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At least 1,765 records · Page 98

Fiber Optics Sensing System (FOSS) deployment on Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID)

Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) is a technology demonstration of an inflatable aeroshell to slow down and protect heavy and valuable payloads when entering atmospheres such as those of the Earth and Mars. The ultimate project goal is to enable future payload deliveries to Mars. The LOFTID is based on more than a decade of development of the hypersonic inflatable aerodynamic decelerator (HIAD) technology, which consists of a stack of the inflatable concentric rings that make up the inflatable structure that is covered with a Flexible Thermal Protection System (FTPS) and, when combined, form the inflatable aeroshell. The goal of the LOFTID demonstration was to verify that a flexible heat shield, packed into a small-volume payload, can be inflated exoatmospherically to sizes much larger than that of the launch vehicle fairing and survive re-entry into the Earth atmosphere while withstanding a temperature excess of 1,600 °C. The LOFTID is part of Technology Demonstration Missions (TDM) under the National Aeronautics and Space Administration (NASA) Space Technology Mission Directorate (STMD). The NASA Armstrong Flight Research Center (AFRC) (Edwards, California) is part of the LOFTID program, where a space-launch version of the fiber optic sensing system (FOSS) is integrated into the avionics bay of the re-entry vehicle to provide high-spatial-density temperature measurements in three strategic locations of the vehicle. The program is part of a partnership agreement between the NASA Launch Service Program (LSP) at Kennedy Space Center (KSC) (Merritt Island, Florida) and the main Center of the LOFTID program at NASA Langley Research Center (LaRC) (Hampton, Virginia). This paper will first give a brief introduction of the FOSS, then discuss how the FOSS was integrated into LOFTID, in terms of fiber sensor integration into various sections of the vehicle, as well as integration of the FOSS interrogator into the avionics bay. Finally, data analysis during the LOFTID re-entry will be discussed.

Allen R Parker↗

Alternative Architectures for Distributed Cooperative Problem-Solving in the National Airspace System

The air traffic management system in the United States is an example of a distributed problem solving system. It has elements of both cooperative and competitive problem-solving. This system includes complex organizations such as Airline Operations Centers (AOCs), the FAA Air Traffic Control Systems Command Center (ATCSCC), and traffic management units (TMUs) at enroute centers and TRACONs, all of which have a major focus on strategic decision-making. It also includes individuals concerned more with tactical decisions (such as air traffic controllers and pilots). The architecture for this system has evolved over time to rely heavily on the distribution of tasks and control authority in order to keep cognitive complexity manageable for any one individual operator, and to provide redundancy (both human and technological) to serve as a safety net to catch the slips or mistakes that any one person or entity might make. Currently, major changes are being considered for this architecture, especially with respect to the locus of control, in an effort to improve efficiency and safety. This paper uses a series of case studies to help evaluate some of these changes from the perspective of system complexity, and to point out possible alternative approaches that might be taken to improve system performance. The paper illustrates the need to maintain a clear understanding of what is required to assure a high level of performance when alternative system architectures and decompositions are developed.

Smith, Phillip J.↗

Efficient screening of rare large pit anomalies on polished surfaces using a minimalist sampling scheme

Lawrence Livermore National Laboratory (LLNL) has made significant strides in generating clean energy through its inertial confinement fusion (ICF) experiments. These experiments rely on high-density carbon (HDC) coated shells to encapsulate the fusion fuel. The success of these experiments is heavily dependent on the surface quality of these shells, as even minor imperfections, such as deep pits, can negatively impact fusion yield. Ensuring the required smoothness involves an extensive surface-finishing process that spans approximately 20 stages, making it both time-intensive and resource-demanding. A critical challenge in this process is the need for high-resolution scans to detect rare deep pits, which can be costly and impractical if performed on every shell. This highlights the necessity of developing more efficient scanning methods to optimize time and cost without compromising accuracy. To address these challenges, we introduce a novel approach that employs the multivariate Dvoretzky–Kiefer–Wolfowitz (DKW) inequality to provide a probabilistic upper bound on the error in estimating pit distribution characteristics via a Kernel Density Estimator (KDE). This error bound enables efficient and reliable estimation of pit distribution characteristics at a specified statistical confidence level using a minimal number of surface scans. The integrated DKW-KDE approach was validated through surface-finishing experiments across two batches of HDC-coated shells, demonstrating consistent and robust performance across multiple stages of the surface-finishing experiments. The validation studies suggest that the integrated DKW-KDE approach achieves comparable accuracy in estimating the risk of deleterious large pits with six scans, thus conserving time and resources. Further evaluations show that performance remains consistent across batches and over multiple polishing stages. In conclusion, based on these findings, one can leverage the minimal-scan insights to strategically improve the bottleneck inspection process, thus enhancing the productivity and quality of shell polishing and similar challenging manufacturing processes.

Inertial confinement fusion↗

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗

A Collaboration Website for Muon Catalyzed Fusion and Muon Beam Production

This research initiative establishes a dynamic online platform geared towards supporting the burgeoning Muon Catalyzed Fusion collaboration, focusing on the concurrent development of particle accelerators and transport beamlines for muon beams. The central feature of this endeavor is the creation of a multifaceted website comprising both public facing and private sections to cater to diverse user needs. The public segment is meticulously designed to serve as an educational hub, featuring information pages targeted at the general public alongside private pages exclusively accessible to collaboration members. These pages will host an array of multimedia elements, ranging from images and text animations to video lectures, covering an extensive spectrum of topics integral to the science of Muon Catalyzed Fusion. Encompassing areas such as Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes, the educational content aims to make complex scientific concepts more accessible to a broader audience. Ensuring seamless accessibility across various devices and operating systems, the website incorporates integration with collaborative tools such as Google Docs for document collaboration, GitHub for code repository management, and WordPress for blogging with interactive commenting features. The bifurcation between public and private sections is a strategic approach to maintaining transparency while safeguarding proprietary research and works in progress. The public pages are strategically crafted to disseminate information, showcasing the latest endeavors and achievements within the NK Labs collaboration, including lectures, published papers, and regular blog posts open to public comments. On the other hand, the private section provides collaboration members with a secure space to share unpublished or nonpublic research, fostering collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. In essence, this ambitious project endeavors to bridge the gap between complex scientific knowledge and public understanding, enhance collaboration among researchers, and serve as a dynamic and inclusive platform for sharing and advancing the state-of-the-art in Muon Catalyzed Fusion and Accelerators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Core/Combustor-Noise Baseline Measurements for the DGEN Aeropropulsion Research Turbofan

Contributions from the combustor to the overall propulsion noise of civilian transport aircraft are starting to become important due to turbofan design trends and advances in mitigation of other noise sources. Future propulsion systems for ultra-efficient commercial air vehicles are projected to be of increasingly higher bypass ratio from larger fans combined with much smaller cores, with ultra-clean burning fuel-flexible combustors. Unless effective noise-reduction strategies are developed, combustor noise is likely to become a prominent contributor to overall airport community noise in the future. The new NASA DGEN Aeropropulsion Research Turbofan (DART) is a cost-efficient testbed for the study of core-noise physics and mitigation. This paper describes the recently completed DART core/combustor-noise baseline test in the NASA GRC Aero-Acoustic Propulsion Laboratory (AAPL). Acoustic data were simultaneously acquired using the AAPL overhead microphone array in the engine aft quadrant farfield, a single midfield microphone, and two semi-infinite-tube unsteady pressure sensors at the core-nozzle exit. Combustor-noise components of measured total-noise signatures were educed using a two-signal source-separation method and are found to occur in the expected frequency range. The acoustic data compare well with results from a limited 2014 feasibility test and will serve as a high-quality baseline for future research using the DART. The research described herein is aligned with the NASA Ultra-Efficient Commercial Transport strategic thrust and is supported by the NASA Advanced Air Vehicle Program, Advanced Air Transport Technology Project, under the Aircraft Noise Reduction Subproject.

Turbomachinery Noise↗

Potential State Regulatory Pathways to Facilitate Low-Carbon Fuels

States and the federal government are increasingly engaged in the challenges around decarbonizing the electric grid. In particular, regulators, consumers, stakeholders, and utilities recognize the need to carefully consider the role natural gas will play in a decarbonized future. A variety of technology and policy options to reduce greenhouse gas emissions associated with natural gas use are available, including energy efficiency programs, demand reduction tools, strategic electrification, and strategies to reduce emissions from natural gas production, transportation, and consumption. Low-carbon fuels – mainly renewable natural gas (RNG) and clean hydrogen – are being considered an important component of decarbonization goals. RNG and hydrogen may be able to meaningfully reduce emissions from processes independent of geologic natural gas, displacing emissions of methane, a powerful greenhouse gas. Although RNG and hydrogen are not cost-competitive today with geologic natural gas and are smaller in scale and potential than other decarbonization options, they can be explored as potential critical tools to decarbonize sectors that are difficult to electrify or shift off of natural gas entirely, such as air travel, industrial processes, maritime transport, long-distance trucking, space heating on cold days, and railroads (Nadel, 2022). The role of this report is to provide informational context for state utility regulators to understand the impacts of and challenges associated with broader integration of low-carbon fuels, followed by examples of state regulatory actions taken to date to facilitate the development of low-carbon fuels. Setting clear guidance to calculate the environmental benefits of low-carbon fuels and continuing federal and state investments in research and development to reduce costs relative to fossil fuels will be important steps to take to signal the desire to grow the market for these fuels. State public utility commissions may play a key role in setting regulatory frameworks for low-carbon fuels and ensuring that ratepayer funds, if utilized, are done so to further the public interest. This report is intended to summarize decisions that states have made to date on low-carbon fuels. In the spirit of understanding the current market and sharing information, this report provides success stories, and lessons learned across states as regulators implement varying strategies to achieve decarbonization objectives while maintaining their focus on affordability, safety, and reliability of the energy system. The report begins with an introduction of the role of natural gas in the U.S. economy (Section I) and background information on natural gas use, decarbonization, and low-carbon fuels (Section II). Next, the report describes the current market by discussing the scale of current production, emissions intensity, resource potential, and costs of low-carbon fuels compared to geologic natural gas (Section III). Following these sections, the report describes four strategies states have employed to facilitate low-carbon fuels: opening exploratory dockets, approving voluntary tariffs for customers, approving interconnection tariffs for producers, and considering portfolio-wide procurement targets (Section IV). This section lists states that have taken actions in each category, citing utility filings, commission decisions, stakeholder comments, and other relevant sources. Finally, the report concludes with suggested questions regulators may wish to consider regarding low-carbon fuels, in the interest of preparing to make decisions in the future (Section V). These questions include: Are there existing regulatory or technical barriers to voluntary purchases of low-carbon fuels? Can customers work with utilities to procure low-carbon fuels; are producers able to interconnect projects without significant barriers to entry? Should the infrastructure and/or commodity costs of low-carbon fuels be socialized among all ratepayers, or borne solely by the large commercial and industrial (C&I) customers currently driving the market? Should regulated natural gas and/or electric utilities own and operate low-carbon fuel production? How should regulators consider the unique decarbonization potential of low-carbon fuels, particularly for hard-to-abate sectors, in decision-making? Is additional direction or clarity from state policymakers needed? What no-regrets approaches can help facilitate both near-term RNG development and long-term development of hydrogen and other zero-carbon fuels? We collectively wish to express our gratitude to the U.S. Department of Energy, Office of Fossil Energy and Carbon Management, for supporting this report and other technical assistance resources for state regulators on natural gas topics. State regulators operate under a variety of policy environments, and states have vastly different types of energy resources, infrastructure, and customers. While there is no optimal regulatory, policy, or technological solution that will be successful in every state, state regulators can benefit by exchanging lessons learned with their peers across the country. We look forward to continued engagement with our fellow commissioners, commission staff, NARUC, the U.S. Department of Energy, and other stakeholders to develop sound regulation in the public interest.

03 NATURAL GAS↗

DART Core/Combustor-Noise Initial Test Results

Contributions from the combustor to the overall propulsion noise of civilian transport aircraft are starting to become important due to turbofan design trends and advances in mitigation of other noise sources. Future propulsion systems for ultra-efficient commercial air vehicles are projected to be of increasingly higher bypass ratio from larger fans combined with much smaller cores, with ultra-clean burning fuel-flexible combustors. Unless effective noise-reduction strategies are developed, combustor noise is likely to become a prominent contributor to overall airport community noise in the future. The new NASA DGEN Aero0propulsion Research Turbofan (DART) is a cost-efficient testbed for the study of core-noise physics and mitigation. This presentation gives a brief description of the recently completed DART core combustor-noise baseline test in the NASA GRC Aero-Acoustic Propulsion Laboratory (AAPL). Acoustic data was simultaneously acquired using the AAPL overhead microphone array in the engine aft quadrant far field, a single midfield microphone, and two semi-infinite-tube unsteady pressure sensors at the core-nozzle exit. An initial assessment shows that the data is of high quality and compares well with results from a quick 2014 feasibility test. Combustor noise components of measured total-noise signatures were educed using a two-signal source-separation method an dare found to occur in the expected frequency range. The research described herein is aligned with the NASA Ultra-Efficient Commercial Transport strategic thrust and is supported by the NASA Advanced Air Vehicle Program, Advanced Air Transport Technology Project, under the Aircraft Noise Reduction Subproject.

Aeroacoustics↗

Core/Combustor-Noise Baseline Measurements for the DGEN Aeropropulsion Research Turbofan

Contributions from the combustor to the overall propulsion noise of civilian transport aircraft are starting to become important due to turbofan design trends and advances in mitigation of other noise sources. Future propulsion systems for ultra-efficient commercial air vehicles are projected to be of increasingly higher bypass ratio from larger fans combined with much smaller cores, with ultra-clean burning fuel-flexible combustors. Unless effective noise-eduction strategies are developed, combustor noise is likely to become a prominent contributor to overall airport community noise in the future. The new NASA DGEN Aeropropulsion Research Turbofan (DART) is a cost-efficient testbed for the study of core-noise physics and mitigation. This paper describes the recently completed DART core/combustor-noise baseline test in the NASA GRC Aero-Acoustic Propulsion Laboratory (AAPL). Acoustic data was simultaneously acquired using the AAPL overhead microphone array in the engine aft quadrant far field, a single midfield microphone, and two semi-infinite-tube unsteady pressure sensors at the core-nozzle exit. Combustor-noise components of measured total-noise signatures were educed using a two-signal source-separation method and are found to occur in the expected frequency range. The acoustic data compares well with results from a limited 2014 feasibility test and will serve as a high-quality baseline for future research using the DART. The research described herein is aligned with the NASA Ultra-Efficient Commercial Transport strategic thrust and is supported by the NASA Advanced Air Vehicle Program, Advanced Air Transport Technology Project, under the Aircraft Noise Reduction Subproject.

Aeroacoustics↗

Materials and Fuels Complex Five-Year Investment Strategy (FY2020-FY2024)

The Department of Energy Office of Nuclear Energy (DOE-NE) mission is to provide the research, development, and demonstration (RD&D) foundation to extend the lives of the current operating reactor fleet, develop the next generation of nuclear reactors, and provide integrated nuclear fuel cycle solutions. The Materials and Fuels Complex (MFC) serves as the foundation of a nuclear RD&D enabling test bed at Idaho National Laboratory (INL) and is an integral part of a National Reactor Innovation Center (NRIC) strategy. MFC facilities focus on developing and maintaining RD&D capabilities that can increase research throughput, reduce barriers to deployment, and facilitate commercialization of new ideas and technologies for clean and secure sources of energy. This document is a complimentary document to the Materials and Fuels Complex Five-Year Mission Strategy FY-20 – FY-24 (INL/EXT-20-57224) that defines specific implementation strategies for increasing research capability and throughput through targeted investments in research facilities, research instruments, and research staff. Refer to INL/EXT-20-57224 for details about MFC, its capabilities, and the overall mission strategy for the Materials and Fuels Complex.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Safe, Efficient, and Fair UTM Airspace Management

Unmanned Aircraft Systems (UAS) are increasingly used to perform crucial commercial activities such as various types of inspections (crops, railroads, and bridges), surveillance, and package delivery. Regulators have become interested in developing UAS Traffic Management (UTM) systems. One promising framework for UTM allocates airspace to UAS operators via an auction. To succeed, an airspace auction must be economically efficient, fair, scalable, incentive-aligned, simple, and capable of continuously modeling airspace and sharing bid status and pricing information. This paper introduces the first airspace auction mechanism that meets these criteria. In the process, we introduce new spatial-temporal fairness constraints and a new abstraction for communicating airspace pricing information, the airspace price field. We evaluate our mechanism on UAS delivery scenarios taken from a Japan Aerospace Exploration Agency(JAXA) study and show that it scales to 1000s of bids.

Strategic deconfliction↗

An Agent-Based Interface to Terrestrial Ecological Forecasting

The latest generation of NASA Earth Observing System (EOS) satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, the highest economic value would come from forecasting impending conditions of the biosphere, to allow decision makers to mitigate dangers or exploit positive trends. NASA's strategic plan for the Earth Science Enterprise i d e n a s ecological forecasting as a focus for research. Ecological forecasting predicts the effects of changes in the physical, chemical and biological environment on ecosystem activity. Possible applications of such a system include predicting shortfalls or bumper crops of agricultural production, populations of threatened or invasive species or wildfire danger in time to allow improves preparation and logistical efficiency. Petabytes of remote sensing data are now available to help measure, understand and forecast changes in the Earth system, but using these data effectively can be surprisingly hard. The volume and variety of data files and formats are daunting. Simple data management activities, such as locating and transferring files, changing file formats, gridding point data, and scaling and reprojecting gridded data, can consume far more personnel time and resources than the actual data analysis. Some scientists commit to a particular data source or resolution just because using anything different would be more effort that it's worth. Better tools can help, but most of the tools developed to date are little more than shell scripts; they lack the flexibility to meet the diverse needs of users and are difficult to extend to handle changes in available data sources.

Golden, Keith↗

Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders: Evidence Report

In April 2010, President Obama declared a space pioneering goal for the United States in general and NASA in particular. "Fifty years after the creation of NASA, our goal is no longer just a destination to reach. Our goal is the capacity for people to work and learn and operate and live safely beyond the Earth for extended periods of time, ultimately in ways that are more sustainable and even indefinite." Thus NASA's Strategic Objective 1.1 emerged as "expand human presence into the solar system and to the surface of Mars to advance exploration, science, innovation, benefits to humanity, and international collaboration" (NASA 2015b). Any space flight, be it of long or short duration, occurs in an extreme environment that has unique stressors. Even with excellent selection methods, the potential for behavioral problems among space flight crews remain a threat to mission success. Assessment of factors that are related to behavioral health can help minimize the chances of distress and, thus, reduce the likelihood of adverse cognitive or behavioral conditions and psychiatric disorders arising within a crew. Similarly, countermeasures that focus on prevention and treatment can mitigate the cognitive or behavioral conditions that, should they arise, would impact mission success. Given the general consensus that longer duration, isolation, and confined missions have a greater risk for behavioral health ensuring crew behavioral health over the long term is essential. Risk, which within the context of this report is assessed with respect to behavioral health and performance, is addressed to deter development of cognitive and behavioral degradations or psychiatric conditions in space flight and analog populations, and to monitor, detect, and treat early risk factors, predictors and other contributing factors. Based on space flight and analog evidence, the average incidence rate of an adverse behavioral health event occurring during a space mission is relatively low for the current conditions. While mood and anxiety disturbances have occurred, no behavioral emergencies have been reported to date in space flight. Anecdotal and empirical evidence indicate that the likelihood of an adverse cognitive or behavioral condition or psychiatric disorder occurring greatly increases with the length of a mission. Further, while cognitive, behavioral, or psychiatric conditions might not immediately and directly threaten mission success, such conditions can, and do, adversely impact individual and crew health, welfare, and performance.

Slack, Kelley J.↗

Convergent Aeronautics Solutions Project

NASA is committed to transforming our aviation system to best meet demands and opportunities of the future. With a vision of safe, efficient, flexible, and environmentally sustainable air transportation, the NASA Aeronautics Research Mission Directorate is conducting research and development to address future needs of the aviation community, the Nation, and the world. While our NASA Aeronautics vision and strategy reaches into the next 25 years and beyond, we recognize that our vision and strategy must be responsive to new discoveries and emerging markets. For this reason, we are empowering our research community to redefine the future of aviation by dreaming up convergent/transformative ideas and studying if those ideas are possible. By modeling the new NASA Aeronautics' Convergent Aeronautics Solutions (CAS) Project after the venture capital community, we created opportunities for teams of intrapreneurs to mature their ideas into concepts through rapid feasibility studies. The CAS Project expects teams to consider the complexities and potential benefits of multi-disciplinary solutions and to leverage technology advances from outside the field of aeronautics. We also expect teams to explore their concepts in a rapid, iterative manner that allows them to learn and adjust their research approach. Within a year or two, teams are responsible for reporting on the feasibility of their concept. The findings inform NASA Aeronautics strategic planning and further investment. This presentation will give an overview of CAS.

Transformative↗

Characterization of Extremes and Compound Impacts: Applications of Machine Learning and Interpretable Neural Networks

Focal Area: This white paper responds to Focal area III by exploring data fusion, learning and explainable AI methods in characterizing hydrological extremes and interconnections. It also addresses Focal area II by using probabilistic AI and ensemble ML for predicting extremes and compound extremes. Science Challenge: A key question associated with the integrated water (or hydrological) cycle grand challenge in the Earth and Environmental Systems Sciences Division (EESSD) strategic plan, is how the frequency and intensity of hydrological events will change. Prediction of the tail behavior (extremes) of the hydrological cycle is especially challenging, because of their stochasticity and low probability. These extreme events and their compound impacts have significant societal and economic consequences. It is anticipated for the next-generation Earth System models (ESMs), that model predictability of the water cycle will improve with increased resolution (e.g., regionally refined E3SM), advanced software and computational architectures, and improved model physics based on the data from ARM measurements and high-fidelity models. However, the challenges for predictability of low-probability high-impact extreme events will unlikely be alleviated with conventional modeling and data-driven approaches, as ESMs are calibrated largely for capturing the high-frequency mean climate states. Recent AI and ML applications have shown great potential in quantifying well-defined climate extremes (e.g., supervised learning of tropical cyclones/atmospheric rivers by ClimateNet1) but few efforts are dedicated to compound events, extreme drivers and uncertainty estimation. We envision the opportunity to develop and apply ML and interpretable AI methods extended on the existing efforts, specifically, for: (1) identification of compound extremes, (2) diagnosing drivers of extremes, (3) bias correction in extreme predictions and (4) probabilistic modeling of extremes.

54 ENVIRONMENTAL SCIENCES↗

Metadata Entry Optimization for NASA's Biological Institutional Scientific Collection (NBISC)

The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.

Sample Repository↗

Metadata Entry Optimization For NASA's Biological Institutional Scientific Collection (NBISC)

The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.

Biospecimen↗

Flexible Fabrics with High Thermal Conductivity for Advanced Spacesuits

This paper describes the effort and accomplishments for developing flexible fabrics with high thermal conductivity (FFHTC) for spacesuits to improve thermal performance, lower weight and reduce complexity. Commercial and additional space exploration applications that require substantial performance enhancements in removal and transport of heat away from equipment as well as from the human body can benefit from this technology. Improvements in thermal conductivity were achieved through the use of modified polymers containing thermally conductive additives. The objective of the FFHTC effort is to significantly improve the thermal conductivity of the liquid cooled ventilation garment by improving the thermal conductivity of the subcomponents (i.e., fabric and plastic tubes). This paper presents the initial system modeling studies, including a detailed liquid cooling garment model incorporated into the Wissler human thermal regulatory model, to quantify the necessary improvements in thermal conductivity and garment geometries needed to affect system performance. In addition, preliminary results of thermal conductivity improvements of the polymer components of the liquid cooled ventilation garment are presented. By improving thermal garment performance, major technology drivers will be addressed for lightweight, high thermal conductivity, flexible materials for spacesuits that are strategic technical challenges of the Exploration

Trevino, Luis A.↗