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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Learning the ground state of a non-stoquastic quantum Hamiltonian in a rugged neural network landscape

Strongly interacting quantum systems described by non-stoquastic Hamiltonians exhibit rich low-temperature physics. Yet, their study poses a formidable challenge, even for state-of-the-art numerical techniques. Here, we investigate systematically the performance of a class of universal variational wave-functions based on artificial neural networks, by considering the frustrated spin- 1/2 1 / 2 J_1-J_2 J 1 − J 2 Heisenberg model on the square lattice. Focusing on neural network architectures without physics-informed input, we argue in favor of using an ansatz consisting of two decoupled real-valued networks, one for the amplitude and the other for the phase of the variational wavefunction. By introducing concrete mitigation strategies against inherent numerical instabilities in the stochastic reconfiguration algorithm we obtain a variational energy comparable to that reported recently with neural networks that incorporate knowledge about the physical system. Through a detailed analysis of the individual components of the algorithm, we conclude that the rugged nature of the energy landscape constitutes the major obstacle in finding a satisfactory approximation to the ground state wavefunction, and prevents learning the correct sign structure. In particular, we show that in the present setup the neural network expressivity and Monte Carlo sampling are not primary limiting factors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
DOE OSTI2026

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer-Based Hydrogen Production Facility: Preprint

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at the National Renewable Energy Laboratory (NREL)'s Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗
DOE OSTI2024

Large-Scale Hydrogen Storage Cyber Risk Assessment

Hydrogen storage systems may become more widely deployed throughout the country, and so it is possible that individual and interconnected systems will be exposed to cyber-attacks. These events can cause physical and financial harm to employees, people in the vicinity of the facility, and the company that owns the facility. The two main ways bad actors may access information or control from a hydrogen storage facility are through information technology and operations technology devices, the former of which refers to data and information from networked devices and the latter of which refers to onsite controls for the physical system. Both types of entryways into the system should be considered when companies conduct cyber risk assessments and when regulators develop or revise relevant codes and standards. This report analyzes cybersecurity risks associated with a generic hydrogen storage system by outlining the system's purpose and the importance of its cybersecurity. The hydrogen storage system architecture and communication protocols are provided to understand potential cyber vulnerabilities. Later, an event tree analysis is performed on hydrogen operation to identify system weaknesses by outlining potential attack scenarios. This report also identifies critical cyber assets related to different hydrogen operations followed by an examination of potential threats, and the impact of cyber assets on those operational assets.

08 HYDROGEN↗
DOE OSTI2024

Large-Scale Hydrogen Storage Cyber Risk Assessment

Hydrogen storage systems are becoming more widely deployed throughout the country, and as their presence continues to grow, it is possible that individual and interconnected systems will be exposed to cyber-attacks. These events can cause physical and financial harm to employees, people in the vicinity, and to the company that owns the facility. The two main mechanisms malicious actors may access information or control from a hydrogen storage facility are through information technology and operations technology devices, the former of which refers to data and information from networked devices and the latter of which refers to onsite controls for the physical system. Both types of entryways into the system should be considered when facility managers conduct cyber risk assessments and when regulators develop or revise relevant codes and standards. This report analyzes cybersecurity risks applicable to a wide variety of hydrogen storage systems by outlining the system's purpose and the importance of its cybersecurity. The hydrogen storage system architecture and communication protocols are provided to understand potential cyber vulnerabilities. Later, an event tree analysis is performed on hydrogen operation to identify system weaknesses by outlining potential attack scenarios. This report also identifies critical cyber assets related to different hydrogen operations followed by an examination of potential threats, and the impact of cyber assets on those operational assets.

08 HYDROGEN↗
NASA NTRS1989

Selective simulation and selective sensor interpretation in monitoring

An approach to selective processing in monitoring is described. The approach is designed to provide informative feedback on whether a system is performing nominally in the current operating context without exceeding available resources for prediction and interpretation. At the center of the approach to selective sensor interpretation and simulation is a causal model of the system being monitored. The architecture of the monitoring system, called PREMON, is described as well as how causal models of physical systems are represented and simulated.

Doyle, Richard J.↗
NASA NTRS1992

Updated SINDA '85/FLUINT

SINDA '85/FLUINT system enables analysis of mutual influences of thermal and fluid aspects of physical systems. Program enables simulation of nonuniform heating and facilitates mathematical modeling of thin-walled heat exchangers. Written in FORTRAN.

Cullimore, Brent↗
NASA NTRS1991

Robust control with structured perturbations

This semi-annual report describes continued progress on the research. Among several approaches in this area of research, our approach to the parametric uncertainties are being matured everyday. This approach deals with real parameter uncertainties which other techniques such as H (sup infinity) optimal control, micron analysis and synthesis, and l(sub 1) optimal control cannot deal. The primary assumption of this approach is that the mathematical models are well obtained so that the most of system uncertainties can be translated into parameter uncertainties of their linear system representations. These uncertainties may be due to modeling, nonlinearity of the physical system, some time-varying parameters, etc. In this report period of research, we are concentrating on implementing a computer aided analysis and design tool based on new results on parametric robust stability. This implementation will help us to reveal further details in this approach.

Keel, Leehyun↗
NASA NTRS2009

Human-rating Automated and Robotic Systems - (How HAL Can Work Safely with Astronauts)

Long duration human space missions, as planned in the Vision for Space Exploration, will not be possible without applying unprecedented levels of automation to support the human endeavors. The automated and robotic systems must carry the load of routine housekeeping for the new generation of explorers, as well as assist their exploration science and engineering work with new precision. Fortunately, the state of automated and robotic systems is sophisticated and sturdy enough to do this work - but the systems themselves have never been human-rated as all other NASA physical systems used in human space flight have. Our intent in this paper is to provide perspective on requirements and architecture for the interfaces and interactions between human beings and the astonishing array of automated systems; and the approach we believe necessary to create human-rated systems and implement them in the space program. We will explain our proposed standard structure for automation and robotic systems, and the process by which we will develop and implement that standard as an addition to NASA s Human Rating requirements. Our work here is based on real experience with both human system and robotic system designs; for surface operations as well as for in-flight monitoring and control; and on the necessities we have discovered for human-systems integration in NASA's Constellation program. We hope this will be an invitation to dialog and to consideration of a new issue facing new generations of explorers and their outfitters.

Baroff, Lynn↗
NASA NTRS1988

NASA Tech Briefs, February 1988

Topics covered include: New Product Ideas; NASA TU Services; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Systems; and Life Sciences.

Source record↗
NASA NTRS1992

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

Hall, Gardiner A.↗
DOE OSTI2025

A real-time distributed solid oxide electrolysis cell (SOEC) model for cyber-physical simulation

System integration and dynamic operability between SOEC and balance-of-plant (BoP) components are major technical challenges before realizing rapid load following of SOEC systems. Cyber-physical simulation (CPS) is a leading-edge digital engineering approach and is regarded as the next step beyond Digital Twins. CPS approach can be used to research SOEC system integration and develop dynamic controls prior to actual pilot testing without using a real SOEC. To seamlessly couple with BoP hardware and access non-observable operational parameters (e.g., local temperature gradient) during transients, a distributed one-dimensional (1D) real-time SOEC model was developed. Its real-time execution was demonstrated for 20 to 640 nodes at the fixed time step of 5 ms. A higher excess air ratio enabled smaller local temperature gradients on SOEC solid materials and faster transients upon current density step change from 0.15 to 0.55 A cm -2 . During the transients, the magnitude of the peak temperature gradient nearly doubled in 10 s from -3.5 to -5.9 °C cm -1 . This represents a significant operating risk that can impact the dynamic operability of SOEC systems. In addition, the local temperature gradient was found to change directions on all nodes in SOEC solid materials, with the greatest impact on the upstream nodes. The SOEC model was also tested at the thermal neutral voltage using actual process air flow parameters as variable model inputs. Variable process air temperatures were found to induce alternating local temperature gradients on SOEC solid materials. These are new operational mechanisms for SOEC degradation relevant for load following operational modes yet distinct from previous reports. To mitigate these unfavorable features, the SOEC can be operated at voltages that are slightly (±20 mV) deviated from the thermal neutral voltage. Here, the corresponding net thermal energy change was less than 1.6% of the electric power consumption. This 1D real-time SOEC model established the basis of cyber-physical simulation of SOEC hybrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1994

Multivariable Hermite polynomials and phase-space dynamics

The phase-space approach to classical and quantum systems demands for advanced analytical tools. Such an approach characterizes the evolution of a physical system through a set of variables, reducing to the canonically conjugate variables in the classical limit. It often happens that phase-space distributions can be written in terms of quadratic forms involving the above quoted variables. A significant analytical tool to treat these problems may come from the generalized many-variables Hermite polynomials, defined on quadratic forms in R(exp n). They form an orthonormal system in many dimensions and seem the natural tool to treat the harmonic oscillator dynamics in phase-space. In this contribution we discuss the properties of these polynomials and present some applications to physical problems.

Dattoli, G.↗
DOE OSTI2023

What Machine Learning Can and Cannot Do for Inertial Confinement Fusion

Machine learning methodologies have played remarkable roles in solving complex systems with large data, well-defined input–output pairs, and clearly definable goals and metrics. The methodologies are effective in image analysis, classification, and systems without long chains of logic. Recently, machine-learning methodologies have been widely applied to inertial confinement fusion (ICF) capsules and the design optimization of OMEGA (Omega Laser Facility) capsule implosion and NIF (National Ignition Facility) ignition capsules, leading to significant progress. As machine learning is being increasingly applied, concerns arise regarding its capabilities and limitations in the context of ICF. ICF is a complicated physical system that relies on physics knowledge and human judgment to guide machine learning. Additionally, the experimental database for ICF ignition is not large enough to provide credible training data. Most researchers in the field of ICF use simulations, or a mix of simulations and experimental results, instead of real data to train machine learning models and related tools. They then use the trained learning model to predict future events. This methodology can be successful, subject to a careful choice of data and simulations. However, because of the extreme sensitivity of the neutron yield to the input implosion parameters, physics-guided machine learning for ICF is extremely important and necessary, especially when the database is small, the uncertain-domain knowledge is large, and the physical capabilities of the learning models are still being developed. In this work, we identify problems in ICF that are suitable for machine learning and circumstances where machine learning is less likely to be successful. This study investigates the applications of machine learning and highlights fundamental research challenges and directions associated with machine learning in ICF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1989

A physical model for earthquakes. III - Thermodynamical approach and its relation to nonclassical theories

An earthquake theory based on fundamental thermodynamical considerations was developed using two principles. The first principle is that physical systems, including fault systems, tend toward a state of minimal Helmholtz free energy, which corresponds to static equilibrium. The second postulate is that, if the system is not at minimal free energy, thermodynamic forces arise which drive the system back toward a minimum. According to this theory, the propagation of a fracture, or the formation of a slip on a frictional surface, are manifestations of the physics which attempt to return the system to minimal free energy. It is shown that the process of return to minimal free energy by the system corresponds to the production of entropy, thereby rendering the process irreversible.

Rundle, John B.↗
NASA NTRS1980

Modeling a maintenance simulation of the geosynchronous platform

A modeling technique used to conduct a simulation study comparing various maintenance routines for a space platform is dicussed. A system model is described and illustrated, the basic concepts of a simulation pass are detailed, and sections on failures and maintenance are included. The operation of the system across time is best modeled by a discrete event approach with two basic events - failure and maintenance of the system. Each overall simulation run consists of introducing a particular model of the physical system, together with a maintenance policy, demand function, and mission lifetime. The system is then run through many passes, each pass corresponding to one mission and the model is re-initialized before each pass. Statistics are compiled at the end of each pass and after the last pass a report is printed. Items of interest typically include the time to first maintenance, total number of maintenance trips for each pass, average capability of the system, etc.

Kleiner, A. F., Jr.↗
NASA NTRS2006

Model-Based Safety Analysis

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Joshi, Anjali↗