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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

An Information Theory Approach to Physical Domain Discovery

The project of physics discovery is often equivalent to finding the most concise description of a physical system. The description with optimum predictive capability for a dataset generated by a physical system is one that minimizes both predictive error on the dataset and the complexity of the description. The discovery of the governing physics of a system can therefore be viewed as a mathematical optimization problem. We outline here a method to optimize the description of arbitrarily complex physical systems by minimizing the entropy of the description of the system. The Recursive Domain Partitioning (RDP) procedure finds the optimum partitioning of each physical domain into subdomains, and the optimum predictive function within each subdomain. Penalty functions are introduced to limit the complexity of the predictive function within each domain. Examples are shown in 1D and 2D. In 1D, the technique effectively discovers the elastic and plastic regions within a stress-strain curve generated by simulations of amorphous carbon material, while in 2D the technique discovers the free-flow region and the inertially-obstructed flow region in the simulation of fluid flow across a plate.

Daniel Shea↗
NASA NTRSDate not supplied

Computational Models of Trustworthiness and Trust in Autonomous Cyber-Physical-Human Systems

In this paper, we propose an approach to developing a concept of actionable trust in multi-agent,cyber-physical-human systems in safety-critical and time-critical environment of air transportation. Actionable trust requires computational models of trustworthiness and trust, for use during system design and in real time, during operations. We describe the models, examine their computability and scalability, as well as what remains to be done.

Autonomous Systems↗
DOE OSTI2025

Quantum simulation of boson-related Hamiltonians: techniques, effective Hamiltonian construction, and error analysis

Elementary quantum mechanics proposes that a closed physical system consistently evolves in a reversible manner. However, control and readout necessitate the coupling of the quantum system to the external environment, subjecting it to relaxation and decoherence. Consequently, system-environment interactions are indispensable for simulating physically significant theories. A broad spectrum of physical systems in condensed-matter and high-energy physics, vibrational spectroscopy, and circuit and cavity QED necessitates the incorporation of bosonic degrees of freedom, such as phonons, photons, and gluons, into optimized fermion algorithms for near-future quantum simulations. In particular, when a quantum system is surrounded by an external environment, its basic physics can usually be simplified to a spin or fermionic system interacting with bosonic modes. Nevertheless, troublesome factors such as the magnitude of the bosonic degrees of freedom typically complicate the direct quantum simulation of these interacting models, necessitating the consideration of a comprehensive plan. This strategy should specifically include a suitable fermion/boson-to-qubit mapping scheme to encode sufficiently large yet manageable bosonic modes, and a method for truncating and/or downfolding the Hamiltonian to the defined subspace for performing an approximate but highly accurate simulation, guided by rigorous error analysis. In this pedagogical tutorial review, we aim to provide such an exhaustive strategy, focusing on encoding and simulating certain bosonic-related model Hamiltonians, inclusive of their static properties and time evolutions. Specifically, we emphasize two aspects: (1) the discussion of recently developed quantum algorithms for these interacting models and the construction of effective Hamiltonians, and (2) a detailed analysis regarding a tightened error bound for truncating the bosonic modes for a class of fermion-boson interacting Hamiltonians.

bosonic Hamiltonian↗
NASA NTRS1975

Diffusion in liquid metal systems

Physical properties of twenty liquid metals are reported; some of the data on such liquid metal properties as density, electrical resistivity, thermal conductivity, and heat capacity are summarized in graphical form. Data on laboratory handling and safety procedure are summarized for each metal; heat-transfer-correlations for liquid metals under various conditions of laminar and turbulent flow are included. Where sufficient data were available, temperature equations of properties were obtained by the method of least-squares fit. All values of properties given are valid in the given liquid phase ranges only. Additional tabular data on some 40 metals are reported in the appendix. Included is a brief description of experiments that were performed to investigate diffusion in liquid indium-gallium systems.

Ukanwa, A. O.↗
NASA NTRS1989

Automatic determination of fault effects on aircraft functionality

The problem of determining the behavior of physical systems subsequent to the occurrence of malfunctions is discussed. It is established that while it was reasonable to assume that the most important fault behavior modes of primitive components and simple subsystems could be known and predicted, interactions within composite systems reached levels of complexity that precluded the use of traditional rule-based expert system techniques. Reasoning from first principles, i.e., on the basis of causal models of the physical system, was required. The first question that arises is, of course, how the causal information required for such reasoning should be represented. The bond graphs presented here occupy a position intermediate between qualitative and quantitative models, allowing the automatic derivation of Kuipers-like qualitative constraint models as well as state equations. Their most salient feature, however, is that entities corresponding to components and interactions in the physical system are explicitly represented in the bond graph model, thus permitting systematic model updates to reflect malfunctions. Researchers show how this is done, as well as presenting a number of techniques for obtaining qualitative information from the state equations derivable from bond graph models. One insight is the fact that one of the most important advantages of the bond graph ontology is the highly systematic approach to model construction it imposes on the modeler, who is forced to classify the relevant physical entities into a small number of categories, and to look for two highly specific types of interactions among them. The systematic nature of bond graph model construction facilitates the process to the point where the guidelines are sufficiently specific to be followed by modelers who are not domain experts. As a result, models of a given system constructed by different modelers will have extensive similarities. Researchers conclude by pointing out that the ease of updating bond graph models to reflect malfunctions is a manifestation of the systematic nature of bond graph construction, and the regularity of the relationship between bond graph models and physical reality.

Feyock, Stefan↗
NASA NTRS1977

Atmospheric cloud physics thermal systems analysis

Engineering analyses performed on the Atmospheric Cloud Physics (ACPL) Science Simulator expansion chamber and associated thermal control/conditioning system are reported. Analyses were made to develop a verified thermal model and to perform parametric thermal investigations to evaluate systems performance characteristics. Thermal network representations of solid components and the complete fluid conditioning system were solved simultaneously using the Systems Improved Numerical Differencing Analyzer (SINDA) computer program.

Source record↗
NASA NTRS1969

Theory of distributed systems.

Physical networks with lumped components and hydraulic, pneumatic, electric, thermal and elastic lines of transfer matrices

Oldenburger, R.↗
NASA NTRS1978

Cargo Logistics Airlift Systems Study (CLASS). Volume 3: Cross impact between the 1990 market and the air physical distribution systems, book 2

Book 2 of this volume is divided into the following sections: (1) commodities and system networks; (2) future mode choice decisions and commodity air eligibility; (3) comparative cargo transportation costs - air, truck, rail and water; (4) elasticities of demand; (5) operating cost; (6) operating profit, rate making, and returns; (7) importance of rate and service on future aircraft; (8) potential market demand for new aircraft; (9) scenario of events affecting system/market growth; and (10) future study and technology requirements.

Burby, R. J.↗
DOE OSTI2025

CIE Curriculum Guide (V.2.0)

The Cyber-Informed Engineering (CIE) Curriculum Guide offers a comprehensive framework, guidance, and resources for integrating CIE into university-level engineering programs and related educational activities. The primary goal is to help educators adopt CIE principles into their teaching to produce future engineers and technicians who understand digital risks in modern engineered systems, thereby addressing the nation’s infrastructure resilience needs. This guide outlines practical integration examples, links to resources to accelerate CIE adoption, and shares insights from partner academic institutions on various implementation strategies. CIE is a framework for embedding engineered controls that mitigate the impact of cyber-attacks in any cyber-physical system used in critical energy infrastructure and other sectors. Developed by the U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), the National Cyber-Informed Engineering Strategy emphasizes embedding CIE into formal education, training, and credentialing. This guide supports this strategic objective by providing examples of integrating CIE concepts into engineering curricula, from class activities to new courses and certificate programs. The importance of educating cyber-informed engineers is underscored by the evolving cybersecurity threats facing engineered systems. As industrial control systems (ICS) increasingly incorporate digital technologies, the responsibility for security extends to both cyber professionals and engineers. CIE addresses critical gaps in designing and protecting physical systems with digital components against cyber risks, ensuring engineers consider digital risk throughout the engineering design lifecycle. Currently, engineering education does not routinely include cyber-informed principles, highlighting a gap in addressing modern engineering system risks. This guide advocates for updating engineering curricula to include digital risk management as a fundamental element. By doing so, future engineers will be equipped to design resilient systems that mitigate digital risks from the outset. Through this guide, engineering faculty can integrate CIE into their curricula, bridging the gap between digital risk and engineering. This approach prepares a cyber-informed workforce capable of safeguarding the cyber-physical systems crucial to national security and public welfare. By embedding CIE into education and training, institutions can produce engineers and technicians who can effectively mitigate cyber impacts throughout the engineering design lifecycle, resulting in more secure critical infrastructures.

42 - ENGINEERING↗
NASA NTRS2015

Advanced Ground Systems Maintenance Physics Models For Diagnostics Project

The project will use high-fidelity physics models and simulations to simulate real-time operations of cryogenic and systems and calculate the status/health of the systems. The project enables the delivery of system health advisories to ground system operators. The capability will also be used to conduct planning and analysis of cryogenic system operations. This project will develop and implement high-fidelity physics-based modeling techniques tosimulate the real-time operation of cryogenics and other fluids systems and, when compared to thereal-time operation of the actual systems, provide assessment of their state. Physics-modelcalculated measurements (called “pseudo-sensors”) will be compared to the system real-timedata. Comparison results will be utilized to provide systems operators with enhanced monitoring ofsystems' health and status, identify off-nominal trends and diagnose system/component failures.This capability can also be used to conduct planning and analysis of cryogenics and other fluidsystems designs. This capability will be interfaced with the ground operations command andcontrol system as a part of the Advanced Ground Systems Maintenance (AGSM) project to helpassure system availability and mission success. The initial capability will be developed for theLiquid Oxygen (LO2) ground loading systems.

System health↗
DOE OSTI2025

DRE: Designing for Resilience through Emulation

Threats to cyber- and cyber-physical systems have continued to increase over the past decade. Now more than ever, it is vital that cyber-physical system stakeholders have the tools to deeply understand their systems and the threats they face. High-fidelity modeling capabilities are powerful tools to support system understanding and decision-making, but they currently lack scientifically rigorous experimentation practices and infrastructures. The purpose of the project Designing for Resilience through Emulation (DRE) was to bring together past research and existing tools into a new pipeline to improve our ability to quantitatively evaluate future cyber scenarios. DRE offers new integrated capabilities for large dataset collection, noise studies, sensitivity analysis, uncertainty quantification, and surrogate modeling using a cyber-physical system emulation environment. These new capabilities significantly improve our ability to establish the credibility of the answers derived from emulation environments, ultimately leading to better critical decision support.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS2011

The Challenge of Grounding Planning in Simulation with an Interactive Model Development Environment

A principal obstacle to fielding automated planning systems is the difficulty of modeling. Physical systems are modeled conventionally based on specification documents and the modeler's understanding of the system. Thus, the model is developed in a way that is disconnected from the system's actual behavior and is vulnerable to manual error. Another obstacle to fielding planners is testing and validation. For a space mission, generated plans must be validated often by translating them into command sequences that are run in a simulation testbed. Testing in this way is complex and onerous because of the large number of possible plans and states of the spacecraft. Though, if used as a source of domain knowledge, the simulator can ease validation. This paper poses a challenge: to ground planning models in the system physics represented by simulation. A proposed, interactive model development environment illustrates the integration of planning and simulation to meet the challenge. This integration reveals research paths for automated model construction and validation.

radio occultation↗
NASA NTRS1992

Analysis of a generalized dual reflector antenna system using physical optics

Reflector antennas are widely used in communication satellite systems because they provide high gain at low cost. Offset-fed single paraboloids and dual reflector offset Cassegrain and Gregorian antennas with multiple focal region feeds provide a simple, blockage-free means of forming multiple, shaped, and isolated beams with low sidelobes. Such antennas are applicable to communications satellite frequency reuse systems and earth stations requiring access to several satellites. While the single offset paraboloid has been the most extensively used configuration for the satellite multiple-beam antenna, the trend toward large apertures requiring minimum scanned beam degradation over the field of view 18 degrees for full earth coverage from geostationary orbit may lead to impractically long focal length and large feed arrays. Dual reflector antennas offer packaging advantages and more degrees of design freedom to improve beam scanning and cross-polarization properties. The Cassegrain and Gregorian antennas are the most commonly used dual reflector antennas. A computer program for calculating the secondary pattern and directivity of a generalized dual reflector antenna system was developed and implemented at LeRC. The theoretical foundation for this program is based on the use of physical optics methodology for describing the induced currents on the sub-reflector and main reflector. The resulting induced currents on the main reflector are integrated to obtain the antenna far-zone electric fields. The computer program is verified with other physical optics programs and with measured antenna patterns. The comparison shows good agreement in far-field sidelobe reproduction and directivity.

Acosta, Roberto J.↗
DOE OSTI2025

Physics-informed Deep Reinforcement Learning-based Control in Power systems

Incorporating physics information into the deep reinforcement learning (DRL) process is a promising approach for addressing the challenges faced in learning-based control design problems for physical systems. Power grid dynamics, being a physical system, adheres to specific physical laws, constraints, as well as operational and control rules. Therefore, consideration of such physics-based law improves the learning process drastically. In general, traditional grid control schemes rely on rule-based mechanisms that cannot adapt to changing operating conditions. To improve the adaptability and computation time, recent research has seen a surge of DRL-based applications in power grid control. A generic DRL-based control design imposes the system performance requirements through the design of reward functions. In some cases, some of the important physics information is injected through this reward function. However, due to the complex dynamics and large state-action space, learning an optimal DRL policy often becomes challenging. Inspired by the latest developments in general machine learning (ML) research, power system researchers have been investigating more direct ways of incorporating physics knowledge into DRL training. This chapter specifically focuses on these aspects of physics-informed DRL designs in grid control. It discusses the significance, applications, research gaps, and open problems that need to be addressed in future research.

artificial intelligence, machine learning↗
NASA NTRS1996

Controlled Quantum Packets

We look at time evolution of a physical system from the point of view of dynamical control theory. Normally we solve motion equation with a given external potential and we obtain time evolution. Standard examples are the trajectories in classical mechanics or the wave functions in Quantum Mechanics. In the control theory, we have the configurational variables of a physical system, we choose a velocity field and with a suited strategy we force the physical system to have a well defined evolution. The evolution of the system is the 'premium' that the controller receives if he has adopted the right strategy. The strategy is given by well suited laboratory devices. The control mechanisms are in many cases non linear; it is necessary, namely, a feedback mechanism to retain in time the selected evolution. Our aim is to introduce a scheme to obtain Quantum wave packets by control theory. The program is to choose the characteristics of a packet, that is, the equation of evolution for its centre and a controlled dispersion, and to give a building scheme from some initial state (for example a solution of stationary Schroedinger equation). It seems natural in this view to use stochastic approach to Quantum Mechanics, that is, Stochastic Mechanics [S.M.]. It is a quantization scheme different from ordinary ones only formally. This approach introduces in quantum theory the whole mathematical apparatus of stochastic control theory. Stochastic Mechanics, in our view, is more intuitive when we want to study all the classical-like problems. We apply our scheme to build two classes of quantum packets both derived generalizing some properties of coherent states.

DeMartino, Salvatore↗
NASA NTRS1993

Case-based approach to handling aircraft malfunctions

Reasoning about physical systems in operation is a difficult task, and any attempt to automate the process must overcome the problems of modeling normal behavior, diagnosing faults, and predicting future behavior. This paper describes a prototypical case-based reasoner (CBR) that operates in the domain of in-flight fault diagnosis and prognosis of aviation subsystems, particularly jet engines. The reasoner operates on the observation that the ability of a CBR program to reason about physical systems can be significantly enhanced by the addition to the CBR program of a model of the physical system to describe the system's structural, functional, and causal behavior.

Karamouzis, Stamos T.↗
DOE OSTI2026

Scientific Discovery with Physics-Informed System Identification (Abbreviated Report)

My fellowship research focused on making physics-based simulations faster and more useful through machine learning. Many problems in science and engineering are governed by partial differential equations, but high-fidelity simulations are often too expensive to run repeatedly. I worked on improving Latent Space Dynamics Identification (LaSDI), a reduced-order modeling framework that compresses large simulation data sets into a smaller representation and then learns how that representation evolves over time. The motivation was to develop reduced models that remain accurate for more challenging systems, especially when predictions must remain reliable over long time intervals or when the underlying dynamics are more complicated than standard methods can easily handle. I also contributed to related work on Quandary, a high-performance software effort for simulation and control of open quantum systems, before focusing primarily on Latent Space Dynamics Identification methods. The main outcomes of the fellowship were two new algorithms (both of which were published), Rollout-LaSDI and Higher-Order LaSDI, together with supporting work on multi-stage Latent Space Dynamics Identification. Rollout-LaSDI improved long-term prediction by training the model to stay accurate over extended time horizons, and Higher-Order LaSDI broadened the method so it could model systems with higher-order time dynamics. My contributions to multistage Latent Space Dynamics Identification also helped show that its later training stages could be simplified without losing effectiveness, and that this behavior held across different model architectures and training strategies. Taken together, these advances improved the accuracy, flexibility, and practical value of reduced-order modeling tools for computational science.

97 MATHEMATICS AND COMPUTING↗