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NASA NTRSDate not supplied

Bionutrients: Microbial Production of on-Demand Nutrients on the International Space Station

Providing adequate nutrition to crew members is essential as deep-space missions cannot rely on consistent Earth-based resupply. The current NASA pre-packaged food system is designed for low-earth-orbit missions with a stated shelf-life of two years and notable vitamin degradation over time. One strategy to mitigate nutrient loss is to implement bioregenerative food sources to supplement the pre-packaged food system. The BioNutrients project is designed to provide targeted production of short shelf-life nutrients in a single-use production pack. BioNutrients-1 includes two strains of edible yeast that have been genetically engineered to produce carotenoids, β-carotene, and zeaxanthin. This five-year mission on the International Space Station (ISS), launched in 2019, tests the long-term storage and nutrient production of the microorganisms of interest. Additional microorganisms are also stored in stasis packs to determine the effects of long-duration storage on the ISS. These organisms may be useful for production of fermented foods, pharmaceuticals, or biomanufacturing processes. Improving on the BioNutrients-1 project, BioNutrients-2 has optimized the production pack hardware by reducing the overall mass and volume of the system. Furthermore, BioNutrients-2 has expanded the projects scope by investigating novel products and microbial food sources. BioNutrients-2 is a six-month mission, launched in 2022, which tests production of fresh foods such as yogurt and kefir. The BioNutrients missions seek to provide advances for in-space biomanufacturing by addressing safe and reliable production of high-value nutrients and on-demand foods for future exploration efforts.

BioNutrients↗

NASA NTRSDate not supplied

Bionutrients: Microbial Production of on-Demand Nutrients on the International Space Station

BioNutrients↗

DOE OSTI2026

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

NASA NTRSDate not supplied

Spaceborne Passive-Microwave Hail Detection: Global Climatologies, Validation, and Challenges Going Forward

In addition to the myriad threats that severe hailstorms pose to society, infrastructure and agriculture, severe hail is difficult to measure in situ, and surface-based hail reporting and detection methods are inconsistent and vulnerable to nonmeteorological biases. This motivates the use of spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We have developed a hail detection algorithm that leverages the sensitivity of spaceborne passive-microwave radiometers to scattering by hail, particularly in the channels from 10 to 89 GHz. We use this retrieval to construct global passive-microwave climatologies of severe hail using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), Global Precipitation Measurement Mission (GPM) Microwave Imager, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and are working to extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We find that this retrieval, which leverages a signature in the Minimum 19-GHz polarization corrected temperature (PCT) combined with the 37-GHz PCT depression normalized by tropopause height constrains the radar reflectivity most tightly, and gives the least appearance of regional biases compared to other passive-microwave approaches in the literature. Satellite platforms offer consistent observations, even in remote, data-sparse, and oceanic regions that ground-based networks exclude. There are, however, potential disconnects between the processes identified aloft by the satellite and the resultant weather at the ground, leading to uncertainties in the retrievals that may propagate into satellite-based climatologies, particularly in the Tropics, where there are abundant strong - but not necessarily hailing - storms that are strongly represented in the current satellite climatologies. We will discuss ongoing efforts to assess and mitigate the contributing factors to these uncertainties, chiefly among them the effects of non-uniform beam filling in the passive-microwave footprint, and the relationships between the size distributions of hailstones aloft and the dynamic processes and environments with which they interact throughout their trajectories.

Sarah D. Bang↗

DOE OSTI2023

Project: Corbomite - Product: ConsoleWorks REACT

TDi Technologies presents ConsoleWorks REACT, an advanced platform designed to tackle the complexities of cyber and operational risk assessment. This comprehensive solution goes beyond asset-focused approaches by considering the impact of both assets and people have on the security and operation of critical infrastructure, specifically targeting preventing gird mis-operation by evaluating real-time human interaction or commands with critical assets. The hypothesis suggests that by integrating the assessment of user commands into the overall risk assessment process, organizations can make more informed decisions, prioritize resources effectively, and respond promptly to potential threats. This hypothesis forms the basis for the development of a proactive and holistic risk management approach that is more comprehensive and context aware than traditional models which only look at assets, patch levels, configuration and threat intel by collecting that information off the network vs directly from the asset, human, and human interaction all in real-time. ConsoleWorks' unique man-in-the-middle architecture is a key feature that sets it apart in the cybersecurity landscape. This architecture enables the real-time observation, enforcement, and commands or interaction risk transparency of user interaction with critical infrastructure to be risk mitigated and audited as they are aggregated with device and human risk factors for a more comprehensive risk threat score across a device or group of devices. This architecture allows ConsoleWorks to act as a secure intermediary between users and critical assets, monitoring all interactions and ensuring that only authorized commands are sent to the asset to be executed. This not only enhances security but also provides a comprehensive audit trail of all user activities, contributing to compliance efforts and facilitating incident investigation and risk management. By integrating this unique architecture with our comprehensive risk assessment methodology, ConsoleWorks REACT provides a powerful solution for managing cyber and operational risks, enabling organizations to maintain a robust security posture and effectively mitigate potential threats. To that end, the primary objective of this project was to research and develop a robust solution that enables the energy industry to mitigate the risks associated with human actions that can compromise the security or operations of assets critical to energy delivery, generation, transmission and operation. ConsoleWorks REACT plays a pivotal role in achieving this goal by leveraging its unique capabilities to monitor and track all user activity. Through its Zero Trust approach, which emphasizes continuous verification, the platform ensures secure access to assets and serves as the centralized human response and notification platform for addressing cyber and operational issues.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1998

Fiber-Supported Droplet Combustion Experiment-2

A major portion of the energy produced in the world today comes from the burning of liquid hydrocarbon fuels in the form of droplets. Understanding the fundamental physical processes involved in droplet combustion is not only important in energy production but also in propulsion, in the mitigation of combustion-generated pollution, and in the control of the fire hazards associated with handling liquid combustibles. Microgravity makes spherically symmetric combustion possible, allowing investigators to easily validate their droplet models without the complicating effects of gravity. The Fiber-Supported Droplet Combustion (FSDC-2) investigation was conducted in the Microgravity Glovebox facility of the shuttles' Spacelab during the reflight of the Microgravity Science Laboratory (MSL- 1R) on STS-94 in July 1997. FSDC-2 studied fundamental phenomena related to liquid fuel droplet combustion in air. Pure fuels and mixtures of fuels were burned as isolated single and duo droplets with and without forced air convection. FSDC-2 is sponsored by the NASA Lewis Research Center, whose researchers are working in cooperation with several investigators from industry and academia. The rate at which a droplet burns is important in many commercial applications. The classical theory of droplet burning assumes that, for an isolated, spherically symmetric, single-fuel droplet, the gas-phase combustion processes are much faster than the droplet surface regression rate and that the liquid phase is at a uniform temperature equal to the boiling point. Recent, more advanced models predict that both the liquid and gas phases are unsteady during a substantial portion of the droplet's burning history, thus affecting the instantaneous and average burning rates, and that flame radiation is a dominant mechanism that can extinguish flames in a microgravity environment. FSDC-2 has provided well-defined, symmetric droplet burning data including radiative emissions to validate these theoretical models for heptane, decane, ethanol, and methanol fuels. Since most commercial combustion systems burn droplets in a convective environment, data were obtained without and with convective flow over the burning droplet (see the following photos).

Colantonio, Renato O.↗

NASA NTRS2020

Huntsville Urban Development: Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, AL

Huntsville, Alabama’s population has grown by approximately 11% since 2010, due in part to the city’s advancing engineering industry. Rapid urban growth negatively impacts the environment by decreasing tree canopy cover and increasing impervious surface cover, which can intensify the urban heat island effect. To examine the impacts of this urban growth on the environment, the team partnered with the City of Huntsville to utilize Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Space Station’s Global Ecosystems Dynamic Investigation (GEDI) and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The team utilized these Earth observations in combination with ancillary datasets to create a suite of end products to assist in mitigating the effects of extreme heat due to urban expansion and tree canopy loss. Annual land surface temperature (LST) was calculated and land cover classes were derived through supervised and threshold classification methods to distinguish trees, other vegetation types, impervious surfaces, and water. From 2010 to 2019, LST increased approximately 4 °F for all census tracts within the city and the total amount of tree cover increased by approximately 3%. The findings will aid the city in future decision-making processes by indicating areas that would benefit from increased green infrastructure.

Greta Paris↗

NASA NTRS2020

Huntsville Urban Development: Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, Alabama

Greta Paris↗

DOE OSTI2021

Using Machine Learning to Track Objects Across Cameras

Video surveillance is one of the most important technologies used by the International Atomic Energy Agency in international safeguards. At large, complicated facilities, multiple surveillance cameras are deployed to monitor the transfer of safeguards-relevant objects across the site. During inspections, all surveillance videos are reviewed to ensure the objects are not manipulated or diverted during transfer, a laborious, time-consuming task. This work describes using deep machine learning algorithms to track objects automatically across multiple cameras, greatly improving the efficiency of the review process. The fundamental problem in this object tracking task across multiple cameras is how to associate the same object, which may show extreme intra-class variations, such as viewpoints, occlusions, and various scales, in different and even non-overlapped cameras. Object re-identification (Re-ID) in nuclear facility video surveillance is even more challenging than classic person or vehicle Re-ID problems because different instances in the same category may display an identical appearance. One observation from nuclear facility surveillance videos is that all objects must be carted (e.g., via forklift) to move. Therefore, the spatial context information of an object, which provides the feature from the carrier, is critical for the object Re-ID task. This work proposes a two-stream convolutional neural networks model that takes features of objects and their surrounding regions into account. Moreover, the custom videos usually are gleaned from different scenes from the training data, which may have extreme variations in illumination changes and/or cluttered backgrounds. Directly applying the trained model to custom videos will dramatically decrease the performance. To tackle this problem, an advanced domain adaptation technique is proposed to mitigate the gap between the data taken from different scenes. The proposed framework will track objects of interest across a nuclear complex. The resulting tracks can be used in further analyses, such as event/activity recognition, anomaly detection, etc.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2025

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 × speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗

NASA NTRS2015

On The Development of Additive Construction Technologies for Application to Development of Lunar/Martian Surface Structures Using In-Situ Materials

For long-duration missions on other planetary bodies, the use of in-situ materials will become increasingly critical. As man's presence on these bodies expands, so must the breadth of the structures required to accommodate them including habitats, laboratories, berms, radiation shielding for natural radiation and surface reactors, garages, solar storm shelters, greenhouses, etc. Planetary surface structure manufacturing and assembly technologies that incorporate in-situ resources provide options for autonomous, affordable, pre-positioned environments with radiation shielding features and protection from micrometeorites, exhaust plume debris, and other hazards. This is important because gamma and particle radiation constitute a serious but reducible threat to long-term survival of human beings, electronics, and other materials in space environments. Also, it is anticipated that surface structures will constitute the primary mass element of lunar or Martian launch requirements. The ability to use in-situ materials to construct these structures will provide a benefit in the reduction of up-mass that would otherwise make long-term Moon or Mars structures cost prohibitive. The ability to fabricate structures in situ brings with it the ability to repair these structures, which allows for self-sufficiency necessary for long-duration habitation. Previously, under the auspices of the MSFC In Situ Fabrication and Repair (ISFR) project and more recently, under the joint MSFC/KSC Additive Construction with Mobile Emplacement (ACME) project, the MSFC Surface Structures Group has been developing materials and construction technologies to support future planetary habitats with in situ resources. One such technology, known as Contour Crafting (additive construction), is shown in Figure 1, along with a typical structure fabricated using this technology. This paper will present the results to date of these efforts, including development of novel nozzle concepts for advanced layer deposition using the Contour Crafting process. This process, conceived initially for rapid development of cementitious structures on Earth, also lends itself exceptionally well to the automated fabrication of planetary surface structures using minimally processed regolith as aggregate, and imported binder material or binders developed from in situ materials. This process has been used successfully in the fabrication of construction elements using lunar regolith simulant and Mars regolith simulant, both with various binder materials. These binder materials have resulted from extensive evaluation and include both "imported" binder materials that might be launched from Earth as well as some binder materials that can theoretically also be derived from existing regolith materials. They were chosen to 1) reduce penetrating radiation as much as possible, primarily with hydrogen-bearing polymers, 2) attempt to provide an air-tight structure, 3) sufficiently mix and adsorb to regolith grains for strength, 4) maximize tolerance to day-night thermal cycling, 5) possibly increase electrical conductivity to dissipate any accumulated static charge, and 6) ease their application on planetary surfaces (specifically, the accommodation of reduced atmosphere and lack of heat sinks). Some of these materials have been tested with respect to radiation mitigation, micrometeorite resistance, and resistance to larger, slower-traveling pieces of regolith impinging on the surface, simulating nearby launch and landing activities. Conceptual designs for a Continuous Feedstock Delivery/Mixing System (CFDMS) will also be presented and future planned activities will be discussed as well.

Werkheiser, Niki↗

DOE OSTI2026

Experimental investigation of a closed vapour box module for a divertor-like configuration in Magnum-PSI

Efficient management of extreme heat fluxes in the divertor region to extend the lifetime of the components remains a critical challenge for the realization of nuclear fusion-based power plants. Among the alternative concepts explored for the divertor region, the use of liquid metals, particularly lithium, is of interest due its ability to dissipate the incoming plasma heat flux through the vapour shielding effect (VS). In this work, we experimentally investigated a ‘closed’ configuration of a dedicated Vapour Box Module (VBM) in the linear plasma device Magnum-PSI. The goal of the experiments is to simulate the vapour box divertor environment conditions and assess its performance in terms of power mitigation and redistribution and lithium confinement. Initial testing without Li demonstrated the efficacy of a closed VBM structure in inducing detachment via neutral gas accumulation. Apertures which enabled non-condensing gas to be effectively pumped while ensuring lithium condensed on the inner surfaces were therefore added. With a lithium capillary porous structure target used, lithium is directly vaporized by the plasma, forming a dense lithium vapour cloud that interacts with the incoming plasma. This resulted in a significant reduction of the target temperature of at least 48%, together with a temperature locking effect, a phenomenon typically observed in the VS regime. Lithium vapour confinement within the VBM was strongly correlated with the wall temperature. Relatively cold walls promoted Li re-condensation and therefore improved Li confinement, although with the expected trade-off of increased hydrogenic retention on lithium-wetted surfaces. As the wall temperature increased, the confinement efficiency decreased, consistent with reduced Li re-condensation and thermally activated Li–H chemistry and remobilization at the walls. Diagnostic measurements through embedded thermocouples and calorimetry revealed that lithium vaporization and re-condensation processes also playedsignificant roles in plasma power dissipation. The results advance the case for a closed divertor chamber with direct lithium evaporation from the strike-points as a viable method to manage divertor heat fluxes in future fusion reactors.

Romano, Fabio [Dutch Institute for Fundamental Ene↗

NASA NTRS2014

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.

Xilinx FPGA↗

DOE OSTI2025

Application of Electrochemical Methods to Molten Salt Reactors: Draft TLR Documenting Assessment of Electrochemical Monitoring

Nuclear Regulatory Commission (NRC) is developing the regulatory framework and technical expertise to support regulatory review of advanced non-water reactors, including molten salt reactors (MSRs). In an MSR, it is essential that the salt chemistry be maintained in a desired range in terms of redox potential for reliable operation and mitigation of corrosion to structural materials in the reactor, particularly the reactor vessel and heater exchanger. Measuring the redox potential of the salt in the reactor would also allow for the material lifetimes to be predicted more accurately, and chemical issues to be diagnosed more quickly. In addition to the chemical composition analysis by ICP-MS, electrochemical methods including potentiometry and linear wave scanning (LSC) were also used in molten salt reactor experiment (MSRE) for redox potential monitoring purposes. Electrochemcial methods offers unique advantages such as quick turnaround in results and unique capability of in-line monitoring of redox potential, and are considered popular electroanalytical techniques that can be used to monitor redox potentials and salt chemistry including impurities. The last two decades have seen significant advances in science and engineering of electrochemical methods for potential application to molten salts. The primary goal of this report is to assist NRC in understanding the monitoring of the salt chemistry by electrochemical methods and provide NRC reviewers with necessary information and tools to support regulatory review of MSR designs. This reports consists of two majors parts—Part 1, chemical potential of molten salts and effects by fission process in MSR; Part 2, assessment of electrochemical methods for application to MSRs. The TRLs of the typical relevant electrochemical methods for molten salts were evaluated based on the DOE TRL guidelines and upon a review of the current status of the electrochemical methods for two typical salt systems, fluoride and chloride, for MSRs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

A robust approach to Gaussian process implementation

Abstract. Gaussian process (GP) regression is a flexible modeling technique used to predict outputs and to capture uncertainty in the predictions. However, the GP regression process becomes computationally intensive when the training spatial dataset has a large number of observations. To address this challenge, we introduce a scalable GP algorithm, termed MuyGPs, which incorporates nearest-neighbor and leave-one-out cross-validation during training. This approach enables the evaluation of large spatial datasets with state-of-the-art accuracy and speed in certain spatial problems. Despite these advantages, conventional quadratic loss functions used in the MuyGPs optimization, such as root mean squared error (RMSE), are highly influenced by outliers. We explore the behavior of MuyGPs in cases involving outlying observations and, subsequently, develop a robust approach to handle and mitigate their impact. Specifically, we introduce a novel leave-one-out loss function based on the pseudo-Huber function (LOOPH) that effectively accounts for outliers in large spatial datasets within the MuyGPs framework. Our simulation study shows that the LOOPH loss method maintains accuracy despite outlying observations, establishing MuyGPs as a powerful tool for mitigating unusual observation impacts in the large data regime. In the analysis of US ozone data, MuyGPs provides accurate predictions and uncertainty quantification, demonstrating its utility in managing data anomalies. Through these efforts, we advance the understanding of GP regression in spatial contexts.

Mukangango, Juliette↗

DOE OSTI2026

Blueprint: Stakeholder-Specific Vulnerability Categorization Guidance

Vulnerability management is a process of discovering, analyzing, and handling new or reported security vulnerabilities in systems to prevent the systems from being exploited, to reduce risk, and to protect assets. For vulnerability analysis, handling, and response, the prioritization of organizational and analyst resources must precede. The Common Vulnerability Scoring System (CVSS) is a standard prioritization method that is used to rate the severity of security vulnerabilities in systems by assigning numerical severity scores, but it does not provide clear guidelines of how the numerical severity scores might inform decisions. The Stakeholder-Specific Vulnerability Categorization (SSVC) provides a method for prioritizing vulnerabilities based on the needs of the stakeholders involved in the vulnerability management process. Instead of the numerical scoring used in the CVSS, the SSVC focuses on contextual decision-making to determine how quickly and effectively an organization should respond to vulnerabilities. The main functionality of the SSVC accommodates the diversity of the stakeholders in the vulnerability management process, including finders, vendors, coordinators, deployers, and others. So, the SSVC should be designed to be used by any of these stakeholders, and it should be customizable to enable specific stakeholder decision models and risk appetites.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Temperature-dependent mechanism on hardening mitigation in thermomechanically processed 800H alloys under neutron irradiation

Irradiation induced hardening is commonly observed in structural materials, and is often associated with the degraded ductility. This study explores the role of thermomechanical processing (TMP) in mitigating irradiation-induced hardening in Incoloy 800H. The radiation response of solution-annealed and TMP-treated samples was systematically investigated to elucidate the underlying mechanisms of hardening reduction. Neutron irradiation was performed on solution-annealed and TMP-treated samples at 359, 431, and 580 °C, revealing consistently lower hardening in TMP samples. Microstructural characterization compared dislocation loops, cavities, clusters, and precipitates to assess their contributions to hardening. The strengthening contributions from individual microstructural features were estimated, and the microstructure-derived yield strength is consistent with the hardness-converted yield strength. The microstructure–properties correlation revealed the temperature-dependent primary hardening mechanism: dislocation loops dominated at lower temperature, whereas Ni3(Al,Ti) γ′ precipitates were predominant at higher temperature. TMP reduced radiation-induced hardening through two mechanisms: (1) increased sink strength from dislocations and Ti(C,N) precipitates limited dislocation loop formation at lower temperatures, and (2) reduced Ti solute within the matrix in TMP samples suppressed γ′ precipitate formation at higher temperatures. These findings identify the mechanisms governing radiation-induced hardening across different temperatures, which lays the foundation for TMP optimization for the development of advanced radiation-tolerant materials.

Zhong, Weicheng [ORNL] (ORCID:0000000231589271)↗

DOE OSTI2021

sCO 2 Brayton Energy Conversion Customer Discovery

All energy production systems need efficient energy conversion systems. Current Rankine cycles use water to generate steam at temperatures where efficiency is limited to around 40%. As existing fossil and nuclear power plants are decommissioned due to end of effective life and/or societies’ desire for cleaner generation options, more efficient energy conversion is needed to keep up with increasing electricity demands. Modern energy generation technologies, such as advanced nuclear reactors and concentrated solar, coupled to high efficiency sCO 2 conversion systems provide a solution to efficient, clean energy systems. Leading R&D communities worldwide agree that the successful development of sCO 2 Brayton power cycle technology will eventually bring about large-scale changes to existing multi-billion-dollar global markets and enable power applications not currently possible or economically justifiable. However, all new technologies face challenges in the path to commercialization and the electricity sector is distinctively risk averse. The Sandia sCO 2 Brayton team needs to better understand what the electricity sector needs in terms of new technology risk mitigation, generation efficiency, reliability improvements above current technology, and cost requirements which would make new technology adoption worthwhile. Relying on the R&D community consensus that a sCO 2 power cycle will increase the revenue of the electrical industry, without addressing the electrical industry’s concerns, significantly decreases the potential for adoption at commercial scale. With a clear understanding of the market perspectives on technology adoption, including military, private sector, and utilities customers, the Sandia Brayton Team can resolve industry concerns for smoother development and faster transition to commercialization. An extensive customer discovery process, similar to that executed through the NSF’s I-Corp program, is necessary in order to understand the pain points of the market and articulate the value proposition of Brayton systems in terms that engage decision makers and facilitate commercialization of the technology.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗