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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimizing an Integrated Solar-Electrolysis System (CRADA CRD-18-749 Final Report)

Electrolysis powered by renewable sources provides a range of potential values such as carbon-free fuel for power, heat, or transportation; storage; and ancillary grid services. Each of these potential benefits has been studied as individual value streams. However, real-world demonstrations of these benefits working in concert are limited in the United States today as electrolyzers lack access to wholesale electricity prices. High power prices make electrolysis uncompetitive compared to traditional steam methane reformation (SMR). A potentially cost-effective way to demonstrate the value of renewable electrolysis is by powering an electrolyzer directly from a renewable generation source rather than from the electric grid. Integrated with a renewable generation source, the cost of fueling an electrolyzer is the opportunity cost of not selling power from the renewable plant to the grid - effectively, the wholesale electricity price. Additionally, an electrolyzer tied directly to a renewable generator potentially reduces excess generation and increases the value of the ancillary services that the renewable generator can provide to the grid.

08 HYDROGEN↗
DOE OSTI2022

Nonlinear Optimization and the Modeling of Energy Systems [Slides]

Energy delivery systems are critical for the function of modern society. (Up to) continental-scale engineered systems move energy from source points to consumers. These systems are increasingly complex and interconnected.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Development of integrated neutronics and thermal analysis capabilities to support design and optimization of fusion engineering demonstration facility systems and blanket design (Final Scientific/Technical Report)

A fusion engineering demonstration facility would be the first step in the commercial fusion plant developmental pathway that aims to be an engineering demonstration of tritium self-sufficiency. One of the primary requirements for tritium self-sufficiency, as well as to ensure low plant tritium release to the external environment, is to minimize the tritium loss through the internal components, which requires accurate predictions of the tritium behavior for a wide range of materials and system conditions. This grant addressed the lack of a comprehensive model which accounts for particular conditions, such as the significance of temperature fields and neutronics information, and the systematic uncertainty quantification of associated material properties that impact tritium generation, utilization, and loss mechanisms in the blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Development of integrated neutronics and thermal analysis capabilities to support design and optimization of fusion engineering demonstration facility systems and blanket design (Final Scientific/Technical Report)

A fusion engineering demonstration facility would be the first step in the commercial fusion plant developmental pathway that aims to be an engineering demonstration of tritium self- sufficiency. One of the primary requirements for tritium self-sufficiency, as well as to ensure low plant tritium release to the external environment, is to minimize the tritium loss through the internal components, which requires accurate predictions of the tritium behavior for a wide range of materials and system conditions. This grant addressed the lack of a comprehensive model which accounts for particular conditions, such as the significance of temperature fields and neutronics information, and the systematic uncertainty quantification of associated material properties that impact tritium generation, utilization, and loss mechanisms in the blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Graph-Learning-Assisted State and Event Tracking for Solar-Penetrated Power Grids with Heterogeneous Data Sources

Unlike transmission systems, distribution systems do not typically contain sufficient metering to enable real-time state estimation. The lack of sufficient real-time measurements prohibits accurate and timely monitoring of the state of distribution systems. As a result, control and optimal operation of distribution systems, especially those containing large numbers of renewable generation units are not possible without proper data and information about the current state of the system. The main motivation of this project is to address this shortcoming by developing an approach which provides “predicted” real-time measurements so that they can be used to execute a distribution system state estimator. Thus, the objective of the project is to make the distribution systems fully observable, such that the hosting capacity for solar generation can be accurately estimated, and unnecessary solar curtailments can be avoided. In order to accomplish this goal, the project investigated the use of a grid-model-informed machine learning (ML) tool which integrates heterogeneous data streams obtained from AMI meters, SCADA as well as PMU measurements and created synchronous measurement snapshots for the state estimator (SE); and developed a hybrid robust SE which provides not only accurate state estimates but also real-time feedback for the ML model refinement.

14 SOLAR ENERGY↗
DOE OSTI2025

Design and Optimization of the Proposed NB2 Guide System in the HFIR Cold Guide Hall

The NB2 Guide Design is used to provide a defined neutron beam flux to at least one monochromator and an end station. The known monochromator configuration will support a sample alignment station and the end station will be able to accommodate either a neutron polarization development instrument or a spin echo neutron spectrometer, as well as the potential for additional monochromators along the guide path. The design proposed will meet the needs specified for those instruments defined by science requirements documents, and will also provide insight into potential opportunities for future instrument developments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Organic Rankine Cycle Integration and Optimization for High Efficiency CHP Genset Systems (Final Technical Report)

This project successfully advanced the integration of Organic Rankine Cycle (ORC) technology with reciprocating engine–based combined heat and power (CHP) systems to improve electrical efficiency, total CHP efficiency, and grid-responsive operation. Over three budget periods, the work progressed from high-temperature ORC component development and thermodynamic model validation to next-generation system design, working fluid transition, and techno-economic analysis. Key technical accomplishments include development and validation of a thermodynamic model capable of accurately predicting ORC performance across an expanded temperature and pressure envelope; successful identification and validation of low-global-warming-potential (GWP) working fluids—most notably R1233zd(E)—as viable replacements for R245fa; and demonstration of scalable ORC architectures suitable for integration with 1–20 MW class reciprocating engines. These advances enable flexible CHP configurations that can increase electrical output while maintaining high overall utilization of available thermal energy. The project also produced a clean-sheet design for a next-generation ORC system targeting substantially higher power output per unit, supported by detailed component selection, heat exchanger evaluation, and system-level modeling. Techno-economic analyses indicate that ORC-enabled flexible CHP systems can meet or exceed Department of Energy (DOE) efficiency targets while providing value to both facility operators and the electric grid.. Late-stage testing of the largest next-generation ORC prototype identified limitations related to pump net positive suction head (NPSH) requirements and condenser flooding under certain operating conditions. Although these issues constrained full validation of that configuration within the project timeframe, they provided clear and actionable design guidance for future system refinements. Importantly, validated modeling, smaller-scale testing, and working fluid evaluations confirmed the technical viability of the overall approach. In aggregate, this project met its core objectives by establishing validated design tools, de-risking key ORC technologies for CHP applications, and defining a credible pathway toward commercialization of flexible, high-efficiency CHP systems. The results form a strong foundation for continued development and deployment beyond the conclusion of the DOE-funded effort.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Market optimization and technoeconomic analysis of hydrogen-electricity coproduction systems

Decarbonization efforts across North America, Europe, and beyond rely on variable renewable energy sources such as wind and solar, as well as alternative fuels, such as hydrogen, to support the sustainable energy transition. These advancements have prompted a need for more flexibility in the electric grid to complement non-dispatchable energy sources and increased demand from electrification. Integrated energy systems are well suited to provide this flexibility, but conventional technoeconomic modeling paradigms neglect the time-varying dynamic nature of the grid and thus undervalue resource flexibility. In this work, we develop a computational optimization framework for dynamic market-based technoeconomic comparison of integrated energy systems that coproduce low-carbon electricity and hydrogen (e.g., solid oxide fuel cells, solid oxide electrolysis) against technologies that only produce electricity (e.g., natural gas combined cycle with carbon capture) or only produce hydrogen. Our framework starts with rigorous physics-based process models, built in the open-source Institute for the Design of Advanced Energy Systems (IDAES) modeling and optimization platform, for six energy process concepts. Using these rigorous models and a workflow to optimally design each technology, the framework is shown to be capable of evaluating new and emerging technologies in varying energy markets under a plethora of future scenarios (i.e., renewables penetration, carbon tax, etc.). Ultimately, our framework finds that solid oxide fuel cell-based coproduction systems achieve positive profits for 85% of the analyzed market scenarios. From these market optimization results, we use multivariate linear regression (R 2 values up to 0.99) to determine which electricity price statistics are most significant to predict the optimized annual profit of each system. The proposed framework provides a powerful tool for directly comparing flexible, multi-product energy process concepts to help discern optimal technology and integration options.

08 HYDROGEN↗
DOE OSTI2022

Flexible atomic layer deposition system for coating porous materials

In this paper, we describe an atomic layer deposition (ALD) system that is optimized for the growth of thin films on high-surface-area, porous materials. The system incorporates a moveable dual-zone furnace allowing for rapid transfer of a powder substrate between heating zones whose temperatures are optimized for precursor adsorption and oxidative removal of the precursor ligands. The reactor can both be evacuated, eliminating the need for a carrier gas during precursor exposure, and rotated, to enhance contact between a powder support and the gas phase, both of which help us to minimize mass transfer limitations in the pores during film growth. The capabilities of the ALD system were demonstrated by growing La 2 O 3 , Fe 2 O 3 , and LaFeO 3 films on a 120 m 2 g -1 MgAl 2 O 4 powder. Analysis of these films using scanning transmission electron microscopy and temperature-programmed desorption of 2-propanol confirmed the conformal nature of the oxide films.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis: Tool Development and Method Evaluation

This report is an update to a prior report that describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and throughout the plant, along with a greater interest in the use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human performance-related organizational and technical design issues are identified and addressed early in the design process. This report describes modeling tools and techniques, based on sociotechnical systems theory, to support these design goals and their application in the current research effort. The report is primarily intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control, feedback, and communication relationships amongst the system’s technical and organizational components. We have employed two STAMP-based tools in this effort. The first is Causal Analysis based on STAMP (CAST), an accident and incident analysis technique that was used to examine a performance- and safety-related incident at an industry partner’s plant involving the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. The second tool is Systems Theoretic Process Analysis (STPA) which is a proactive risk analysis tool used to examine existing and potential, planned sociotechnical systems. STPA was used to identify risk factors in the current design of a generic nuclear power plant (NPP) preventive maintenance system. Our analyses focused on identifying near-term system improvements and longer-term design requirements for an optimized IAE system. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived time and schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the eventual event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. STPA findings exposed several areas of concern in the design of current preventive maintenance systems. We also present two preliminary information automation models. The proactive issue resolution (PIR) model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system and represents an end-state vision for our work. From our results, we have generated an initial set of preliminary system-level requirements and safety constraints for these models. We have also focused on early development of easy to learn, easy to use “transportable” tools for sociotechnical systems analysis. We intend these to be used by NPP personnel as a means of gaining reliable and relatively quick insight into (1) sociotechnical systems factors impacting incidents and accidents, (2) potential sociotechnical risk factors in existing or planned system designs, and (3) potential weaknesses in a system’s safety and/or information control structure. We conclude the report with a set of summary recommendations, a discussion of planned and potential follow-on research and development, and a draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Applicability study of Bayesian optimization in core neutronic design using a toy model

At the Japan Atomic Energy Agency (JAEA), an innovative design approach named ARKADIA (Advanced Reactor Knowledge- and AI-aided Design Integration Approach through the whole plant life cycle) for advanced nuclear reactors is currently under development. One task in ARKADIA is to build a system that automatically optimizes core and fuel designs by conducting core neutronic and thermal-hydraulic calculations, fuel integrity evaluations, and plant dynamic analyses. This system will be implemented to automatically find an optimal design that minimizes (or maximizes) objective function defined by core performance while varying the core and fuel design parameters such as fuel pin diameter, core height and diameter. In this study, as the first step of system development, we focused only on core neutronic design and conducted a study of automatic optimization. As the optimization algorithm, Bayesian optimization (BO), an effective method for optimization problems with expensive computational cost of objective function, was utilized. The applicability of BO was studied based on single- and two-objective optimization examples of core neutronic design in a toy model. As a result, in the former, it was shown that BO can give the optimal solution, which matches the reference solution calculated by a brute force calculation well, with a small number of required calculations. Usability on core neutronic designs, where the computational cost per case is high, was confirmed. In the latter, it was found that BO can give a Pareto solutions-set that shows good agreement with the reference solution. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

The Usage of Observing System Simulation Experiments and Reinforcement Learning to Optimize Experimental Design and Operation

Various organizations regularly conduct field campaigns across the globe designed to probe and improve atmospheric process understanding. However, these campaigns are mostly designed ad-hoc, and rely on anecdotes and knowledge of what was successful in previous campaigns. Such ad-hoc experiment design results in sub-optimal instrument siting and operation strategies. Inadequate targeted data collection of extreme weather is a major limitation to Earth and Environmental Systems Science Division (EESSD)’s goals of data model integration (4.5.3), which limits the knowledge gained through the collected observations, holding back significant advances in predictability. While advances in instrument design are always chipping away at these limitations, we are not optimally utilizing the instrumentation we currently possess.

54 ENVIRONMENTAL SCIENCES↗