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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This paper discusses a proof-of-concept prototype for ground-based automatic generation of validated rover command sequences from high-level goals using AI-based planning software.
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We present a novel use of Monte Carlo Tree Search (MCTS),adapted to explore a search space produced by the choice points embedded in Python code. The choice points are non-deterministic assignment statements and subroutine calls. We present MCTS extensions required for doing tree search in this context which includes control constructs like hierarchical decomposition (subroutine calls), iterative while loops and conditional statements. We demonstrate how the system works in a simulated rideshare scenario in an urban setting, and present preliminary experiments as a proof of concept.
The National Aeronautics and Space Administration Integrated Vehicle Health Management program touches on many different research areas while striving to enable the automated detection, diagnosis, prognosis, and mitigation of adverse events at the aircraft and system level. At the system level, the research focus is on the evaluation of multidisciplinary integrated methods, tools, and technologies for achieving the program goal. The participating program members form a diverse group of government, industry, and academic researchers. The program team developed the Research and Test Integration Plan in order to track significant test and evaluation activities, which are important for understanding, demonstrating, and communicating the overall project state and project direction. The Plan is a living document, which allows the project team the flexibility to construct conceptual test scenarios and to track project resources. The Plan also incorporates several desirable feature requirements for Plan users and maintainers. A wiki has proven to be the most efficient and effective means of implementing the feature requirements for the Plan. The wiki has proven very valuable as a research project management tool, and there are plans to expand its scope.
The Integrated Research Plan (IRP) describes the portfolio of Human Research Program (HRP) research and technology tasks. The IRP is the HRP strategic and tactical plan for research necessary to meet HRP requirements. The need to produce an IRP is established in HRP-47052, Human Research Program - Program Plan, and is under configuration management control of the Human Research Program Control Board (HRPCB). Crew health and performance is critical to successful human exploration beyond low Earth orbit. The Human Research Program (HRP) is essential to enabling extended periods of space exploration because it provides knowledge and tools to mitigate risks to human health and performance. Risks include physiological and behavioral effects from radiation and hypogravity environments, as well as unique challenges in medical support, human factors, and behavioral or psychological factors. The Human Research Program (HRP) delivers human health and performance countermeasures, knowledge, technologies and tools to enable safe, reliable, and productive human space exploration. Without HRP results, NASA will face unknown and unacceptable risks for mission success and post-mission crew health. This Integrated Research Plan (IRP) describes HRP s approach and research activities that are intended to address the needs of human space exploration and serve HRP customers and how they are integrated to provide a risk mitigation tool. The scope of the IRP is limited to the activities that can be conducted with the resources available to the HRP; it does not contain activities that would be performed if additional resources were available. The timescale of human space exploration is envisioned to take many decades. The IRP illustrates the program s research plan through the timescale of early lunar missions of extended duration.
Increasing heat poses a growing threat to cities worldwide due to both climate change and the urban heat island effect. While heat planning and governance are still emergent, research suggests that silos and conflicts within cities' networks of plans often impede heat resilience. Integrated heat resilience planning, therefore, requires a systematic and comprehensive analysis of the silos and conflicts relevant to heat resilience within networks of plans. This study is the first to combine three complementary plan evaluation methods to assess how cities' networks of plans address heat resilience. We applied 1) plan cross-referencing, 2) Plan Quality Evaluation for Heat Resilience, and 3) Plan Integration for Resilience Scorecard™ (PIRS™) for Heat to 19 plans from seven Arizona cities. We find similarities and differences in how these cities' networks of plans address heat hazards. The plans have consistently high-quality participation and coordination principles but lack details on vulnerability and climate change uncertainty, suggesting a need to move beyond immediate heat risks. We also identify opportunities to diversify policy mechanisms, spatially target high heat risk areas, and enhance the connection between planning efforts. These results validate that plan elements are interlinked and the importance of integrative plan development processes to improve heat resilience.
The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.
A detailed Lunar Ultraviolet Telescope Experiment (LUTE) program plan representing major decisions and tasks leading to those decisions for program execution are presented. The purpose of this task was to develop an integrated plan of project activities for the LUTE project, and to display the plan as an integrated network that shows the project activities, all critical interfaces, and schedules. The integrated network will provide the project manager with a frame work for strategic planning and risk management throughout the life of the project.
Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.
Progress toward the development of effective, practical solutions to space-based observatory scheduling problems within the HSTS scheduling framework is reported. HSTS was developed and originally applied in the context of the Hubble Space Telescope (HST) short-term observation scheduling problem. The work was motivated by the limitations of the current solution and, more generally, by the insufficiency of classical planning and scheduling approaches in this problem context. HSTS has subsequently been used to develop improved heuristic solution techniques in related scheduling domains and is currently being applied to develop a scheduling tool for the upcoming Submillimeter Wave Astronomy Satellite (SWAS) mission. The salient architectural characteristics of HSTS and their relationship to previous scheduling and AI planning research are summarized. Then, some key problem decomposition techniques underlying the integrated planning and scheduling approach to the HST problem are described; research results indicate that these techniques provide leverage in solving space-based observatory scheduling problems. Finally, more recently developed constraint-posting scheduling procedures and the current SWAS application focus are summarized.
This document supplements the white paper titled CBS Integrated Research Plan: Problem Statement. The Problem Statement describes why it is important to implement a fully integrated research plan to derive risk estimates for the combined, potentially synergistic, effects of the three major spaceflight hazards (space radiation; isolated, confined, and extreme environments; altered gravity). These risk estimates will help establish acceptable maximum decrement or change in a physiological or behavioral parameter during or after spaceflight, and the acceptable limit of exposure to the combined spaceflight hazards. This Implementation Strategy describes how the research plan will accomplish the CBS Integrated Research Plan goals. The Implementation Strategy includes approaches to evaluate relationships among biological responses underlying three risks that are managed by three of NASA’s Human Research Project (HRP) organizational “elements”. This CBS (Acute effects of radiation on CNS, BMed, Sensorimotor) Integrated Research Plan also identifies strategies to monitor and mitigate decrements to operationally relevant performance. Currently, the strategy that was initiated in 2018, includes an eight-year research plan and a four-year validation plan that extend to the year 2030. Once the monitoring tools and countermeasures are developed, they will be validated and refined during four years of early exploration missions. The planned tasks and their associated research products and deliverables have been mapped to the individual research emphases to clearly demonstrate how each research area helps ensure crew health and safety during exploration missions.
Payload and module integration development and qualification test plan for combined mission flights of Apollo applications program