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At least 883 records · Page 49

Use of VIIRS DNB Data to Monitor Power Outages and Restoration for Significant Weather Events

NASA fs Short-term Prediction Research and Transition (SPoRT) project operates from NASA's Marshall Space Flight Center in Huntsville, Alabama. The team provides unique satellite data to the National Weather Service (NWS) and other agencies and organizations for weather analysis. While much of its work is focused on improving short-term weather forecasting, the SPoRT team supported damage assessment and response to Hurricane Superstorm Sandy by providing imagery that highlighted regions without power. The team used data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. The VIIRS low-light sensor, known as the day-night-band (DNB), can detect nighttime light from wildfires, urban and rural communities, and other human activity which emits light. It can also detect moonlight reflected from clouds and surface features. Using real time VIIRS data collected by our collaborative partner at the Space Science and Engineering Center of the University of Wisconsin, the SPoRT team created composite imagery to help detect power outages and restoration. This blackout imagery allowed emergency response teams from a variety of agencies to better plan and marshal resources for recovery efforts. The blackout product identified large-scale outages, offering a comprehensive perspective beyond a patchwork GIS mapping of outages that utility companies provide based on customer complaints. To support the relief efforts, the team provided its imagery to the USGS data portal, which the Federal Emergency Management Agency (FEMA) and other agencies used in their relief efforts. The team fs product helped FEMA, the U.S. Army Corps of Engineers, and U.S. Army monitor regions without power as part of their disaster response activities. Disaster responders used the images to identify possible outages and effectively distribute relief resources. An enhanced product is being developed and integrated into a web mapping service (WMS) for dissemination and use by a broader end user community.

Jedlovec, Gary↗

FY 2022 Idaho National Laboratory Site Sustainability Plan

The mission of the Department of Energy (DOE) is to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions. This FY 2022 Idaho National Laboratory Site Sustainability Plan (SSP) was developed to enable and sustain Idaho National Laboratory’s (INL’s) mission to discover, demonstrate, and secure innovative nuclear solutions, clean energy options, and critical infrastructure. DOE Order 436.1, “Departmental Sustainability,” provides requirements and assigns responsibilities for managing sustainability within DOE to ensure that DOE missions are carried out in a sustainable manner, to institute wholesale cultural change to factor sustainability into all DOE decisions, and to ensure DOE achieves sustainability goals. DOE Order 436.1 also requires DOE sites to commit appropriate personnel resources, establish a financing plan that prioritizes the use of life-cycle cost effective private-sector financing, optimize the application of appropriations and budgeted funds, and establish specific performance measures and deliverables designed to achieve the listed requirements. The SSP was developed according to the narrative requirements from the “FY 2022 DOE Site Sustainability Plan Guidance” document issued in September 2021. The SSP contains strategies and activities that will lead to continual energy, water, and waste reductions that move the INL site toward meeting DOE sustainability goals and requirements. The SSP summarizes energy and available fuel use reporting requirements and references criteria for instituting sustainable design. SSP requirements are integrated into each INL site contractor’s Integrated Safety Management System and Environmental Management System (EMS). Finally, the Sustainability Program directives, based on this SSP, are integrated into INL/LTD-21-62463, Annual Laboratory Plan 2021, and operations and acquisition systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

FY 2023 Idaho National Laboratory Site Sustainability Plan

The mission of the Department of Energy (DOE) is to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions. This FY 2022 Idaho National Laboratory Site Sustainability Plan (SSP) was developed to enable and sustain Idaho National Laboratory’s (INL’s) mission to discover, demonstrate, and secure innovative nuclear solutions, clean energy options, and critical infrastructure. DOE Order 436.1, “Departmental Sustainability,” provides requirements and assigns responsibilities for managing sustainability within DOE to ensure that DOE missions are carried out in a sustainable manner, to institute wholesale cultural change to factor sustainability into all DOE decisions, and to ensure DOE achieves sustainability goals. DOE Order 436.1 also requires DOE sites to commit appropriate personnel resources, establish a financing plan that prioritizes the use of life-cycle cost effective private-sector financing, optimize the application of appropriations and budgeted funds, and establish specific performance measures and deliverables designed to achieve the listed requirements. The SSP was developed according to the narrative requirements from the “FY 2022 DOE Site Sustainability Plan Guidance” document issued in September 2021. The SSP contains strategies and activities that will lead to continual energy, water, and waste reductions that move the INL site toward meeting DOE sustainability goals and requirements. The SSP summarizes energy and available fuel use reporting requirements and references criteria for instituting sustainable design. SSP requirements are integrated into each INL site contractor’s Integrated Safety Management System and Environmental Management System (EMS). Finally, the Sustainability Program directives, based on this SSP, are integrated into INL/LTD-21-62463, Annual Laboratory Plan 2021, and operations and acquisition systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Towards a Circular Economy for PET Bottles in the U.S. - 4P Model

The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.

carbon↗

Advancing Asset Management in Water Infrastructure Systems

Aging water system infrastructure, including drinking water, wastewater, and stormwater, poses a growing challenge for utilities and municipalities. These water systems have well documented challenges with respect to their age, condition, and level of service. ASCE annual report cards consistently rate these infrastructure systems in the United States as underfunded, overcapacity, or past service life (ASCE 2025 Report Card). For example, Chini and Stillwell (2017) estimated that the mean water loss in drinking water systems, i.e., non-revenue water, is approximately 16% across the United States. These concerns are not just relegated to the United States, with Courtenay, British Columbia, identifying 17% of their water main pipes as in a ‘poor’ condition state, defined as a category condition 5 out of 5 (City of Courtenay, 2024). These cases illustrate the challenges utilities are facing to manage extensive networks of infrastructure to deliver a consistent and high level of service. For buried infrastructure such as water systems, studies suggest that preventative interventions can lead to lower maintenance costs and fewer service disruptions (Mazumder et al, 2018; Li et al, 2014). The demonstrated need and benefit of appropriately applied asset management is juxtaposed against the relatively sparse literature that evaluates water systems within an asset management construct. Since 2020, just 37 papers specifically reference asset management in the Journal of Water Resources Planning and Management. Of those, only a few specifically look to develop strategies for improved asset management. Therefore, we highlight four key research areas that represent opportunities for advancement of asset management research for water systems. First, advances in condition assessment and forecasting are needed to better estimate asset deterioration using diverse datasets. Second, machine learning (ML) and artificial intelligence (AI) hold promise for predictive maintenance and investment prioritization, though questions of generalizability and model transparency remain. Third, applying a value of information framework can guide utilities in making cost-effective sensor deployment and data collection decisions, to direct monitoring strategies towards data-informed asset management decisions. Finally, integrated infrastructure management is critical, requiring coordinated planning with other infrastructure systems and stakeholder engagement to reduce costs and enhance service delivery.

Chini, Christopher M.↗

Renewable Energy and Efficiency Technologies in Scenarios of U.S. Decarbonization in Two Types of Models: Comparison of GCAM Modeling and Sector-Specific Modeling

Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Capability for Integrated Systems Risk-Reduction Analysis

NASA's Human Research Program (HRP) is working to increase the likelihoods of human health and performance success during long-duration missions, and subsequent crew long-term health. To achieve these goals, there is a need to develop an integrated understanding of how the complex human physiological-socio-technical mission system behaves in spaceflight. This understanding will allow HRP to provide cross-disciplinary spaceflight countermeasures while minimizing resources such as mass, power, and volume. This understanding will also allow development of tools to assess the state of and enhance the resilience of individual crewmembers, teams, and the integrated mission system. We will discuss a set of risk-reduction questions that has been identified to guide the systems approach necessary to meet these needs. In addition, a framework of factors influencing human health and performance in space, called the Contributing Factor Map (CFM), is being applied as the backbone for incorporating information addressing these questions from sources throughout HRP. Using the common language of the CFM, information from sources such as the Human System Risk Board summaries, Integrated Research Plan, and HRP-funded publications has been combined and visualized in ways that allow insight into cross-disciplinary interconnections in a systematic, standardized fashion. We will show examples of these visualizations. We will also discuss applications of the resulting analysis capability that can inform science portfolio decisions, such as areas in which cross-disciplinary solicitations or countermeasure development will potentially be fruitful.

Mindock, J.↗

Ames Engineering Directorate

The Ames Engineering Directorate is the principal engineering organization supporting aerospace systems and spaceflight projects at NASA's Ames Research Center in California's Silicon Valley. The Directorate supports all phases of engineering and project management for flight and mission projects-from R&D to Close-out-by leveraging the capabilities of multiple divisions and facilities.The Mission Design Center (MDC) has full end-to-end mission design capability with sophisticated analysis and simulation tools in a collaborative concurrent design environment. Services include concept maturity level (CML) maturation, spacecraft design and trades, scientific instruments selection, feasibility assessments, and proposal support and partnerships. The Engineering Systems Division provides robust project management support as well as systems engineering, mechanical and electrical analysis and design, technical authority and project integration support to a variety of programs and projects across NASA centers. The Applied Manufacturing Division turns abstract ideas into tangible hardware for aeronautics, spaceflight and science applications, specializing in fabrication methods and management of complex fabrication projects. The Engineering Evaluation Lab (EEL) provides full satellite or payload environmental testing services including vibration, temperature, humidity, immersion, pressure/altitude, vacuum, high G centrifuge, shock impact testing and the Flight Processing Center (FPC), which includes cleanrooms, bonded stores and flight preparation resources. The Multi-Mission Operations Center (MMOC) is composed of the facilities, networks, IT equipment, software and support services needed by flight projects to effectively and efficiently perform all mission functions, including planning, scheduling, command, telemetry processing and science analysis.

Small Satellites↗

In Situ Resource Utilization (ISRU) Envisioned Future Priorities

The National Aeronautics and Space Administration (NASA) of the United States of America (US) has initiated the Artemis Moon to Mars program to send astronauts (the first woman and person of color) back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface in the 2030’s. A major objective of this program is to characterize the resources that exist on the Moon and Mars, and learn how to utilize them for sustained and affordable exploration. Commonly known as In Situ Resource Utilization (ISRU), the search for, acquisition, and processing of resources in space has the potential to greatly reduce the dependency on transporting mission consumables and infrastructure from Earth, thereby reducing mission costs, risks, and dependency on Earth. Through the extraction and processing of resources into mission commodities such as rocket propellants, life support consumables, and fuel cell reactants, ISRU enhances and evolves the cis-lunar, lander, and surface transportation systems required for human exploration; expanding and ehancing HOW humans get to, explore, and return from the Moon. Through the extraction and processing of resources into metals, silicon, and other manufacturing and construction feedstock, ISRU enhances and allows for the expansion of critical infrastructure through in situ manufacturing and construction capabilities needed for WHAT humans do on the Moon and in cis-lunar space. Because of this, ISRU supports and enables commercial involvement beyond NASA and governmental agencies by both lowering the cost of sustained transportation to/from/on the Moon as well as supporting the market required for needing these transportation systems. To achieve this vision, NASA’s Space Technology Mission Directorate (STMD) ensures the coordinated development of ISRU and other critical space and surface infrastructure elements such as propulsion, power, manufacturing, construction, and robotics through the Strategic Technology Architecture Roundtable (STAR) process. Through STAR, an integrated framework and process has been created allowing for capabilities and technologies to be linked and assessed, gaps to be identified, specifications and metrics to be established, and provide a means to prioritize and implement technology development and missions. For lunar ISRU, three primary areas of development have been initiated, (1) understanding, mapping, extracting, and processing water and other volatiles found in polar permanently shadowed regions (PSRs), (2) methods, technologies to extract oxygen from regolith, and (3) methods, technologies, and use cases for metals, silicon, and other feedstock commodities extracted and produced from lunar resources. This presentation will briefly discuss the STAR process and elaborate on the current status and future plans for ISRU development, demonstration, and architecture implementation of NASA’s Envisioned Future Priorities plan for ISRU.

In Situ Resource Utilization↗

Geothermal-Enabled Zero Energy Community: A Techno-Economic Design Study to Address Cold-Climate Challenges

In northern climates, developing a zero-energy community is increasingly costly. Building loads are higher, thanks to the colder weather, and solar PV is both less effective, due to lower solar incidence, and misalignment with the buildings' energy needs (summer production, winter demands). We present a novel application for geothermal energy production in support of a zero-energy community, combining appropriate energy efficiency (demand design), geothermal production (supply design), and asset dispatch as an integrated technoeconomic package. This poster presents the process used to explore this system integration challenge, initial results, and discusses some of the technical opportunities for increasing the community-scale adoption of geothermal as an electric and thermal resource. Results indicate that under certain conditions, community-scale geothermal resources are quite competitive with today's grid tariffs and with PV, showing an LCOE within $0.01/kWh before consideration of important grid modernization factors such as resiliency and reliability.

15 GEOTHERMAL ENERGY↗

Identifying requisite changes to support modern maintenance practices - 294

Modern data science and processing require the use of modern maintenance records. With traditional record-keeping practices, the isolated nature of the data, as well as the presence of handwritten maintenance work orders and incomplete service logs, severely limit the amount of progress that can be made towards advanced condition-based maintenance. These condition-based methods of diagnostics, prognostics, and maintenance planning are a primary goal of next-generation plant operations and maintenance strategies, and are all dependent on the availability of quality plant data including maintenance data. By implementing changes to maintenance record-keeping practices, such as the use of a computerized maintenance management system, key data will become available to allow for implementation of state-of-the-art data analysis methods. This paper covers the benefits of utilizing digital record systems to increase maintenance data availability in terms of condition-based maintenance and asset management. The ability of these methods to enable state-of-the-art practices within industrial organizations is discussed to offer insight into ways that these improvements to operating strategy will contribute to improvements in world-class maintenance excellence. A discussion of the future of asset management in terms of data analytics, maintenance decision support, and data integration is provided to illustrate the changing landscape of plant management. The result is an examination of innovative maintenance strategies and discussion of challenges related to the future of asset management and implementing modern maintenance practices. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

REopt: Enabling Renewable Energy, Storage, and Combined Heat and Power

Deployment of distributed energy resources including combined heat and power (CHP), photovoltaics (PV), and battery storage is growing as building and campus owners seek to reduce energy costs and increase resilience to grid outages. While deployment of a single technology is widespread, integrated systems of multiple technologies are also becoming more common to provide maximum economic and resilience benefits. To accelerate deployment, decision makers require tools to evaluate the technical and economic feasibility of these integrated systems. This paper presents a framework for optimizing the size and dispatch strategy of CHP with PV and battery storage to minimize life-cycle cost of energy. The modeling methodology is presented, with a particular focus on the linearization of cost and performance metrics required for implementation in a mixed integer linear program. A case study is used to examine the technical and economic viability of integrated CHP, PV, and battery systems, compared to CHP-only or PV+battery storage systems. In the case study we show how the integrated systems can provide increased economic and resilience benefits compared to single technologies on their own. The case study presented shows the combined CHP, PV, and battery system resulted in a 7% lower life cycle cost than CHP only, and a 22% lower life cycle cost than PV+battery storage. The life cycle emissions for CHP, PV, and battery storage resulted in a 24% reduction than CHP only and a 17% increase than PV+battery storage.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Design and Operation of Energy Systems with Large Amounts of Variable Generation: IEA Wind TCP Task 25 (Final Summary Report)

This report summarizes findings on wind integration from the 17 countries or sponsors participating in the International Energy Agency Wind Technology Collaboration Program (IEA Wind TCP) Task 25 from 2006-2020. Both real experience and studies are reported. Many wind integration studies incorporate solar energy, and most of the results discussed here are valid for other variable renewables in addition to wind. The national case studies address several impacts of wind power on electric power systems. In this report, they are grouped under long-term planning issues and short-term operational impacts. Long-term planning issues include grid planning and capacity adequacy. Short-term operational impacts include reliability, stability, reserves, and maximizing the value of wind in operational timescales (balancing related issues). The first section presents the variability and uncertainty of power system-wide wind power, and the last section presents recent studies toward 100% shares of renewables. The appendix provides a summary of ongoing research in the national projects contributing to Task 25 for 2021-2024. The design and operation of power and energy systems is an evolving field. As ambitious targets toward net-zero carbon energy systems are announced globally, many scenarios are being made regarding how to reach these future decarbonized energy systems, most of them involving large amounts of variable renewables, mainly wind and solar energy. The secure operation of power systems is increasingly challenging, and the impacts of variable renewables, new electrification loads together with increased distribution system resources will lead to somewhat different challenges for different systems. Tools and methods to study future power and energy systems also need to evolve, and both short-term operational aspects (such as power system stability) and long-term aspects (such as resource adequacy) will probably see new paradigms of operation and design. The experience of operating and planning systems with large amounts of variable generation is accumulating, and research to tackle the challenges of inverter-based, nonsynchronous generation is on the way. Energy transition and digitalization also bring new flexibility opportunities, both short and long term.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advancing uncertainty characterization for understanding projected water scarcity in multi-sector, multi-actor river basins across scales.

Invited Talk at AGU Fall Meeting 2023 Modeling how human institutions and infrastructure interact with the water cycle is essential to better understand the vulnerability, and resilience of water resources systems from the local to the global scale. This is especially true when investigating multi-sector, multi-actor responses to the effects of long-term changes and short-term shocks. It is also well recognized that uncertainty present throughout the modeling cycle (e.g., in data, functional relations, and model coupling approaches) limits our ability to trace the interactive dynamics of human-water systems, as well as to quantify their implications for management and planning. Systems with large numbers of diverse stakeholders further compound this challenge, as uncertain drivers and complex dynamics might have very disparate effects on water users. The work presented is conducted through the Integrated Multisector Multiscale Modeling (IM3) Science Focus Area, which explores how human and natural systems co-evolve in response to change. Through this multi-year effort, we have developed exploratory modeling methods to better characterize how the uncertain human and natural drivers of water scarcity yield consequential vulnerabilities in institutionally complex, multi-sectoral systems. This talk will specifically present on a series of uncertainty characterization experiments performed in the Upper Colorado River Basin, a sub-basin of the Colorado with thousands of water users. These complementary and systematic experiments are aimed at understanding: How are various uncertain stressors (e.g., climate change, demand growth) affecting the diverse water users of this basin in terms of water shortage? What are the key drivers of this shortage for each user? Methods and results from this work are used to address additional questions on the ability of adaptation to modulate the effects of these uncertain drivers, and on their compounding effects across spatial scales and through sectoral interactions.

Hadjimichael, Antonia↗

An Extensible, User- Modifiable Framework for Planning Activities

This software provides a development framework that allows planning activities for the Mars Science Laboratory rover to be altered at any time, based on changes of the Activity Dictionary. The Activity Dictionary contains the definition of all activities that can be carried out by a particular asset (robotic or human). These definitions (and combinations of these definitions) are used by mission planners to give a daily plan of what a mission should do. During the development and course of the mission, the Activity Dictionary and actions that are going to be carried out will often be changed. Previously, such changes would require a change to the software and redeployment. Now, the Activity Dictionary authors are able to customize activity definitions, parameters, and resource usage without requiring redeployment. This software provides developers and end users the ability to modify the behavior of automatically generated activities using a script. This allows changes to the software behavior without incurring the burden of redeployment. This software is currently being used for the Mars Science Laboratory, and is in the process of being integrated into the LADEE (Lunar Atmosphere and Dust Environment Explorer) mission, as well as the International Space Station.

Joshing, Joseph C.↗

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

Jay Lemery↗

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

John Lemery↗

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗