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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Extending Analysis of Asay Windows to High Areal Mass Range [Slides]

The accretion layer addition to Asay window analysis results in new equations of motion that depend on the location of collisions within the layer. Asay window equations of motion can be represented in terms of experiment observables. Balance of linear momentum for variable mass systems provides a framework for developing equations of motion for Asay window diagnostics under a variety of operating assumptions. The growth in the accretion layer thickness during an experiment substantially influences mass and density measurements when high accumulation of areal mass is present.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Extending the Asay window measurement model to high areal mass ranges [Slides]

The accretion layer addition to Asay window analysis results in new equations of motion that depend on the location of collisions within the layer. Asay window equations of motion can be represented in terms of experiment observables. Balance of linear momentum for variable mass systems provides a framework for developing equations of motion for Asay window diagnostics under a variety of operating assumptions. The growth in the accretion layer thickness during an experiment substantially influences mass and density measurements when high accumulation of areal mass is present.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

National Security Programs - Cyber: MMAREJBLIGE – Modular Multi Agent Grid Emulation for Joined Breakdowns in Linked Generative Emulations - 23-0644

Modular Multi Agent Grid Emulations for Joined Breakdowns in Linked Generative Emulations (MMAREJBLIGE) introduces an agent-based modeling framework into real-time cyber-physical emulation to achieve a context-aware environment that introduces operator/attacker/external-condition variability to improve emulation fidelity and testing rigor. We detail our agent framework design, internal communication via message passing, and time synchronization, as well as the individual components of the system. We include a brief analysis of several scenarios run on a real-time, hardware-in-the-loop, Industrial Control Systems (ICS) test-bed which include normal operation, physical disruption, disruption with mitigation, and disruption with mitigation during a cyber denial-of-service (DOS) attack.

42 ENGINEERING↗
DOE OSTI2023

A network analysis of the long-term quality of life and mental distress of COVID-19 survivors 1 year after hospital discharge

Objectives COVID-19 survivors suffer from persistent mental distress and impaired quality of life (QOL) after recovery from the infection. However, the symptom-symptom interaction between these psychological variables remained unexplored. The present study aimed to determine the symptom network of mental distress (depression, anxiety, sleep disturbance, fatigue, and post-traumatic stress disorder) and their association with QOL among 535 COVID-19 survivors 1 year after hospital discharge. Methods 9-item Patient Health Questionnaire, 7-item Generalized Anxiety Disorder Scale, Chalder fatigue scale, Impact of Event Scale-Revised, Pittsburgh Sleep Quality Index, and 36-Item Short-Form Health Survey were applied to measure depression, anxiety, fatigue, PTSD, sleep disturbances, and QOL, respectively. Two networks were estimated using Gaussian graphical model. Network 1 consisted of mental symptoms to determine the central and bridge symptoms. Network 2 additionally included QOL to determine which mental symptoms were mostly related to QOL. Results 60% of the COVID-19 survivors experienced mental distress 1 year after hospital discharge. Uncontrollable and excessive worry, psychomotor symptoms, intrusion, and daytime dysfunction were the most central symptoms. Daytime dysfunction and fatigue (especially mental fatigue and loss of energy) served as the bridge symptoms across the mental distress network and exhibited the most substantial association with QOL. Conclusion Our study demonstrated several key symptoms that played a vital role in mental distress and QOL among COVID-19 survivors. Prompt screening and targeted interventions for these symptoms might hold great promise in preventing mental distress and improving QOL in COVID-19 survivors.

Peng, Pu↗
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 OSTI2025

Exploring the Future Energy Value of Long-Duration Energy Storage

Long-duration energy storage is commonly viewed as a key technology for providing flexibility to the grid and broader energy systems over a multidecadal time frame. However, prior work has typically used present-day grid infrastructures to characterize the relationship between the duration and arbitrage value of storage in electricity markets. This study leverages established National Renewable Energy Laboratory grid planning and operations tools, analysis, and data to execute a price-taker model of an energy storage system for several 8760 h price series representative of current and future contiguous United States grid infrastructures with varying shares of variable renewable energy (VRE). We find that the total value of energy storage typically increases with VRE shares, but any increase in the relative value of longer storage durations over time depends on the region and grid mix. Some regions see incremental value increasing notably, up to 20–40 h in 2050, while others do not. The negative effect of lower roundtrip efficiency on value is also found to be scenario-dependent, with the energy value in higher VRE scenarios being less sensitive to roundtrip efficiency and more supportive of longer storage durations. Long-duration storage value and deployment potential are a function of evolving electricity sector infrastructure, markets, and policy, making it critical to consistently revisit potential long-duration storage contributions to the grid.

14 SOLAR ENERGY↗
DOE OSTI2024

Microbial Reduction of Geogenic and Synthetic Goethite and Hematite

The microbial reduction of Fe(III) is a major component of Fe cycling in terrestrial and aquatic environments and is affected by the Fe(III) mineralogy of the system. The majority of the research examining the bioreduction of Fe(III) oxides by Fe(III)-reducing bacteria (IRB) has focused on the reduction of poorly crystalline Fe(III) phases, primarily ferrihydrite; however, crystalline Fe(III) oxides like goethite (α-FeOOH) and hematite (α-Fe 2 O 3 ) comprise the majority of Fe(III) oxides in soils. This study examined the bioreduction of goethite and hematite of geogenic and synthetic origin by Shewanella putrefaciens CN2, a well-studied model IRB, in laboratory incubations. Overall, the rate and extent of Fe(II) production were greater for goethite than for hematite, and for geogenic Fe(III) oxides relative to their synthetic analogs. Although there was substantial production of Fe(II) (i.e., >5 mM Fe(II)) in many of the systems, X-ray diffraction analysis of the solids at the end of the incubation did not indicate the formation of any Fe(II)-bearing secondary minerals (e.g., magnetite, siderite, green rust, etc.). The results of this study demonstrate the variability in the extent of bioreduction of geogenic goethite and hematite, and furthermore, that synthetic goethite and hematite may not be good analogs for the biogeochemical behavior of Fe(III) oxides in aquatic and terrestrial environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Opinion: The importance of historical and paleoclimate aerosol radiative effects

Abstract. Estimating past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols affected the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo-observations and in part because less attention has been paid to the problem. Because of the lack of information we do not seek here to determine the change in the radiative forcing due to aerosol changes but rather to estimate the uncertainties in those changes. Here we argue that current uncertainties from emission uncertainties (90 % confidence interval range spanning 2.8 W m−2) are just as large as model spread uncertainties (2.8 W m−2) in calculating preindustrial to present-day aerosol radiative effects. There are no estimates of radiative forcing for important aerosols such as wildfire and dust aerosols in most paleoclimate time periods. However, qualitative analysis of paleoclimate proxies suggests that changes in aerosols between different past climates are similar in magnitude to changes in aerosols between the preindustrial and present day; plus, there is the added uncertainty from the variability in aerosols and fires in the preindustrial. From the limited literature we crudely estimate a paleoclimate aerosol uncertainty for the Last Glacial Maximum relative to preindustrial of 4.8 W m−2, and we estimate the uncertainty in the aerosol feedback in the natural Earth system over the paleoclimate (Last Glacial Maximum to preindustrial) to be about 3.2 W m−2 K−1. In order to more accurately assess the uncertainty in historical aerosol radiative effects, we propose a new model intercomparison project, which would include multiple plausible emission scenarios tested across a range of state-of-the-art climate models over the historical period. These emission scenarios would then be compared to the available independent aerosol observations to constrain which are most probable. In addition, future efforts should work to characterize and constrain paleo-aerosol forcings and uncertainties. Careful propagation of aerosol uncertainties in the literature is required to ensure an accurate quantification of uncertainties in projections of future climate changes.

Environmental Sciences & Ecology↗
DOE OSTI2022

Preliminary Sensitivity Analysis for Sensors Impacts on Building Control Performance

This report describes the preliminary sensitivity analysis for sensor impacts on building control performance through the US Department of Energy’s Oak Ridge National Laboratory’s Flexible Research Platform (FRP-2) building. The rooftop unit system provides cooling and heating to the building. The main heating coil is a gas heating coil. Each zone is served by a variable air volume box with an electricity reheat coil. The rooftop unit and variable air volume box controls adopted the practical control sequences from ASHRAE Guideline 36-2018: High-Performance Sequences of Operation. For sensors, the incipient (time-changing) sensor errors, including bias sensor error and precision sensor error, are the inputs of interest. The outputs are energy consumption and thermal comfort (e.g., the predicted percentage of dissatisfied occupants). The large-scale simulation (3,600 cases) was conducted on a cloud platform by integrating sensor errors and ASHRAE Guideline 36 control sequences into an emulator based on the EnergyPlus simulation program with Python energy management system feature. The surrogate models were developed based on cloud simulation results. The uncertainty analysis showed that the sensor errors substantially affect building energy consumption and thermal comfort. The sensitivity analysis shows a ranking of sensor error impacts for each interested output item (e.g., cooling energy, reheat coil heating energy, predicted percentage of dissatisfied occupants). In FY 2022, sensor locations, types, and costs will be evaluated. The field test in Oak Ridge National Laboratory’s Flexible Research Platform building regarding sensor impacts will also be performed. Finally, a comparative analysis will be conducted based on the field test results and emulator results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP)

Anthropogenic climate change is unfolding rapidly, yet its regional manifestation can be obscured by internal variability. A primary goal of climate science is to identify the externally forced climate response from among the noise of internal variability. Separating the forced response from internal variability can be addressed in climate models by using a large ensemble to average over different possible realizations of internal variability. However, with only one realization of the real world, it is a major challenge to isolate the forced response directly in observations. In the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP), contributors used existing and newly developed statistical and machine learning methods to estimate the forced response over 1950–2022 within individual realizations of the climate system. Participants used neural networks, linear inverse models, fingerprinting methods, and low-frequency component analysis, among other approaches. These methods were trained using large ensembles from multiple climate models and then applied to observations. Here, we evaluate method performance within large ensembles and investigate the estimates of the forced response in observations. Our results show that many different types of methods are skillful for estimating the forced response in climate models, though the relative skill of individual methods varies depending on the variable and evaluation metric. Methods with comparable skill in models can give a wide range of estimates of the forced response pattern in observations, illustrating the epistemic uncertainty in forced response estimates. ForceSMIP gives new insights into the forced response in observations, its uncertainty, and methods for its estimation.

Climate attribution↗
DOE OSTI2024

A Comprehensive Stress Drop Map From Trench to Depth in the Northern Chilean Subduction Zone

We compute stress drops for earthquakes in Northern Chile recorded between 2007 and 2021. By applying two analysis techniques, (a) the spectral ratio (SR) method and (b) the spectral decomposition (SDC) method, a stress drop map for the subduction zone consisting of 51,510 stress drop values is produced. We build an extended set of empirical Green’s functions (EGF) for the SR method by systematic template matching. Outputs are used to compare with results from the SDC approach, where we apply cell-wise obtained global EGF's to compensate for the structural heterogeneity of the subduction zone. We find a good consistency of results of the two methods. The increased spatial coverage and quantity of stress drop estimates from the SDC method facilitate a consistent stress drop mapping of the different seismotectonic domains. Albeit only small differences of median stress drop, strike-perpendicular depth sections clearly reveal systematic variations, with earthquakes at different seismotectonic locations exhibiting distinct values. In particular, interface seismicity is characterized by the lowest observed median value, whereas upper plate earthquakes show noticeably higher stress drop values. Intermediate depth earthquakes show comparatively high average stress drop and a rather strong depth-dependent increase of median stress drop. Additionally, we observe spatio-temporal variability of stress drops related to the occurrence of the two megathrust earthquakes in the study region. The presented study is the first coherent large scale 3D stress drop mapping of the Northern Chilean subduction zone. It provides an important component for further detailed analysis of the physics of earthquake ruptures.

58 GEOSCIENCES↗
DOE OSTI2020

Impact of climate change on water availability and its propagation through the Western U.S. power grid

Climate impact assessment for power systems has tended to focus on the effects of water availability on generation without explicitly considering how these impacts propagate through the interconnected grid to affect generation in other locations. We investigate the impact of projected water availability on the operations of the contemporary Western U.S. power grid, focusing specifically on regional interdependencies. Hydrologic simulations derived from three GCMs (CCSM4, INMCM4 and GFDL-CM3) and two radiative scenarios (RCP4.5 and RCP8.5) are used to force a large-scale, distributed water management model (MOSART-WM), which translates water availability into power generation constraints at hydropower plants and water-dependent thermo-electric plants. Power system dynamics are evaluated using the production cost model PLEXOS. We find that the inter-regional connections across the Western U.S. electricity infrastructure are key in managing drastic variations in regional water availability. Net generation in the Northwest and Northern California is substantially sensitive to local water availability. Generation from the Desert Southwest emerges as a critical resource to compensate for variations in water availability in those regions. Climate change impacts on Northwestern water availability therefore drive future changes in other regions’ generation and regional power flows. The large inter-annual hydrological variability of Northern California exacerbates grid stress arising from long-term changes in water availability in the Northwest. While the regional power flow directions seem insensitive to long-term variations in water availability, the analysis highlights the need to consider other compounding regional factors such as changes in Southern California net load or changes in regional fuel prices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

De-Risking High-Recovery Brackish Water Desalination via Flow Reversal and Feed Flushing Using Techno-Economic Assessment

Novel desalination technologies have demonstrated enhanced performance and improved financial metrics over existing processes adopted by industry. Establishing quantitative performance targets is essential for achieving financial benefits over the current state of the art. Herein, we demonstrate how WaterTAP, a techno-economic assessment (TEA) tool, can be used to identify minimum performance metrics necessary to achieve financial benefit over using existing processes. This study evaluates the feasibility of increasing water recovery at the Chino Desalter I above 90 % through the addition of a third variable configuration reverse osmosis (VCRO) stage. Sensitivity analyses revealed flow reversal frequency, feed flushing volume (used as a cleaning step), and membrane lifespan are key factors influencing the financial viability of the VCRO process. The TEA analysis demonstrated that the system must achieve a recovery of 84 % and a 1-year membrane lifespan to have a breakeven LCOW, while achieving 90 % recovery can ultimately reduce the LCOW by 16 %. Notably, a trade-off between decreasing frictional losses and increased osmotic pressure across the recovery range, resulted in a stable specific energy consumption across the recovery range, enabling meaningful LCOW reductions without an energy penalty, a key finding that contrasts with conventional RO. This work demonstrates how TEA can guide system design by identifying key performance targets and exploring trade-offs, enabling data-driven decisions to de-risk innovative processes. These findings underscore the importance of leveraging TEA to evaluate scaling mitigation strategies and optimize inland desalination systems for sustainable and cost-effective operation.

14 SOLAR ENERGY↗
DOE OSTI2023

Vertical Gradient of Size-Resolved Aerosol Compositions over the Arctic Reveals Cloud Processed Aerosol in-Cloud and above Cloud

Arctic aerosols play a significant role in the aerosol-radiation and aerosol-cloud interactions, but ground-based measurements are insufficient to explain the interaction of aerosols and clouds in a vertically stratified Arctic atmosphere. This study shows the vertical variability of aerosol particle composition via tethered balloon system at Oliktok Point, Alaska, in August 2019, at different cloud layers for two case studies (background aerosol condition and polluted condition). Multi-modal micro-spectroscopy analysis of samples during the background case reveals a broadening of chemically specific size distribution above cloud top with a high abundance of sulfate and core-shell morphology, suggesting possible cloud processing of aerosols. The pollution case also indicates a broadening of size distribution at the upper cloud layer with the dominance of carbonaceous aerosol, which suggests the potential of carbonaceous aerosols for Arctic cloud formation. Here this study provides insights into the vertical profile of Arctic aerosols on cloud formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Perturbations of Gibbons-Maeda black holes in Einstein-Maxwell-dilaton theories

The study of perturbations around black hole backgrounds in general relativity and Einstein-Maxwell theory has a long history, going back to the work of Regge and Wheeler in the 1950s. As part of a broader investigation of perturbations around black holes in supergravity, we describe here our results for the perturbations around the Gibbons-Maeda static charged black holes in a class of Einstein-Maxwell-Dilaton theories. Our analysis follows the general strategy developed by Chandrasekhar and Xanthopoulos for the perturbations of the Reissner-Nordström black hole. Here, the analysis is considerably more involved, because of the presence of the dilaton field, which couples to the other polar modes. We nonetheless find that the problem is completely solvable, in the sense that one can separate variables and eventually describe all the perturbations in terms of diagonalised second-order radial equations. We are able to prove the mode stability of all the Gibbons-Maeda black hole solutions. Published by the American Physical Society 2024

Pope, C. N. (ORCID:0000000284012564)↗
DOE OSTI2024

Coupled Multiphysics Modeling of Lithium-Ion Batteries for Automotive Crashworthiness Applications

Considerable advances have been made in battery safety models, but achieving predictive accuracy across a wide range of conditions continues to be challenging. Interactions between dynamically evolving mechanical, electrical, and thermal state variables make model prediction difficult during mechanical abuse scenarios. In this study, we develop a physics-based modeling approach that allows for choosing between different mechanical and electrochemical models depending on the required level of analysis. We demonstrate the use of this approach to connect cell-level abuse response to electrode-level and particle-level transport phenomena. A pseudo-two-dimensional model and simplified single-particle models are calibrated to electrical-thermal cycling data and applied to mechanically induced short-circuit scenarios to understand how the choice of electrochemical model affects the model prediction under abuse scenarios. These models are implemented using user-defined subroutines on ls-dyna finite element software and can be coupled with existing automotive crash safety models.

analysis and design of components↗
DOE OSTI2020

A transported Livengood-Wu integral model for knock prediction in CFD simulation

This work describes the development of a transported Livengood-Wu (L-W) integral model for computational fluid dynamics (CFD) simulation to predict auto-ignition and engine knock tendency. The currently employed L-W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition combustion for three different fuels, showing good accuracy in prediction of auto-ignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L-W integral model is coupled with G-equation model to indicate end-gas auto-ignition and knock tendency in CFD simulations of a direct injection spark ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely Co-Optima Alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multi-variable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency indicated by the fuel energy contained in the auto-ignited region of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

Yue, Zongyu↗