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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

BILLIARDS: A Demonstration Mission for Hundred-Meter Class Near Earth Asteroid Disruption

Currently, no planetary defense demonstration mission has ever been flown. While Nuclear Explosive Devices (NEDs) have significantly more energy than a kinetic impactor launched directly from Earth, they present safety and political complications, and therefore may only be used when absolutely necessary. The Baseline Instrumented Lithology Lander, Inspector, and Asteroid Redirection Demonstration System (BILLIARDS) is a demonstration mission for planetary defense, which is capable of delivering comparable energy to the lower range of NED capabilities in the form of a safer kinetic impactor. A small asteroid (<10m) is captured by a spacecraft, which greatly increases the mass available as a kinetic impactor, without the need to bring all of the mass out of Earth's gravity well. The small asteroid is then deflected onto a collision course with a larger (approx. 100m) asteroid. This collision will deflect or disrupt the larger asteroid. To reduce the cost and complexity, an asteroid pair which has a natural close approach is selected.

Planetary Defense↗
NASA NTRS2015

Analysis of Potentially Hazardous Asteroids

The National Aeronautics and Space Administration initiated a new project focused on Planetary Defense on October 1, 2014. The new project is funded by NASAs Near Earth Object Program (Lindley Johnson, Program Executive). This presentation describes the objectives, functions and plans of four tasks encompassed in the new project and their inter-relations. Additionally, this project provides for outreach to facilitate partnerships with other organizations to help meet the objectives of the planetary defense community. The four tasks are (1) Characterization of Near Earth Asteroids, (2) Physics-Based Modeling of Meteor Entry and Breakup (3) Surface Impact Modeling and (4) Physics-Based Impact Risk Assessment.

Asteroids↗
DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗
DOE OSTI2022

Genetic mapping of sorghum resistance to an Illinois isolate of Colletotrichum sublineola

Anthracnose leaf blight (ALB) is an economically important disease of sorghum [Sorghum bicolor (L.) Moench] caused by the fungal pathogen Colletotrichum sublineola Henn. ex Sacc. & Trotter. Although qualitative and quantitative resistance have been identified for ALB, the usefulness of resistance loci differs depending on the pathogen pathotype. Identifying resistance effective against unique pathogen pathotypes is critical to managing ALB, as the disease is managed primarily through the deployment of host resistance. We isolated C. sublineola from ALB-infected leaves collected in Illinois and found that the strain was a novel pathotype, as it produced a unique combination of virulence against a set of differential lines. Using this isolate, we inoculated 579 temperate-adapted sorghum conversion lines in 2019 and 2020. We then conducted a genome-wide association study (GWAS) and a metabolic pathway analysis using the Pathway Associated Study Tool (PAST). We identified 47 significant markers distributed across all chromosomes except chromosome 8. We identified 32 candidate genes based on physical proximity with significant markers, some of which have a known role in host defense. We identified 47 pathways associated with ALB resistance, indicating a role for secondary metabolism in defense to ALB. Our results are important to improve the understanding of the genetic basis of ALB resistance in sorghum and highlight the importance of developing durable resistance to ALB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

IntraShuffler: A Privacy Preserving Framework for Heterogeneous DP Federated Learning

Heterogeneous Differential Privacy (HDP) in Federated Learning (FL) allows clients to select individual privacy budgets () according to institutional policies and data sensitivity. In practice, many HDP-FL systems employ -aware server aggregation to improve model utility by re-weighting client updates according to their declared privacy budgets. However, gradient updates in FL retain structural patterns induced by non-independent and identically-distributed (non-IID) data, and these additional signals exposed by -aware aggregation create new opportunities for inference by an honest-but-curious server. In this work, we first show that a server equipped with gradient denoising and surrogate modeling can mount a Privacy Inference Attack that infers distributional attributes of clients and links updates from the same client across training rounds, measured via surrogate inference accuracy and linkage success, under realistic knowledge constraints. The Shuffle-Model has been widely studied as a defense against such inference risks by anonymizing update sources, but it is fundamentally incompatible with HDP-FL -aware aggregation. To address this challenge, we propose IntraShuffler, a middleware defense framework designed for HDP-FL systems. IntraShuffler introduces a privacy-aware shuffling mechanism that groups clients into privacy-compatible buckets and performs parameter-level shuffling within each bucket to disrupt persistent gradient structure while preserving -aware aggregation. Experiments across four different datasets show that IntraShuffler reduces gradient recoverability by over 60% and decreases surrogate inference accuracy from 0.78 to 0.33 while maintaining comparable model utility across multiple FL aggregation rules.

Riya, Farhin Farhad [ORNL]↗
DOE OSTI2020

MimicGAN: Robust Projection onto Image Manifolds with Corruption Mimicking

In the past few years, Generative Adversarial Networks (GANs) have dramatically advanced our ability to represent and parameterize high-dimensional, non-linear image manifolds. As a result, they have been widely adopted across a variety of applications, ranging from challenging inverse problems like image completion, to problems such as anomaly detection and adversarial defense. A recurring theme in many of these applications is the notion of projecting an image observation onto the manifold that is inferred by the generator. In this context, Projected Gradient Descent (PGD) has been the most popular approach, which essentially optimizes for a latent vector that minimizes the discrepancy between a generated image and the given observation. However, PGD is a brittle optimization technique that fails to identify the right projection (or latent vector) when the observation is corrupted, or perturbed even by a small amount. Such corruptions are common in the real world, for example images in the wild come with unknown crops, rotations, missing pixels, or other kinds of non-linear distributional shifts which break current encoding methods, rendering downstream applications unusable. To address this, we propose corruption mimicking—a new robust projection technique, that utilizes a surrogate network to approximate the unknown corruption directly at test time, without the need for additional supervision or data augmentation. The proposed method is significantly more robust than PGD and other competing methods under a wide variety of corruptions, thereby enabling a more effective use of GANs in real-world applications. Finally, more importantly, we show that our approach produces state-of-the-art performance in several GAN-based applications—anomaly detection, domain adaptation, and adversarial defense, that benefit from an accurate projection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Accident-Tolerant Fuel

Advanced light water reactor (LWR) fuels have been developed incrementally for more than 60 years before the term Accident Tolerant Fuel (ATF) was created. There are many different categories of ATF concepts, which range from near-term marginal enhancements to fission gas release in fuel or hydrogen pickup in the cladding, to transformational fuel types with new engineered fission product barriers. In this work we characterize these different types of ATF, and give several important examples for each.We conclude that transformational ATF concepts have the greatest potential to enhance the traditional definition of defense-in-depth by enhancing current barriers and/or by providing additional barriers to fission product release. This objective can primarily be achieved by introducing a new fission product barrier that enhances defense-in-depth by design, for example the added barriers to fission product release in some engineered ATF concepts. We recommend future gap analyses and a phenomena identification and ranking to assess the applicability of existing safe acceptable fuel design limits and the standard review plan to specific ATF concepts.

Brown, Nicholas↗
DOE OSTI2021

Characterization of Two Extraordinary AmLi Neutron Sources

Two legacy AmLi sources, MRC-101 and MRC-103, are routinely used for neutron detector characterization and testing campaigns that Pacific Northwest National Laboratory manages for the Defense Threat Reduction Agency within the U.S. Department of Defense. However, applicability of source measurement data has been substantially limited due to the lack of original manufacturer documentation and cross comparison to other sources. This paper summarizes results of the measurement campaign conducted to better quantify source radionuclide content, neutron energy spectrum and emission rate of the AmLi sources. The source characterization study consisted of three major consecutive measurement exercises. First, gamma spectrometry measurements using a high purity germanium detector were used to estimate the radionuclide content and potential impurities of the AmLi sources. Then neutron spectral measurements were taken to determine the unique neutron energy distribution. Finally, assessments of the total neutron yields of the sources were made with measurements in a neutron well counter. The neutron detection efficiency for these measurements was determined via detailed Monte Carlo modeling based on the neutron energy distribution measured with the rotating neutron spectrometer. The most exciting and unexpected finding of the study was a significant contamination of the source material with beryllium, contributing up to 17% to the total neutron emission rate and correspondingly changing the neutron energy spectrum. Also, the obtained lithium-only portion of the measured energy distribution of the sources was compared against several AmLi spectra previously reported by different researchers.

AWCC, AmLi, beryllium contamination, neutron spect↗
DOE OSTI2026

Longitudinal Multi-omics Reveal Phase-Dependent Viral Adaptive Strategies and Functional Potential During Formation of Algal-bacterial Granular Sludge

Virus-host interactions within microbial aggregates critically influence microbiome function and stability, yet how physicochemical stresses shape the interactive dynamics remains largely unexplored. Here, we investigated virus–host dynamics during the transition of algal-bacterial granular sludge (ABGS) from activated sludge under continuous hydraulic shear using integrated metagenomics and metatranscriptomics. Hydraulic stress initially reduced host a-diversity, which coincided with a marked increase in viral lysogenicity. During this host diversity bottleneck, viral microdiversity increased, and genes related to virion structure and DNA packaging were under positive selection (pN/pS >1). As host diversity recovered, viral microdiversity declined, while viral anti-defense systems (ADS) significantly increased in abundance. Lagged correlation analysis revealed a significant positive correlation between viral ADS and host defense systems (DS), suggesting an evolutionary arms race. Furthermore, active lysogenic infections were accompanied by enrichment of DS and auxiliary viral genes (AVGs) involved in genetic information processing and amino acid metabolism, potentially enhancing host fitness. Overall, our study unveils a phase-dependent co-evolutionary interplay between viruses and hosts during ABGS formation, providing insights into the development and maintenance of microbial structural and functional resilience in engineered ecosystems.

Qi, Huiyuan↗
DOE OSTI2022

BefA, a microbiota-secreted membrane disrupter, disseminates to the pancreas and increases β cell mass

Microbiome dysbiosis is a feature of diabetes, but how microbial products influence insulin production is poorly understood. Here, we report the mechanism of BefA, a microbiome-derived protein that increases proliferation of insulin-producing β cells during development in gnotobiotic zebrafish and mice. BefA disseminates systemically by multiple anatomic routes to act directly on pancreatic islets. We detail BefA’s atomic structure, containing a lipid-binding SYLF domain, and demonstrate that it permeabilizes synthetic liposomes and bacterial membranes. A BefA mutant impaired in membrane disruption fails to expand β cells, whereas the pore-forming host defense protein, Reg3, stimulates β cell proliferation. Our work demonstrates that membrane permeabilization by microbiome-derived and host defense proteins is necessary and sufficient for β cell expansion during pancreas development, potentially connecting microbiome composition with diabetes risk.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A tri-level optimization model for interdependent infrastructure network resilience against compound hazard events

Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges in this problem space, we propose a novel policy-guided tri-level optimization model applied to a proof-of-concept case study with fuel distribution and transportation networks – encompassing one realistic network; one fictitious, yet realistic network; as well as networks drawn from three synthetic distributions. Mathematically, our approach takes the form of a defender-attacker-defender (DAD) model—a multi-agent tri-level optimization, comprised of a defender, attacker, and an operator acting in sequence. Here, in this study, our notional operator may choose proxy actions to operate an interdependent system comprised of fuel terminals and gas stations (functioning as supplies) and a transportation network with traffic flow (functioning as demand) to minimize unmet demand at gas stations. A notional attacker aims to hypothetically disrupt normal operations by reducing supply at the supply terminals, and the notional defender aims to identify best proxy defense policy options which include hardening supply terminals or allowing alternative distribution methods such as trucking reserve supplies. We solve our DAD formulation at a metropolitan scale and present practical defense policy insights against hypothetical compound hazards. We demonstrate the generalizability of our framework by presenting results for a realistic network; a fictitious, yet realistic network; as well as for three networks drawn from synthetic distributions. Additionally, we demonstrate the scalability of the framework by investigating runtime performance as a function of the network size. Steps for future research are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

America’s Cutting Edge CNC machining and metrology training

This paper describes the workforce development activities supported by America’s Cutting Edge (ACE), a national initiative for machine tool technology development and advancement. ACE is supported by the Department of Defense Industrial Base Analysis and Sustainment (IBAS) program from the Office of Industrial Policy. Both the online and in-person components of the computer numerically controlled (CNC) machining and metrology training programs are summarized and participation information is provided.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Life strategies for Aminicenantia in subseafloor oceanic crust

Abstract After decades studying the microbial “deep biosphere” in subseafloor oceanic crust, the growth and life strategies in this anoxic, low energy habitat remain poorly described. Using both single cell genomics and metagenomics, we reveal the life strategies of two distinct lineages of uncultivated Aminicenantia bacteria from the basaltic subseafloor oceanic crust of the eastern flank of the Juan de Fuca Ridge. Both lineages appear adapted to scavenge organic carbon, as each have genetic potential to catabolize amino acids and fatty acids, aligning with previous Aminicenantia reports. Given the organic carbon limitation in this habitat, seawater recharge and necromass may be important carbon sources for heterotrophic microorganisms inhabiting the ocean crust. Both lineages generate ATP via several mechanisms including substrate-level phosphorylation, anaerobic respiration, and electron bifurcation driving an Rnf ion translocation membrane complex. Genomic comparisons suggest these Aminicenantia transfer electrons extracellularly, perhaps to iron or sulfur oxides consistent with mineralogy of this site. One lineage, called JdFR-78, has small genomes that are basal to the Aminicenantia class and potentially use “primordial” siroheme biosynthetic intermediates for heme synthesis, suggesting this lineage retain characteristics of early evolved life. Lineage JdFR-78 contains CRISPR-Cas defenses to evade viruses, while other lineages contain prophage that may help prevent super-infection or no detectable viral defenses. Overall, genomic evidence points to Aminicenantia being well adapted to oceanic crust environments by taking advantage of simple organic molecules and extracellular electron transport.

Environmental Sciences & Ecology↗
DOE OSTI2020

A deubiquitylase with an unusually high-affinity ubiquitin-binding domain from the scrub typhus pathogen Orientia tsutsugamushi

Ubiquitin mediated signaling contributes critically to host cell defenses during pathogen infection. Many pathogens manipulate the ubiquitin system to evade these defenses. Here we characterize a likely effector protein bearing a deubiquitylase (DUB) domain from the obligate intracellular bacterium Orientia tsutsugamushi, the causative agent of scrub typhus. The Ulp1-like DUB prefers ubiquitin substrates over ubiquitin-like proteins and efficiently cleaves polyubiquitin chains of three or more ubiquitins. The co-crystal structure of the DUB (OtDUB) domain with ubiquitin revealed three bound ubiquitins: one engages the S1 site, the second binds an S2 site contributing to chain specificity and the third binds a unique ubiquitin-binding domain (UBD). The UBD modulates OtDUB activity, undergoes a pronounced structural transition upon binding ubiquitin, and binds monoubiquitin with an unprecedented ~5 nM dissociation constant. The characterization and high-resolution structure determination of this enzyme should aid in its development as a drug target to counter Orientia infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Single nucleotide variants drive evolutionary phage-host arms race in anaerobic carbon dioxide-converting microbiome

Microbial bioconversions are shaped by environmental perturbations and the adaptation of resident microbiomes. Prokaryotes coexist with bacteriophages, yet their coevolutionary trajectories remain underexplored. Here, we investigate the effects of a cultivation vessel leak on an anaerobic consortium performing carbon dioxide reduction. Using time-series shotgun metagenomic sequencing, we reconstruct microbial and viral genomes to track community shifts. We further apply single-nucleotide variant profiling and CRISPR array analysis to monitor viral microdiversity and host defense mechanisms. After bioaugmentation restores bioconversion efficiency, the consortium undergoes pronounced restructuring, with new dominant taxa emerging from the rare biosphere. We identify patterns consistent with phage predation selectively removing certain species, while others exhibit resilience to infection. This shift aligns with a widespread viral outbreak and a transient increased frequency of single nucleotide variants in bacterial CRISPR–Cas defense genes. Expansion of CRISPR spacers further supports that CRISPR-mediated processes influence microbial resilience. Concurrently, phages infecting resilient hosts exhibited adaptive evolution, marked by high genetic heterogeneity. Selective pressure varies across their genomes, targeting infectivity genes and protospacer-adjacent motifs. These findings highlight a dynamic evolutionary arms race driven by the selection of beneficial genetic variants, providing a mechanistic framework for multi-omics investigations, and informing biotechnological applications, including phage-based microbiome manipulation.

Ghiotto, G↗
DOE OSTI2022

Mechanisms of woody-plant mortality under rising drought, CO 2 and vapour pressure deficit

Drought-associated woody plant mortality may have increased over the past several decades, and is projected to increase in the future, impacting terrestrial climate forcing, biodiversity, and resource availability. The mechanisms underlying such mortality, however, are debated owing to interactions between multiple drivers and mechanisms. In this work, we synthesize knowledge of drought-related tree mortality under a warming and drying atmosphere with rising atmospheric CO 2 . Drought-associated mortality results from the depletion of pools of water and carbon within a plant and declines in their fluxes relative to demand by living tissues. These pools and fluxes are interdependent and underlay plant defenses against biotic agents. Death via failure to maintain a positive water balance is particularly dependent on soil-to-root conductance, capacitance, vulnerability to hydraulic failure, cuticular water losses, and dehydration tolerance, all of which could be exacerbated by reduced carbon supply rates to support cellular survival e.g. the carbon starvation process. The depletion of plant water and carbon pools accelerates under rising vapor pressure deficit; however, increasing CO 2 can mitigate these impacts. Advancing knowledge and reducing predictive uncertainties requires studies that integrate carbon, water, and defensive processes, and utilize a range of experimental and modeling approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A bipartite bacterial virulence factor targets the complement system and neutrophil activation

Abstract The complement system and neutrophils constitute the two main pillars of the host innate immune defense against infection by bacterial pathogens. Here, we identify T-Mac, a novel virulence factor of the periodontal pathogen Treponema denticola that allows bacteria to evade both defense systems. We show that T-Mac is expressed as a pre-protein that is cleaved into two functional units. The N-terminal fragment has two immunoglobulin-like domains and binds with high affinity to the major neutrophil chemokine receptors FPR1 and CXCR1, blocking N -formyl-Met-Leu-Phe- and IL-8-induced neutrophil chemotaxis and activation. The C-terminal fragment functions as a cysteine protease with a unique proteolytic activity and structure, which degrades several components of the complement system, such as C3 and C3b. Murine infection studies further reveal a critical T-Mac role in tissue damage and inflammation caused by bacterial infection. Collectively, these results disclose a novel innate immunity-evasion strategy, and open avenues for investigating the role of cysteine proteases and immunoglobulin-like domains of gram-positive and -negative bacterial pathogens.

Kurniyati, Kurni↗
DOE OSTI2023

Inferring adversarial behaviour in cyber‐physical power systems using a Bayesian attack graph approach

Abstract Highly connected smart power systems are subject to increasing vulnerabilities and adversarial threats. Defenders need to proactively identify and defend new high‐risk access paths of cyber intruders that target grid resilience. However, cyber‐physical risk analysis and defense in power systems often requires making assumptions on adversary behaviour, and these assumptions can be wrong. Thus, this work examines the problem of inferring adversary behaviour in power systems to improve risk‐based defense and detection. To achieve this, a Bayesian approach for inference of the Cyber‐Adversarial Power System (Bayes‐CAPS) is proposed that uses Bayesian networks (BNs) to define and solve the inference problem of adversarial movement in the grid infrastructure towards targets of physical impact. Specifically, BNs are used to compute conditional probabilities to queries, such as the probability of observing an event given a set of alerts. Bayes‐CAPS builds initial Bayesian attack graphs for realistic power system cyber‐physical models. These models are adaptable using collected data from the system under study. Then, Bayes‐CAPS computes the posterior probabilities of the occurrence of a security breach event in power systems. Experiments are conducted that evaluate algorithms based on time complexity, accuracy and impact of evidence for different scales and densities of network. The performance is evaluated and compared for five realistic cyber‐physical power system models of increasing size and complexities ranging from 8 to 300 substations based on computation and accuracy impacts.

Sahu, Abhijeet↗