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NASA NTRS2016

Wireless Technology Use Case Requirement Analysis for Future Space Applications

This report presents various use case scenarios for wireless technology -including radio frequency (RF), optical, and acoustic- and studies requirements and boundary conditions in each scenario. The results of this study can be used to prioritize technology evaluation and development and in the long run help in development of a roadmap for future use of wireless technology. The presented scenarios cover the following application areas: (i) Space Vehicles (manned/unmanned), (ii) Satellites and Payloads, (iii) Surface Explorations, (iv) Ground Systems, and (v) Habitats. The requirement analysis covers two parallel set of conditions. The first set includes the environmental conditions such as temperature, radiation, noise/interference, wireless channel characteristics and accessibility. The second set of requirements are dictated by the application and may include parameters such as latency, throughput (effective data rate), error tolerance, and reliability. This report provides a comprehensive overview of all requirements from both perspectives and details their effects on wireless system reliability and network design. Application area examples are based on 2015 NASA Technology roadmap with specific focus on technology areas: TA 2.4, 3.3, 5.2, 5.5, 6.4, 7.4, and 10.4 sections that might benefit from wireless technology.

Abedi, Ali↗

NASA NTRS2021

Exploration Medical Capability Medical Scenarios

Medical systems supporting exploration class missions to cislunar space, the lunar surface, and the vicinity of Mars require an evolution in medical capability beyond that available for today’s low Earth orbit centric paradigm. Progress in developing more capable medical systems will be driven by the requirements of prolonged mission duration, increasing distance from Earth, and the realities of orbital mechanics, all necessitating a concomitant need for progressively Earth independent medical decision-making capabilities. These medical systems (which include the crewmembers) are expected to be capable of evaluating, diagnosing, treating and managing a defined list of medical conditions as well as addressing unanticipated medical conditions that may arise. The prioritized medical capabilities and associated resources needed to treat these medical conditions and support anticipated inflight medical events provide robust content that informs system designers and allows for a more complete evaluation of both medical and overall mission risk. Communication of these medical capabilities to system, vehicle, and mission designers can be enhanced using scenarios that characterize the system’s operations. Carefully considered scenarios provide the context needed to explore expected human and system interfaces, roles of ground and inflight crew (including periods of interrupted or delayed communications), identify training needs, assess data needs, etc. Mission-based scenario content varies dependent upon the needs, medical capabilities, conditions and context they are intended to illustrate. This document explicitly seeks to capture and codify those scenarios that have been useful to the Exploration Medical Capability Element of the Human Research Program in defining the enhanced medical systems required for future space exploration. It is expected that this document will continue to evolve through the refinement and characterization of current and future scenarios, respectively, as our knowledge grows, and requirements increasingly focus on Earth independent spaceflight operations.

Derek M Nusbaum↗

DOE OSTI2026

Rapid Evaluation Framework for the CMIP7 Assessment Fast Track

As Earth system models (ESMs) grow in complexity and in volume of output data, there is an increasing need for rapid, comprehensive evaluation of their scientific performance. The upcoming Assessment Fast Track for the Seventh Phase of the Coupled Model Intercomparison Project (CMIP7) will require expeditious response for model analyses designed to inform and drive integrated Earth system assessments. To meet this challenge, the Rapid Evaluation Framework (REF), a community-driven platform for benchmarking and performance assessment of ESMs, was designed and developed. The initial implementation of the REF, constructed to meet the near-term needs of the CMIP7 Assessment Fast Track, builds upon four disparate community evaluation and benchmarking tools that are coupled together using the Coordinated Model Evaluation Capabilities (CMEC) framework. The REF runs within a containerized workflow for portability and reproducibility and is aimed at generating and organizing diagnostics covering a variety of model variables. The REF leverages well documented observational datasets to provide assessments of model fidelity across a collection of diagnostics. All diagnostics were identified and selected with community involvement and consultation. Operational integration with the Earth System Grid Federation (ESGF) will permit automated execution of the REF for selected diagnostics as soon as model output data are published on ESGF by the originating modeling centers. The REF is designed to be portable across a range of current computational platforms to facilitate use by modeling centers for assessing the evolution of model versions or gauging the relative performance of CMIP simulations before being published on ESGF. When integrated into production simulation workflows, results from the REF provide immediate quantitative feedback that allows model developers and scientists to quickly identify model biases and performance issues. After the REF is released to the community, its subsequent development and support will be prioritized by an international consortium of scientists and engineers, enabling a broader impact across Earth science disciplines. For instance, the REF will facilitate improvements to models and will enhance confidence in model projections through process-based selection of models based on their performance with respect to observations. Production of reproducible diagnostics and community-based assessments are key features of the REF. Furthermore, providing interoperability with existing evaluation packages assures that contributions from previous community efforts will be available for use in future model intercomparison projects.

Hoffman, Forrest [ORNL] (ORCID:0000000158024134)↗

NASA NTRS2024

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗

DOE OSTI2024

A Pathway Analysis Framework for Evaluating the Economic and Environmental Viability of Biomass-Based Plastic Production

Plastic production from fossil feedstocks (e.g., naphtha, coal, and natural gas) is not sustainable and causes known environmental impacts such as global warming. A possible solution is to shift production pathways to use biomass, which is a sustainable feedstock that can sequester atmospheric carbon dioxide. This study presents an optimization-based pathway analysis framework for evaluating the carbon footprints of the production of mainstream plastics from biomass and fossil feedstocks. We use the modeling framework to quickly navigate complex interdependencies that exist between the production pathways of different plastics and to determine pathways of minimum production cost under a range of carbon pricing scenarios. The framework interprets carbon prices as an exogenous taxation scheme or an endogenous negative value perceived by producers. The proposed approach reveals the biomass feedstock quantities needed to displace fossil counterparts and the plastics and technologies that should be prioritized. The framework can also be used for evaluating system-wide trade-offs between production costs and carbon footprints that arise from pathway interdependencies. We also evaluate hidden environmental impacts associated with the large-scale use of biomass as a feedstock, such as land use and water eutrophication that results from a significant increase in fertilizer use. Therefore, it is important to highlight that there are trade-offs between decarbonization and other environmental issues. Here, the proposed framework provides an integrative platform for basic techno-economic and life-cycle data that can be used for analyzing diverse scenarios and determining necessary technology targets (e.g., yields, footprints, and costs) to achieve required levels of decarbonization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2024

Applications of Remote Sensing for Land Use Planning Scenarios with Suitability Analysis

In regions undergoing rapid urbanization, such as West Africa, land use planning (LUP) is vital to accommodate growing population and manage natural resources. Suitability analysis modeling is a widely used tool in LUP to determine the extent to which a land area is suitable for a designated purpose, but there is a gap in the integration of remote sensing time series data into land use decisions. The goal of this study was to incorporate remote sensing time series information with suitability analyses to inform LUP decisions in urban areas. In the study area of Kumasi, Ghana, land cover trends and land surface temperature (LST) from 2000 to 2019 were used to understand climate change trends. Suitability analyses determined the fitness of land areas for predetermined uses. These background processes informed a genetic algorithm to project plausible futures for three land use scenarios. One scenario represented current land use planning practices for addressing population growth, another scenario prioritized minimizing climate change impacts while also accommodating population growth, and the final scenario focused on both of these climate and population goals in addition to high density urban development. Each of these scenarios was successful in achieving population accommodation and respective climate change mitigation goals. The results for these scenarios provide insight into plausible land use distributions in 2050 based on different planning approaches. The genetic algorithm was able to effectively develop results for each scenario through the integration of remotely sensed trends and suitability models, providing a novel approach to land use decision-making.

remote sensing time series↗

DOE OSTI2022

More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)

Abstract Earth system models account for seasonal snow cover, but many do not accommodate the deeper snowpack on ice sheets (aka firn) that slowly transforms to ice under accumulating snowfall. To accommodate and resolve firn depths of up to 60 m in the Energy Exascale Earth System Model's land surface model (ELM), we add 11 layers to its snowpack and evaluate three dry snow compaction equations in multi‐century simulations. After comparing results from ELM simulations (forced with atmospheric reanalysis) with empirical data, we find that implementing into ELM a two‐stage firn densification model produces more accurate dry firn densities at intermediate depths of 20–60 m. Compared to modeling firn using the equations in the (12 layer) Community Land Model (version 5), switching to the two‐stage firn densification model (with 16 layers) significantly decreases root‐mean‐square errors in upper 60 m dry firn densities by an average of 41 kg m −3 (31%). Simulations with three different firn density parameterizations show that the two‐stage firn densification model should be used for applications that prioritize accurate upper 60 m firn air content (FAC) in regions where the mean annual surface temperature is greater than roughly −31°C. Because snow metamorphism, firn density, and FAC are major components in modeling ice sheet surface albedo, melt water retention, and climatic mass balance, these developments advance broader efforts to simulate the response of land ice to atmospheric forcing in Earth system models.

58 GEOSCIENCES↗

DOE OSTI2023

Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids

As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many electric utilities de-energize power lines to prevent electric faults and failures. These preemptive power shutoffs are effective in reducing ignitions, but they could result in wide-scale power outages. Advanced technology, such as networked microgrids, can help reduce the size of the resulting power outages; however, even microgrid technology might not be sufficient to supply power to everyone, thus forcing hard questions about how to prioritize the provision of power among customers. In this paper, we present an optimization problem that configures networked microgrids to manage wildfire risk while maximizing the power served to customers; however, rather than simply maximizing the amount of power served in kilowatts, our formulation also considers the ability of customers to cope with power outages, as measured by social vulnerability, and it discourages the disconnection of particularly vulnerable customer groups. To test our model, we leverage a synthetic but realistic distribution feeder, along with publicly available social vulnerability indices and satellite-based wildfire risk map data, to quantify the parameters in our optimal decision-making model. Our case study results demonstrate the benefits of networked microgrids in limiting load shed and promoting equity during scenarios with high wildfire risk.

distribution systems↗

NASA NTRS2011

Visual Object Recognition and Tracking of Tools

A method has been created to automatically build an algorithm off-line, using computer-aided design (CAD) models, and to apply this at runtime. The object type is discriminated, and the position and orientation are identified. This system can work with a single image and can provide improved performance using multiple images provided from videos. The spatial processing unit uses three stages: (1) segmentation; (2) initial type, pose, and geometry (ITPG) estimation; and (3) refined type, pose, and geometry (RTPG) calculation. The image segmentation module files all the tools in an image and isolates them from the background. For this, the system uses edge-detection and thresholding to find the pixels that are part of a tool. After the pixels are identified, nearby pixels are grouped into blobs. These blobs represent the potential tools in the image and are the product of the segmentation algorithm. The second module uses matched filtering (or template matching). This approach is used for condensing synthetic images using an image subspace that captures key information. Three degrees of orientation, three degrees of position, and any number of degrees of freedom in geometry change are included. To do this, a template-matching framework is applied. This framework uses an off-line system for calculating template images, measurement images, and the measurements of the template images. These results are used online to match segmented tools against the templates. The final module is the RTPG processor. Its role is to find the exact states of the tools given initial conditions provided by the ITPG module. The requirement that the initial conditions exist allows this module to make use of a local search (whereas the ITPG module had global scope). To perform the local search, 3D model matching is used, where a synthetic image of the object is created and compared to the sensed data. The availability of low-cost PC graphics hardware allows rapid creation of synthetic images. In this approach, a function of orientation, distance, and articulation is defined as a metric on the difference between the captured image and a synthetic image with an object in the given orientation, distance, and articulation. The synthetic image is created using a model that is looked up in an object-model database. A composable software architecture is used for implementation. Video is first preprocessed to remove sensor anomalies (like dead pixels), and then is processed sequentially by a prioritized list of tracker-identifiers.

English, James↗

DOE OSTI2024

Evolving Competitive Markets in SAPP: Leveraging Competitive Wholesale Electricity Markets to Drive Renewable Generation Capacity in the Southern African Power Pool (SAPP)

The SADC region has significant natural resource potential to increase renewable energy generation, improve electricity reliability, and support economic development. This research finds an apparent lack of confidence from electricity infrastructure investors in SAPP wholesale electricity markets, which increases risk perception and lowers the likelihood of capital deployment. With respect to free market fundamentals, competitive market obstacles and renewable energy development obstacles are characterized. Stakeholders identified the top obstacles to well-functioning competitive markets as insufficient transmission infrastructure for interconnection and regional movement of electricity, dominance of national single-buyer markets, and lack of or weak nation-state regulatory frameworks. Stakeholders prioritized the top three obstacles for renewable energy development as a lack of viable commercial arrangements for variable renewable energy (VRE) balancing, lack of functional and consistent nation-level regulations, and higher project costs related to reliance on imported equipment. With respect to potential solution options, stakeholders prioritized the development of new cost allocation and finance methods to facilitate new transmission expansion, training to educate new or potential new market entrants on SAPP processes, as well as modeling and analysis of regional SAPP participation benefits disaggregated to the nation-state level. From these perspectives, this research identified strategy options for consideration including transitioning SAPP to a regional transmission operator (RTO) for operation and planning of cross-border transmission facilities and market administration, shifting operations of SAPP member transmission systems to Independent System Operators (ISOs), establishing a regional regulatory authority and enhancing market data transparency. Implementing these reforms is expected to be challenging, but not insurmountable, given the domestic political, legal, and jurisdictional complexities of the SADC region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2000

In Situ Resource Utilization Technologies for Enhancing and Expanding Mars Scientific and Exploration Missions

The primary objectives of the Mars exploration program are to collect data for planetary science in a quest to answer questions related to Origins, to search for evidence of extinct and extant life, and to expand the human presence in the solar system. The public and political engagement that is critical for support of a Mars exploration program is based on all of these objectives. In order to retain and to build public and political support, it is important for NASA to have an integrated Mars exploration plan, not separate robotic and human plans that exist in parallel or in sequence. The resolutions stemming from the current architectural review and prioritization of payloads may be pivotal in determining whether NASA will have such a unified plan and retain public support. There are several potential scientific and technological links between the robotic-only missions that have been flown and planned to date, and the combined robotic and human missions that will come in the future. Taking advantage of and leveraging those links are central to the idea of a unified Mars exploration plan. One such link is in situ resource utilization (ISRU) as an enabling technology to provide consumables such as fuels, oxygen, sweep and utility gases from the Mars atmosphere.

Sridhar, K. R.↗

NASA NTRS2000

ISRU Technologies for Mars Life Support

The primary objectives of the Mars Exploration program are to collect data for planetary science in a quest to answer questions related to Origins, to search for evidence of extinct and extant life, and to expand the human presence in the solar system. The public and political engagement that is critical for support of a Mars exploration program is based on all of these objectives. In order to retain and to build public and political support, it is important for NASA to have an integrated Mars exploration plan, not separate robotic and human plans that exist in parallel or in sequence. The resolution stemming from the current architectural review and prioritization of payloads may be pivotal in determining whether NASA will have such a unified plan and retain public support. There are several potential scientific and technological links between the robotic-only missions that have been flown and planned to date, and the robotic + human missions that will come in the future. Taking advantage of and leveraging those links are central to the idea of a unified Mars exploration plan. One such link is in situ resource utilization (ISRU) as an enabling technology to provide consumables such as fuels, oxygen, sweep and utility gases from the Mars atmosphere. ISRU for propellant production and for generation of life support consumables is a key element of human exploration mission plans because of the tremendous savings that can be realized in terms of launch costs and reduction in overall risk to the mission. The Human Exploration and Development of Space (HEDS) Enterprise has supported ISRU technology development for several years, and is funding the MIP and PROMISE payloads that will serve as the first demonstrations of ISRU technology for Mars. In our discussion and presentation at the workshop, we will highlight how the PROMISE ISRU experiment that has been selected by HEDS for a future Mars flight opportunity can extend and enhance the science experiments on board.

Finn, John E.↗

DOE OSTI2023

In Cell Thermal Creep Frames for Demonstration Project Preparations

The thrust of advanced nuclear reactor demonstrations demands the accelerated qualification of in-core materials to enable licensing processes and developing the performance data. Due to the high-operating temperatures of such reactors, long-term mechanical behavior under constant load is essential to determine the geometrical and mechanical integrity of in-core components during operation and off-normal conditions. Therefore, the thermal creep behavior of neutron-irradiated advanced reactor materials must be determined. The feasibility of using subsize specimens for the irradiation campaigns and the limited available infrastructure challenge the assessment of thermal creep behavior of advanced reactor materials. Therefore, the U.S. Department of Energy Office of Nuclear Energy (DOE-NE) National Reactor Innovation Center (NRIC) prioritizes the development of a thermal creep testing infrastructure for multiple subsize specimens to accelerate the demonstration and deployment of advanced reactor concepts. This report describes the activities for the construction of a thermal creep testing capability at Idaho National Laboratory (INL). The overall project consists of conceptual design, out-of-cell demonstration, and in-cell demonstration phases. During fiscal year (FY)-2021, the team finished the conceptual design of a thermal creep test facility that can test multiple subsize specimens. This conceptual design consisted of the determination of technical and functional requirements, the determination of the design space, and the preparation of the technical drawings. Technical and functional requirements were categorized as required and desired capabilities and the conceptual design was performed to meet all the required capabilities with the flexibility to achieve the desired capabilities. The design space identified the operational capacity of the creep frame for different advanced reactor relevant materials with the consideration of the feasible operation in the hotcell at the Fuels and Applied Science Building (FASB) at INL. Based on the requirements and design space, the multiple specimen creep frame was designed. The official INL engineering drawing process was started and the procurement of materials for construction was initiated. For FY-2022, the out-of-cell demonstration and final installation of the multiple creep frame is planned.

36 MATERIALS SCIENCE↗

NASA NTRS2007

Revitalization of Space-Related Human Factors, Environmental and Habitability Data

The NASA Chief Health and Medical Officer (CHMO) recently directed that the agency establish crew health standards to aid in the development of requirements for future vehicles and habitats. Response to this direction includes development of a new NASA habitability and human factors standard and an accompanying design handbook. The new standard contains high-level, over-arching principles to assure its applicability and usability across all NASA development programs. The handbook will provide detailed design requirements and suggestions that will meet the standards. The information contained in NASA-STD-3000 will be updated and included in the new design handbook. In this approach, each new program will derive detailed program-specific requirements from the new standard using the handbook as a design guide and resource. With the completion of the standard, the focus of this year s effort is the development of the new handbook: Human Integration Design Handbook (HIDH). This is an opportunity for the space flight human factors and habitability community to consolidate up-to-date data for use by NASA programs and designers as well as outside researchers and policy makers looking for the next research focus. The goal of the handbook is to help NASA design and build human space flight systems which accommodate the capabilities and limitations of the crew so as to provide an environment where the crew can live and work effectively, safely, and comfortably. Handbook contents will address that primary goal, addressing unique aspects of space flight and habitation, including reduced gravity conditions, time lags, EVA systems and day/night cycles, not addressed in other standards or handbooks. The handbook will be divided into topics similar to NASA-STD-3000 (anthropometrics, architecture, workstations, etc.) and each topic area will contain elements for designers, human factors practitioners, program managers, operators, and researchers. The handbook will include the following elements: (1) Design considerations include a clear and concise summary of what is important to designers in space vehicle / habitat design, design information to translate Earth-base knowledge to the space environment, space issues and the data necessary to address those issues, and a consistent set of terminology. (2) Updates to Lessons Learned and example solutions from Shuttle and Station program experience will provide historical examples to help prevent repeating mistakes or reinvention of the wheel. (3) Requirements will aid in the translation of standards into program specific requirements. The scope of included requirements will define the pool that each program needs to consider and tailor for their specific program. (4) Requirements rationale will help understanding of the importance of these considerations. The HIDH development team at JSC is finalizing the format of the new handbook, prioritizing topic areas for expansion and update, and contacting subject matter experts within the scientific community to assist with this effort. Plans are also being made to continue handbook expansion and maintenance to assure it remains a valuable resource for human factors and human space flight programs.

Russo, Dane↗

NASA NTRSDate not supplied

Baseline Medical System Translation for the Impact Medical Database

NASA has developed a new evidence-based data-driven probabilistic risk assessment and tradespace analysis tool as a successor to the Integrated Medical Model (IMM). This updated decision support tool is known as IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). Whereas IMM focuses on the resources and risks associated with International Space Station (ISS) and Low Earth Orbit (LEO) missions, IMPACT estimates the frequency and consequences of medical conditions that might arise during exploration missions. One of the services offered by IMM is a series of generic or baseline medical systems associated with typical mission types or DRMs (Design Reference Missions), such that requestors may prioritize questions pertaining to the mission itself over the medical supplies indicated by the model outputs for that DRM. In a mission focused request, the appropriate baseline medical system is used in place of a prepared or optimized medical kit. In preparation, an effort was undertaken to create baseline systems of medical resources within IMPACT suitable for typical DRMs. Using an existing baseline medical system within IMM’s Integrated Medical Evidence Database (iMED) as a starting point, the resources found within the medical kit were compared to and substituted for equivalent resources available within the IMPACT MD (Medical Database). In consultation with clinicians with knowledge of IMPACT’s MD, each resource was matched as closely as possible to a similarly purposed resource in IMPACT, seeking to preserve the treatment capabilities and procedures offered by the IMM medical system while reconciling the differences in modeled resources and medical conditions between the models. To demonstrate the efficacy of this work, a prototype ISS medical system in IMPACT was translated from the baseline used in the IMM. The appropriate medical system was then run through its associated medical model to compare and validate the resultant risks and risk mitigation provided by each baseline ISS medical kit.

S Schwartz↗

NASA NTRSDate not supplied

Informing Dionaea muscipula (Venus Flytrap) Conservation Through Habitat Modeling and Forecasted Land Cover Change

The carnivorous Dionaea muscipula (Venus flytrap, Droseraceae) is threatened by habitat loss, fire suppression, and poaching. For rare plant species like D. muscipula with specialized habitat requirements and fragmented distribution, habitat suitability modeling is an important method for guiding conservation efforts. To support the D. muscipula conservation, this study: 1) modeled suitable habitat across the extent of the species’ known range and 2) forecasted land cover change due to development in the study area to the year 2050. Habitat modeling was conducted by overlaying high-confidence presence data observed since 1980 (n=292) with environmental predictor variables (n=23). Suitable habitats were then compared with land cover change to identify areas at risk of habitat loss due to human development. According to those models, nearly half (107.1km2) of modeled highly suitable D. muscipula habitat outside of protected lands are likely to face development pressure. On the other hand, 39.4% (139.9km2) of highly suitable habitats overlap with protected lands and may serve as lasting D. muscipula habitat. Results from this study can inform D. muscipula conservation, including targeted seed banking of populations at risk of extirpation, prioritization of habitats for protection and management, and reintroduction to suitable habitats within protected areas.

Kathryn Caruso↗

DOE OSTI2025

Addressing the Split Incentive Challenge for Enhanced Solar Adoption in Multifamily Rental Properties [Abstract]

The split incentive problem is particularly pronounced in rental markets, where landlords prioritize investments that directly increase property value or rental income. Since energy savings from solar photovoltaic (PV) systems primarily benefit tenants, landlords may perceive little return on investment unless mechanisms exist to recapture some of the financial gains. The primary objective of this project is to develop a publicly available, web-based tool to analyze the U.S. Department of Energy’s ResStock database, which models the U.S. residential building stock. The tool allows users to filter buildings by location, type, HVAC system, square footage, and other characteristics, and outputs typical electric load profiles. By leveraging location-specific electric load data, Fram Energy aims to advance business strategies that address the split incentive barrier and promote the adoption of solar PV installations in rental properties. In addition, a machine learning model will be developed to weigh the marginal contribution of building features across the dataset in predicting electricity demand, supporting guided decision making in forecasting electric load profiles. Lastly, based on each building’s location, load profile, and utility’s electricity rate, an optimized solar photovoltaic array and battery energy storage system will be sized to provide energy arbitrage opportunities.

14 SOLAR ENERGY↗