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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

The JT9D Jet Engine Diagnostics Program

The various engine deterioration phenomena that affect JT9D performance retention were studied, and approaches to improve performance retention of engines were identified. The program included surveys of historical data, monitoring of in service engines, ground and flight testing of instrumented engines, analysis, and analytical modeling. Performance deterioration is made up of both short and long term modes, both of which are flight cycle related phenomena. Short term deterioration occurs primarily during airplane acceptance testing prior to delivery to the airline. This effect is caused by flight load and power induced clearance closures and engine deflections with resulting rubbing of airfoils and seals. Long term deterioration is caused by erosion of airfoils and gas path seals during ground operation and take off and by cyclic induced thermal distortion of the high pressure turbine airfoils. Studies of possible remedial approaches have shown that performance retention within 1 to 2 percent of initial revenue service performance can be achieved with a proper program of hot section and cold section maintenance.

Olsson, W. J.↗
NASA NTRS2009

International Space Station Solar Alpha Rotary Joint Failure Analysis: The Materials and Processes Perspective

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the ISS configurations spanning ISS Stage 12A. The objective of this analysis is to validate and correlate analytical models used to verify the ISS critical interface dynamic loads and improve its fatigue life prediction. On-Orbit dynamic responses were measured during the ISS configurations throughout ISS Stage 12A by the two main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS) and the Structural Dynamic Measurement System (SDMS). These nominal on-orbit events include Russian vehicle docking and undockings. Also, the ISS photogrammetric system recorded the movements of the 2A and 4A solar arrays during a modified ISS maneuver. Modal analyses were performed on the measured data to extract modal parameters including frequency, damping and mode shapes. Correlation and comparisons between the test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the ISS configurations under consideration.

Dasgupta, Rajib↗
NASA NTRS2009

ISS Stage 12A Post-Flight Modal Analysis, Model Validation and Correlation

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the ISS configurations spanning ISS Stage 12A. The objective of this analysis is to validate and correlate analytical models used to verify the ISS critical interface dynamic loads and improve its fatigue life prediction. On-Orbit dynamic responses were measured during the ISS configurations throughout ISS Stage 12A by the two main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS) and the Structural Dynamic Measurement System (SDMS). These nominal on-orbit events include Russian vehicle docking and undockings. Also, the ISS photogrammetric system recorded the movements of the 2A and 4A solar arrays during a modified ISS maneuver. Modal analyses were performed on the measured data to extract modal parameters including frequency, damping and mode shapes. Correlation and comparisons between the test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the ISS configurations under consideration.

Fitzpatrick, Kristin↗
NASA NTRS1984

Evaluation methodologies for an advanced information processing system

The system concept and requirements for an Advanced Information Processing System (AIPS) are briefly described, but the emphasis of this paper is on the evaluation methodologies being developed and utilized in the AIPS program. The evaluation tasks include hardware reliability, maintainability and availability, software reliability, performance, and performability. Hardware RMA and software reliability are addressed with Markov modeling techniques. The performance analysis for AIPS is based on queueing theory. Performability is a measure of merit which combines system reliability and performance measures. The probability laws of the performance measures are obtained from the Markov reliability models. Scalar functions of this law such as the mean and variance provide measures of merit in the AIPS performability evaluations.

Schabowsky, R. S., Jr.↗
DOE OSTI2025

Impacts of benchmarking choices on inferred model skill of the Arctic–Boreal terrestrial carbon cycle

Abstract Land surface models require continuous validation against observations to improve and reduce simulation uncertainty. However, inferred model performance can be heavily influenced by subjective choices made in the selection and application of observational data products. A key area often misrepresented by models is the Arctic–Boreal region, which is a potential tipping point region in Earth’s climate system due to large permafrost carbon stocks that are vulnerable to release with climate warming. We use the International Land Model Benchmarking (ILAMB) framework to evaluate how the model skill of TRENDY-v9 models varies based on the choice of observational-based benchmark and how benchmarks are applied in model evaluation. This analysis uses global datasets integrated into ILAMB and new, regionally-specific observational products from the Arctic–Boreal Vulnerability Experiment. Our results cover the overall time period of 1979–2019 and show that model scores can vary substantially depending on the data product applied, with higher model scores indicating better model performance against observations. The lowest model scores occur when benchmarked against regional, compared to global, datasets. We also evaluate observed and modeled functional relationships between ecosystem respiration and air temperature and between gross primary production and precipitation. Here, we find that the magnitude and shape of the responses are strongly impacted by the choice of observational dataset and the approach used to construct the functional relationship benchmark. These results suggest that model evaluation studies could conclude a false sense of model skill if only using a single benchmark data product or if not applying regional data products when performing a regional model analysis. Collectively, our findings highlight the influence of benchmarking choices on model evaluation and point to the need for benchmarking guidelines when assessing model skill.

Poe, Jeralyn (ORCID:0000000318495278)↗
NASA NTRS1972

Transportation Systems Evaluation

A methodology for the analysis of transportation systems consisting of five major interacting elements is reported. The analysis begins with the causes of travel demand: geographic, economic, and demographic characteristics as well as attitudes toward travel. Through the analysis, the interaction of these factors with the physical and economic characteristics of the transportation system is determined. The result is an evaluation of the system from the point of view of both passenger and operator. The methodology is applicable to the intraurban transit systems as well as major airlines. Applications of the technique to analysis of a PRT system and a study of intraurban air travel are given. In the discussion several unique models or techniques are mentioned: i.e., passenger preference modeling, an integrated intraurban transit model, and a series of models to perform airline analysis.

Fanning, M. L.↗
NASA NTRS1982

Optical communications research to demonstrate 2.5 bits/detected photon

The transmission of information by optical signals over a space channel with a power efficiency of 2.5 bits/detected photon markedly increases the amount of information that can be transmitted to satellites. An account is given of the research program at the Jet Propulsion Laboratory that is attempting to demonstrate that optical signals can be used to transmit information over a space channel with this power efficiency. It is noted, however, that the ability to attain 2.5 bits/detected photon (or higher) depends heavily on the validity of the mathematical models used in the performance analysis. Therefore, verification of the channel dark current noise models is a crucial first step. Another prerequisite is a high-brightness, single-spatial mode laser emitter. It is believed that single spatial model devices with power outputs of about 1W can be achieved by coherently combining a number of GaAs lasers in what effectively amounts to a phased array.

Lesh, J. R.↗
NASA NTRS1992

The evolution equation for the flame surface density in turbulent premixed combustion

One central ingredient in flamelet models for turbulent premixed combustion is the flame surface density. This quantity conveys most of the effects of the turbulence on the rate of energy release and is obtained via a modeled transport equation, called the Sigma-equation. Past theoretical work has produced a rigorous approach that leads to an exact, but unclosed, formulation for the turbulent Sigma-equation. In this exact Sigma-equation, it appears that the dynamical properties of the flame surface density are determined by a single parameter, namely the turbulent flame stretch. Unfortunately, the flame surface density and the turbulent flame stretch are not available from experiments and, in the absence of experimental data, little is known on the validity of the closure assumptions used in current flamelet models. Direct Numerical Simulation (DNS) is the obvious, complementary approach to get basic information on these fundamental quantities. Three-dimensional DNS of premixed flames in isotropic turbulent flow is used to estimate the different terms appearing in the Sigma-equation. A new methodology is proposed to provide the source and sink terms for the flame surface density, resolved both temporally and spatially throughout the turbulent flame brush. Using this methodology, the effects of the Lewis number on the rate of production of flame surface area are described in great detail and meaningful comparisons with flamelet models can be performed. The analysis reveals in particular the tendency of the models to overpredict flame surface dissipation as well as their inability to reproduce variations due to thermo-diffusive phenomena. Thanks to the detailed information produced by a DNS-based analysis, this type of comparison not only underscores the shortcomings of current models but also suggests ways to improve them.

Trouve, A.↗
DOE OSTI2024

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗
NASA NTRS1993

PERTS: A Prototyping Environment for Real-Time Systems

PERTS is a prototyping environment for real-time systems. It is being built incrementally and will contain basic building blocks of operating systems for time-critical applications, tools, and performance models for the analysis, evaluation and measurement of real-time systems and a simulation/emulation environment. It is designed to support the use and evaluation of new design approaches, experimentations with alternative system building blocks, and the analysis and performance profiling of prototype real-time systems.

Liu, Jane W. S.↗
DOE OSTI2020

Experimental validation of solid oxide fuel cell polarization modeling: An LSM-YSZ/YSZ/Ni-YSZ case study

Polarization modeling based on the measured I-V curves is a useful tool for analyzing SOFC performance and diagnosing performance limitations. Using the polarization model, the overpotential of a cell is usually separated into different polarization contributions, including area specific ohmic polarization, activation polarization, and anodic and cathodic concentration polarizations. In this study, we aim to experimentally validate the accuracy of the polarization model. As a case study, anode-supported cells with LSM-YSZ/YSZ/Ni-YSZ configuration are used. By curve-fitting the I-V curves of a cell tested under different cathode oxygen partial pressures into the polarization model, the contributions of different polarization losses are quantified. To validate the polarization model, independent experiments/studies including electrochemical impedance spectroscopy, cathode kinetics study, ex-situ diffusivity measurement, and tortuosity measurement using 3D reconstructed anode are conducted. The results from polarization modeling and from validation studies are in good agreement, thereby validating the polarization model for SOFC performance analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

3D inelastic analysis methods for hot section components

The objective is to develop analytical tools capable of economically evaluating the cyclic time dependent plasticity which occurs in hot section engine components in areas of strain concentration resulting from the combination of both mechanical and thermal stresses. Three models were developed. A simple model performs time dependent inelastic analysis using the power law creep equation. The second model is the classical model of Professors Walter Haisler and David Allen of Texas A and M University. The third model is the unified model of Bodner, Partom, et al. All models were customized for linear variation of loads and temperatures with all material properties and constitutive models being temperature dependent.

Dame, L. T.↗
NASA NTRS1984

Structural analysis of the Space Shuttle Orbiter

The structural analysis of the Space Shuttle orbiter was planned with two concepts in mind: use derivatives or subsets of the same basic finite element model whenever feasible, and substantiate the model's predictive capability by performing ground tests. The analysis cycle (model modal loads stress (MMLS)) starts with the finite element model conception and ends with the detailed stress analysis and margins of safety. The structural analysis of the orbiter encompasses a variety of static and dynamic problems. The salient features of these problems and their solutions are examined.

Henry R. Grooms↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
NASA NTRS2012

International Space Station Modal Correction Analysis

This paper summarizes the on-orbit modal test and the related modal analysis, model validation and correlation performed for the ISS Stage ULF4, DTF S4-1A, October 11,2010, GMT 284/06:13:00.00. The objective of this analysis is to validate and correlate analytical models with the intent to verify the ISS critical interface dynamic loads and improve fatigue life prediction. For the ISS configurations under consideration, on-orbit dynamic responses were collected with Russian vehicles attached and without the Orbiter attached to the ISS. ISS instrumentation systems that were used to collect the dynamic responses during the DTF S4-1A included the Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS), Structural Dynamic Measurement System (SDMS), Space Acceleration Measurement System (SAMS), Inertial Measurement Unit (IMU) and ISS External Cameras. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping and mode shape information. Correlation and comparisons between test and analytical modal parameters were performed to assess the accuracy of models for the ISS configuration under consideration. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. Section 2.0 of this report presents the math model used in the analysis. This section also describes the ISS configuration under consideration and summarizes the associated primary modes of interest along with the fundamental appendage modes. Section 3.0 discusses the details of the ISS Stage ULF4 DTF S4-1A test. Section 4.0 discusses the on-orbit instrumentation systems that were used in the collection of the data analyzed in this paper. The modal analysis approach and results used in the analysis of the collected data are summarized in Section 5.0. The model correlation and validation effort is reported in Section 6.0. Conclusions and recommendations drawn from this analysis are included in Section 7.0.

Fotz[atrocl. Lrostom↗
DOE OSTI2025

RAVEN Template for Dynamic Representativity Analysis of the High Temperature Test Facility

These slides present a walkthrough of the template that has been developed for using RAVEN to perform representativity analysis using models of the High Temperature Test Facility and the General Atomics Modular High Temperature Gas-cooled Reactor. The presentation provides participants in the HTTF benchmark with a walkthrough on how to use RAVEN for their sensitivity analysis and how to read results from the MHTGR-350 to perform representativity

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Validation of MFUEL Metal Fuel Performance Models of SAS4A/SASSYS-1

The fuel characterization models of SAS4A/SASSYS-1 (SAS) have recently been extended to include a new U-Pu-Zr metal fuel model, MFUEL. MFUEL is equipped with mechanistic physics based models to predict the pre-transient characterization and transient response of metal fuel, with emphasis on fuel melting, cladding failure, and the metal fuel’s impact on core reactivity. The MFUEL model will be available in the full version of SAS4A/SASSYS-1 5.7, which is scheduled to be released in June 2023. Fast reactor fuel pins that operated in EBR-II and FFTF with low smear density U-Zr and U-Pu-Zr metal fuels and irradiation resistant ferritic-martensitic cladding showed significant advantages in achieving high burnups and assuring inherent safety characteristics during anticipated transients, design basis events, and beyond design basis events. For safety analysis, a fuel performance model must be able to predict (1) Fuel pin mechanics and compositional and dimensional changes, (2) Clad failure, and (3) Fuel pin thermal resistance. Achieving these high level goals accurately is strongly related to the model performance of individual physical processes taking place within a fuel pin during its lifetime. Metal fuels typically operate above the mid-point temperature of melting during normal, as well as off-normal, conditions. At these elevated temperatures, the availability of thermal activation provides a driving force for various diffusional processes leading to complex phase transformations, micro-structure evolution, significant amounts of fuel swelling, interconnected porosity formation, excessive amounts of fission gas release, and fuel clad chemical interactions. Clad failure in fast reactors primarily occurs as a result of creep rupture augmented by clad wastage formation. The reaction is driven by thermal creep induced dislocation motion, grain boundary cavity nucleation, growth and breakup of grain boundaries. The high level complexity and limited available data requires introducing physics-based modeling approaches to gain extrapolation ability and sensitivity with respect to various conditions. The objective of this report is to perform validation of MFUEL using the experimental data for (1) Normal operation EBR-II fuel behavior, (2) Normal operation PHENIX fuel behavior, (3) HT9 Pressure tube ramp-and-hold creep rupture tests, (4) Whole Pin Furnace (WPF) creep strain, creep rupture and eutectic tests, (5) Fuel Behavior Test Apparatus (FBTA) eutectic tests, and (6) TREAT M5-7 OverPower tests up to clad failure. Section-2 includes a brief description of the MFUEL models. A detailed description of the MFUEL physics-based, semi-empirical models will be presented in the SAS V 5.7 theory manual. Section-3, 4, and 5 describes the validation effort for the pre-transient irradiation, furnace transients, and TREAT M-Series transients, respectively.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2009

Modeling Joule Heating Effect on Lunar O2 Generation via Electrolytic Reduction.

Kennedy Space Center is leading research work on lunar O2 generation via electrolytic reduction of regolith; the metal oxide present in the regolith is dissociated in oxygen anions and metal cations leading to the generation of gaseous oxygen at the anode and liquid metal at the cathode. Electrical resistance of molten regolith is high, leading to heating of the melt when electrical current is applied between the electrodes (Joule heating). The authors have developed a 3D model using a rigorous approach for two coupled physics (thermal and electrical potential) to not only study the effect of Joule heating on temperature distribution throughout the molten regolith but also to evaluate and optimize the design of the electrolytic cells. This paper presents the results of the thermal analysis performed on the model and used to validate the design of the electrolytic cell.

Dominquez, Jesus↗