Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “event driven”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Irradiation-Induced Structural Disorder and Its Influence on the Mechanical Response of Polycrystalline MoS2

Molybdenum disulfide (MoS2) thin films are widely used as dry-film lubricants and protective coatings in aerospace and other radiation-exposed environments. Conventional synthesis routes produce polycrystalline films whose grain boundaries and other native defects cause their mechanical and tribological behavior to differ substantially from that of ideal single crystals. Under irradiation, these films progressively evolve from polycrystalline structures, composed of layered MoS2 grains, into highly disordered and eventually amorphous structures, altering both their tribological performance and mechanical integrity. Here, we employ reactive atomistic simulations to investigate irradiation-driven structural evolution in bulk polycrystalline MoS2. Using controlled primary knock-on atom (PKA) events, we characterize the progressive transition from a polycrystalline microstructure to an amorphous network by tracking defect accumulation and structural disorder. We then establish how this transition modifies the dominant deformation mechanisms and the temperature-dependent tensile response. Specifically, irradiation suppresses interlayer sliding and delamination, mechanisms which facilitate the deformation of the pristine polycrystal, resulting in defect-induced hardening. Broadly, our results establish direct process–structure–property relationships linking irradiation-induced defect accumulation, microstructural evolution, deformation mechanisms, and mechanical behavior, providing an atomistic framework for understanding the structural integrity and long-term reliability of irradiated MoS2 coatings.

Moore, Daniel [Sandia National Laboratories (SNL)]↗
DOE OSTI2025

Model-free estimation of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Abstract An accurate description of information is relevant for a range of problems in atomistic machine learning (ML), such as crafting training sets, performing uncertainty quantification (UQ), or extracting physical insights from large datasets. However, atomistic ML often relies on unsupervised learning or model predictions to analyze information contents from simulation or training data. Here, we introduce a theoretical framework that provides a rigorous, model-free tool to quantify information contents in atomistic simulations. We demonstrate that the information entropy of a distribution of atom-centered environments explains known heuristics in ML potential developments, from training set sizes to dataset optimality. Using this tool, we propose a model-free UQ method that reliably predicts epistemic uncertainty and detects out-of-distribution samples, including rare events in systems such as nucleation. This method provides a general tool for data-driven atomistic modeling and combines efforts in ML, simulations, and physical explainability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The ultrafast pixel array camera system and its applications in high energy density physics

Diagnostics in high energy density physics, shock physics, and related fields are primarily driven by a need to record rapidly time-evolving signals in single-shot events. These measurements are often limited by channel count and signal degradation issues on cable links between the detector and digitizer. Here we present the Ultrafast Pixel Array Camera (UPAC), a compact and flexible detector readout system with 32 waveform-recording channels at up to 10 Gsample/s and 1.8 GHz analog bandwidth. The compact footprint allows the UPAC to be directly embedded in the detector environment. A key enabling technology is the PSEC4A chip, an eight-channel switch-capacitor array sampling device with up to 1056 samples/channel. The UPAC system includes a high-density input connector that can plug directly into an application-specific detector board, programmable control, and serial readout, with less than 5 W of power consumption in full operation. We present the UPAC design and characterization, including a measured timing resolution of ~20 ps or better on acquisitions of sub-nanosecond pulses with minimal system calibrations. Example applications of the UPAC are also shown to demonstrate operation of a solid-state streak camera, an ultrafast imaging array, and a neutron time-of-flight spectrometer.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Particle simulations of driven collisionless magnetic reconnection at the dayside magnetopause

Particle simulations (including both ions and electrons) of the driven collisionless magnetic reconnection process at the earth's dayside magnetopause were carried out using a specially developed two-and-one-half-dimensional electromagnetic particle code with a driven inflow boundary and an open outflow boundary. The simulations were used to examine many features associated with the dayside magnetic reconnection process, including the acceleration and heating of particles and the generation of energetic particles and particle heat flux. In addition, the fluctuating electromagnetic field associated with a driven collisionless magnetic reconnection was examined and compared with the satellite observations of flux transfer events at the day-side magnetopause.

Ding, D. Q.↗
NASA NTRS1992

Are coronal type II shocks piston driven?

Flare blast waves and shocks piston driven by coronal mass ejections (CMEs) have been proposed to be responsible for generating type II radio bursts in the solar corona. The idea for piston-driven shocks came primarily from temporal association of shocks and CMEs. Our compilation of CME events with simultaneous radio observations with positional information supports idea of flare blast waves.

Gopalswamy, N.↗
NASA NTRS2000

Qualitative Discovery in Medical Databases

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

Maluf, David A.↗
NASA NTRS2002

Magnetic TRAnsition Region Probe (MTRAP)

MTRAP (Magnetic Transition Region Probe) will reveal the fine-scale physical processes in the Sun's magnetic transition region, the complex layer from the upper photosphere to the upper chromosphere/lower transition region. In the magnetic transition region plasma forces and magnetic forces are of comparable strength, which results in complex interplay of the two, which interplay governs the coupling of the convectively-driven deeper layers to the magnetically-driven upper transition region and inner corona. The fine-scale magnetic structure, processes, and events in the magnetic transition region are key to the genesis of the Sun's entire hot, dynamic outer atmosphere and to the initiation of large eruptive events. MTRAP will be a single spacecraft in Sun-synchronous Earth orbit. Because MTRAP will probe and measure the 3-D structure and dynamics of the magnetic field and plasma in the chromosphere and transition region with unprecedented resolution, the required telescope size and telemetry rates dictate that MTRAP be in Earth orbit, not in deep space. The observations will feature visible and infrared maps of vector magnetic and velocity fields in the magnetic transition region and photosphere. These will have large field of view (greater than 100,000 km), high resolution (greater than 100 km), and high sensitivity (greater than 30 G in transverse field). These observations of the lower atmosphere will be complemented by UV maps of the structure, velocity, and magnetic field (including the full vector field if technically feasible) higher up, in the upper chromosphere and lower transition region. MTRAP will also have an EUV imaging spectrograph observing coronal structure and dynamics in the same field of view with comparable resolution. Specific phenomena to be analyzed include spicules, bright points, jets, the base of plumes, and the triggering of eruptive flares and coronal mass ejections. Additional information is included in the original extended abstract.

Moore, R. L.↗
DOE OSTI2022

Advancing Clean Energy Equity

This year’s Financial Innovations Roundtable (June 16-17, 2022) focused on advancing clean energy equity and was co-hosted by the University of New Hampshire's Carsey School of Public Policy and the Federal Reserve Bank of New York. Clean energy technologies are better than ever, with costs continuing to decline. Yet the low-income and under-resourced communities – particularly communities of color, Native communities, and other traditionally marginalized populations – that are disproportionately impacted by climate and severe weather-related events lag in clean energy investments. Community Development Financial Institutions (CDFIs) have a long track record of providing access to capital to low- and moderate-income communities nationwide. Green Banks, established at state and local levels, use innovative financing to attract private capital and incentivize investments in clean and renewable energy. Together, the nation's network of more than 1,300 CDFIs and 21 Green Banks have the financing expertise and deep market understanding and relationships to finance a transition to clean energy. This event explored how Green Banks and CDFIs can funnel creditworthy projects to market and efficiently raise capital for them. Building on the Carsey School White Paper, Clean Energy Project Development for Low-Income Communities: Strengthening the Ecosystem for Delivering Solar Energy and Deep Efficiency Retrofits (Hangen, 2022), the FIR sought to identify options and create opportunities for Green Banks, CDFIs, and impact investors to collaborate in offering a range of products, approaches, and tools to better serve communities and individuals who have thus far been left out of the transition to clean energy. The event had 101 participants from a variety of sectors including CDFIs, Green Banks, mission-driven clean energy organizations, government agencies, banks, and impact investment professionals.

14 SOLAR ENERGY↗
DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Temporal sequence transformer to advance long-term streamflow prediction

Accurate streamflow prediction is crucial for understanding climate change impacts on water resources and for effective management of extreme hydrological events. While Long Short-Term Memory (LSTM) networks have been the dominant data-driven approach for streamflow forecasting, recent advancements in transformer architectures for time series tasks have shown promise in outperforming traditional LSTM models. This study introduces a transformer-based model that integrates historical streamflow data with climatic variables to enhance streamflow prediction accuracy. We evaluated our transformer model against a benchmark LSTM across five diverse basins in the United States. Results demonstrate that the transformer architecture consistently outperforms the LSTM model across all evaluation metrics, highlighting its potential as a more effective tool for hydrological forecasting. This research contributes to the ongoing development of advanced AI techniques for improved water resource management and climate change adaptation strategies.

Singh, Ruhaan [Farragut High School]↗
NASA NTRS1989

Physical phenomena and the microgravity response

The living biological cell is not a sack of Newtonian fluid containing systems of chemical reactions at equilibrium. It is a kinetically driven system, not a thermodynamically driven system. While the cell as a whole might be considered isothermal, at the scale of individual macromolecular events there is heat generated, and presumably sharp thermal gradients exist at the submicron level. Basic physical phenomena to be considered when exploring the cell's response to inertial acceleration include particle sedimentation, solutal convection, motility electrokinetics, cytoskeletal work, and hydrostatic pressure. Protein crystal growth experiments, for example, illustrate the profound effects of convection currents on macromolecular assembly. Reaction kinetics in the cell vary all the way from diffusion-limited to life-time limited. Transport processes vary from free diffusion, to facilitated and active transmembrane transport, to contractile-protein-driven motility, to crystalline immobilization. At least four physical states of matter exist in the cell: aqueous, non-aqueous, immiscible-aqueous, and solid. Levels of order vary from crystalline to free solution. The relative volumes of these states profoundly influence the cell's response to inertial acceleration. Such subcellular phenomena as stretch-receptor activation, microtubule re-assembly, synaptic junction formation, chemotactic receptor activation, and statolith sedimentation were studied recently with respect to both their basic mechanisms and their responsiveness to inertial acceleration. From such studies a widespread role of cytoskeletal organization is becoming apparent.

Todd, Paul↗
DOE OSTI2026

A Systematic Review on Coordinated Restoration Strategies for Power Distribution Grids

Power distribution grids are increasingly exposed to High-Impact Low-Probability (HILP) events, which cause widespread disruptions with severe societal and economic impacts. The growing complexity of modern grids, driven by the integration of distributed energy resources and smart grid technologies, has introduced new challenges to effective service restoration. While significant research has explored individual restoration strategies, such as network reconfiguration and microgrid formation, limited attention has been given to methods in which they can be effectively coordinated. Furthermore, the absence of systematic review papers addressing this issue hampers the development of cohesive restoration frameworks capable of addressing the operational complexities of modern grids. This paper presents a systematic review synthesizing existing knowledge on power grid restoration, identifying key limitations, and highlighting opportunities for coordinated strategies. By addressing research gaps and emphasizing the integration of diverse approaches, this study provides critical insights for advancing grid resiliency and recovery, offering a foundation for future research and practical applications in the face of HILP events.

Systematic review↗
DOE OSTI2025

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗
NASA NTRS1982

Absence of silicic volcanism on Mars - Implications for crustal composition and volatile abundance

It is believed that explosive basic to ultrabasic eruptions may be responsible for small cinder conelike features on Mars and perhaps for the ancient flank-scoured paterae. Eruptions of this type may have been driven by near-surface water/ice-magma interactions or volatile rich magmas. Noting that the paterae represent a unique style of volcanism that stopped approximately 2 b.y. ago, it is suggested that the volatiles associated with these features were derived from mantle sources and that the cessation of patera formation may coincide with the termination of the period of maximum planetary degassing. Since approximately 2 b.y. ago volcanism has been dominantly effusive, except for such minor explosive ash events as those that blanketed part of the summit of Hecates Tholus. It is proposed that such eruptions were driven by volatiles generated by differentiation of a magma chamber, similar to Icelandic explosive eruptions.

Francis, P. W.↗
DOE OSTI2022

Enhanced Component Performance Study: Motor-Driven Pumps 1998-2020

This report presents an enhanced performance evaluation of motor-driven pumps (MDPs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MDP failure modes considered for standby systems are fail to start (FTS), fail to run (FTR) for one hour of operation (FTR≤1H), FTR after one hour of operation (FTR>1H), and for normally running systems FTS and FTR. An eight-hour unreliability estimate is also calculated and trended. The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP frequency of start demands (demands per reactor year) • Standby MDP frequency of FTR≤1H hours (hours per reactor year) • Standby MDP frequency of FTR>1H hours • Normally running MDP frequency of run hours. The following decreasing trends were identified for MDPs for the most recent 10-year period: • Standby MDP FTR≤1H failure probability • Normally running MDP FTR failure rate • Standby MDP unavailability • Normally running MDP total unreliability (8-hour mission) • Standby MDP frequency of FTR≤1H events (failures per reactor year) • Normally running MDP frequency of FTR events.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Software predicts disaster-driven grid failures

A new, free, open-source software reliably predicts how damage from hurricanes, ice storms, earthquakes, and other extreme events will restrict power delivery from utility grids. The Severe Contingency Solver for Electric Power Transmission is the only software available—commercially or open-source—that reliably supports analysis of extreme events that cause widespread damage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

EMIC Wave-Driven Bounce Resonance Scattering of Energetic Electrons in the Inner Magnetosphere

While electromagnetic ion cyclotron (EMIC) waves have been long studied as a scattering mechanism for ultrarelativistic (megaelectron volt) electrons via cyclotron‐resonant interactions, these waves are also of the right frequency to resonate with the bounce motion of lower‐energy (approximately tens to hundreds of kiloelectron volts) electrons. Here we investigate the effectiveness of this bounce resonance interaction to better determine the effects of EMIC waves on subrelativistic electron populations in Earth's inner magnetosphere. Using wave and plasma parameters directly measured by the Van Allen Probes, we estimate bounce resonance diffusion coefficients for four different events, illustrative of wave and plasma parameters to be encountered in the inner magnetosphere. The range of electron energies and pitch angles affected is examined to better assess the realistic effects of EMIC‐driven bounce resonance on energetic electron populations based on actual, locally observed event‐based parameters. Significant local diffusion coefficients (~ > 10(exp −6) s(exp −1)) for 50‐ to 100‐keV electrons are achieved for both H+ band wave events as well as He+ band, with diffusion coefficients peaking for near‐90° pitch angles but remaining elevated for intermediate ones as well. Diffusion coefficients for higher‐energy 200‐keV electrons are typically multiple orders of magnitude lower (ranging from 10(exp −11) to 10(exp −6) s(exp −1)) and often peak at lower pitch angles (~20–30°). These results suggest that both H+ and He+ band EMIC waves can play a role in shaping lower‐energy electron dynamics via bounce‐resonant interactions, in addition to their role in relativistic electron loss via cyclotron resonance.

Blum, L. W.↗
DOE OSTI2026

Exploring the connection between compact object mergers and fast X-ray transients

Context. The connection between compact object mergers and some extragalactic fast X-ray transients (FXRTs) has long been hypothesised but never ultimately established. Aims. In this work, we investigate two FXRTs, the LEIA X-ray Transient LXT 240402A and the Einstein Probe EP 250207b, whose precise positions lie close to nearby (z ≲ 0.1) quiescent galaxies with a negligible probability of chance coincidence, identifying them as particularly promising cases of merger-driven explosions in the local Universe. Methods. We used Chandra to derive accurate localisations for both events and secure otherwise ambiguous associations with their optical counterparts. Deep optical and near-infrared observations with VLT, GTC, and LBT were performed to characterise the surrounding environment and search for kilonova emission, the hallmark of neutron star mergers. Complementary early-time X-ray monitoring with Swift and Einstein Probe was used to constrain the non-thermal afterglow. Results. We find that both FXRTs remain compatible with a compact binary merger progenitor, which produced low-mass ejecta and kilonova emission subdominant to the afterglow. However, alternative explanations such as a distant (z ≳ 1) core-collapse supernova cannot be conclusively ruled out.

79 ASTRONOMY AND ASTROPHYSICS↗