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Analysis of Gaps in Techno-Economic Analysis to Advance Heliostat Technologies for Concentrating Solar-Thermal Power

The Heliostat Consortium (HelioCon) was launched in 2021 to advance heliostat technology. One of its first efforts was to do a detailed analysis of gaps in technology and capabilities in the heliostat industry and complete a roadmap study describing high-priority gaps. HelioCon gathered gaps through a series of outreach activities with representatives and experts from industries and research institutes. Here, this paper discusses the gap analysis for the techno-economic analysis (TEA) topic. One of the main objectives of the TEA topic is to relate the cost and performance of heliostats and heliostat components to the overall system performance. In this study, we limit the scope of this topic to the heliostat field, tower, and receiver and do not consider downstream applications or uses of thermal energy. We conducted a thorough review of existing models and compiled a list of the state of the art in open-source tools currently available to researchers. We collected an initial list of gaps for the TEA of heliostats from industry developers and experts. Each gap is briefly described, and the heliostat development cycle stages that the gap impacts are indicated. We ranked the initial list of TEA gaps into tiers depending on their potential impact. For TEA, most of the gaps identified are related to developing models or data. Strictly speaking, none of these gaps are essential for heliostat development, but all would aid in the heliostat development process.

14 SOLAR ENERGY↗

New space processing experiments for the Skylab missions.

The M512 Materials Processing Facility, which is the main item of equipment for the Skylab space manufacturing experiments is described. It is basically an electron-beam welding apparatus, consisting of a battery power supply, a 20-kV electron beam source, and a spherical 40-cm-diam vacuum chamber. It will be used to perform the M551 Metals Melting Experiment, the M552 Exothermic Brazing Experiment, the M553 Sphere Forming Experiment, the M554 Composite Casting Experiment, the M555 Gallium Arsenide Crystal Growth Experiment, the M561 Whisker-Reinforced Composites Experiment, the M562 Indium Antimonide Crystal Growth, Experiment, the M563 Mixed III-V Crystal Growth Experiment, the M564 Alkali Halide Eutectics Experiment, the M565 Silver Grids Melted in Space Experiment, and the M566 Copper-Aluminum Eutectic Experiment. Three apparatus systems designed to broaden the technical scope of the experiments and to gain experience with new experimental techniques are described. These are an electrophoretic separator, an electromagnetic levitation system, and a versatile electric furnace with an electronic control system.

Bredt, J. H.↗

U.S. Spacesuit Knowledge Capture – Creation, Curation, and Dissemination

The U.S. spacesuit is a special system that has intrigued and fascinated the world since Neil Armstrong set foot on the Moon in 1969. With over 50 years since that momentous achievement, NASA is planning to land the first woman and next man on the Moon in the near future. This goal begets the need to build a new spacesuit, a spacesuit created from the legacy knowledge of the Extravehicular Mobility Unit (EMU), combined with knowledge gained from technology development over the decades. As NASA transitions to its new horizon, the U.S. Spacesuit Knowledge Capture (SKC) Program is poised to help. The SKC Program’s primary function has been to capture, curate, and disseminate spacesuit-related knowledge among scientists, engineers, and technicians. The SKC Program was created in 2007 to capture knowledge primarily from spacesuit subject-matter experts (SMEs) who were retiring from NASA. These SMEs had 30 to 50 years of spacesuit knowledge. Over the years, the SKC Program has evolved and expanded its scope with a current focus on complementing the buildup of the Exploration EMU (xEMU) at the Johnson Space Center. As part of this focus, the SKC Program recently teamed with the xEMU Community of Practice (CoP) for knowledge sharing. The xEMU CoP provides a forum where early career engineers, professionals new to human spaceflight, and the xEMU community can come together regularly to seek guidance, share knowledge, meet their peers, discover resources, and ask questions. The CoP created an environment where the knowledge can be easily and routinely captured and recorded. The recorded events are archived and curated in an SKC Program library and disseminated as appropriate. This paper details the roles that the SKC Program and CoP play in the xEMU buildup, along with the navigation of the creation, curation, and dissemination processes.

Cinda Chullen↗

Agricultural Breadbaskets Shift Poleward Given Adaptive Farmer Behavior Under Climate Change

Modern food production is spatially concentrated in global “breadbaskets”. A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climaterelated losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end-of-century warming using 7 process-based models simulating 5 major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

adaptation↗

Evaluating the carbon capture potential of industrial waste as a feedstock for enhanced weathering

Abstract Limiting anthropogenic global climate warming since the start of the industrial period to less than 2 °C will very likely require both deep and rapid reductions in anthropogenic greenhouse gas emissions and a range of approaches toward carbon dioxide removal (CDR). One prominent CDR approach is enhanced weathering (EW), in which crushed silicate rock is applied on land or in the open ocean to accelerate natural weathering processes that absorb carbon dioxide from Earth’s ocean–atmosphere system. However, in addition to a range of potential environmental, socioeconomic, and ethical issues associated with this pathway, bottlenecks in feedstock sourcing represent a key barrier for deployment of EW at scale. Here, we evaluate the potential of silicate wastes produced from industrial processes—such as steel slag and cement waste—as feedstocks for the EW process. An empirical model that links industrial alkaline waste production to gross domestic product at purchase power parity is developed to forecast waste production in the alternative futures described by the shared socioeconomic pathway (SSP) framework. By incorporating these results into an intermediate-complexity Earth system model, we also explore the impacts of EW using industrial waste on changes to global temperature, ocean pH, and ocean aragonite saturation state, while also quantifying overall CDR efficiency through the end of the century. We estimate a maximum cumulative end-of-century capture potential of ∼400 GtCO 2 for industrial waste, which could represent a significant fraction of the projected CDR requirement of many mitigation scenarios in the SSP framework. However, feedstock-dependent environmental impacts and the technoeconomics of feedstock redistribution may ultimately limit deployment scope.

Xu, Pengxiao (ORCID:0009000633724293)↗

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

Technology Applications that Support Space Exploration

Several enabling technologies have been identified that would provide significant benefits for future space exploration. In-Space demonstrations should be chosen so that these technologies will have a timely opportunity to improve efficiencies and reduce risks for future spaceflight. An early window exists to conduct ground and flight demonstrations that make use of existing assets that were developed for the Space Shuttle and the Constellation programs. The work could be mostly performed using residual program civil servants, existing facilities and current commercial launch capabilities. Partnering these abilities with the emerging commercial sector, along with other government agencies, academia and with international partners would provide an affordable and timely approach to get the launch costs down for these payloads, while increasing the derived benefits to a larger community. There is a wide scope of varied technologies that are being considered to help future space exploration. However, the cost and schedule would be prohibitive to demonstrate all these in the near term. Determining which technologies would yield the best return in meeting our future space needs is critical to building an achievable Space Architecture that allows exploration beyond Low Earth Orbit. The best mix of technologies is clearly to be based on our future needs, but also must take into account the availability of existing assets and supporting partners. Selecting those technologies that have complimentary applications will provide the most knowledge, with reasonable cost, for future use The plan is to develop those applications that not only mature the technology but actually perform a useful task or mission. These might include such functions as satellite servicing, a propulsion stage, processing lunar regolith, generating and transmitting solar power, cryogenic fluid transfer and storage and artificial gravity. Applications have been selected for assessment for future consideration and are addressed in this paper. These applications have been made available to the various NASA study groups that are determining the next steps the Agency must take to secure a sound foundation for future space exploration The paper also addresses how follow-on demonstrations, as launch performance grows, can build on the earlier applications to provide increased benefits for both the commercial and scientific communities. The architecture of incrementally building upon previous successes and insights dramatically lowers the overall associated risk for developing and maturing the key enabling technologies. The goal is to establish a potential business case that encourages commercial activity, thereby reducing the cost for the demonstration while using the technology maturation in developing readiness for future space exploration with overall less risk.

Henderson, Edward M.↗

NASA Risk Management Handbook

The purpose of this handbook is to provide guidance for implementing the Risk Management (RM) requirements of NASA Procedural Requirements (NPR) document NPR 8000.4A, Agency Risk Management Procedural Requirements [1], with a specific focus on programs and projects, and applying to each level of the NASA organizational hierarchy as requirements flow down. This handbook supports RM application within the NASA systems engineering process, and is a complement to the guidance contained in NASA/SP-2007-6105, NASA Systems Engineering Handbook [2]. Specifically, this handbook provides guidance that is applicable to the common technical processes of Technical Risk Management and Decision Analysis established by NPR 7123.1A, NASA Systems Engineering Process and Requirements [3]. These processes are part of the \Systems Engineering Engine. (Figure 1) that is used to drive the development of the system and associated work products to satisfy stakeholder expectations in all mission execution domains, including safety, technical, cost, and schedule. Like NPR 7123.1A, NPR 8000.4A is a discipline-oriented NPR that intersects with product-oriented NPRs such as NPR 7120.5D, NASA Space Flight Program and Project Management Requirements [4]; NPR 7120.7, NASA Information Technology and Institutional Infrastructure Program and Project Management Requirements [5]; and NPR 7120.8, NASA Research and Technology Program and Project Management Requirements [6]. In much the same way that the NASA Systems Engineering Handbook is intended to provide guidance on the implementation of NPR 7123.1A, this handbook is intended to provide guidance on the implementation of NPR 8000.4A. 1.2 Scope and Depth This handbook provides guidance for conducting RM in the context of NASA program and project life cycles, which produce derived requirements in accordance with existing systems engineering practices that flow down through the NASA organizational hierarchy. The guidance in this handbook is not meant to be prescriptive. Instead, it is meant to be general enough, and contain a sufficient diversity of examples, to enable the reader to adapt the methods as needed to the particular risk management issues that he or she faces. The handbook highlights major issues to consider when managing programs and projects in the presence of potentially significant uncertainty, so that the user is better able to recognize and avoid pitfalls that might otherwise be experienced.

Dezfuli, Homayoon↗

High-speed assembly language (80386/80387) programming for laser spectra scan control and data acquisition providing improved resolution water vapor spectroscopy

An assembly language program using the Intel 80386 CPU and 80387 math co-processor chips was written to increase the speed of data gathering and processing, and provide control of a scanning CW ring dye laser system. This laser system is used in high resolution (better than 0.001 cm-1) water vapor spectroscopy experiments. Laser beam power is sensed at the input and output of white cells and the output of a Fabry-Perot. The assembly language subroutine is called from Basic, acquires the data and performs various calculations at rates greater than 150 faster than could be performed by the higher level language. The width of output control pulses generated in assembly language are 3 to 4 microsecs as compared to 2 to 3.7 millisecs for those generated in Basic (about 500 to 1000 times faster). Included are a block diagram and brief description of the spectroscopy experiment, a flow diagram of the Basic and assembly language programs, listing of the programs, scope photographs of the computer generated 5-volt pulses used for control and timing analysis, and representative water spectrum curves obtained using these programs.

Allen, Robert J.↗

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-Meador↗

The Natural Products Magnetic Resonance Database (NP-MRD) for 2025

The Natural Products Magnetic Resonance Database or NP-MRD (https://np-mrd.org) is a comprehensive, freely accessible, web-based resource for the deposition, distribution, extraction and retrieval of nuclear magnetic resonance (NMR) data on natural products. The NP-MRD was initially established to support compound de-replication and data dissemination for the natural products community. However, that community has now grown to include many users from the metabolomics, microbiomics, foodomics and nutrition science fields. Indeed, since its launch in 2021, the NP-MRD has expanded enormously in size, scope and popularity. The current version of NP-MRD now contains nearly 7X more compounds (281,859 vs. 40,908) and 7X more NMR spectra (5.1 million vs. 817,000) than the first release. More specifically, an additional 4.6 million predicted spectra and another 11,000 spectra simulated from experimental chemical shifts were deposited into the database. Likewise, the number of NMR raw spectral data depositions has grown from a 165 spectra per year to more than 10,000 per year. As a result of this expansion, the number of monthly webpage views has grown from 55 to 20,000 and the number of monthly visitors has increased from 7 to 2500. To address this growth and to better support the expanding needs of its diverse community of users, many additional improvements to the NP-MRD have been made. These include significant enhancements to the data submission process, important improvements to the visualization and display of NMR spectra, notable updates to the database’s spectral search utilities and useful additions to support better NMR spectral analysis/prediction. Significant efforts have also been undertaken to remediate and update many of NP-MRD’s database entries. This manuscript describes these database improvements and expansion efforts, along with how they have been implemented and what future upgrades to the NP-MRD are planned.

Artifical Intelligence↗

NASA Human Spaceflight Scenarios - Do All Our Models Still Say No?

Historically, NASA human spaceflight planning has included healthy doses of life cycle cost analysis. Planners put projects and their cost estimates in a budget context. Estimated costs became expected budgets. Regardless, real budgets rarely matched expectations. So plans would come and go as NASA canceled projects. New projects would arise and the cycle would begin again. Repeatedly, NASA schedule and performance ambitions come up against costs growing at double-digit rates while budgets barely rise a couple of percent a year. Significant skepticism greets proposed NASA programs at birth, as cost estimates for new projects are traditionally very high, and worse, far off the mark for those carried forward. In this environment the current "capability driven framework" for NASA human spaceflight evolved, where long term life cycle cost analysis are even viewed as possibly counter-productive. Here, a space exploration project, for example the Space Launch System, focuses on immediate goals. A life cycle is that of a project, not a program, and for only that span of time to a near term milestone like a first test launch. Unfortunately, attempting to avoid some pitfalls in long-term life cycle cost analysis breeds others. Government audits have noted that limiting the scope of cost analysis "does not provide the transparency necessary to assess long-term affordability" making it difficult to understand if NASA "is progressing in a cost-effective and affordable manner." Even in this short-term framework, NASA realizes the importance of long-term considerations, that it must "maximize the efficiency and sustainability of the Exploration Systems development programs", that this is "critical to free resources for re-investment...such as other required deep space exploration capabilities." Assuming the value of long-term life cycle cost analysis, where due diligence meets reconnaissance, and accepting past shortcomings, the work here approaches life cycle cost analysis for human spaceflight differently. 1) If costs have traditionally been so high that adding them up is discouraging, are there any new facts on the ground offering paths to significantly lower costs? 2) If NASA's spaceflight budget and process is an over-arching constraint, with its planning limitations favoring short-term outlooks, is there a way to step outside the budget box? 3) If life cycle answers have historically been too uncertain to be useful, is there a process where stakeholders gain valuable insights merely from emphasizing a common understanding around questions? We analyze the potential life cycle cost of assorted NASA human spaceflight architectures - an architecture as a sum of individual systems, working together. With the prior questions of high costs, limited budgets and uncertainties in mind, public private partnerships are central in these architectures. The cost data for current commercial public private partnerships is encouraging, as are cost estimates for future partnership approaches beyond low Earth orbit. Private capital, directly or indirectly, an ingredient of public private partnerships, may be a significant factor in finding a path around the limits of the NASA spaceflight budget. Also, understanding and reviewing the pros, cons and uncertainties of assorted architectures can assist in developing a common understanding around key questions as important if not more so than the numbers and answers. Lastly, a scenario planning technique is briefly explored that can mature a common understanding about the agencies situation at hand and how diverse stakeholders can go forward together. Scenario planning, rather than focusing on answers, places emphasis on stakeholders developing a common understanding about the future. Putting aside costs, this is especially true of questions about sustainability and growth, results, benefits and expectations. While efficiency exercises or analysis look to reduce resources in one place to apply them elsewhere, moving around slices in a pie, scenario planning can get at the heart of the matter, growing the pie, transforming it, and making the pieces relevant. Especially important is the question of sustainability for different scenarios in the broad sense of the word - not just the narrow ability to survive or continue, but also the ability to adapt, prosper and grow.

space systems life cycle costs↗

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification Validation (IVV) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASA's Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domaincomponent, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IVV enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

Fault management↗

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification & Validation (IV&V) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASAs Office of Safety and Mission Assurance (OSMA) defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domain/component, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IV&V enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.

IV&V↗

ARC-100 Reactor Security-by-Design Summary 2025

This report applies the security-by-design methodology developed in a previous National Nuclear Security Administration–sponsored work to the ARC-100, a sodium-cooled fast reactor (SFR) being developed by ARC Clean Technology, Inc (ARC). The report contains no proprietary information specific to the ARC 100 reactor. The insights developed in this report are high-level, and generally applicable to other sodium fast reactor designs. The information presented here is the result of a qualitative safety-based analysis and would not inform any potential adversary beyond what would be found in a docketed safety analysis report. The scope of this present report covers ARC-100’s reactor core, used fuel storage, used fuel assembly wash station, cesium trap, sodium cold trap, noble gas decay tanks, used fuel dry storage facility, damaged fuel storage facility, and radioactive waste building. These systems are also compared to a generic SFR design assumed in the previous study. The security assessment results show changes in structures, systems, and components (SSCs) safety importance relative to the generic SFR SSCs. Several SSCs have higher importance rankings than others, and it is recommended that protection efforts are prioritized for these SSCs. Results from this work will furnish a technical justification for the feasibility of these solutions for the ARC reactor's design and, where applicable, identify any regulatory benefits conferred by the proactive design aspect within a risk management framework. This initiative will contribute to a more secure design of the ARC reactor and support its licensing process.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

LLMs and GenAI Tools to Depict Contributions of Human Systems to Spaceflight Tasks Execution

Recent advancements in Artificial Intelligence and Machine Learning (AI/ML) technologies, particularly Large Language Models (LLMs) capable of sophisticated syntax analysis, offer substantial potential in automating complex processes, thereby saving time and human resources. This study explores the development of an LLM-driven model designed to analyze and categorize a diverse set of Mars mission tasks into 18 predefined Human System Task Categories (HSTCs) based on their textual descriptions. As part of developing the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA projects Performance Risk Model (PRisM) proof-of-concept, we established a framework to project performance scores from small-scale tests onto a preliminary list of Mars tasks. The foundation of our model was a comprehensive spreadsheet populated by NASA experts and clinicians, which detailed each Mars task alongside binary indicators of HSTC involvement. This dataset enabled the initial application of supervised ML, training and testing on existing HSTC labels. The HSTCs were originally defined from a medical system perspective, focusing on task impairments due to deteriorated human health. To expand our model's scope to include categories impacting performance, we face the challenge of generating binary labels (0 or 1) for new categories without pre-existing data. We address this by employing Generative AI (GenAI) software to determine whether a given task involved a new category by asking, "Does task A involve using category B?" We validate our approach by comparing the GenAI's binary classifications with the expert-provided labels for existing HSTCs. Notably, we utilize Ollama [4], a locally hosted GenAI tool that does not require cloud access, thus safeguarding NASA's proprietary data from unauthorized exposure. This study demonstrates the feasibility of leveraging cutting-edge AI tools to advance research, paving the way for automation and rapid decision-making in space exploration.

Mona Matar↗

Ice Shelves and Landfast Ice on the Antarctic Perimeter: Revised Scope of Work

Ice shelves respond quickly and profoundly to a warming climate. Within a decade after mean summertime temperature reaches approx. O C and persistent melt pending is observed, a rapid retreat and disintegration occurs. This link was documented for ice shelves in the Antarctic Peninsula region (the Larsen 'A', 'B' and Wilkins Ice shelves) by the results of a previous grant under ADRO-1. Modeling of ice flow and the effects of meltwater indicated that melt pending accelerates shelf breakup by increasing fracture penetration. SAR data supplemented an AVHRR- and SSM/I-based image analysis of extent and surface characteristic changes. This funded grant is a revised, scaled-down version of an earlier proposal under the ADRO-2 NRA. The overall objective remains the same: we propose to build on the previous study by examining other ice shelves of the Antarctic and incorporate an examination of the climate-related characteristics of landfast ice. The study now considers just a few shelf and fast ice areas for study, and is funded for two years. The study regions are the northeastern Ross Ice Shelf, the Larsen 'B' and 'C' shelves, fast ice and floating shelf ice in the Pine Island Glacier area, and fast ice along the Wilkes Land coast. Further, rather than investigating a host of shelf and fast ice processes, we will home in on developing a series of characteristics associated with climate change over shelf and fast ice areas. Melt pending and break-up are the end stages of a response to a warming climate that may begin with increased melt event frequency (which changes both albedo and emissivity temporarily), changing firn backscatter (due to percolation features), and possibly increased rifting of the shelf surface. Fast ice may show some of these same processes on a seasonal timescale, providing insight into shelf evolution.

Scambos, Ted↗