cyber events from the bulk transmission system to the active distribution systems and distributed energy resources at the grid edge.

co-simulation↗
DOE OSTI2022

Benchmarking and Exploring Parameter Space of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation

High intensity proton pulses strike the Spallation Neutron Source (SNS)’s mercury target to provide bright neutron beams. These strikes deposit extensive energy into the mercury and its steel vessel. Prediction of the resultant loading on the target is difficult when helium gas is intentionally injected into the mercury to reduce the loading and to mitigate the pitting damage on the vessel. 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. We present a study comparing the measured target strains in the SNS target station with the simulation results of the solid mechanics simulation framework. We investigate a wide range of various physical model parameters, including the number of bubble families, bubble size distribution, viscosity, surface tension, etc. to understand their impact on simulation accuracy. Our initial findings reveal that using 8-10 bubble families in the model renders a simulation strain envelope that covers the experimental ones. Further optimization studies are planned to predict the strain response more accurately.

Lin, Lianshan↗
DOE OSTI2022

User-Oriented Improvements in the MOOSE framework in support of Multiphysics Simulation

The MOOSE Framework is a foundational capability used by NEAMS to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms including optimization, improved user experience, streamlined APIs, parallelism, and new capability. The work transcribed in the report was in direct support of the simulation tools and is already deployed or will be deployed in the coming months. The capabilities implemented were, in the same order as this report, chainable execution objects or executors, support for transfers between applications at the same level in a coupling scheme, support for boundary/subdomain restricted transfers, support for transfers between applications with different coordinate or unit systems, support for MOOSE applications in the NEAMS workbench, deployment of MOOSE application of the INL HPC OnDemand platform, addition of a triangular meshing library in libMesh and increased support of face variables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Modeling transient edge plasma transport with dynamic recycling

The work presents numerical simulation studies of the role that dynamic plasma recycling on the main wall and divertor target surfaces plays in transient edge plasma transport phenomena, such as edge localized modes (ELMs). The studies are performed by coupling the edge plasma transport code UEDGE [Rognlien et al., J. Nucl. Mater. 196–198, 347 (1992)] and the wall reaction–diffusion transport code FACE [Smirnov et al., Fusion Sci. Technol. 71, 75 (2017)]. The two-dimensional, time-dependent, two-way coupling of the codes, in a realistic tokamak geometry, is accomplished using the Integrated Plasma Simulator framework [Elwasif et al., in 18th Euromicro Conference on Parallel, Distributed and Network-Based Processing (PDP 2010), Pisa, Italy (IEEE, 2010), pp. 419–427] for all modeled material plasma boundaries. The simulations show that dynamic plasma recycling has substantially different characteristics on the main wall and on the divertor plates. It is demonstrated that during an ELM cycle the outer wall can dynamically absorb and release a number of particles comparable to that expelled by the ELM from the core plasma, by far exceeding the dynamic retention capacity of the divertor surfaces. The resulting evolution of the edge and divertor plasma conditions during an ELM cycle is analyzed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A-LEAF

A-LEAF is an electricity market simulation framework. It includes models for short-term market operations and long-term investment planning of generation, storage, and transmission. Model formulations include least cost and two-stage market equilibrium. Simulations can be flexibly structured over one or more years, including options for periodic samples or jumping to a single future year. Years can be simulated as 365 consecutive days at hourly or 5-minute sample rates, or they can be subsampled using a representative day group selection algorithm.

MANN, WILLIAM↗
NASA NTRSDate not supplied

Assessing the feasibility of a spaceborne 3D lightning observing concept

The distribution of electrical charge in thunderclouds results from thermodynamic, microphysical, and kinematic processes, which also modulate thunderstorm evolution. It is no surprise that the connection between lightning and these physical processes is so strong that the increase and vertical growth of lightning activity closely follows the vertical growth of the thundercloud, but unraveling these connections is not trivial and requires observations of the three-dimensional (3D) structure of electrical activity in a cloud. Ground-based 3D lightning mapping networks give excellent 3D flash-level detail but are limited to regional coverage. Satellite-based optical lightning mappers give excellent global coverage but are largely limited to 2D summaries of flash rate and radiant intensity, albeit new flash products and stereographic techniques are chipping away this limitation. New observing strategies are needed to expand and diversify the corpus of 3D lightning datasets and motivate studies that unravel connections lightning has with these key physical processes and the surrounding environment. This study examines the feasibility of using a distributed network of orbing satellites with VHF-based lightning detectors to obtain global maps of 3D lightning activity and assess efficacy of this approach for use in a new, small satellite mission concept called CubeSpark. CubeSpark combines new VHF and high-resolution, bispectral optical instruments on a constellation of low-Earth orbiting (LEO) satellites to globally map the 3D electrical structure of thunderstorms and study how it relates to thunderstorm evolution, extreme weather, nitrogen oxide production and distribution, upper atmospheric electrical phenomena, and how 3D flash observations can complement existing satellite-based lightning mappers and improve decision support tools. To locate lightning discharges, CubeSpark seeks to use the VHF time-of-arrival technique, similar to ground-based total lightning mapping networks. The vertical location accuracy of these satellite retrievals will be of poorer quality compared to a ground-based network, which has non-trivial implications for lightning flash reconstruction and lightning-based interpretations of deep convection. We adapt a Lightning Mapping Array (LMA) simulation framework to an orbiting network and use it to address feasibility of 3D lightning detection from space with particular attention to location accuracy of VHF detections of lightning in the vertical. These simulations inform a constellation design study that defines a realistic orbital configuration and depicts the global coverage for CubeSpark. Results indicate that a 3D location accuracy of <1-2 km for each dimension can be achieved across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high- latitudes.

Lightning↗
DOE OSTI2022

Circular Economy Modeling Efforts at NREL: Circular Economy Lifecycle Analysis and Visualization (CELAVI) and the Circular Economy Agent-Based Model (ABM)

Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.

circular economy↗
DOE OSTI2025

Influence of Pore Water on the Fracture of Silica Sand at Particle Scale

The fracture of particles has a significant influence on the engineering behavior of granular materials. There are no reported conclusive answers in the literature to explain the influence of pore water on the fracture of sand, gravel, railroad ballast rock, aggregates, rockfill, and so on. Here, in this paper, two novel techniques were adopted to investigate the influence of pore water on the fracture of natural silica sand at the particle scale. The three-dimensional (3D) synchrotron microcomputed tomography (SMT) imaging technique was used to acquire and analyze multiple 3D images of specimens composed of wetted silica sand that were subjected to confined one-dimensional (1D) compression loading up to the fracture stage. A few representative particles were identified and digitally separated from the liquid water and gas phases. The 3D SMT images offer clear experimental evidence of the phase transition of water from liquid to gas within the opening cracks. In addition, a computational fluid dynamics numerical simulation framework for water flow into an opening crack was adopted and the results show that the fast opening of the crack induced cavitation, water phase transition, and water hammer effects. The results of the numerical simulations agree with the confined 1D compression experiments where the onset of the bubbles (gas phase) within the crack is mainly generated during the secondary cavitation stage, and the generated bubble near the crack mouth opening resulted from the primary cavitation, which was directly caused by the crack expansion. The results reported in this paper present a new cavitation phenomenon that occurs during particle fracture, which offers a physics-based explanation of why water-wetted sand fractures at smaller stresses than dry and can pave the way for more in-depth future studies on the fracture of water-wetted sand.

cavitation↗