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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Development Challenges of Game-Changing Entry System Technologies From Concept to Mission Infusion

NASA's Space Technology Mission Directorate (STMD) and the Game Changing Development Program (GCDP) were created to develop new technologies. This paper describes four entry system technologies that are funded by the GCDP and summarizes the lessons learned during the development. The investments are already beginning to show success, mission infusion pathways after five years of existence. It is hoped that our experience and observations, drawn from projects supported by the GCD program/STMD, Orion and SMD can help current and future technology development projects. Observations on fostering a culture of success and on constraints that limit greater success are also provided.

Entry↗
NASA NTRS2015

Space Technology Mission Directorate: Game Changing Development

NASA and the aerospace community have deep roots in manufacturing technology and innovation. Through it's Game Changing Development Program and the Advanced Manufacturing Technology Project NASA develops and matures innovative, low-cost manufacturing processes and products. Launch vehicle propulsion systems are a particular area of interest since they typically comprise a large percentage of the total vehicle cost and development schedule. NASA is currently working to develop and utilize emerging technologies such as additive manufacturing (i.e. 3D printing) and computational materials and processing tools that could dramatically improve affordability, capability, and reduce schedule for rocket propulsion hardware.

Gaddis, Stephen W.↗
NASA NTRS2016

Game Changing Development Program - Next Generation Life Support Project: Oxygen Recovery From Carbon Dioxide Using Ion Exchange Membrane Electrolysis Technology

This report summarizes the Phase I research and development work performed during the March 13, 2015 to July 13, 2016 period. The proposal for this work was submitted in response to NASA Research Announcement NNH14ZOA001N, "Space Technology Research, Development, Demonstration, and Infusion 2014 (SpaceTech-REDDI-2014)," Appendix 14GCD-C2 "Game Changing Development Program, Advanced Oxygen Recovery for Spacecraft Life Support Systems Appendix" The Task Agreement for this Phase I work is Document Control Number: GCDP-02-TA-15015. The objective of the Phase I project was to demonstrate in laboratories two Engineering Development Units (EDU) that perform critical functions of the low temperature carbon dioxide electrolysis and the catalytic conversion of carbon monoxide into carbon and carbon dioxide. The low temperature carbon dioxide electrolysis EDU was built by the University of Delaware with Dr. Feng Jiao as the principal investigator in charge of this EDU development (under NASA Contract NNC15CA04C). The carbon monoxide catalytic conversion EDU was built by the NASA Glenn Research Center with Kenneth Burke as the principal investigator and overall project leader for the development of both EDUs. Both EDUs were successfully developed and demonstrated the critical functions for each process. The carbon dioxide electrolysis EDU was delivered to the NASA Johnson Space Center and the carbon monoxide catalytic conversion EDU was delivered to the NASA Marshall Spaceflight Center.

Oxygen Recovery↗
NASA NTRS2017

Space Technology: Game Changing Development Deep Space Engine (DSE) 100 lbf and 5 lbf Thruster Development and Qualification

Science mission studies require spacecraft propulsion systems that are high-performance, lightweight, and compact. Highly matured technology and low-cost, short development time of the propulsion system are also very desirable. The Deep Space Engine (DSE) 100-lbf thruster is being developed to meet these needs. The overall goal of this game changing technology project is to qualify the DSE thrusters along with 5-lbf attitude control thrusters for space flight and for inclusion in science and exploration missions. The aim is to perform qualification tests representative of mission duty cycles. Most exploration missions are constrained by mass, power and cost. As major propulsion components, thrusters are identified as high-risk, long-lead development items. NASA spacecraft primarily rely on 1960s' heritage in-space thruster designs and opportunities exist for reducing size, weight, power, and cost through the utilization of modern materials and advanced manufacturing techniques. Advancements in MON-25/MMH hypergolic bipropellant thrusters represent a promising avenue for addressing these deficiencies with tremendous mission enhancing benefits. DSE is much lighter and costs less than currently available thrusters in comparable thrust classes. Because MON-25 propellants operate at lower temperatures, less power is needed for propellant conditioning for in-space propulsion applications, especially long duration and/or deep-space missions. Reduced power results in reduced mass for batteries and solar panels. DSE is capable of operating at a wide propellant temperature range (between -22 F and 122 F) while a similar existing thruster operates between 45 F and 70 F. Such a capability offers robust propulsion operation as well as flexibility in design. NASA's Marshall Space Flight Center evaluated available operational Missile Defense Agency heritage thrusters suitable for the science and lunar lander propulsion systems.

Barnett, Gregory↗
NASA NTRS2019

Synthetic Biology off Planet for Game-Changing Solutions for a Greener Earth

Synthetic biology – creating new capabilities with life – promises to create a greener future for planet Earth, from fields as diverse as pharmaceuticals to manufacturing, agriculture and nanotechnology. Progress can be stymied by such considerations as economics, politics, legal and philosophical issues surrounding GMOs. Often solutions to these problems already exist, so it is difficult for a new, superior method to displace the old. As we move humans beyond Earth, to long duration stays in the International Space Station, and then onward to the Moon and Mars, the challenges of supporting human life will need radical new solutions. While there are new constraints, such as worrying about the mass of a solution, constraints offer opportunities for game-changing solutions that will then allow revolutions back on our home planet.

Rothschild, Lynn J.↗
NASA NTRSDate not supplied

Synthetic biology off planet for game-changing solutions for a greener Earth

Synthetic biology – creating new capabilities with life – promises to create a greener future for planet Earth, from fields as diverse as pharmaceuticals to manufacturing, agriculture and nanotechnology. Progress can be stymied by such considerations as economics, politics, legal and philosophical issues surrounding GMOs. Often solutions to these problems already exist, so it is difficult for a new, superior method to displace the old. As we move humans beyond Earth, to long duration stays in the International Space Station, and then onward to the Moon and Mars, the challenges of supporting human life will need radical new solutions. For example, while life on Earth uses an enzymatic machinery which evolved close to 3 billion years ago, synthetic biology promises to be able to engineer the systems to adapt to current natural or industrial environments. A focus on solutions off planet require a focus on a circular economy. While there are new constraints, such as worrying about the mass of a solution, constraints offer opportunities for game-changing solutions that will then allow revolutions back on our home planet.

Lynn J Rothschild↗
DOE OSTI2025

Game Strategies for Entanglement Paths in Quantum Network Infrastructure

Entanglement distribution is a core function of quantum networks, and the paths used for this purpose are composed of quantum and conventional network components and are routed through physical facility sites. A game theoretic model is formulated for the defense of entanglement paths in a quantum network infrastructure by modeling the correlations and probabilities of reinforcement and failure of its components. A sum-form utility function is used to capture the cost-benefit trade-offs in reinforcing the entanglement path components to defend against their failures and attacks. Under Nash Equilibrium criteria, estimates of survival probabilities of entanglement paths are derived using the parameters and correlations of quantum, conventional, hybrid, and facility components. They provide insights into the dependencies of entanglement paths on its components, including cross-boundary effects of conventional, quantum, and facility components.

Rao, Nageswara [ORNL] (ORCID:0000000234085941)↗
DOE OSTI2022

The role of information structures in game-theoretic multi-agent learning

Multi-agent learning (MAL) studies how agents learn to behave optimally and adaptively from their experience when interacting with other agents in dynamic environments. The outcome of a MAL process is jointly determined by all agents’ decision-making. Hence, each agent needs to think strategically about others’ sequential moves, when planning future actions. The strategic interactions among agents makes MAL go beyond the direct extension of single-agent learning to multiple agents. With the strategic thinking, each agent aims to build a subjective model of others decision-making using its observations. Such modeling is directly influenced by agents’ perception during the learning process, which is called the information structure of the agent’s learning. As it determines the input to MAL processes, information structures play a significant role in the learning mechanisms of the agents. This review creates a taxonomy of MAL and establishes a unified and systematic way to understand MAL from the perspective of information structures. Here we define three fundamental components of MAL: the information structure (i.e., what the agent can observe), the belief generation (i.e., how the agent forms a belief about others based on the observations), as well as the policy generation (i.e., how the agent generates its policy based on its belief). In addition, this taxonomy enables the classification of a wide range of state-of-the-art algorithms into four categories based on the belief-generation mechanisms of the opponents, including stationary, conjectured, calibrated, and sophisticated opponents. We introduce Value of Information (VoI) as a metric to quantify the impact of different information structures on MAL. Finally, we discuss the strengths and limitations of algorithms from different categories and point to promising avenues of future research.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Game Theory↗
DOE OSTI2025

Path integral games with de Sitter α-vacua

The α-vacua are a 1-parameter family of quantum field vacua in de Sitter space which are invariant under the isometry group SO(1, d). In this work give a path integral construction of the de Sitter α-vacua. We explain that these states can be prepared by acting on the Bunch-Davies vacuum with a certain non-local charge operator. While most conserved charges live on a single codimension-1 manifold, we show that this particular charge lives on a pair of two codimension-1 manifolds which are antipodal mirrors of each other. The rules for the manipulation of this charge as an insertion in the path integral are explained. We further explain how this charge can be used to solve for the wavefunctionals of the α-vacua at $\mathcal{I}$ | (in the regime that α is small) by deforming the equator of de Sitter space to $\mathcal{I}$ + /$\mathcal{I}$ – .

Global Symmetries↗