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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Observational window effects on multi-object reverberation mapping

ABSTRACT Contemporary reverberation mapping campaigns are employing wide-area photometric data and high-multiplex spectroscopy to efficiently monitor hundreds of active galactic nuclei (AGNs). However, the interaction of the window function(s) imposed by the observation cadence with the reverberation lag and AGN variability time-scales (intrinsic to each source over a range of luminosities) impact our ability to recover these fundamental physical properties. Time dilation effects due to the sample source redshift distribution introduce added complexity. We present comprehensive analysis of the implications of observational cadence, seasonal gaps, and campaign baseline duration (i.e. the survey window function) for reverberation lag recovery. We find that the presence of a significant seasonal gap dominates the efficacy of any given campaign strategy for lag recovery across the parameter space, particularly for those sources with observed-frame lags above 100 d. Using the Australian Dark Energy Survey as a baseline, we consider the implications of this analysis for the 4MOST/Time-Domain Extragalactic Survey campaign providing concurrent follow-up of the Legacy Survey of Space and Time deep-drilling fields, as well as upcoming programmes. We conclude that the success of such surveys will be critically limited by the seasonal visibility of some potential field choices, but show significant improvement from extending the baseline. Optimizing the sample selection to fit the window function will improve survey efficacy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Axion dark matter experiment: Run 1B analysis details

Searching for axion dark matter, the ADMX Collaboration acquired data from January to October 2018, over the mass range 2.81–3.31 μeV, corresponding to the frequency range 680–790 MHz. Using an axion haloscope consisting of a microwave cavity in a strong magnetic field, the ADMX experiment excluded Dine-Fischler-Srednicki-Zhitnisky (DFSZ) axions at 90% confidence level and 100% dark matter density over this entire frequency range, except for a few gaps due to mode crossings. This paper explains the full ADMX analysis for run 1B, motivating analysis choices informed by details specific to this run.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Spin-Dependent $\pi$$\pi$* Gap in Graphene on a Magnetic Substrate

Here, we present a detailed analysis of the electronic properties of graphene/Eu/Ni(111). By using angle- and spin-resolved photoemission spectroscopy and ab initio calculations, we show that the intercalation of Eu in the graphene/Ni(111) interface gives rise to a gapped freestanding dispersion of the $\pi$$\pi$* Dirac cones at the K point with an additional lifting of the spin degeneracy due to the mixing of graphene and Eu states. The interaction with the magnetic substrate results in a large spin-dependent gap in the Dirac cones with a topological nature characterized by a large Berry curvature and a spin-polarized Van Hove singularity, whose closeness to the Fermi level gives rise to a polaronic band.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intelligent resolution: Integrating Cryo-EM with AI-driven multi-resolution simulations to observe the severe acute respiratory syndrome coronavirus-2 replication-transcription machinery in action

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale.

Trifan, Anda↗
NASA NTRS2012

Development of IR Contrast Data Analysis Application for Characterizing Delaminations in Graphite-Epoxy Structures

Objective: Develop infrared (IR) flash thermography application based on use of a calibration standard for inspecting graphite-epoxy laminated/honeycomb structures. Background: Graphite/Epoxy composites (laminated and honeycomb) are widely used on NASA programs. Composite materials are susceptible for impact damage that is not readily detected by visual inspection. IR inspection can provide required sensitivity to detect surface damage in composites during manufacturing and during service. IR contrast analysis can provide characterization of depth, size and gap thickness of impact damage. Benefits/Payoffs: The research provides an empirical method of calibrating the flash thermography response in nondestructive evaluation. A physical calibration standard with artificial flaws such as flat bottom holes with desired diameter and depth values in a desired material is used in calibration. The research devises several probability of detection (POD) analysis approaches to enable cost effective POD study to meet program requirements.

Havican, Marie↗
DOE OSTI2020

Modelling urban-scale occupant behaviour, mobility, and energy in buildings: A survey

The proliferation of urban sensing, IoT, and big data in cities provides unprecedented opportunities for a deeper understanding of occupant behaviour and energy usage patterns at the urban scale. This enables data-driven building and energy models to capture the urban dynamics, specifically the intrinsic occupant and energy use behavioural profiles that are not usually considered in traditional models. Although there are related reviews, none have investigated urban data for use in modelling occupant behaviour and energy use at multiple scales, from buildings to neighbourhood to city. This survey paper aims to fill this gap by providing a critical summary and analysis of the works reported in the literature. We present the different sources of occupant-centric urban data that are useful for data-driven modelling and categorise the range of applications and recent data-driven modelling techniques for urban behaviour and energy modelling, along with the traditional stochastic and simulation-based approaches. Finally, we present a set of recommendations for future directions in data-driven modelling of occupant behaviour and energy in buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2025

Probing the Mechanism of Selective Phosphate Adsorption from Wastewater Using Aqueous and Synchrotron X-ray Characterization

Ion exchange shows promise for recovering phosphate from wastewater as value-added products, but requires high phosphate selectivity to compete with conventional treatment. Hybrid anion exchange (HAIX) resins, which contain non-selective basic functional groups and selective iron oxide nanoparticles (FeOnp), can effectively remove phosphate from wastewater. However, knowledge gaps remain regarding the mechanisms of phosphate selectivity and influence of competing ions, hindering needed efforts to model adsorption dynamics and design scalable adsorption processes for varying wastewaters. To address these gaps, we integrated aqueous-phase adsorption analysis with solid-phase, synchrotron-based X-ray characterization; this integration facilitated elucidation of the distribution and speciation of iron, phosphate, and competing anions on HAIX resins. We compared a quaternary ammonium-functionalized HAIX resin (SBA) to a tertiary amine version (WBA) to determine the role of functional groups. X-ray radiography revealed differences in FeOnp speciation (goethite vs. ferrihydrite) and distribution (peripheral vs. homogeneous) between the resins, resulting in varied phosphate affinity and intraparticle diffusion resistance. Using micro-X-ray fluorescence (μ-XRF) and micro-X-ray absorption near-edge structure (μ-XANES) spectroscopy, we identified differences in where and how phosphate binds across resin types and wastewaters. Across wastewater compositions, FeOnp sites in WBA contribute more to phosphate adsorption than in SBA, possibly due to variations in Fe distribution and speciation. Phosphate adsorption densities calculated from quantitative μ-XRF maps matched those from aqueous analysis, demonstrating the effectiveness of this integrated approach. Altogether, results demonstrate the use of synchrotron-based X-ray characterization for investigating adsorption mechanisms and advance HAIX as a phosphate recovery technology from complex wastewaters.

Nutrient recovery↗
DOE OSTI2023

Type Ia supernova observations combining data from the Euclid mission and the Vera C. Rubin Observatory

ABSTRACT The Euclid mission will provide first-of-its-kind coverage in the near-infrared over deep (three fields, ∼10–20 square degrees each) and wide (∼10 000 square degrees) fields. While the survey is not designed to discover transients, the deep fields will have repeated observations over a two-week span, followed by a gap of roughly six months. In this analysis, we explore how useful the deep field observations will be for measuring properties of Type Ia supernovae (SNe Ia). Using simulations that include Euclid’s planned depth, area, and cadence in the deep fields, we calculate that more than 3700 SNe between 0.0 < $z$ < 1.5 will have at least five Euclid detections around peak with signal-to-noise ratio larger than 3. While on their own, Euclid light curves are not good enough to directly constrain distances, when combined with legacy survey of space and time (LSST) deep field observations, we find that uncertainties on SN distances are reduced by 20–30 per cent for $z$ < 0.8 and by 40–50 per cent for $z$ > 0.8. Furthermore, we predict how well additional Euclid mock data can be used to constrain a key systematic in SN Ia studies – the size of the luminosity ‘step’ found between SNe hosted in high-mass (>1010 M⊙) and low-mass (<1010 M⊙) galaxies. This measurement has unique information in the rest-frame near-infrared (NIR). We predict that if the step is caused by dust, we will be able to measure its reduction in the NIR compared to optical at the 4σ level. We highlight that the LSST and Euclid observing strategies used in this work are still provisional and some level of joint processing is required. Still, these first results are promising, and assuming that Euclid begins observations well before the Nancy Roman Space Telescope (Roman), we expect this data set to be extremely helpful for preparation for Roman itself.

Astronomy & Astrophysics↗
DOE OSTI2026

Reliability Assessment of Cooling Fans for PV Inverters: Testing, Modeling, and Case Studies

The reliability of photovoltaic (PV) inverters is critical for long-term solar system performance, with cooling fan failures frequently leading to costly downtime. While much research exists on general cooling fan reliability, little attention has been given to fans operating within PV inverters and their unique environmental challenges. Here, this article proposes a comprehensive methodology to address this gap. First, a failure mode and effects analysis is performed on fans to identify the key failure mechanisms in PV applications, their corresponding stressors, and the models necessary for lifetime prediction. Second, an accelerated life test is designed and conducted to collect valuable experimental data for PV inverter fans in a reasonable amount of time. Third, a mathematical conversion of dynamic mission profiles into effective constant stress levels is derived. Fourth, case studies are given, showcasing lifetime estimates that account for geographic variations in mission profile data. The results demonstrate that this integrated approach leads to an accurate reliability assessment for PV inverter cooling fans.

accelerated life testing (ALT)↗
DOE OSTI2021

Characterizing Machine Learning I/O Workloads on Leadership Scale HPC Systems

High performance computing (HPC) is no longer solely limited to traditional workloads such as simulation and modeling. With the increase in the popularity of machine learning (ML) and deep learning (DL) technologies, we are observing that an increasing number of HPC users are incorporating ML methods into their workflow and scientific discovery processes, across a wide spectrum of science domains such as biology, earth science, and physics. This gives rise to a diverse set of I/O patterns than the traditional checkpoint/restart-based HPC I/O behavior. The details of the I/O characteristics of such ML I/O workloads have not been studied extensively for large-scale leadership HPC systems. This paper aims to fill that gap by providing an in-depth analysis to gain an understanding of the I/O behavior of ML I/O workloads using darshan - an I/O characterization tool designed for lightweight tracing and profiling. We study the darshan logs of more than 23, 000 HPC ML I/O jobs over a time period of one year running on Summit - the second-fastest supercomputer in the world. This paper provides a systematic I/O characterization of ML I/O jobs running on a leadership scale supercomputer to understand how the I/O behavior differs across science domains and the scale of workloads, and analyze the usage of parallel file system and burst buffer by ML I/O workloads.

Paul, Arnab↗
DOE OSTI2024

Proteome profiling of enriched membrane-associated proteins unraveled a novel sophorose and cello-oligosaccharide transporter in Trichoderma reesei

Trichoderma reesei is an organism extensively used in the bioethanol industry, owing to its capability to produce enzymes capable of breaking down holocellulose into simple sugars. The uptake of carbohydrates generated from cellulose breakdown is crucial to induce the signaling cascade that triggers cellulase production. However, the sugar transporters involved in this process in T. reesei remain poorly identified and characterized. To address this gap, this study used temporal membrane proteomics analysis to identify five known and nine putative sugar transporters that may be involved in cellulose degradation by T. reesei. Docking analysis pointed out potential ligands for the putative sugar transporter Tr44175. Further functional validation of this transporter was carried out in Saccharomyces cerevisiae. The results showed that Tr44175 transports a variety of sugar molecules, including cellobiose, cellotriose, cellotetraose, and sophorose. This study has unveiled a transporter Tr44175 capable of transporting cellobiose, cellotriose, cellotetraose, and sophorose. Our study represents the first inventory of T. reesei sugar transportome once exposed to cellulose, offering promising potential targets for strain engineering in the context of bioethanol production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optical reflectance imaging reveals interlayer coupling in mechanically stacked MoS 2 and WS 2 bilayers

Optical reflectance imaging is a popular technique for characterizing 2D materials, thanks to its simplicity and speed of data acquisition. The use of this method for studying interlayer phenomena in stacked 2D layers has, however, remained limited. Here we demonstrate that optical imaging can reveal the nature of interlayer coupling in stacked MoS 2 and WS 2 bilayers through their observed reflectance contrast versus the substrate. Successful determination of interlayer coupling requires co-optimization of the illumination wavelength and the thickness of an underlying SiO 2 film. Our observations are supported by multilayer optical calculations together with an analysis of the effect of any interlayer gap. This approach promises quick characterization of constructed 2D material systems.

Nguyen, Vu↗
NASA NTRS1982

Unsteady Subsonic Loadings Due to Control-Surface Motion

RHOIV computer program predicts unsteady lifting-surface loadings caused by motions of leading edge and trailing-edge control surfaces having sealed gaps at hinge lines and side edges. Analysis is based on linear, subsonic, potential-flow theory using kernel function method. Linear combinations of pressure distributions are used that are continuous except at planform edges and hinge lines. Loading solution is obtained by downwash collocation for deflection or motion of main wing and control surfaces.

Rowe, W. S.↗
NASA NTRS1991

Temperature dependence of optical properties of GaAs

The effect of temperature on the optical properties of GaAs was investigated using spectroscopic ellipsometry measurements, between room temperature and about 610 C in increments of 50 C, of pseudodielectric functions and related optical constants of GaAs. A quantitative analysis of the pseudodielectric function spectrum was carried out using a harmonic-oscillator approximation (HOA) to fit the measured dielectric functions. Good fits were obtained with this model, which provides a convenient means of reproducing the GaAs dielectric function at any temperature, by using the temperature-dependent oscillator parameters. The HOA analysis also provides information about band-gap variation with temperature. Using the measured optical constants at a number of fixed temperatures, an algorithm was developed for computing the dielectric function spectrum at an arbitrary temperature in the range 22-610 C.

Yao, Huade↗
NASA NTRS2015

The Global Exploration Roadmap: Opportunities for Lunar Science

The Global Exploration Roadmap (GER) has been developed by the International Space Exploration Coordination Group (ISECG comprised of 14 space agencies) to define various pathways to getting humans beyond low Earth orbit and eventually to Mars. Such pathways include visiting asteroids or the Moon before going on to Mars. This document has been written at a very high level and many details are still to be determined. However, a number of important papers regarding international space exploration can form a basis for this document.This poster will focus on developing the Lunar Vicinity scenario by adding detail via mapping a number of recent reportsdocuments into the GER. The documents highlighted here are in no way meant to be all encompassing and other documents can and should be added, (e.g., the JAXA Space Exploration Roadmap). This exercise is intended to demonstrate that existing documents can be mapped into the GER despite the major differences in granularity, and that this mapping is a way to promote broader national and international buy-in to the Lunar Vicinity scenario.The documents used here are: the Committee on Space Research (COSPAR) Panel on Exploration report on developing a global space exploration program, the Strategic Knowledge Gaps (SKGs) report from the Lunar Exploration Analysis Group (LEAG), the Lunar Exploration Roadmap developed by LEAG, the National Research Council report Scientific Context for the Exploration of the Moon (SCEM), and two journal articles, the scientific rationale for resuming lunar surface exploration, and the astrobiological benefits of human space exploration.In addition, the ISECG is in the process of developing a Science White Paper (SWP) to accompany the next edition of the GER, due in late 2016. The SWP will be an important tool to communicate science which will be able to be accomplished at human exploration destinations to policymakers. This abstract will discuss the process of developing this SWP and ways in which the global science community can become engaged in its development.

Schmidt, Gregory↗
NASA NTRS1993

AUREOL-3 observations of new boundaries in the auroral ion precipitation

Interesting and well-separated structures in the 1-20 keV ion precipitation pattern have been revealed by an analysis of more than 50 crossings of the nightside (21-03 MLT) auroral zone by the AUREOL-3 satellite. First, velocity-dispersed ion structures (VDIS) are crossed near the poleward edge of the oval, and are the best ionospheric signature of ion beams flowing along the plasma sheet boundary layer. Proceeding equatorward, a large majority of VDIS events are bounded by a new and interesting narrow band of strongly reduced precipitation, or a gap, which delineates VDIS from the diffuse precipitation region connected to the CPS. A statistical analysis shows that the gap has an extent of about 1-2 deg, which is almost independent of magnetic activity; its location, about 70 deg ILAT, shifts significantly equatorward with higher magnetic activity levels. Intense electron arcs are observed near the equatorward edge of the gap. An important result is that the overall sequence of VDIS-gap-CPS can be explained in terms of orbital dynamics in the tail. The gap in precipitation appears as the counterpart of the 'wall' regime in the equatorial plane, in which a cross-tail current carried by energetic ions is strongly enhanced between 8 and 12 R(E). This region has important consequences for the development of substorms.

Bosqued, Jean M.↗
DOE OSTI2025

Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions

Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗