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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Risk-Constrained Reinforcement Learning for Inverter-Dominated Power System Controls

Here, this paper develops a risk-aware controller for grid-forming inverters (GFMs) to minimize large frequency oscillations in GFM inverter-dominated power systems. To tackle the high variability from loads/renewables, we incorporate a mean-variance risk constraint into the classical linear quadratic regulator (LQR) formulation for this problem. The risk constraint aims to bound the time-averaged cost of state variability and thus can improve the worst-case performance for large disturbances. The resulting risk-constrained LQR problem is solved through the dual reformulation to a minimax problem, by using a reinforcement learning (RL) method termed as stochastic gradient-descent with max-oracle (SGDmax). In particular, the zero-order policy gradient (ZOPG) approach is used to simplify the gradient estimation using simulated system trajectories. Numerical tests conducted on the IEEE 68-bus system have validated the convergence of our proposed SGDmax for GFM model and corroborate the effectiveness of the risk constraint in improving the worst-case performance while reducing the variability of the overall control cost.

Frequency control↗
DOE OSTI2024

Coherency-Aware Learning Control of Inverter-Dominated Grids: A Distributed Risk-Constrained Approach

Here, this letter investigates the importance of integrating the coherency knowledge for designing controllers to dampen sustained oscillations in wide-area power networks with significant penetration of inverter-interfaced resources. Coherency is a fundamental property of power systems, where time-scale separation in frequency dynamics leads to clustered behavior among generators of different groups. Large-scale penetration of inverter-driven low inertia resources replacing conventional synchronous generators (SGs) can lead to perturbation in the coherent partitioning; hence, integrating such information is of utmost importance for oscillation control designs. We present the coherency-aware design of a distributed output feedback-based reinforcement learning method that additionally incorporates risk constraints to capture the uncertainties related to net-load fluctuations. The use of domain-aware coherency information has produced improved training and oscillation performance than the coherency-agnostic control design, hence proving to be effective in controller design. Finally, we validated the proposed method with numerical experiments on the benchmark IEEE 68-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

Design and Performance of a Miniature Radar L-Band Transceiver

Radar electronics developed for past JPL space missions historically had been custom designed and as such, given budgetary, time, and risk constraints, had not been optimized for maximum flexibility or miniaturization. To help reduce cost and risk of future radar missions, a generic radar module was conceived. The module includes a 1.25-GHz (L-band) transceiver and incorporates miniature high-density packaging of integrated circuits in die/chip form. The technology challenges include overcoming the effect of miniaturization and high packaging density to achieve the performance, reliability, and environmental ruggedness required for space missions. The module was chosen to have representative (generic) functionality most likely required from an L-band radar. For very large aperture phased-array spaceborne radar missions, the large dimensions of the array suggest the benefit of distributing the radar electronics into the antenna array. For such applications, this technology is essential in order to bring down the cost, mass, and power of the radar electronics module replicated in each panel of the array. For smaller sized arrays, a single module can be combined with the central radar controller and still provide the bene.ts of configuration .exibility, low power, and low mass. We present the design approach for the radar electronics module and the test results for its radio frequency (RF) portion: a miniature, low-power, radiation-hard L-band transceiver.

McWatters, D.↗
DOE OSTI2023

Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning

Constrained multiagent reinforcement learning (C-MARL) is gaining importance as MARL algorithms find new applications in real-world systems ranging from energy systems to drone swarms. Most C-MARL algorithms use a primal-dual approach to enforce constraints through a penalty function added to the reward. In this paper, we study the structural effects of this penalty term on the MARL problem. First, we show that the standard practice of using the constraint function as the penalty leads to a weak notion of safety. However, by making simple modifications to the penalty term, we can enforce meaningful probabilistic (chance and conditional value at risk) constraints. Second, we quantify the effect of the penalty term on the value function, uncovering an improved value estimation procedure. We use these insights to propose a constrained multiagent advantage actor critic (C-MAA2C) algorithm. Simulations in a simple constrained multiagent environment affirm that our reinterpretation of the primal-dual method in terms of probabilistic constraints is effective, and that our proposed value estimate accelerates convergence to a safe joint policy.

chance constraints↗
DOE OSTI2023

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗
NASA NTRS1981

System analysis approach to deriving design criteria (Loads) for Space Shuttle and its payloads. Volume 2: Typical examples

The achievement of an optimized design from the system standpoint under the low cost, high risk constraints of the present day environment was analyzed. Space Shuttle illustrates the requirement for an analysis approach that considers all major disciplines (coupling between structures control, propulsion, thermal, aeroelastic, and performance), simultaneously. The Space Shuttle and certain payloads, Space Telescope and Spacelab, are examined. The requirements for system analysis approaches and criteria, including dynamic modeling requirements, test requirements, control requirements, and the resulting design verification approaches are illustrated. A survey of the problem, potential approaches available as solutions, implications for future systems, and projected technology development areas are addressed.

Ryan, R. S.↗
NASA NTRS1988

A new code for Galileo

Over the past six to eight years, an extensive research effort was conducted to investigate advanced coding techniques which promised to yield more coding gain than is available with current NASA standard codes. The delay in Galileo's launch due to the temporary suspension of the shuttle program provided the Galileo project with an opportunity to evaluate the possibility of including some version of the advanced codes as a mission enhancement option. A study was initiated last summer to determine if substantial coding gain was feasible for Galileo and, is so, to recommend a suitable experimental code for use as a switchable alternative to the current NASA-standard code. The Galileo experimental code study resulted in the selection of a code with constant length 15 and rate 1/4. The code parameters were chosen to optimize performance within cost and risk constraints consistent with retrofitting the new code into the existing Galileo system design and launch schedule. The particular code was recommended after a very limited search among good codes with the chosen parameters. It will theoretically yield about 1.5 dB enhancement under idealizing assumptions relative to the current NASA-standard code at Galileo's desired bit error rates. This ideal predicted gain includes enough cushion to meet the project's target of at least 1 dB enhancement under real, non-ideal conditions.

Dolinar, S.↗
NASA NTRS2002

Advances in Robotic, Human, and Autonomous Systems for Missions of Space Exploration

Space exploration missions are evolving toward more complex architectures involving more capable robotic systems, new levels of human and robotic interaction, and increasingly autonomous systems. How this evolving mix of advanced capabilities will be utilized in the design of new missions is a subject of much current interest. Cost and risk constraints also play a key role in the development of new missions, resulting in a complex interplay of a broad range of factors in the mission development and planning of new missions. This paper will discuss how human, robotic, and autonomous systems could be used in advanced space exploration missions. In particular, a recently completed survey of the state of the art and the potential future of robotic systems, as well as new experiments utilizing human and robotic approaches will be described. Finally, there will be a discussion of how best to utilize these various approaches for meeting space exploration goals.

Gross, Anthony R.↗
NASA NTRS2009

Air Quality Monitoring: Risk-Based Choices

Air monitoring is secondary to rigid control of risks to air quality. Air quality monitoring requires us to target the credible residual risks. Constraints on monitoring devices are severe. Must transition from archival to real-time, on-board monitoring. Must provide data to crew in a way that they can interpret findings. Dust management and monitoring may be a major concern for exploration class missions.

James, John T.↗
NASA NTRS2018

System-of-Systems Tools for the Analysis of Technological Choices in Space Propulsion

Difficulties in space mission architecture design arise from many factors. Performance, cost, and risk constraints become less obvious due to complex interactions between the systems involved in the mission; decisions regarding long-term goals can heavily impact technological choices for short-term parts of the mission, while conversely decisions in the near future will impact the whole flexibility of long-term plans. Furthermore, the space community is broadening its borders, and space agencies from different countries are collaborating with industry and commercial partners towards large-scale endeavors. This paradigm shift is prompting the development of non-traditional approaches to the design of space missions. This paper reports the results of the first year of a continuing collaboration of the authors to develop and demonstrate System-of-System engineering methodologies for the deep analysis of dependencies and synthesis of robust architectures in exploration mission contexts. We present the procedure that we followed to develop and apply our methodology, obstacles found, steps taken to improve the methods based on the needs of experts and decision makers, required data for the analysis, and results produced by our holistic analysis. In particular, we focus on the analysis of technological choices for space propulsion for a generic cislunar mission, including both complex interactions between subsystems in different type of propulsion and availability of different providers. We identify critical systems and sets of systems based on cascading effects of performance degradation, assessment of the robustness of different designs in the operational domain, and simultaneous analysis of schedule dependencies between the constituent systems.

Guariniello, Cesare↗
DOE OSTI2026

Guideline for Characterizing and Evaluating a Candidate Project Site for Solar Thermal Applications

This document presents a structured procedure for characterizing and evaluating candidate project sites for concentrating solar power (CSP) and solar heat for industrial processes (SHIP) applications. The objective is to provide project developers, researchers, and other stakeholders with a consistent, technology-agnostic framework for early-stage site assessment, enabling informed decision-making prior to significant investment in project development. Site selection is a critical factor in project success or failure for both CSP and SHIP projects. Key factors such as solar resource availability, land characteristics, environmental and regulatory constraints, infrastructure availability, and community context are determined by the choice of project site and can materially impact project performance, cost, schedule, and overall viability. This procedure is designed to systematically evaluate these factors, identify potential fatal flaws, and prioritize the most favorable candidate sites for further development. The process begins with rapid screening-level evaluation, using publicly available data to assess solar resource, land availability and suitability, zoning and land-use compatibility, and exclusion zones such as protected lands or sensitive habitats. Sites that meet the minimum screening criteria advance to a more detailed characterization. Subsequent sections of this report provide guidance for a next-level assessment of the most important technical and environmental parameters, including: 1) Solar resource quality, variability, and uncertainty using multiyear datasets and, where appropriate, on-site measurement campaigns; 2) Meteorological conditions such as wind, temperature, extreme weather events, and soiling impacts; 3) Land characteristics including slope, shading, and geotechnical conditions; and 4) Environmental and regulatory considerations, including permitting processes, endangered species, cultural resources, and visual impacts. The procedure also addresses infrastructure and integration considerations, including: 1) Grid interconnection requirements for CSP power generation projects; 2) Electrical and operational integration for SHIP facilities; 3) Water availability, quality, and permitting constraints, which are particularly critical for CSP in arid regions; and 4) Site access, construction logistics, and availability of workforce and supporting services. Recognizing the importance of social and economic context, the procedure includes evaluation of community engagement factors, such as stakeholder sentiment, proximity to sensitive visual receptors, workforce development opportunities, and local economic incentives. The outputs of these assessments are synthesized in a cost and risk evaluation, translating site characteristics into expected impacts on capital cost, operating cost, schedule, and technical risk. This is complemented by screening-level performance modeling, including 8760 simulations and long-term projections, to quantify expected energy or thermal output, assess variability thereof, and support comparison between candidate sites. Finally, the procedure provides high-level guidance on a structured go/no-go decision framework, categorizing sites based on identified risks and constraints, and outlining a clear path forward to feasibility studies and front-end engineering design for viable projects. By standardizing the site characterization process across both CSP and SHIP applications, this guideline aims to: 1) Improve consistency and transparency in early-stage project evaluation; 2) Reduce development risk and avoid investment in nonviable project sites; 3) Support collaboration between developers, researchers, and public agencies; and 4) Accelerate successful deployment of concentrating solar technologies for both power generation and industrial process heat.

14 SOLAR ENERGY↗
NASA NTRS2013

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Ono, Masahiro↗
NASA NTRS2019

Ground Risk Assessment Service Provider (GRASP) Development Effort as a Supplemental Data Service Provider (SDSP) for Urban Unmanned Aircraft System (UAS) Operations

NASA’s Unmanned Aircraft System (UAS) Traffic Management (UTM) project aims to enable the integration of new aviation paradigms such as Unmanned Aircraft Systems (UAS) while providing the necessary infrastructure for future concepts such as On-Demand Mobility (ODM) and Urban Air Mobility (UAM) operations in the National Airspace System (NAS). In order to do so, the UTM project has developed an architecture to allow communication among UAS operators, UAS Service Suppliers (USS), Air Navigation Service Providers (ANSP), and the public. As part of this framework, the Supplemental Data Service Providers (SDSP) are envisioned as model and/or data based services that disseminate essential or enhanced information to ensure safe operations within low-altitude airspace. These services include terrain and obstacle data, specialized weather data, surveillance, constraint information, risk monitoring, etc. This paper highlights the development efforts of a non-participant casualty risk assessment SDSP called Ground Risk Assessment Service Provider (GRASP) which assists operators with preflight planning. GRASP is based on the previously introduced UTM Risk Assessment Framework (URAF) and allows UAS operators to simulate and visualize potential non-participant casualty risks associated with their proposed flight. The risk assessment capability also allows operators to revise their flight plans if the casualty risks are determined to be above acceptable thresholds. GRASP is configured to account for future improvements including servicing airborne aircraft as part of NASA’s System-Wide Safety (SWS) project.

Ancel, Ersin↗
DOE OSTI2021

A unifying modeling abstraction for infinite-dimensional optimization

Infinite-dimensional optimization (InfiniteOpt) problems involve modeling components (variables, objectives, and constraints) that are functions defined over infinite-dimensional domains. Examples include continuous-time dynamic optimization (time is an infinite domain and components are functions of time), PDE optimization problems (space and time are infinite domains and components are functions of space-time), as well as stochastic and semi-infinite optimization (random space is an infinite domain and components are a function of such random space). InfiniteOpt problems also arise from combinations of these problem classes (e.g., stochastic PDE optimization). Given the infinite-dimensional nature of objectives and constraints, one often needs to define appropriate quantities (measures) to properly pose the problem. Moreover, InfiniteOpt problems often need to be transformed into a finite dimensional representation so that they can be solved numerically. Here in this work, we present a unifying abstraction that facilitates the modeling, analysis, and solution of InfiniteOpt problems. The proposed abstraction enables a general treatment of infinite-dimensional domains and provides a measure-centric paradigm to handle associated variables, objectives, and constraints. This abstraction allows us to transfer techniques across disciplines and with this identify new, interesting, and useful modeling paradigms (e.g., event constraints and risk measures defined over time domains). Our abstraction serves as the backbone of an intuitive Julia-based modeling package that we call InfiniteOpt.jl. We demonstrate the developments using diverse case studies arising in engineering.

42 ENGINEERING↗
NASA NTRS1984

A system-level approach to automation research

Automation is the application of self-regulating mechanical and electronic devices to processes that can be accomplished with the human organs of perception, decision, and actuation. The successful application of automation to a system process should reduce man/system interaction and the perceived complexity of the system, or should increase affordability, productivity, quality control, and safety. The expense, time constraints, and risk factors associated with extravehicular activities have led the Automation Technology Branch (ATB), as part of the NASA Automation Research and Technology Program, to investigate the use of robots and teleoperators as automation aids in the context of space operations. The ATB program addresses three major areas: (1) basic research in autonomous operations, (2) human factors research on man-machine interfaces with remote systems, and (3) the integration and analysis of automated systems. This paper reviews the current ATB research in the area of robotics and teleoperators.

Harrison, F. W.↗
NASA NTRS1999

Reinventing the Design Process: Teams and Models

The future of space mission designing will be dramatically different from the past. Formerly, performance-driven paradigms emphasized data return with cost and schedule being secondary issues.

Design↗