Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Event capturing”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Heavy Elements and Electromagnetic Transients from Neutron Star Mergers

Compact binary mergers involving neutron stars can eject a fraction of their mass to space. Being extremely neutron rich, this material undergoes rapid neutron capture nucleosynthesis, and the resulting radioactivity powers fast, short-lived electromagnetic transients known as kilonova or macronova. Such transients are exciting probes of the most extreme physical conditions and their observation signals the enrichment of the Universe with heavy elements. Here the current understanding of the mass ejection mechanisms, the properties of the ejecta, and the resulting radioactive transients are reviewed. The first well-observed event in the aftermath of GW170817 delivered a wealth of insights, but much of today's picture of such events is still based on a patchwork of theoretical studies. Apart from summarizing the current understanding, questions where no consensus has been reached yet are also pointed out, and possible directions for the future research are sketched. In an appendix, a publicly available heating rate library based on the WinNet nuclear reaction network is described, and a simple fit formula to alleviate the implementation in hydrodynamic simulations is provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

3D printing of void-free glass monoliths: rheological and geometric considerations

Direct ink writing (DIW) is a versatile additive manufacturing technique capable of printing 3D architectures from a broad range of materials. The key advantage of DIW is the ability to spatially control both the architecture and the composition of the printed part, which enables the production of components with previously unachievable combinations of functionalities. One emergent application space for DIW has been in additively manufactured glass optics, where a “green body” is patterned layer-by-layer by extruding a silica-based slurry through a microfluidic nozzle and then thermally consolidated to transparent glass. A critical aspect of the process is ensuring that the printed part is completely free of voids that can occur in the interstitial spaces between the extruded filaments. This outcome is governed by the interplay between ink rheology and strains imposed by the printing process and geometric packing of the filaments. Here, we explore the strain- and rate-dependent deformation events in the DIW process to determine conditions that enable the printing of void-free monoliths without sacrificing shape fidelity. We focus on yield stress fluids consisting of fumed silica nanoparticles dispersed in organic solvents at varied volume fractions to control the rheological properties. We investigate the printability of these ink materials as a function of print process variables and devise the appropriate dimensionless parameters that capture the geometry-dependent and rate-dependent effects on the deformation of the extruded ink. Lastly, we use these scaling arguments to construct a phase diagram for void-free monolith printability.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mapping Philadelphia's Floodscape: A 35‐Year Analysis of Coastal Urban Flood Hazards and Drivers

Low-lying coastal urban cities face significant flooding risks from river flooding (fluvial), storm surges and high tides (coastal), and intense local rainfall (pluvial). Accurately assessing these hazards requires modeling frameworks capable of capturing both the individual and combined effects of multiple flood drivers, as well as the diversity of flood scenarios that can arise from their interactions. In this study, we implemented a physics-based, high-resolution modeling approach to assess flood hazards in Philadelphia, PA, a coastal city exemplifying multi-driver flood risks over multiple decades (1985–2019), by simulating a wide range of flood events at a 10-m resolution. By integrating watershed, coastal, and urban flood models, we explicitly resolved the interaction between fluvial, pluvial, and coastal processes across the city. From these simulations, we identified flood hazard hotspots and systematically attributed the primary drivers of flooding for each event. The results suggested that 44% of Philadelphia's flood events were compound floods, primarily driven by fluvial-surge and fluvial-pluvial combinations. Notably, 77% of these events involved fluvial flooding, either as a single flood driver or in combination with other drivers, underscoring the dominant role of riverine processes in the city's flood hazard. Overall, this study demonstrates the value of a comprehensive, process-based approach for urban flood hazard assessment and highlights the importance of considering the full spectrum of flood scenarios to inform targeted and adaptive flood management strategies in coastal cities.

Compound flooding↗
DOE OSTI2024

Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0

Abstract. Using the regionally refined mesh (RRM) configuration of the US Department of Energy's Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM), we simulate and evaluate four meteorologically distinct atmospheric river events over California. We test five different RRM configurations, each differing in terms of the areal extent of the refined mesh and the resolution (ranging from 800 m to 3.25 km). We find that SCREAM RRM generally has a good representation of the AR-generated precipitation in CA, even for the control simulation which has a very small 3 km refined patch, and is able to capture the fine-scale regional distributions that are controlled largely by the fine-scale topography of the state. It is found that SCREAM generally has a wet bias over topography, most prominently over the Sierra Nevada mountain range, with a corresponding dry bias on the lee side. We find that refining the resolution beyond 3 km (specifically 1.6 km and 800 m) has virtually no benefit towards reducing systematic precipitation biases but that improvements can be found when increasing the areal extent of the upstream refined mesh. However, these improvements are relatively modest and only realized if the size of the refined mesh is expanded to the scale where employing RRM no longer achieves the substantial cost benefit it was intended for.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Populating the Hydrogen Component Reliability Database (HYCRED) with Incident Data from Hydrogen Dispensing

Safety, risk, and reliability issues are vital to ensure the continuous and profitable operation of hydrogen technologies. Quantitative risk assessment (QRA) has been used to enable the safe deployment of engineering systems, especially hydrogen fueling stations. However, QRA studies require reliability data which are essential to collect to make the studies as realistic and relevant as possible. These data are currently lacking and data from other industries, such as oil and gas, are used in hydrogen system QRAs. This may lead to inaccurate results since hydrogen fueling stations have differences in physical properties, system design, and operational parameters when compared to other fueling stations, thus necessitating new data sources are necessary to capture the effects of these differences. To address this gap, we developed a structure for a hydrogen component reliability database, (HyCReD) [1], which could be used to generate reliability data to be used in QRA studies. In this paper, we demonstrate populating the HyCReD database with information extracted from new narrative reports on hydrogen fueling station incidents, specifically focused on the dispensing processes. We analyze five new events and demonstrate the feasibility of populating the database and types of meaningful insights that can be obtained at this stage.

component reliability↗
DOE OSTI2024

The BIRDIES Experiment: Measuring Beryllium Isotopes to Resolve Dynamics in the Stratosphere

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM.

58 GEOSCIENCES↗
DOE OSTI2026

Data Driven Approach to Public Opinion Mining on Autonomous Vehicles: Sentiment Analysis of Social Media Comments Using Large Language Models

In the realm of online identity, social media has emerged as a rich and dynamic source of user-generated content, making it an invaluable resource for understanding public sentiment on a wide range of topics. Individuals often share their raw emotions and candid opinions on these platforms without fear of judgment or backlash. In this study, we conduct a sentiment analysis on user comments collected from various online platforms, with a specific focus on discussions surrounding autonomous vehicles. Leveraging the capabilities of large language models (LLMs), we classify each comment into one of five sentiment categories: Very Negative, Negative, Neutral, Positive, and Very Positive. Our approach demonstrates the effectiveness of LLMs in capturing nuanced contextual sentiment, offering a scalable and state-of-the-art alternative to traditional manual annotation methods. The results reveal key trends and insights into public perception, enabling a deeper understanding of how autonomous vehicle technologies are received by the online community. Our findings underscore the dynamic nature of public sentiment, which is shaped not only by advances in autonomous vehicle technology but also by contextual events such as regulatory developments, political adjustment and safety incidents.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Study of Microphonic Effects on the C100 Cryomodule for High Energy Electron Beam Accelerators

The Continuous Electron Beam Accelerator Facility (CEBAF) at Thomas Jefferson National Laboratory (JLab) is a particle accelerator which can accelerate an electron beam to relativistic speeds and apply the beam onto target samples. The C100 superconducting radio frequency (SRF) cavity is the primary accelerating structure of the C100 cryomodule, one of the many cryomodules which compose the CEBAF linear accelerator. SRF cavities are particularly sensitive to internal and external vibrations that can result in a phenomenon called microphonics which degrade the operational stability of a cryomodule. The purpose of this thesis is to investigate the significance of mechanical disturbances on the electromagnetic resonant frequency of a C100 SRF cavity. Knowledge of the mechanical resonance of the cavities and cryomodule sheds light into how these disturbances are most easily realized as deformation which causes radio frequency (RF) detuning. Three studies were conducted: the development and hammer test calibration of a Finite Element Analysis (FEA) model of a C100 cavity, the development and hammer test calibration of an FEA model of a C100 cavity string, and the hammer test of the C100-10R cryomodule at the Cryomodule Test Facility (CMTF). The cavity FEA model was found to accurately predict two modes found in two real cavities in a simply supported configuration. The cavity string FEA model leveraged the calibrated cavity FEA model but was not found to accurately predict the modal behavior of a real cavity string. Even so, the modal behavior of the cavity string inside the C100-10R cryomodule was captured during a hammer test while it was partially assembled. Finally, the C100-10R cryomodule was placed in the CMTF to study RF detuning. The RF detuning spectra during hammer hits and background noise was captured. The results of the hammer testing indicate two strong peaks at low frequencies (9-10 Hz and 22-23 Hz). These two frequencies were found to be nearly coincident to four instances of mechanical resonance found during the hammer testing done on the partially-assembled C100-10R. Because of this, these two modes are believed to contribute to RF detuning of the cryomodule. This test event also included the testing of the effectiveness of a configuration of BNNT canisters designed to act as dampers. While these tests show promising results, the lurking variables render these tests somewhat inconclusive.

Hull, Caleb James↗
DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multitask Machine Learning of Collective Variables for Enhanced Sampling of Rare Events

Computing accurate reaction rates is a central challenge in computational chemistry and biology because of the high cost of free energy estimation with unbiased molecular dynamics. In this work, a data-driven machine learning algorithm is devised to learn collective variables with a multitask neural network, where a common upstream part reduces the high dimensionality of atomic configurations to a low dimensional latent space and separate downstream parts map the latent space to predictions of basin class labels and potential energies. Here, the resulting latent space is shown to be an effective low-dimensional representation, capturing the reaction progress and guiding effective umbrella sampling to obtain accurate free energy landscapes. This approach is successfully applied to model systems including a 5D Müller Brown model, a 5D three-well model, the alanine dipeptide in vacuum, and an Au(110) surface reconstruction unit reaction. It enables automated dimensionality reduction for energy controlled reactions in complex systems, offers a unified and data-efficient framework that can be trained with limited data, and outperforms single-task learning approaches, including autoencoders.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant

Radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant (FDNPP) have been steadily decreasing over the past eight years since the release of radioactive elements in March 2011. Currently, the radiation monitoring program is expected to transition to long-term monitoring after most of the remediation activities are completed. The main long-term monitoring objectives are to (1) confirm the continuing reduction of contaminant and hazard levels, (2) provide assurance for the public, (3) accumulate the basic datasets for scientific knowledge and future preparation, and (4) detect changes or anomalies in contaminant mobility (if they occur), or any unexpected processes or events. In this work, we have developed a methodology for optimizing the monitoring locations of radiation air dose-rate monitoring. Our approach consists of three steps in order to determine monitoring locations in a systematic manner: (1) prioritizing the critical locations, such as schools or regulatory requirement locations, (2) diversifying locations that cover the key environmental controls that are known to influence contaminant mobility and distributions, and (3) capturing the heterogeneity of radiation air-dose rates across the domain. Therefore, for the second step, we use a Gaussian mixture model to identify the representative locations among multiple environmental variables, such as elevation and land-cover types. For the third step, we use a Gaussian process model to capture and estimate the heterogeneity of air-dose rates across the domain. Employing an integrated dose-rate map derived from Bayesian geostatistical methods as a reference map, we distribute the monitoring locations in such a way as to capture the heterogeneity of the reference map. Our results have shown that this approach allows us to select monitoring locations in a systematic manner such that the heterogeneity of air dose rates is captured by the minimal number of monitoring locations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. Furthermore, this study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cloud, Aerosol, and Radiative Properties Over the Western North Atlantic Ocean

This study examines the atmospheric properties of weather states (WSs) derived from the International Satellite Cloud Climatology Project (ISCCP) over the Western North Atlantic Ocean. In particular, radiation and aerosol data corresponding to two sites in the study domain, Pennsylvania State University and Bermuda, were examined to characterize the atmospheric properties of the various satellite-derived WSs. At both sites, the fair weather WS was most prevalent, followed by the cirrus WS. Differences in the seasonality of the various WSs were observed at the two sites. Fractional sky cover and effective shortwave cloud transmissivity derived from ground-based radiation measurements were able to capture differences among the satellite-derived WSs. Speciated aerosol optical thicknesses (AOT) from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) were used to investigate potential differences in aerosol properties among the WSs. The clear sky WS exhibited below-average seasonal values of AOT at both sites year-round, as well as relatively high rates of occurrence with low AOT events. In addition, the clear sky WS showed above-average contributions from dust and black carbon to the total AOT year-round. Finally, transitions between various WSs were examined under low, high, and mid-range AOT conditions. The most common pathway was for the WSs to remain in the same state after a 3 hr interval. Some WSs, such as midlatitude storms, deep convection, middle top, and shallow cumulus, were more prevalent as ending states under high AOT conditions. This work motivates examining differences in aerosol properties between WSs in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thallium-208: A Beacon of In Situ Neutron Capture Nucleosynthesis

Here, we demonstrate that the well-known 2.6 MeV gamma-ray emission line from thallium-208 could serve as a real-time indicator of astrophysical heavy element production, with both rapid (r) and intermediate (i) neutron capture processes capable of its synthesis. We consider the r process in a Galactic neutron star merger and show Tl-208 to be detectable from ~12 hours to ~ten days, and again ~1–20 years postevent. Detection of Tl-208 represents the only identified prospect for a direct signal of lead production (implying gold synthesis), arguing for the importance of future MeV telescope missions which aim to detect Galactic events but may also be able to reach some nearby galaxies in the Local Group.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Illinois Compressed Air Energy Storage

Compressed Air Storage Energy (CAES) is one of the few mid- technology readiness level (TRL) energy storage technologies that can address the long-duration infrastructure needed for dealing with variable electric output from renewable energy sources and be reliable backup source for replacing natural gas during supply interruptions. In CAES the goal is to capture and store compressed air in subsurface sedimentary strata when off-peak power is available, or there is a need for grid balancing. The stored high-pressure air is returned to the surface and used to power turbines during reductions in either renewable energy or supply issues with fossil fuels. The Illinois CAES project evaluates the feasibility of capturing surplus electrical energy from renewable sources and off-peak energy at a fossil fuel power plant at the University of Illinois Urbana - Champaign (UIUC) campus. The UIUC Abbott Power Plant uses natural gas and coal to generate electricity (capacity: 35 MWe by coal and 49 MWe by NG). UIUC receives additional electricity from on campus solar farm, and off-campus wind farm. Also, UIUC offsets electricity usage by integrating geothermal energy systems into building heating Also, UIUC offsets steam, hot and chilled water usage by integrating geothermal energy systems into building heating and cooling systems. Furthermore, the two UIUC solar farms (Solar Farm 1 is 21 acres and Solar Farm 2 is 54 acres) to generate 4.68 megawatts (MW) and 12.1 MW, respectively. Campus receives 8.6% of the wind-generated electricity from the Rail Splitter Wind Farm. The project objectives were to design an integrated system to 1) capture surplus electrical energy from renewable sources and the Abbott Power Plant using a CAES system, 2) store both the compressed air and the thermal heat generated by compression in the subsurface as part of an adiabatic system, 3) simulate the movement of the air and heat in the subsurface, 4) recover the compressed air and stored thermal heat to rotate turbine generators during sustained interruption due to weather events or fossil fuel disruptions.

03 NATURAL GAS↗
DOE OSTI2024

Neutrino constraints on inelastic dark matter captured in the Sun

Abstract The flux of neutrinos from annihilation of gravitationally captured dark matter in the Sun has significant constraints from direct-detection experiments. However, these constraints are relaxed for inelastic dark matter as inelastic dark matter interactions generate less energetic nuclear recoils compared to elastic dark matter interactions. In this paper, we explore the possibility for large volume underground neutrino experiments to detect the neutrino flux from captured inelastic dark matter in the Sun. The neutrino spectrum has two components: a mono-energetic “spike” from pion and kaon decays at rest and a broad-spectrum “shoulder” from prompt primary meson decays. We focus on detecting the shoulder neutrinos from annihilation of hadrophilic inelastic dark matter with masses in the range 4–100 GeV and the mass splittings in up to 300 keV. We determine the event selection criterion for DUNE to identify GeV-scale muon neutrinos and anti-neutrinos originating from hadrophilic dark matter annihilation in the Sun, and forecast the sensitivity from contained events. We also map the current bounds from Super-Kamiokande and IceCube on elastic dark matter, as well as the projected limits from Hyper-Kamiokande, to the parameter space of inelastic dark matter. We find that there is a region of parameter space that these neutrino experiments are more sensitive to than the direct-detection experiments. For dark matter annihilation to heavy-quarks, the projected sensitivity of DUNE is weaker than current (future) Super (Hyper) Kamiokande experiments. However, for the light-quark channel, only the spike is observable and DUNE will be the most sensitive experiment.

Astronomy & Astrophysics↗
DOE OSTI2023

Detection efficiency measurement and operational tests of the X-Arapuca for the first module of DUNE far detector

The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for long-baseline neutrino oscillation studies, able to resolve the neutrino mass hierarchy and measure δ$_{CP}$. DUNE will also have sensitivity to supernova neutrinos and to processes beyond the Standard Model, such as nucleon decay searches. The Far Detector (FD) will consist of four liquid argon TPC (17.5 kt total mass) with systems for the detection of charge and scintillation light produced by an ionization event. The charge detection system permits both calorimetry and position determination. In addition, the photon-detection system (PDS) enhances the detector capabilities for all DUNE physics drivers. The PDS of the first FD module consists of light collector modules placed in the inactive space between the innermost wire planes of the TPC anode. The light collectors, the so-called X-ARAPUCAS, are functionally a light trap that captures wavelength-shifted photons inside boxes with highly reflective internal surfaces where they are guided to Silicon Photo-multipliers (SiPM) by wavelength-shifting (WLS) bars. Functionality and operational tests of the X-ARAPUCAS to be installed in ProtoDUNE-SP phase II (FD DUNE prototype at the scale 1:20), as well as the measurement of their absolute detection efficiency is reported in this publication.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗