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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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1,190 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Mathematical Characterization of Battery Models

The purpose of this document is to demonstrate the use of the Extended Kalman Filter as a tool for battery state estimation and the estimation of battery state of charge. The mathematical details based on the equivalent circuit model are presented followed by an electrochemical engineering model. A simplified first-order model is used to demonstrate the procedure followed by second and third-order models. Next a simplified electrochemistry model is presented along with observer development. State observability is calculated for the simpler equivalent circuit models and the simplified electrochemistry model. An outline of the battery model parameter identification method is presented, and model performance based on experimental and flight data is demonstrated.

Battery↗
DOE OSTI2026

Mode Multiplexing for Scalable Cavity-Enhanced Operations in Neutral-Atom Arrays

Neutral-atom arrays provide a versatile platform for quantum information processing. However, in large-scale arrays, efficient photon collection remains a bottleneck for key tasks such as fast, nondestructive qubit readout and remote entanglement distribution. We propose a cavity-based approach that enables fast, parallel operations over many atoms using multiple modes of a single optical cavity. By selectively shifting the relevant atomic transitions, each atom can be coupled to a distinct cavity mode, allowing independent simultaneous processing. We present practical system designs that support cavity-mode multiplexing with up to 50 modes, enabling rapid mid-circuit syndrome extraction and significantly enhancing entanglement distribution rates between remote atom arrays. This approach offers a scalable solution to core challenges in neutral-atom arrays, advancing the development of practical quantum technologies.

Aqua, Ziv [Massachusetts Institute of Technology (↗
NASA NTRS1981

Battery failure model derived from flaw theory

A previously derived failure model for battery lifetime is discussed in terms of growth rate of the flaw, distribution of flaw sizes, and number of flaws. Equations are presented for determining the failure model for a nickel cadmium battery.

Schulman, I.↗
NASA NTRS1985

Battery-Charge-State Model

Charge-state model for lead/acid batteries proposed as part of effort to make equivalent of fuel gage for battery-powered vehicles. Models based on equations that approximate observable characteristics of battery electrochemistry. Uses linear equations, easier to simulate on computer, and gives smooth transitions between charge, discharge, and recuperation.

Vivian, H. C.↗
DOE OSTI2026

A Data-Driven Method for Modeling Creep-Fatigue Stress- Strain Behavior Using Neural ODEs

In this paper, we introduce a data-driven machine learning approach for modeling one-dimensional stress–strain behavior under cyclic loading, utilizing experimental data from the nickel-based Alloy 617. The study employs uniaxial creep–fatigue test data acquired under various loading histories and compares two distinct neural network-based ODE models. The first model, known as the black-box model, comprehensively describes the strain–stress relationship using a Neural ODE equation. To interpret this black-box model, we apply the Sparse Identification of Nonlinear Dynamical Systems (SINDy) technique, transforming the black-box model into an equation-based model using symbolic regression. The second model, the Neural flow rule model, incorporates Hooke’s Law for the linear elastic component, with the nonlinear part characterized by a Neural ODE. Both models are trained with experimental data to accurately reflect the observed stress–strain behavior. We conduct a detailed comparison with the standard Chaboche model, which includes three back stresses. Our results demonstrate that the neural network-based ODE models precisely capture the experimental creep–fatigue mechanical behavior, exceeding the standard Chaboche model’s accuracy. Furthermore, an interpretable model derived from the black-box neural ODE model through symbolic regression achieves accuracy comparable to the Chaboche model, enhancing its interpretability. The results highlight the potential of neural network-based ODE models to depict complex creep–fatigue behavior, eliminating the necessity for experts to define a specific, material-focused model form.

creep-fatigue↗
DOE OSTI1994

Nuclear Safety [Vol. 35, No. 1, January-June 1994]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: THE CHERNOBYL ACCIDENT: 1 Chernobyl Accident Management Actions, A. R Sich 25 The IAEA-ASSET Approach to Avoiding Accidents is to Recognize the Precursors to Prevent Incidents, F. Reisch; ACCIDENT ANALYSIS: 36 A Review of the Available Information on the Triggering Stage of a Steam Explosion, D. F. Fletcher; 58 Analysis and Modeling of Flow-Blockage-Induced Steam Explosion Events in the High-Flux Isotope Reactor, R. P. Taleyarkhan, V. Georgevich, C. W. Nestor, U. Gat, B. L. Lepard, D. H. Cook, J. Freels, S. J. Chang, C. Luttrell, R. C. Gwaltney, and J. Kirkpatrick; 74 An Analysis of Disassembling the Radial Reflector of a Thermionic Space Nuclear Reactor Power System, M. S. El-Genk and D. V. Paramonov; CONTROL AND INSTRUMENTATION: 86 Standards for High-Integrity Software, D. R. Wallace, D. R. Kuhn, L M. Ippolito, and L. Beltracchi; DESIGN FEATURES: 98 Adoption of New Design Features for the Next Generation Nuclear Power Reactors, L. S. Tong; 114 Review of Nuclear Piping Seismic Design Requirements, G. C. Slagis and S. E. Moore; ENVIRONMENTAL EFFECTS: 128 PC-Based Probabilistic Safety Assessment Study for a Geological Waste Repository Placed in a Bedded Salt Formation, S. A. Khan; OPERATING EXPERIENCES: 142 Managing Aging in Nuclear Power Plants: Insights from NRC’s Maintenance Team Inspection Reports, A. Fresco and M. Subudhi; 150 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 153 Selected Safety-Related Events, Compiled by G. A. Murphy; RECENT DEVELOPMENTS: 158 Reports, Standards, and Safety Guides, D. S. Queener; 168 Proposed Rule Changes as of Dec. 31, 1993; ANNOUNCEMENTS: 177 Symposium on Radioactive and Mixed Waste—Risk as a Basis for Waste Classification; 177 1995 Incineration Conference 178 Ninth Power Plant Dynamics Control and Testing Symposium; 174 The Authors

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

A Case Study of AI-assisted Creation of a Thermodynamics Model of Precipitation Formation During Rapid Depressurization of a Vented Container

Precipitation may form in humid containers undergoing rapid depressurization. This precipitation may be liquid, i.e. fog, if the dewpoint is crossed above the freezing point of water, or direct snow crystallization if the dewpoint is crossed below the freezing point. Accurate modeling of this effect is potentially important for rapidly ascending vented containers in aircraft, spacecraft, and launch vehicles, as well as rapidly depressurizing vacuum chambers. A transient thermodynamics model of precipitation formation during the rapid depressurization of a container was developed in python. The model is written for a generic container and includes an optional water pool and water vapor source. Details of the model and results from several example cases spanning the full capabilities of the model, including a validation case, will be presented. Although the model is not novel, in contrast to prior works, this one was treated as a case study of the assistance of AI Large Language Models (LLMs) to create physical models. Impressions, performance, time, and cost of using AI for this task will be discussed.

precipitation↗