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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Envelope-driven comfort risk in residential demand response

Residential demand response (DR) is a valuable resource for grid reliability, but remains challenging because the highly heterogeneous residential building stock leads to widely varying and hard-to-predict load and comfort responses during DR events. Although prior research has estimated the technical potential of DR-capable technologies for achieving energy demand savings, little is known about how they affect thermal comfort. In particular, it remains unclear how indoor thermal conditions due to DR depend on the thermal envelope characteristics of the housing stock. To address this gap, this study provides a systematic, location-specific assessment of indoor thermal performance during DR-events across the US housing stock using both typical DR weather data and detailed building metadata. We evaluate how envelope characteristics influence indoor temperatures during realistic simulated summer and winter DR events across 37 US locations, applying both temperature threshold and rate of temperature change criteria to estimate region-level probabilities of discomfort. Additionally, we show the impact of distinct weather patterns that intensify or abate thermal stress on comfort outcomes. Results show a near-universal overheating risk in summer DR events, where comfort outcomes are strongly influenced by rapid risk of comfort violations. In contrast, overall winter DR discomfort risk is lower, risk escalation is more gradual and shows greater sensitivity to event duration. These findings offer a data-driven quantification of comfort risk across diverse climates and building envelopes, demonstrating the need for region-specific DR scheduling and discomfort mitigation strategies tailored to local weather patterns and the performance of existing residential buildings.

Demand response↗
DOE OSTI2015

Pharmacology of smac mimetics; chemotype differentiation based on physical association with caspase regulators and cellular transport

Cellular levels of inhibitor of apoptosis (IAP) proteins are elevated in multiple human cancers and their activities often play a part in promoting cancer cell survival by blocking apoptotic pathways, controlling signal transduction pathways and contributing to resistance. These proteins function through interactions of their BIR (baculoviral IAP repeat) protein domains with pathway components and these interactions are endogenously antagonized by Smac/Diablo (second mitochondrial activator of caspases/direct IAP binding protein with low isoelectric point). This report describes development of synthetic smac mimetics (SM) and compares their binding, antiproliferative and anti-tumor activities. All dimeric antagonists inhibit in vitro smac tetrapeptide binding to recombinant IAP proteins, rescue IAP-bound caspase-3 activity and show anti-proliferative activity against human A875 melanoma cells. One heterodimeric SM, SM3, binds tightly to IAP proteins in vitro and slowly dissociates (greater than two hours) from these protein complexes compared to the other antagonists. In addition, in vitro SM anti-proliferation potency is influenced by ABCB1 transporter (ATP-binding cassette, sub-family B; MDR1, P-gp) activities and one antagonist, SM5, does not appear to be an ABCB1 efflux pump substrate. All dimeric smac mimetics inhibit the growth of human melanoma A875 tumors implanted in athymic mice at well-tolerated doses. One antagonist, SM4, shows broad spectrum in vivo anti-tumor activity and modulates known pharmacodynamic markers of IAP antagonism. These data taken together demonstrate the range of diverse dimeric IAP antagonist activities and supports their potential as anticancer agents. - Highlights: • We report a novel series of dimeric IAP antagonists with potent antitumor activities. • One chemotype induced markers of apoptosis and had antitumor activity in different tumor types. • Another chemotype demonstrated efficacy in a tumor model with elevated ABCB1 levels.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A Pathway Analysis Framework for Evaluating the Economic and Environmental Viability of Biomass-Based Plastic Production

Plastic production from fossil feedstocks (e.g., naphtha, coal, and natural gas) is not sustainable and causes known environmental impacts such as global warming. A possible solution is to shift production pathways to use biomass, which is a sustainable feedstock that can sequester atmospheric carbon dioxide. This study presents an optimization-based pathway analysis framework for evaluating the carbon footprints of the production of mainstream plastics from biomass and fossil feedstocks. We use the modeling framework to quickly navigate complex interdependencies that exist between the production pathways of different plastics and to determine pathways of minimum production cost under a range of carbon pricing scenarios. The framework interprets carbon prices as an exogenous taxation scheme or an endogenous negative value perceived by producers. The proposed approach reveals the biomass feedstock quantities needed to displace fossil counterparts and the plastics and technologies that should be prioritized. The framework can also be used for evaluating system-wide trade-offs between production costs and carbon footprints that arise from pathway interdependencies. We also evaluate hidden environmental impacts associated with the large-scale use of biomass as a feedstock, such as land use and water eutrophication that results from a significant increase in fertilizer use. Therefore, it is important to highlight that there are trade-offs between decarbonization and other environmental issues. Here, the proposed framework provides an integrative platform for basic techno-economic and life-cycle data that can be used for analyzing diverse scenarios and determining necessary technology targets (e.g., yields, footprints, and costs) to achieve required levels of decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Discovering High Entropy Alloy Electrocatalysts in Vast Composition Spaces with Multiobjective Optimization

High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO)-based virtual screening approaches focus on catalytic activity as the sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multiobjective BO framework for HEAs that simultaneously targets activity, cost-effectiveness, and entropic stabilization. With diversity-guided batch selection further boosting its data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to 10 elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Jack-of-all-trades effects drive biodiversity–ecosystem multifunctionality relationships in European forests

There is considerable evidence that biodiversity promotes multiple ecosystem functions (multifunctionality), thus ensuring the delivery of ecosystem services important for human well-being. However, the mechanisms underlying this relationship are poorly understood, especially in natural ecosystems. We develop a novel approach to partition biodiversity effects on multifunctionality into three mechanisms and apply this to European forest data. We show that throughout Europe, tree diversity is positively related with multifunctionality when moderate levels of functioning are required, but negatively when very high function levels are desired. For two well-known mechanisms, ‘complementarity’ and ‘selection’, we detect only minor effects on multifunctionality. Instead a third, so far overlooked mechanism, the ‘jack-of-all-trades’ effect, caused by the averaging of individual species effects on function, drives observed patterns. Simulations demonstrate that jack-of-all-trades effects occur whenever species effects on different functions are not perfectly correlated, meaning they may contribute to diversity–multifunctionality relationships in many of the world’s ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

UTILIZATION OF THE WAVEFRONT SENSOR AND SHORT-EXPOSURE IMAGES FOR SIMULTANEOUS ESTIMATION OF QUASI-STATIC ABERRATION AND EXOPLANET INTENSITY

Heretofore, the literature on exoplanet detection with coronagraphic telescope systems has paid little attention to the information content of short exposures and methods of utilizing the measurements of adaptive optics wavefront sensors. This paper provides a framework for the incorporation of the wavefront sensor measurements in the context of observing modes in which the science camera takes millisecond exposures. In this formulation, the wavefront sensor measurements provide a means to jointly estimate the static speckle and the planetary signal. The ability to estimate planetary intensities in as little as a few seconds has the potential to greatly improve the efficiency of exoplanet search surveys. For simplicity, the mathematical development assumes a simple optical system with an idealized Lyot coronagraph. Unlike currently used methods, in which increasing the observation time beyond a certain threshold is useless, this method produces estimates whose error covariances decrease more quickly than inversely proportional to the observation time. This is due to the fact that the estimates of the quasi-static aberrations are informed by a new random (but approximately known) wavefront every millisecond. The method can be extended to include angular (due to diurnal field rotation) and spectral diversity. Numerical experiments are performed with wavefront data from the AEOS Adaptive Optics System sensing at 850 nm. These experiments assume a science camera wavelength {lambda} of 1.1 {mu}, that the measured wavefronts are exact, and a Gaussian approximation of shot-noise. The effects of detector read-out noise and other issues are left to future investigations. A number of static aberrations are introduced, including one with a spatial frequency exactly corresponding the planet location, which was at a distance of Almost-Equal-To 3{lambda}/D from the star. Using only 4 s of simulated observation time, a planetary intensity, of Almost-Equal-To 1 photon ms{sup -1}, and a stellar intensity of Almost-Equal-To 10{sup 5} photons ms{sup -1} (contrast ratio 10{sup 5}), the short-exposure estimation method recovers the amplitudes' static aberrations with 1% accuracy, and the planet brightness with 20% accuracy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Genomic prediction of hybrid performance for agronomic traits in sorghum

Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76–0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12–90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Cybersecurity Automated Information Extraction Techniques: Drawbacks of Current Methods, and Enhanced Extractors

We address a crucial element of applied information extraction—accurate identification of basic security entities in text-—by evaluating previous methods and presenting new labelers. Our survey reveals that the previous efforts have not been tested on documents similar to the targeted sources (news articles, blogs, tweets, etc.) and that no sufficiently large publicly available annotated corpus of these documents exists. By assembling a representative test corpus, we perform a quantitative evaluation of previous methods in a realistic setting, revealing an overall lack of recall, and giving insight to the models' beneficial and inhibiting elements. In particular, our results show that many previous efforts overfit to the non-representative test corpora in this domain. Informed by this evaluation, we present three novel cyber entity extractors, which seek to leverage the available labeled data but remain worthwhile on the more diverse documents encountered in the wild. Each new model increases the state of the art in recall, with maximal or near maximal F1 score. Our results establish that the state of the art in cyber entity tagging is characterized by F1 = 0.61.

Bridges, Robert↗
DOE OSTI2017

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different from that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.

Li, Minjing↗
DOE OSTI2021

Directional Laplacian Centrality for Cyber Situational Awareness

Cyber operations is drowning in diverse, high-volume, multi-source data. To get a full picture of current operations and identify malicious events and actors, analysts must see through data generated by a mix of human activity and benign automated processes. Although many monitoring and alert systems exist, they typically use signature-based detection methods. We introduce a general method rooted in spectral graph theory to discover patterns and anomalies without a priori knowledge of signatures. We derive and propose a new graph-theoretic centrality measure based on the derivative of the graph Laplacian matrix in the direction of a vertex. To build intuition about our measure, we show how it identifies the most central vertices in standard network datasets and compare to other graph centrality measures. Finally, we focus our attention on studying its effectiveness in identifying important IP addresses in network flow data. Using both real and synthetic network flow data, we conduct several experiments to test our measure’s sensitivity to two types of injected attack profiles and show that vertices participating in injected attack profiles exhibit noticeable changes in our centrality measures, even when the injected anomalies are relatively small, and in the presence of simulated network dynamics.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Value of Information App (Value of Information App for Binary Geothermal Decisions and Binary Geothermal Possibilities) (Negative/Positive) [SWR-25-15]

Code base to run Streamlit Value of Information App for binary decision with geothermal techno economics. An open-source VOI app that models binary decisions (e.g. do something (drill) or walk away (do nothing)) and binary geothermal scenarios (positive or negative) has been developed. Users can input their anticipated economic values (profits or losses) directly into the value matrix to represent all four combinations of these actions and geothermal possibilities. VOI in general requires probabilities to be assigned for “probability of success”, or probability of experiencing a positive geothermal scenario versus negative. The users of the App can toggle this probability of success both in the demo problem and in the Value of Imperfect Information problem. The VOI App allows users to upload their own labeled data to evaluate how well it allows them to distinguish between positive versus negative sites. We have been using IGNENIOUS data to test and demonstrate; industry members have prepared their own labeled data, and have present their examples from diverse use cases at a conference workshop. The VOI App is open to the public at: https://voigeothermalrising.streamlit.app

Trainor-Guitton, Whitney [National Renewable Energ↗
DOE OSTI2024

MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

43 PARTICLE ACCELERATORS↗
NASA NTRS1978

The management of energy utilization in a spacecraft tracking station and its industrial applications

The mission of a tracking station within the NASA/Jet Propulsion Deep Space Network is characterized by a wide diversity of spacecraft types, communications ranges, and data accuracy requirements. In the present paper, the system architecture, communications techniques, and operators interfaces for a utility controller are described. The control equipment as designed and installed is meant to be a tool to study applications of automated control in the dynamic environment of a tracking station. It allows continuous experimenting with new technology without disruption of the tracking activities.

Reynolds, R.↗
NASA NTRS1980

Search and rescue emergency locating transmitter detection/location procedure via TIROS satellite

A procedure is described which works effectively to detect and locate emergency locating transmitters (ELTs) and emergency position indicating radio beacons (EPIRBs) in a multisignal environment. Using data generated from several manufactured ELTs with diverse superimposed Doppler curves, as many as 9 simultaneous ELTs can be detected and located at a variety of signal strengths. It is noted that average position errors of 10 km are attainable today at signal power to noise spectral density ratios as low as 17 dB-Hz.

Wren, P. E.↗
NASA NTRS2003

HRTEM and EFTEM Observations of Matrix in the Oxidized CV3 Chondrite ALH 84028: Implications for the Origins of Matrix Olivines

The determination of the nature, distribution, and origin of organic material in carbonaceous chondrites is fundamental to understanding early solar nebular conditions and the origin of life. Using a variety of extraction techniques, followed by detailed chemical analysis, an extensive suite of organic compounds has been identified in carbonaceous chondrites. These data have provided key information on the diversity and isotopic composition of the organic component in chondrites. However, one disadvantage of extraction techniques is that all information regarding the spatial distribution of the organics on a fine scale is lost. This is especially important for the insoluble macromolecular carbon, which constitutes approximately 70% of the carbon in carbonaceous chondrites such as Murchison. The distribution and mineralogical associations may provide important constraints on the possible origins of the carbonaceous material. Our previous studies of the CV3 chondrites Allende and Vigarano have demonstrated that energy filtered transmission electron microscopy (EFTEM), combined with high resolution TEM (HRTEM) are powerful tools for the in situ characterization of insoluble organic matter in carbonaceous chondrites. In this study, we have used SEM and TEM techniques to characterize the matrix mineralogy of the CV3 chondrite ALH 84028 and examine the distribution and mineralogical associations of carbon. We are especially interested in establishing whether the occurrence of poorly graphitized carbon (PGC), observed in Allende matrix olivines, is common to all oxidized CV3 chondrites or is a unique feature of Allende.

Abreu, Neyda M.↗
NASA NTRS2005

A Thorium-rich Mare Basalt Rock Fragment from the Apollo 12 Regolith: A Sample from a Young Procellarum Flow?

In this abstract, we report on the composition, mineralogy and petrography of a basaltic rock fragment, 12032,366-18, found in the Apollo 12 regolith. Age data, collected as part of an investigation by Barra et al., will be presented in detail in. Here, only the age dating result is summarized. This rock fragment garnered our attention because it is significantly enriched in incompatible elements, e.g., 7 ppm thorium, compared to other known lunar basalts. Its mineral- and trace-element chemistry set it apart from other Apollo 12 basalts and indeed from all Apollo and Luna basalts. What makes it potentially very significant is the possibility that it is a sample of a relatively young, thorium-rich basalt flow similar to those inferred to occur in the Procellarum region, especially northwestern Procellarum, on the basis of Lunar Prospector orbital data. Exploiting the lunar regolith for the diversity of rock types that have been delivered to a landing site by impact processes and correlating them to their likely site of origin using remote sensing will be an important part of future missions to the Moon. One such mission is Moonrise, which would collect regolith samples from the South Pole-Aitken Basin, concentrating thousands of rock fragments of 3-20 mm size from the regolith, and returning the samples to Earth.

Jolliff, B. L.↗