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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Hybrid Modeling Improves Health and Performance Monitoring

Scientific Monitoring Inc. was awarded a Phase I Small Business Innovation Research (SBIR) project by NASA's Dryden Flight Research Center to create a new, simplified health-monitoring approach for flight vehicles and flight equipment. The project developed a hybrid physical model concept that provided a structured approach to simplifying complex design models for use in health monitoring, allowing the output or performance of the equipment to be compared to what the design models predicted, so that deterioration or impending failure could be detected before there would be an impact on the equipment's operational capability. Based on the original modeling technology, Scientific Monitoring released I-Trend, a commercial health- and performance-monitoring software product named for its intelligent trending, diagnostics, and prognostics capabilities, as part of the company's complete ICEMS (Intelligent Condition-based Equipment Management System) suite of monitoring and advanced alerting software. I-Trend uses the hybrid physical model to better characterize the nature of health or performance alarms that result in "no fault found" false alarms. Additionally, the use of physical principles helps I-Trend identify problems sooner. I-Trend technology is currently in use in several commercial aviation programs, and the U.S. Air Force recently tapped Scientific Monitoring to develop next-generation engine health-management software for monitoring its fleet of jet engines. Scientific Monitoring has continued the original NASA work, this time under a Phase III SBIR contract with a joint NASA-Pratt & Whitney aviation security program on propulsion-controlled aircraft under missile-damaged aircraft conditions.

Source record↗
DOE OSTI2024

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗
NASA NTRS2006

Effects of Kinetic Processes in Shaping Io's Global Plasma Environment: A 3D Hybrid Model

The global dynamics of the ionized and neutral gases in the environment of Io plays an important role in the interaction of Jupiter s corotating magnetospheric plasma with Io. Stationary simulations of this problem have already been done using the magnetohydrodynamics (MHD) and the electrodynamics approaches. One of the major results of recent simplified two-fluid model simulations [Saur, J., Neubauer, F.M., Strobel, D.F., Summers, M.E., 2002. J. Geophys. Res. 107 (SMP5), 1-18] was the production of the structure of the double-peak in the magnetic field signature of the Io flyby. These could not be explained before by standard MHD models. In this paper, we present a hybrid simulation for Io with kinetic ions and fluid electrons. This method employs a fluid description for electrons and neutrals, whereas for ions a particle approach is used. We also take into account charge-exchange and photoionization processes and solve self-consistently for electric and magnetic fields. Our model may provide a much more accurate description for the ion dynamics than previous approaches and allows us to account for the realistic anisotropic ion velocity distribution that cannot be done in fluid simulations with isotropic temperatures. The first results of such a simulation of the dynamics of ions in Io s environment are discussed in this paper. Comparison with the Galileo IO flyby results shows that this approach provides an accurate physical basis for the interaction and can therefore naturally reproduce all the observed salient features.

Lipatov, Alexander S.↗
NASA NTRSDate not supplied

Hybrid Modeling for Complex Systems Health Management

The research work presents application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. The powertrain model consists of Li-ion batteries, electronic speed controller with pulse-width modulation, and brush-less DC motor with connected propeller. Results obtained from combination of laboratory and simulation tests are discussed in this work.

PINNS↗
NASA NTRS1996

Hybrid modeling of the formation and structure of thin current sheets in the magnetotail

Hybrid simulations are used to investigate the formation of a thin current sheet inside the plasma sheet of a magnetotail-like configuration. The initial equilibrium is subjected to a driving electric field which is qualitatively similar to what would be expected from solar wind driving. As a result, a new current sheet with the thickness of approximately the ion inertial length is formed. The current density inside the current sheet region is supplied largely by the electrons. Ion acceleration in the cross-tail direction is absent as the driving electric field fails to penetrate into the equatorial region.

Hesse, Michael↗
NASA NTRSDate not supplied

Hybrid Modeling of Unmanned Aerial Vehicle Electric Powertrain for Fault Detection and Diagnostics

This paper shows the application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived principles and empirical equations, as well as fully connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. It has already been applied to Li-ion batteries in the past, and in this work, we extend the applications to other components of an electric powertrain, namely electronic speed controller with pulse-width modulation, and brushless DC motor with connected propeller. Training and testing of the model is carried out using experimental data from Li-ion battery discharge and powertrain testing in a laboratory environment.

Physics-Informed Machine Learning↗
NASA NTRS1980

Solutions of contact problems by the assumed stress hybrid model

A method was developed for contact problems which may be either frictional or frictionless and may involve extensive sliding between deformable bodies. It was based on an assumed stress hybrid approach and on an incremental variational principle for which the Euler's equations of the functional include the equilibrium and compatibility conditions at the contact surface. The tractions at an assumed contact surface were introduced as Lagrangian multipliers in the formulation. It was concluded from the results of several example solutions that the extensive sliding contact between deformable bodies can be solved by the present method.

Kubomura, K.↗
NASA NTRS2001

Hybrid Modeling for Scenario-Based Evaluation of Failure Effects in Advanced Hardware-Software Designs

This paper describes an incremental scenario-based simulation approach to evaluation of intelligent software for control and management of hardware systems. A hybrid continuous/discrete event simulation of the hardware dynamically interacts with the intelligent software in operations scenarios. Embedded anomalous conditions and failures in simulated hardware can lead to emergent software behavior and identification of missing or faulty software or hardware requirements. An approach is described for extending simulation-based automated incremental failure modes and effects analysis, to support concurrent evaluation of intelligent software and the hardware controlled by the software

Malin, Jane T.↗
NASA NTRS1991

Traction free finite elements with the assumed stress hybrid model

An effective approach in the finite element analysis of the stress field at the traction free boundary of a solid continuum was studied. Conventional displacement and assumed stress finite elements were used in the determination of stress concentrations around circular and elliptical holes. Specialized hybrid elements were then developed to improve the satisfaction of prescribed traction boundary conditions. Results of the stress analysis indicated that finite elements which exactly satisfy the free stress boundary conditions are the most accurate and efficient in such problems. A general approach for hybrid finite elements which incorporate traction free boundaries of arbitrary geometry was formulated.

Kafie, Kurosh↗
NASA NTRS2023

Multiscale Hybrid Modeling of the Impact Response of the Earth's Magnetotail to Ionospheric O+ Outflow

Ionospheric outflow plays an important role in coupling the ionosphere with the solar wind-magnetosphere system. Previous multi-fluid MHD studies explored the global influence of oxygen ions of ionospheric origin (O+) on magnetospheric dynamics. A detailed exploration of the interaction of ionospheric ions with the magnetotail requires kinetic treatment for ions. We perform a self-consistent investigation of these processes with a three-dimensional space-time adaptive hybrid code, HYPERS, powered by an intelligent Event-driven Multi-Agent Planning System (EMAPS). By comparing simulations with and without outflow we conclude that oxygen ions, flowing from the ionosphere through the lobes into the tail or directly entering the inner magnetosphere, are able to significantly modify the magnetotail configuration and induce X-points and current sheet structures at locations where magnetic reconnection does not occur in a simulation without outflow, potentially very close to the Earth. This finding may have implications for interpreting substorms and magnetotail reconnection events observed for southward magnetic field simultaneously with significant contents of oxygen ions of ionospheric origin.

multiscale↗
DOE OSTI2025

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗