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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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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Proper orthogonal decomposition based reduced-order modeling of flux-Limited gray thermal radiation

Here, in this work, a proper orthogonal decomposition (POD) based reduced-order model (ROM) is developed to solve gray, flux-limited thermal radiation diffusion. We focus on the variable opacity radiation penetration benchmark posed by Olson, Auer, and Hall. The T -3 relationship for opacity in conjunction with high-temperature radiation penetrating an initially cold material produces a strong thermal radiation shock. This class of problems is particularly challenging for standard POD-based reduced-order modeling due to the nonlinearities presented by 1) the T 4 source term, and 2) flux-limited diffusion operator. To address these challenges and develop a cost competitive ROM, we employ a “hyper-reduction” technique through discrete empirical interpolation (DEIM) and allow for adaptive reduced-order projections through principal interval decomposition (PID). Performance of the proposed methodology is quantified by comparing the cost savings and accuracy relative to a full-order computation. Reference solutions and snapshot data are obtained through a full-order calculation performed by the University of Chicago maintained astrophysics code, FLASH. For consistency and potential extensibility, the developed ROM is also implemented in FLASH. We find that in the initialization regime, where the thermal radiation wave is initially created by the warming of the material, this class of problems is highly reducible and suitable for POD-based ROMs. However, the strong convective nature of the wave propagation regime is less reducible and more challenging to create an efficient ROM.

42 ENGINEERING↗

DOE OSTI2021

Measuring cosmological distances using cluster edges as a standard ruler

ABSTRACT The line-of-sight velocity dispersion profile of galaxy clusters exhibits a ‘kink’ corresponding to the spatial extent of orbiting galaxies. Because the spatial extent of a cluster is correlated with the amplitude of the velocity dispersion profile, we can utilize this feature as a gravity-calibrated standard ruler. Specifically, the amplitude of the velocity dispersion data allows us to infer the physical cluster size. Consequently, observations of the angular scale of the ‘kink’ in the profile can be translated into a distance measurement to the cluster. Assuming the relation between cluster radius and cluster velocity dispersion can be calibrated from simulations, we forecast that with existing data from the Sloan Digital Sky Survey we will be able to measure the Hubble constant with 3.0 per cent precision. Implementing our method with data from the Dark Energy Spectroscopic Instrument (DESI) will result in a 1.3 per cent measurement of the Hubble constant. Adding cosmological supernova data improves the uncertainty of the DESI measurement to 0.7 per cent. While these error estimates are statistical only, they provide strong motivation for pursuing the necessary simulation program required to characterize and calibrate the systematic uncertainties impacting our proposed measurement. Whether or not our proposed measurement can in fact result in competitive H0 constraints will depend on what the eventual systematics floor for this method is.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Advancing Manufacturing Water Resilience: Addressing Risks through New Approaches and Technologies

Water is indispensable in manufacturing operations, and many manufacturers operate on the assumption that water of sufficient quality and quantity will be available whenever and wherever needed. As such, the importance of water to this sector has been overlooked, despite its critical importance for operations and meeting production demands, due to perceived sufficient availability and low cost of water to manufacturers. However, the situation is changing as water-related risks are markedly increasing due to aging infrastructure, changing climate, and resource extraction, which alter global and regional water cycles and characteristics. These changes are occurring against a backdrop of intensifying competition from other sectors for scarce and/or unevenly distributed water resources and changing trends in water needs. Section 1 of this report explores those risks in the U.S. context, while the remaining sections detail the work needed to advance the resilience of manufacturing water supplies to these changing risks by filling critical data gaps, re-evaluating the value of water to manufacturers, and advancing opportunities for novel technologies and analyses. The intended audience for this report is broad, including manufacturers, decision makers, researchers, and policymakers.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Advancing Manufacturing Water Resilience: Addressing Risks through New Approaches and Technologies

36 MATERIALS SCIENCE↗

NASA NTRS2015

Light Microsopy Module, International Space Station Premier Automated Microscope

The Light Microscopy Module (LMM) was launched to the International Space Station (ISS) in 2009 and began science operations in 2010. It continues to support Physical and Biological scientific research on ISS. During 2015, if all goes as planned, five experiments will be completed: [1] Advanced Colloids Experiments with a manual sample base -3 (ACE-M-3), [2] the Advanced Colloids Experiment with a Heated Base -1 (ACE-H-1), [3] (ACE-H-2), [4] the Advanced Plant Experiment -03 (APEX-03), and [5] the Microchannel Diffusion Experiment (MDE). Preliminary results, along with an overview of present and future LMM capabilities will be presented; this includes details on the planned data imaging processing and storage system, along with the confocal upgrade to the core microscope. [1] New York University: Paul Chaikin, Andrew Hollingsworth, and Stefano Sacanna, [2] University of Pennsylvania: Arjun Yodh and Matthew Gratale, [3] a consortium of universities from the State of Kentucky working through the Experimental Program to Stimulate Competitive Research (EPSCoR): Stuart Williams, Gerold Willing, Hemali Rathnayake, et al., [4] from the University of Florida and CASIS: Anna-Lisa Paul and Rob Ferl, and [5] from the Methodist Hospital Research Institute from CASIS: Alessandro Grattoni and Giancarlo Canavese.

Microscopy↗

DOE OSTI2024

Assessment of Cloud-based Applications for Enabling a Scalable Riskinformed Predictive Maintenance Strategy

The current light-water reactor fleet uses time-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging artificial intelligence (AI) and cloud computing technologies to achieve a cost-effective, predictive-maintenance strategy. This paper presents discussion and results on the application of cloud computing in the nuclear industry. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve. The models were hosted on three different systems: a local personal computer, Idaho National Laboratory’s high-performance computer system, and Microsoft Azure. The data were loaded and processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was determined that cloud computing affords adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, the benefit is that the plants no longer need to manage their own servers, software, cybersecurity, and information technology support staff for in-house data analytics purpose. Many of these features can be offloaded to the cloud provider for a potential cost savings. Demonstrating how AI can improve the maintenance and operation of non-safety-related systems seems the likely path forward for implementing AI and cloud computing resources inside nuclear power plants.

azure↗

DOE OSTI2020

Finite-temperature density matrix embedding theory

We describe a formulation of the density matrix embedding theory at finite temperature. We present a generalization of the ground-state bath orbital construction that embeds a mean-field finite-temperature density matrix up to a given order in the Hamiltonian, or the Hamiltonian up to a given order in the density matrix. In this work, we assess the performance of the finite-temperature density matrix embedding on the one-dimensional Hubbard model both at half-filling and away from it, and the two-dimensional Hubbard model at half-filling, comparing to exact data where available, as well as results from finite-temperature density matrix renormalization group, dynamical mean-field theory, and dynamical cluster approximations. The accuracy of finite-temperature density matrix embedding appears comparable to that of the ground-state theory, with, at most, a modest increase in bath size, and competitive with that of cluster dynamical mean-field theory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Determining biomolecular structures near room temperature using X-ray crystallography: concepts, methods and future optimization

For roughly two decades, cryocrystallography has been the overwhelmingly dominant method for determining high-resolution biomolecular structures. Competition from single-particle cryo-electron microscopy and micro-electron diffraction, increased interest in functionally relevant information that may be missing or corrupted in structures determined at cryogenic temperature, and interest in time-resolved studies of the biomolecular response to chemical and optical stimuli have driven renewed interest in data collection at room temperature and, more generally, at temperatures from the protein–solvent glass transition near 200 K to ∼350 K. Fischer has recently reviewed practical methods for room-temperature data collection and analysis [Fischer (2021), Q. Rev. Biophys. 54 , e1]. Here, the key advantages and physical principles of, and methods for, crystallographic data collection at noncryogenic temperatures and some factors relevant to interpreting the resulting data are discussed. For room-temperature data collection to realize its potential within the structural biology toolkit, streamlined and standardized methods for delivering crystals prepared in the home laboratory to the synchrotron and for automated handling and data collection, similar to those for cryocrystallography, should be implemented.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Microbial sensitivity to temperature and sulfate deposition modulates greenhouse gas emissions from peat soils

Abstract Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Microbial processes play a key role in regulating CH 4 emissions from peatland ecosystems, yet the complex interplay between soil substrates and microbial communities in controlling CH 4 emissions as a function of global change remains unclear. Herein, we performed an integrated analysis of multi‐omics data sets to provide a comprehensive understanding of the molecular processes driving changes in greenhouse gas (GHG) emissions in peatland ecosystems with increasing temperature and sulfate deposition in a laboratory incubation study. We sought to first investigate how increasing temperatures (4, 21, and 35°C) impact soil microbiome–metabolome interactions; then explore the competition between methanogens and sulfate‐reducing bacteria (SRBs) with increasing sulfate concentrations at the optimum temperature for methanogenesis. Our results revealed that peat soil organic matter degradation, mediated by biotic and potentially abiotic processes, is the main driver of the increase in CO 2 production with temperature. In contrast, the decrease in CH 4 production at 35°C was linked to the absence of syntrophic communities and the potential inhibitory effect of phenols on methanogens. Elevated temperatures further induced the microbial communities to develop high growth yield and stress tolerator trait‐based strategies leading to a shift in their composition and function. On the other hand, SRBs were able to outcompete methanogens in the presence of non‐limiting sulfate concentrations at 21°C, thereby reducing CH 4 emissions. At higher sulfate concentrations, however, the prevalence of communities capable of producing sufficient low‐molecular‐weight carbon substrates for the coexistence of SRBs and methanogens was translated into elevated CH 4 emissions. The use of omics in this study enhanced our understanding of the structure and interactions among microbes with the abiotic components of the system that can be useful for mitigating GHG emissions from peatland ecosystems in the face of global change.

AminiTabrizi, Roya↗

NASA NTRS1984

Astronomical application of IR CID technology

A portable microcomputer data system was developed to test a 2 x 64-element Si:Bi charge injection device (CID) infrared detector array on the Lick Observatory Shane telescope. An existing 0.5 m spectrograph was used for the tests after modification, and a spectral resolution of 1000 was achieved. Slow device response, due to the low background conditions in the spectrograph were shown. Astronomical data were later obtained, and a device read noise on the order of a few hundred electrons was achieved. The signal to noise ratios of the resulting spectra were about a factor of five lower than what could have been achieved with discrete photoconductive detectors. It is concluded that the CID array is competitive for applications in backgrounds lower than those used in the tests.

Rank, D. M.↗

NASA NTRS1990

AlSb/InAs/AlSb quantum wells

Researchers studied the InAs/AlSb system recently, obtaining 12nm wide quantum wells with room temperature mobilities up to 28,000 cm(exp 2)/V center dot S and low-temperature mobilities up to 325,000 cm(exp 2)/V center dot S, both at high electron sheet concentrations in the 10(exp 12)/cm(exp 2) range (corresponding to volume concentrations in the 10(exp 18)/cm(exp 2) range). These wells were not intentionally doped; the combination of high carrier concentrations and high mobilities suggest that the electrons are due to not-intentional modulation doping by an unknown donor in the AlSb barriers, presumably a stoichiometric defect, like an antisite donor. Inasmuch as not intentionally doped bulk AlSb is semi-insulating, the donor must be a deep one, being ionized only by draining into the even deeper InAs quantum well. The excellent transport properties are confirmed by other observations, like excellent quantum Hall effect data, and the successful use of the quantum wells as superconductive weak links between Nb electrodes, with unprecendentedly high critical current densities. The system is promising for future field effect transistors (FETs), but many processing problems must first be solved. Although the researchers have achieved FETs, the results so far have not been competitive with GaAs FETs.

Kroemer, Herbert↗

NASA NTRSDate not supplied

Machine Learning Application in Aircraft Engine Conceptual Design

In the current competitive environment, the successful creation and application of machine learning (ML) technologies have become crucial across multiple industries. This study outlines the process of creating and implementing ML models for conceptualizing and evaluating aircraft engines. These models use supervised deep-learning algorithms to analyze patterns within an open-source repository containing data on both production and research conventional turbofan engines. Key focus areas include crucial engine parameters such as thrust-specific fuel consumption (TSFC), engine weight, engine diameter, and turbomachinery stage counts. While developing ML models is fundamental, ensuring their seamless deployment is equally important. To address this, a conversational AI chatbot is constructed using natural language processing (NLP) techniques to facilitate the deployment of these ML models. The comprehensive workflow includes several key stages: gathering and enhancing engine data, training and cross validating the ML models, testing and evaluating their performance, and finally, deploying, monitoring, and updating the ML models. By following this systematic approach, the aim is to streamline the development and deployment process of ML models tailored for aircraft engine conceptual design.

Aircraft Engine↗

DOE OSTI2020

Phosphorus alleviation of nitrogen‐suppressed methane sink in global grasslands

Abstract Grassland ecosystems account for more than 10% of the global CH 4 sink in soils. A 4‐year field experiment found that addition of P alone did not affect CH 4 uptake and experimental addition of N alone significantly suppressed CH 4 uptake, whereas concurrent N and P additions suppressed CH 4 uptake to a lesser degree. A meta‐analysis including 382 data points in global grasslands corroborated these findings. Global extrapolation with an empirical modelling approach estimated that contemporary N addition suppresses CH 4 sink in global grassland by 11.4% and concurrent N and P deposition alleviates this suppression to 5.8%. The P alleviation of N‐suppressed CH 4 sink is primarily attributed to substrate competition, defined as the competition between ammonium and CH 4 for the methane mono‐oxygenase enzyme. The N and P impacts on CH 4 uptake indicate that projected increases in N and P depositions might substantially affect CH 4 uptake and alter the global CH 4 cycle.

Zhang, Lihua↗

DOE OSTI2022

Linking remotely sensed ecosystem resilience with forest mortality across the continental United States

Episodes of forest mortality have been observed worldwide associated with climate change, impacting species composition and ecosystem services such as water resources and carbon sequestration. Yet our ability to predict forest mortality remains limited, especially across large scales. Time series of satellite imagery has been used to document ecosystem resilience globally, but it is not clear how well remotely sensed resilience can inform the prediction of forest mortality across continental, multi-biome scales. Here, we leverage forest inventories across the continental United States to systematically assess the potential of ecosystem resilience derived using different data sets and methods to predict forest mortality. Here we found high resilience was associated with low mortality in eastern forests but was associated with high mortality in western regions. The unexpected resilience–mortality relation in western United States may be due to several factors including plant trait acclimation, insect population dynamics, or resource competition. Overall, our results not only supported the opportunity to use remotely sensed ecosystem resilience to predict forest mortality but also highlighted that ecological factors may have crucial influences because they can reverse the sign of the resilience–mortality relationships.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Recommended conventions for reporting results from direct dark matter searches

Abstract The field of dark matter detection is a highly visible and highly competitive one. In this paper, we propose recommendations for presenting dark matter direct detection results particularly suited for weak-scale dark matter searches, although we believe the spirit of the recommendations can apply more broadly to searches for other dark matter candidates, such as very light dark matter or axions. To translate experimental data into a final published result, direct detection collaborations must make a series of choices in their analysis, ranging from how to model astrophysical parameters to how to make statistical inferences based on observed data. While many collaborations follow a standard set of recommendations in some areas, for example the expected flux of dark matter particles (to a large degree based on a paper from Lewin and Smith in 1995), in other areas, particularly in statistical inference, they have taken different approaches, often from result to result by the same collaboration. We set out a number of recommendations on how to apply the now commonly used Profile Likelihood Ratio method to direct detection data. In addition, updated recommendations for the Standard Halo Model astrophysical parameters and relevant neutrino fluxes are provided. The authors of this note include members of the DAMIC, DarkSide, DARWIN, DEAP, LZ, NEWS-G, PandaX, PICO, SBC, SENSEI, SuperCDMS, and XENON collaborations, and these collaborations provided input to the recommendations laid out here. Wide-spread adoption of these recommendations will make it easier to compare and combine future dark matter results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

From Neglect to Progress: Assessing Social Sustainability and Decent Work in the Tourism Sector

Measuring social sustainability performance involves assessing firms’ implementation of social goals, including working conditions, health and safety, employee relationships, diversity, human rights, community engagement, and philanthropy. The concept of social sustainability is closely linked to the notion of decent work, which emphasizes productive work opportunities with fair income, secure workplaces, personal development prospects, freedom of expression and association, and equal treatment for both genders. However, the tourism sector, known for its significant share of informal labor-intensive work, faces challenges that hinder the achievement of decent work, such as extended working hours, low wages, limited social protection, and gender discrimination. This study assesses the social sustainability of the Portuguese tourism industry. The study collected data from the “Quadros do Pessoal” statistical tables for the years 2010 to 2020 to analyze the performance of Portuguese firms in the tourism sector and compare them with one another and with the overall national performance. The study focused on indicators such as employment, wages, and work accidents. The findings reveal fluctuations in employment and remuneration within the tourism sector and high growth rates in the tourism sector compared to the national average. A persistent gender pay gap is identified, which emphasizes the need to address this issue within the tourism industry. Despite some limitations, such as the lack of comparable data on work quality globally, incomplete coverage of sustainability issues, and challenges in defining and measuring social sustainability indicators, the findings have implications for policy interventions to enhance social sustainability in the tourism industry. By prioritizing decent work, safe working conditions, and equitable pay practices, stakeholders can promote social sustainability, stakeholder relationships, and sustainable competitive advantage. Policymakers are urged to support these principles to ensure the long-term sustainability of the tourism industry and foster a more inclusive and equitable society. This study provides insights for Tourism Management, sustainable Human Resource Management, Development Studies, and organizational research, guiding industry stakeholders in promoting corporate social sustainability, firm survival, and economic growth.

Santos, Eleonora (ORCID:0000000346930804)↗

NASA NTRS1983

New applications for phosphoric acid fuel cells

New applications for phosphoric acid fuel cells were identified and evaluated. Candidates considered included all possibilities except grid connected electric utility applications, on site total energy systems, industrial cogeneration, opportunistic use of waste hydrogen, space and military applications, and applications smaller than 10 kW. Applications identified were screened, with the most promising subjected to technical and economic evaluation using a fuel cell and conventional power system data base developed in the study. The most promising applications appear to be the underground mine locomotive and the railroad locomotive. Also interesting are power for robotic submersibles and Arctic villages. The mine locomotive is particularly attractive since it is expected that the fuel cell could command a very high price and still be competitive with the conventionally used battery system. The railroad locomotive's attractiveness results from the (smaller) premium price which the fuel cell could command over the conventional diesel electric system based on its superior fuel efficiency, and on the large size of this market and the accompanying opportunities for manufacturing economy.

Stickles, R. P.↗

NASA NTRS2012

Space Transportation Infrastructure Supported By Propellant Depots

A space transportation infrastructure is described that utilizes propellant depot servicing platforms to support all foreseeable missions in the Earth-Moon vicinity and deep space out to Mars. The infrastructure utilizes current expendable launch vehicle (ELV) systems such as the Delta IV Heavy, Atlas V, and Falcon 9, for all crew, cargo, and propellant launches to orbit. Propellant launches are made to Low-Earth-Orbit (LEO) Depot and an Earth-Moon Lagrange Point 1 (L1) Depot to support a new reusable in-space transportation vehicles. The LEO Depot supports missions to Geosynchronous Earth Orbit (GEO) for satellite servicing and to L1 for L1 Depot missions. The L1 Depot supports Lunar, Earth-Sun L2 (ESL2), Asteroid and Mars Missions. New vehicle design concepts are presented that can be launched on current 5 meter diameter ELV systems. These new reusable vehicle concepts include a Crew Transfer Vehicle (CTV) for crew transportation between the LEO Depot, L1 Depot and missions beyond L1; a new reusable lunar lander for crew transportation between the L1 Depot and the lunar surface; and Mars orbital Depot are based on International Space Station (ISS) heritage hardware. Data provided includes the number of launches required for each mission utilizing current ELV systems (Delta IV Heavy or equivalent) and the approximate vehicle masses and propellant requirements. Also included is a discussion on affordability with ideas on technologies that could reduce the number of launches required and thoughts on how this infrastructure include competitive bidding for ELV flights and propellant services, developments of new reusable in-space vehicles and development of a multiuse infrastructure that can support many government and commercial missions simultaneously.

Smitherman, David↗