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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 27: Knowledge diffusion and US government technology policy: Issues and opportunities for sci/tech librarians

Federal involvement in simulating economic growth through the development and application of technology policy is currently the subject of serious debate. A recession and the recognition that an internationally competitive economy is a prerequisite for the attainment of national goals have fostered a number of technology policy initiatives aimed at improving the economic competitiveness of American industry. This paper suggests that the successful implementation of U.S. technology policy will require the adoption of a knowledge diffusion model, the development of user oriented information products and services, and a more 'activist' approach on the part of sci/tech librarians in the provision of scientific and technical information (STI). These changes will have a dramatic impact on the sci/tech library of the future and the preparation of sci/tech librarians.

Pinelli, Thomas E.↗
NASA NTRS1992

NASA/DoD Aerospace Knowledge Diffusion Research Project. XXVII - Knowledge diffusion and U.S. government technology policy: Issues and opportunities for sci/tech librarians

Federal involvement in stimulating economic growth through the development and application of technology policy is currently the subject of serious debate. A recession and the recognition that an internationally competitive economy is a prerequisite for the attainment of national goals have fostered a number of technology policy initiatives aimed at improving the economic competitiveness of American industry. This paper suggests that the successful implementation of U.S. technology policy will require the adoption of a knowledge diffusion model, the development of user oriented information products and services, and a more 'activist' approach on the part of sci/tech librarians in the provision of scientific and technical information (STI). These changes will have a dramatic impact on the sci/tech library of the future and the preparation of sci/tech librarians.

Pinelli, Thomas E.↗
NASA NTRS2000

An Examination of the U.S. Regional Airline Policies Regarding Child Restraint Systems

A prior study examined the policies of U.S. air carriers with regard to the use of infant restraint systems on board commercial aircraft. This study expands on that earlier study by examining the policies of commuter air carriers in the United States regarding the use of infant restraint systems. The management policy of the commuter air carriers has been investigated and officials of the commuter air carriers were surveyed to determine how the carriage of infants onboard their aircraft varied among commuter airlines. The topics investigated included seat space for infants, restraint systems for infants, and amenities for infant passengers. The results of this study have been analyzed to ascertain if any recommendations can be made to the commuter airlines regarding the carriage of infants onboard their aircraft.

Carstenson, Larry↗
NASA NTRS1994

Revision to Planetary Protection Policy for Mars Missions

Under existing COSPAR policy adopted in 1984, missions to Mars (landers, probes, and some orbiters) are designated as Category IV missions. As such, the procedures for implementing planetary protection requirements could include trajectory biasing, cleanrooms, bioload reduction, sterilization of hardware, and bioshields, i. e. requirements could be similar to Viking. However, in 1992, a U. S. National Academy of Sciences study recommended that controls on forward contamination of Mars be tied to specific mission objectives. The report recommended that Mars landers with life detection instruments be subject to at least Viking-level sterilization procedures for bioload reduction, while spacecraft (including orbiters) without life detection instruments be subject to at least Viking-level pre sterilization procedures for bioload reduction but need not be sterilized. In light of this, it is proposed that the current policy's Category IV missions and their planetary protection requirements be divided into two subcategories as follows: Category IV A, for missions comprising landers and probes without life detection experiments and some orbiters, which will meet a specified bioburden limit for exposed surfaces; Category IV B, for landers and probes with life detection experiments, which will require complete system sterilization. For Category IV A missions, bioburden specifications will be proposed and implementing procedures discussed. A resolution will be proposed to modify the existing COSPAR policy to reflect these changes. Similar specifications, procedures, and resolution for Category IV B missions will be the subject of a later study.

DeVincenzi, D. L.↗
NASA NTRS2001

Certifying Domain-Specific Policies

Proof-checking code for compliance to safety policies potentially enables a product-oriented approach to certain aspects of software certification. To date, previous research has focused on generic, low-level programming-language properties such as memory type safety. In this paper we consider proof-checking higher-level domain -specific properties for compliance to safety policies. The paper first describes a framework related to abstract interpretation in which compliance to a class of certification policies can be efficiently calculated Membership equational logic is shown to provide a rich logic for carrying out such calculations, including partiality, for certification. The architecture for a domain-specific certifier is described, followed by an implemented case study. The case study considers consistency of abstract variable attributes in code that performs geometric calculations in Aerospace systems.

Lowry, Michael↗
NASA NTRS2004

Extreme Environments Development of Decision Processes and Training Programs for Medical Policy Formulation

The purpose of this workshop was to survey existing health and safety policies as well as processes and practices for various extreme environments; to identify strengths and shortcomings of these processes; and to recommend parameters for inclusion in a generic approach to policy formulation, applicable to the broadest categories of extreme environments. It was anticipated that two additional workshops would follow. The November 7, 2003 workshop would be devoted to the evaluation of different model(s) and a concluding expert evaluation of the usefulness of the model using a policy formulation example. The final workshop was planned for March 2004.

Stough, Roger↗
NASA NTRS2006

The New Jettison Policy for the International Space Station

During more than seven years of operations by the International Space Station (ISS), approximately three dozen pieces of debris were released and subsequently cataloged by the U.S. Space Surveillance Network (SSN). The individual mass of these objects ranged from less than 1 kg to 70 kg. Although some of these debris were separated from the ISS accidentally, some were intentionally cast-off, especially the larger items. In addition, small operational satellites are candidates for launch from the ISS, such as the TNS-O satellite deployed from ISS in March 2005. Recently an official ISS Jettison Policy was developed to ensure that decisions to deliberately release objects in the future were based upon a complete evaluation of the benefits and risks to the ISS, other resident space objects, and people on the Earth. The policy identifies four categories of items which might be considered for release: (1) items that pose a safety issue for return on-board a visiting vehicle, (2) items that negatively impact ISS utilization, return, or on-orbit stowage manifests, (3) items that represent an EVA timeline savings, and (4) items that are designed for jettison. Some of the principal issues to be addressed during this evaluation process are the potential for the object to recontact the ISS within the first two days after jettison, the potential of the object to breakup prior to reentry, the ability of the SSN to track the object, and the risk to people on Earth from components which might survive reentry. This paper summarizes the history of objects released from ISS, examines the specifics of the ISS jettison policy, and addresses the overall impact of ISS debris on the space environment.

Johnson, Nicholas L.↗
NASA NTRS2006

A Model-Driven Architecture Approach for Modeling, Specifying and Deploying Policies in Autonomous and Autonomic Systems

Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self-Management. The Model Driven Architecture (MDA) approach focuses on building models that can be transformed into code in an automatic manner. In this paper, we look at ways to implement Policy-Based Self-Management by means of models that can be converted to code using transformations that follow the MDA philosophy. We propose a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system.

Pena, Joaquin↗
NASA NTRS2011

Systems, methods and apparatus for modeling, specifying and deploying policies in autonomous and autonomic systems using agent-oriented software engineering

Systems, methods and apparatus are provided through which in some embodiments, an agent-oriented specification modeled with MaCMAS, is analyzed, flaws in the agent-oriented specification modeled with MaCMAS are corrected, and an implementation is derived from the corrected agent-oriented specification. Described herein are systems, method and apparatus that produce fully (mathematically) tractable development of agent-oriented specification(s) modeled with methodology fragment for analyzing complex multiagent systems (MaCMAS) and policies for autonomic systems from requirements through to code generation. The systems, method and apparatus described herein are illustrated through an example showing how user formulated policies can be translated into a formal mode which can then be converted to code. The requirements-based programming systems, method and apparatus described herein may provide faster, higher quality development and maintenance of autonomic systems based on user formulation of policies.

Hinchey, Michael G.↗
NASA NTRS2016

Potential Impact of a US Climate Policy and Air Quality Regulations on Future Air Quality and Climate Change

We have investigated how future air quality and climate change are influenced by the US air quality regulations that existed or were proposed in 2013 and a hypothetical climate mitigation policy that aims to reduce 2050 CO2 emissions to be 50% below 2005 emissions. Using the NASA GISS ModelE2 general circulation model, we look at the impacts for year 2030 and 2055. The US energy-sector emissions are from the GLIMPSE project (GEOS-Chem LIDORT Integrated with MARKAL (MARKet ALlocation) for the Purpose of Scenario Exploration), and other US emissions data sets and the rest of the world emissions data sets are based on the RCP4.5 scenario. The US air quality regulations are projected to have a strong beneficial impact on US air quality and public health in year 2030 and 2055 but result in positive radiative forcing. Under this scenario, no more emission constraints are added after 2020, and the impacts on air quality and climate change are similar between year 2030 and 2055. Surface particulate matter with a diameter smaller than 2.5 micron PM(sub 2:5) is reduced by 2 approximately μg/m(sup -3) on average over the USA, and surface ozone by approximately 8 ppbv. The improved air quality prevents about 91 400 premature deaths in the USA, mainly due to the PM(sub 2:5) reduction approximately (74 200 lives saved). The air quality regulations reduce the light-reflecting aerosols (i.e., sulfate and organic matter) more than the light-absorbing species (i.e., black carbon and ozone), leading to a strong positive radiative forcing (RF) over the USA by both aerosols' direct and indirect forcing: the total RF is approximately 0.04 W m(sup -2) over the globe, and approximately 0.8 W m(sup -2) over the USA. Under the hypothetical climate policy, a future CO2 emissions cut is achieved in part by relying less on coal, and thus SO2 emissions are noticeably reduced. This provides air quality co-benefits, but it could lead to potential climate disbenefits over the USA. In 2055, the US mean total RF is +C02 W m(sup -2) due to positive aerosol direct and indirect forcing, while the global mean total RF is -0.06 W m(sup -2) due to the dominant negative CO2 RF (instantaneous RF). To achieve a regional-scale climate benefit via a climate policy, it is critical (1) to have multinational efforts to reduce greenhouse gas (GHG) emissions and (2) to simultaneously target emission reduction of light-absorbing species (e.g., BC and O3) on top of long-lived species. The latter is very desirable as the resulting climate benefit occurs faster and provides cobenefits to air quality and public health.

Air quality↗
DOE OSTI2021

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. Here, the framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure --- this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2022

How to Build a Connected Community: Policies to Promote Grid-interactive Efficient Buildings and Demand Flexibility

Efficient, connected, grid-interactive, smart, and flexible buildings are key to decarbonizing the U.S. energy economy, optimizing energy use, reducing electric consumers’ bills, integrating variable renewable energy resources, and improving the reliability and performance of the nation’s electricity grids. Such grid-interactive efficient buildings have high levels of energy efficiency layered with other distributed energy resources (DERs) and intelligent controls to provide demand flexibility. Policy support is unfolding at the federal, state, and local levels to transform homes and workplaces into state-of-the-art energy-efficient buildings and community-level grid services. This paper starts by describing the potential benefits. Next, it highlights existing policies — with a focus on state-level actions — that support grid-interactive efficient building deployment and demand flexibility. Finally, it identifies current trends and gaps, policies and programs that promote grid-interactive efficient buildings, and aggregations of grid-interactive efficient buildings referred to as Virtual Power Plants.

Schwartz, Lisa C↗
DOE OSTI2022

Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery

We developed Distilled Graph Attention Policy Networks (DGAPNs), a curiosity-driven reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention Network (sGAT) that leverages self-attention over both node and edge attributes as well as encoding spatial structure -- this capability is of considerable interest in areas such as molecular and synthetic biology and drug discovery. An attentional policy network is then introduced to learn decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with enhanced stability. Exploration is efficiently encouraged by incorporating innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while increasing the diversity of proposed molecules and reducing the complexity of paths to chemical synthesis.

Wu, Yulun↗
DOE OSTI2023

Method and apparatus for constructing informative outcomes to guide multi-policy decision making

In Multi-Policy Decision-Making (MPDM), many computationally-expensive forward simulations are performed in order to predict the performance of a set of candidate policies. In risk-aware formulations of MPDM, only the worst outcomes affect the decision making process, and efficiently finding these influential outcomes becomes the core challenge. Recently, stochastic gradient optimization algorithms, using a heuristic function, were shown to be significantly superior to random sampling. In this disclosure, it was shown that accurate gradients can be computed-even through a complex forward simulation—using approaches similar to those in dep networks. The proposed approach finds influential outcomes more reliably, and is faster than earlier methods, allowing one to evaluate more policies while simultaneously eliminating the need to design an easily-differentiable heuristic function.

Olson, Edwin↗
DOE OSTI2022

SPATIAL GRAPH ATTENTION AND CURIOSITY-DRIVEN POLICY FOR ANTIVIRAL DRUG DISCOVERY

We developed Distilled Graph Attention Policy Network (DGAPN), a reinforcement learning model to generate novel graph-structured chemical representations that optimize user-defined objectives by efficiently navigating a physically constrained domain. The framework is examined on the task of generating molecules that are designed to bind, noncovalently, to functional sites of SARS-CoV-2 proteins. We present a spatial Graph Attention (sGAT) mechanism that leverages self-attention over both node and edge attributes as well as encoding the spatial structure - this capability is of considerable interest in synthetic biology and drug discovery. An attentional policy network is introduced to learn the decision rules for a dynamic, fragment-based chemical environment, and state-of-the-art policy gradient techniques are employed to train the network with stability. Exploration is driven by the stochasticity of the action space design and the innovation reward bonuses learned and proposed by random network distillation. In experiments, our framework achieved outstanding results compared to state-of-the-art algorithms, while reducing the complexity of paths to chemical synthesis.

Wu, Y↗
DOE OSTI2026

A Real2Sim Digital Twin Pipeline for Photorealistic Robot Simulation: Evaluating VLA Policy Deployment on a Bimanual Mobile Robot

Digital twins that are automatically constructed from robot sensor data offer a promising pathway for scalable Real2Sim and Sim2Real transfer. However, it remains an open question whether photorealistic reconstruction alone is sufficient to support reliable deployment of vision-language-action (VLA) policies. We present a generative-AI-assisted Real2Sim pipeline that generates simulation-ready digital twins from real-world RGB observations with minimal manual intervention. The pipeline uses prompted segmentation to isolate scene components and a generative 3D model to directly produce simulation assets, eliminating the need for traditional multi-view reconstruction or manual 3D modeling.\r\nTo evaluate simulation fidelity, we deploy and compare policies from two VLA models in both the real robot and the reconstructed\r\nsimulation under identical tasks and initial conditions. We compare joint-level action trajectories and analyze how divergence evolves over time in closed-loop execution. Although the reconstructed environments are visually accurate, we observe increasing trajectory divergence during closedloop operation. These results indicate that photorealistic reconstruction alone is insufficient to preserve closed-loop control behavior\r\nin VLA policies, particularly in contact-rich manipulation settings where small perceptual errors compound over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Community Solar Policy Screening Workbook for Multifamily Affordable Housing Building Portfolios

This workbook provides a framework to help Multifamily Affordable Housing (MFAH) housing providers evaluate state-level policy landscapes as they relate to MFAH community solar development. By exploring which programs and policies aid in the technical and economic feasibility of MFAH solar projects, building owners can gain an understanding of where in their portfolios to begin developing solar. This workbook also walks through the steps necessary for MFAH building owners to assess their portfolios using this framework. It was developed by the National Renewable Energy Laboratory for the National Community Solar Partnership (NCSP) Multifamily Affordable Housing Collaborative. Learn more about the NCSP and the Collaborative at https://www.energy.gov/communitysolar/community-solar.

14 SOLAR ENERGY↗