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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 271 records · Page 15

Extravehicular Activity on the Lunar Surface: Mapping Mitigation Risk Consequence for Crew Needing Assistance or Rescue

The lunar environment offers unique challenges for human health and safety over the course of performing Extravehicular Activities (EVAs) during early Artemis missions. Driver medical conditions leading to an injured EVA crewmember needing assistance or rescue were analyzed and correlated to established, defined consequence categories. Catastrophic Drivers were identified, and three mitigation strategies were analyzed to determine if there was a potential change in consequence with their application. Risk consequence across the mitigations were compared with each other and the original risk without mitigations. Mitigations were further evaluated in a broader context with prospective preventions to understand the design and risk trade space associated with an early Artemis EVA.

Risk↗

Extravehicular Activity on the Lunar Surface: Mapping Mitigation Risk Consequence for Crew Needing Assistance or Rescue

The lunar environment offers unique challenges for human health and safety over the course of performing Extravehicular Activities (EVAs) during early Artemis missions. Driver medical conditions leading to an injured EVA crewmember needing assistance or rescue were analyzed and correlated to established, defined consequence categories. Catastrophic Drivers were identified, and three mitigation strategies were analyzed to determine if there was a potential change in consequence with their application. Risk consequence across the mitigations were compared with each other and the original risk without mitigations. Mitigations were further evaluated in a broader context with prospective preventions to understand the design and risk trade space associated with an early Artemis EVA.

Risk↗

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗

Simulating Z 2 lattice gauge theory on a quantum computer

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of Z 2 gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of 6 and is therefore essential for obtaining reliable masses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Healthy Indoor Air Quality: A Guide to Understanding Pollutants in Extreme Cold Climates

Internal air quality management through commonly supported recommendations in extreme cold weather climates is complicated by cold air infiltration. Air filtration and IAQ monitoring, through central and stand-alone systems can improve internal air quality to the benefit of occupant health and safety. This fact sheet includes reference information for pollutants, sources, health effects, and mitigation strategies.

cold climate↗

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

Conceptual Thermal Control System Design for a Lunar Surface Habitat

NASA is currently considering a Surface Habitat (SH) to provide 30-60 day habitability for a crew of up to four to explore the Lunar surface at a South Pole location. The SH concept is comprised of an inflatable volume for the habitable space, a metallic airlock and a descent stage with access to a pressurized rover and other surface assets provided through the airlock. A conceptual architecture for the SH Thermal Control System (TCS) is presented with resource estimates. The TCS design employs a dual loop architecture with a water/propylene glycol mix for the internal crew spaces with a freeze tolerant coolant utilized for the external loop. The internal loop is partitioned into low and moderate temperature service with a sublimator available for operational scenarios prior to thermal radiator deployment (or redeployment). Analytical models are utilized to optimize radiator geometry/orientation as well as the TCS internal/external loop architecture. Heritage hardware is utilized for the TCS concept wherever possible and low mass, dust tolerant, deployable/retractable thermal radiators (in partial gravity) present a technology challenge. The TCS must accommodate infrequent eclipse periods lasting up to 100 hours in duration and mitigation strategies to reduce the energy needed to maintain the SH and associated systems above survival temperature limits during this period are explored. Mitigation options include retractable or freezable radiators, other reconfigurable radiator geometries, alternate fluids, re-generable heat exchangers, temperature excursions, thermal energy storage and optimized inflatable optical properties. Finally, TCS sensitivity to SH Electrical Power System (EPS) growth is considered with both operational and dormant impacts quantified.

Thermal Control↗

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗

Reducing the risks of wildfires

Anyone who has lived in New Mexico for at least a year realizes that the Land of Enchantment has six seasons. In addition to the four seasons everyone else has, we have a wildfire season, which typically comes during late spring and early summer. Wildfires sometimes even last through the monsoon season, when thunderstorms are lighter than usual. Wildfires, it seems, are inevitable in Los Alamos and the surrounding communities that make up part of northern New Mexico. In recent history, the 2000 Cerro Grande Fire destroyed 150,000 acres (including 7,500 acres of Laboratory property) and 235 Los Alamos homes. In 2011, the Las Conchas Fire burned more than 156,000 acres and threatened Los Alamos and the Lab. To minimize the chances of wildfires and to strengthen defenses against wildfires, the Laboratory every year carries out various fire-mitigation strategies throughout its 42 square miles.

54 ENVIRONMENTAL SCIENCES↗

Factors Impacting Habitable Volume Requirements: Results from the 2011 Habitable Volume Workshop

This report documents the results of the Habitable Volume Workshop held April 18-21, 2011 in Houston, TX at the Center for Advanced Space Studies-Universities Space Research Association. The workshop was convened by NASA to examine the factors that feed into understanding minimum habitable volume requirements for long duration space missions. While there have been confinement studies and analogs that have provided the basis for the guidance found in current habitability standards, determining the adequacy of the volume for future long duration exploration missions is a more complicated endeavor. It was determined that an improved understanding of the relationship between behavioral and psychosocial stressors, available habitable and net habitable volume, and interior layouts was needed to judge the adequacy of long duration habitat designs. The workshop brought together a multi-disciplinary group of experts from the medical and behavioral sciences, spaceflight, human habitability disciplines and design professionals. These subject matter experts identified the most salient design-related stressors anticipated for a long duration exploration mission. The selected stressors were based on scientific evidence, as well as personal experiences from spaceflight and analogs. They were organized into eight major categories: allocation of space; workspace; general and individual control of environment; sensory deprivation; social monotony; crew composition; physical and medical issues; and contingency readiness. Mitigation strategies for the identified stressors and their subsequent impact to habitat design were identified. Recommendations for future research to address the stressors and mitigating design impacts are presented.

Simon, M.↗

Decision Gate Process for Assessment of a Technology Development Portfolio

The NASA Dust Management Project (DMP) was established to provide technologies (to TRL 6 development level) required to address adverse effects of lunar dust to humans and to exploration systems and equipment, which will reduce life cycle cost and risk, and will increase the probability of sustainable and successful lunar missions. The technology portfolio of DMP consisted of different categories of technologies whose final product is either a technology solution in itself, or one that contributes toward a dust mitigation strategy for a particular application. A Decision Gate Process (DGP) was developed to assess and validate the achievement and priority of the dust mitigation technologies as the technologies progress through the development cycle. The DGP was part of continuous technology assessment and was a critical element of DMP risk management. At the core of the process were technology-specific criteria developed to measure the success of each DMP technology in attaining the technology readiness levels assigned to each decision gate. The DGP accounts for both categories of technologies and qualifies the technology progression from technology development tasks to application areas. The process provided opportunities to validate performance, as well as to identify non-performance in time to adjust resources and direction. This paper describes the overall philosophy of the DGP and the methodology for implementation for DMP, and describes the method for defining the technology evaluation criteria. The process is illustrated by example of an application to a specific DMP technology.

Kohli, Rajiv↗

Decision Gate Process for Assessment of a NASA Technology Development Portfolio

The NASA Dust Management Project (DMP) was established to provide technologies (to Technology Readiness Level (TRL) 6) required to address adverse effects of lunar dust to humans and to exploration systems and equipment, to reduce life cycle cost and risk, and to increase the probability of sustainable and successful lunar missions. The technology portfolio of DMP consisted of different categories of technologies whose final product was either a technology solution in itself, or one that contributes toward a dust mitigation strategy for a particular application. A Decision Gate Process (DGP) was developed to assess and validate the achievement and priority of the dust mitigation technologies as the technologies progress through the development cycle. The DGP was part of continuous technology assessment and was a critical element of DMP risk management. At the core of the process were technology-specific criteria developed to measure the success of each DMP technology in attaining the technology readiness levels assigned to each decision gate. The DGP accounts for both categories of technologies and qualifies the technology progression from technology development tasks to application areas. The process provided opportunities to validate performance, as well as to identify non-performance in time to adjust resources and direction. This paper describes the overall philosophy of the DGP and the methodology for implementation for DMP, and describes the method for defining the technology evaluation criteria. The process is illustrated by example of an application to a specific DMP technology.

Kohli, Rajiv↗

Pre- and Post-Production Processes Increasingly Dominate Greenhouse Gas Emissions From Agri-Food Systems

We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (GtCO2 eq. yr(exp -1)), corresponding to 31%(range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 GtCO2 eq. yr(exp -1); emissions from land use change, due to deforestation and peatland degradation, were 3.5 GtCO2 eq. yr(exp -1); and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 GtCO2 eq. yr(exp -1). Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and postproduction processes emitted the most CO2 (3.9 GtCO2 yr(exp -1)), preceding land use change (3.3 GtCO2 yr(exp -1)) and farm gate (1.2 GtCO2 yr(exp -1)) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 MtCH4 yr(exp -1)) and of nitrous oxide (7.8 MtN2Oyr(exp -1)). Pre- and post-production processes were also significant emitters of methane (49 MtCH4 yr(exp -1)), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 GtCO2 eq. yr(exp -1)). They also more than doubled in non-Annex I parties (to 3.5 GtCO2 eq. yr(exp -1)), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 MtCO2 eq. yr(exp -1)), the USA (700 MtCO2 eq. yr(exp -1)) and the EU-27 (600 MtCO2 eq. yr(exp -1)). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM; FAO, 2021a), with annual updates.

FAOSTAT agri-food systems emissions database↗

Security Vulnerability and Mitigation in Photovoltaic Systems

Software and firmware vulnerabilities pose security threats to photovoltaic (PV) systems. When patches are not available or cannot be timely applied to fix vulnerabilities, it is important to mitigate vulnerabilities such that they cannot be exploited by attackers or their impacts will be limited when exploited. However, the vulnerability mitigation problem for PV systems has received little attention. This paper analyzes known security vulnerabilities in PV systems, proposes a multi-level mitigation framework and various mitigation strategies including neural network-based attack detection inside inverters, and develops a prototype system as a proof-of-concept for building vulnerability mitigation into PV system design.

14 SOLAR ENERGY↗

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.

DeWitte, Lisa↗

Assured Contingency Landing Management for Advanced Air Mobility

Advanced Air Mobility (AAM) is quickly developing as a new air transportation system that moves people and packages in the regions previously not / less served by the current aviation systems. Such AAM must operate safely despite the potential to encounter hazards and experience anomalies and failures in-flight. It becomes especially important to have systematic auto-mitigation strategies to perform safe contingency actions in AAM flight operations, as pilots have limited Situational Awareness (SA) and limited time to make prompt decisions when encountering failures/anomalies in high-density low altitude airspace. This paper presents Assured Contingency Landing Management (ACLM) with an online landing strategy selection to decide between the following three options when a contingency landing is required: (1) Return-to-launch landing site, (2) Land immediately at a nearby clear but unprepared site, (3) Land at a prepared landing site from the approximate footprint. Our presented algorithm shows a real-time auto-mitigation loop with multiple threads that run simultaneously to check controllability, reachability, and intermediate decisions to hold/ loiter or continue the flight plan as the landing strategy solution is being computed. Case study simulation is demonstrated with the safety-critical propulsion system and battery system and shows how different failure scenarios impact the landing strategy selection.

Autonomous Mitigation↗

Miscalculation, Misperception and Risk Reduction

In the current security environment, the most likely wars for which the US and its allies must be prepared are wars against nuclear-armed states. Such wars bring unique risks of both vertical and horizontal escalation. Some are “accepted risks;” for example, the US may choose to escalate a conflict to clarify its commitment to an issue and defend its interest. Other are “unacceptable risks;” especially, the risk of miscalculation by the U.S. or an adversary. The focus here is on this latter category. Miscalculation is an error of judgment—the failure to accurately assess a situation. Miscalculation can result from hidden, incomplete, or ambiguous information, or from inaccurate processing of available information because of bias, overconfidence, denial, delusion, etc. Miscalculation is related to misperception. For some, they are synonymous. This paper characterizes the risks of miscalculation and introduces a discussion of a risk mitigation strategy.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Characterizing climate pathways using feature importance on echo state networks

The 2022 National Defense Strategy of the United States listed climate change as a serious threat to national security. Climate intervention methods, such as stratospheric aerosol injection, have been proposed as mitigation strategies, but the downstream effects of such actions on a complex climate system are not well understood. The development of algorithmic techniques for quantifying relationships between source and impact variables related to a climate event (i.e., a climate pathway) would help inform policy decisions. Data-driven deep learning models have become powerful tools for modeling highly nonlinear relationships and may provide a route to characterize climate variable relationships. In this paper, we explore the use of an echo state network (ESN) for characterizing climate pathways. ESNs are a computationally efficient neural network variation designed for temporal data, and recent work proposes ESNs as a useful tool for forecasting spatiotemporal climate data. However, ESNs are noninterpretable black-box models along with other neural networks. The lack of model transparency poses a hurdle for understanding variable relationships. We address this issue by developing feature importance methods for ESNs in the context of spatiotemporal data to quantify variable relationships captured by the model. We conduct a simulation study to assess and compare the feature importance techniques, and we demonstrate the approach on reanalysis climate data. In the climate application, we consider a time period that includes the 1991 volcanic eruption of Mount Pinatubo. This event was a significant stratospheric aerosol injection, which acts as a proxy for an anthropogenic stratospheric aerosol injection. Furthermore, we are able to use the proposed approach to characterize relationships between pathway variables associated with this event that agree with relationships previously identified by climate scientists.

black-box models↗