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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 235 records · Page 13

Comparative Modelling of the Spectra of Cool Giants

Our ability to extract information from the spectra of stars depends on reliable models of stellar atmospheres and appropriate techniques for spectral synthesis. Various model codes and strategies for the analysis of stellar spectra are available today. Aims. We aim to compare the results of deriving stellar parameters using different atmosphere models and different analysis strategies. The focus is set on high-resolution spectroscopy of cool giant stars. Methods. Spectra representing four cool giant stars were made available to various groups and individuals working in the area of spectral synthesis, asking them to derive stellar parameters from the data provided. The results were discussed at a workshop in Vienna in 2010. Most of the major codes currently used in the astronomical community for analyses of stellar spectra were included in this experiment. Results. We present the results from the different groups, as well as an additional experiment comparing the synthetic spectra produced by various codes for a given set of stellar parameters. Similarities and differences of the results are discussed. Conclusions. Several valid approaches to analyze a given spectrum of a star result in quite a wide range of solutions. The main causes for the differences in parameters derived by different groups seem to lie in the physical input data and in the details of the analysis method. This clearly shows how far from a definitive abundance analysis we still are.

stars↗

Approximation Model Building for Reliability & Maintainability Characteristics of Reusable Launch Vehicles

This paper describes the development of parametric models for estimating operational reliability and maintainability (R&M) characteristics for reusable vehicle concepts, based on vehicle size and technology support level. A R&M analysis tool (RMAT) and response surface methods are utilized to build parametric approximation models for rapidly estimating operational R&M characteristics such as mission completion reliability. These models that approximate RMAT, can then be utilized for fast analysis of operational requirements, for lifecycle cost estimating and for multidisciplinary sign optimization.

Unal, Resit↗

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗

Reliability of voting in fault-tolerant software systems for small output spaces

Under a voting strategy in a fault-tolerant software system there is a difference between correctness and agreement. An independent N-version programming reliability model is proposed for treating small output spaces which distinguishes between correctness and agreement. System reliability is investigated using analytical relationships and simulation. A consensus majority voting strategy is proposed and its performance is analyzed and compared with other voting strategies. Consensus majority strategy automatically adapts the voting to different component reliability and output space cardinality characteristics. It is shown that absolute majority voting strategy provides a lower bound on the reliability provided by the consensus majority, and 2-of-n voting strategy an upper bound. If r is the cardinality of the output space it is proved the 1/r is a lower bound on the average reliability of fault-tolerant system components below which the system reliability begins to deteriorate as more versions are added.

Mcallister, David F.↗

Reliability of voting in fault-tolerant software systems for small output spaces

Under a voting strategy in a fault-tolerant software system there is a difference between correctness and agreement. An independent N-version programming reliability model is proposed for treating small output spaces which distinguishes between correctness and agreement. System reliability is investigated using analytical relationships and simulation. A consensus majority voting stratey is proposed and its performance is analyzed and compared with other voting strategies. A consensus voting strategy automatically adapts the voting to diffeerent component reliability and output space cardinality characteristics. It is shown that absolute majority voting strategy provides a lower bound on the reliability provided by the consensus majority, and the 2-of-n voting strategy an upper bound. If r is the cardinality of output space it is proved that 1/r is a lower bound on the average reliability of fault-tolerant system components below which the system reliability begins to deteriorate as more versions are added.

Mcallister, David F.↗

Impact of coverage on the reliability of a fault tolerant computer

A mathematical reliability model is established for a reconfigurable fault tolerant avionic computer system utilizing state-of-the-art computers. System reliability is studied in light of the coverage probabilities associated with the first and second independent hardware failures. Coverage models are presented as a function of detection, isolation, and recovery probabilities. Upper and lower bonds are established for the coverage probabilities and the method for computing values for the coverage probabilities is investigated. Further, an architectural variation is proposed which is shown to enhance coverage.

Bavuso, S. J.↗

Integrated Reliability and Economic Modeling for Transmission Across Large Regions: A Space Odyssey

Power flow modeling and stability analysis are needed to more-comprehensively assess system reliability but the development of the system portfolios and conditions require use of economic models (e.g., production cost). What are the state of art methods for efficiently linking economic and reliability models to enable examination of multiple snapshots and perform detailed nodal analyses?

24 POWER TRANSMISSION AND DISTRIBUTION↗

The SYSGEN user package

The user documentation of the SYSGEN model and its links with other simulations is described. The SYSGEN is a production costing and reliability model of electric utility systems. Hydroelectric, storage, and time dependent generating units are modeled in addition to conventional generating plants. Input variables, modeling options, output variables, and reports formats are explained. SYSGEN also can be run interactively by using a program called FEPS (Front End Program for SYSGEN). A format for SYSGEN input variables which is designed for use with FEPS is presented.

Carlson, C. R.↗

Modeling of turbulence and transition

The first objective is to evaluate current two-equation and second order closure turbulence models using available direct numerical simulations and experiments, and to identify the models which represent the state of the art in turbulence modeling. The second objective is to study the near-wall behavior of turbulence, and to develop reliable models for an engineering calculation of turbulence and transition. The third objective is to develop a two-scale model for compressible turbulence.

Shih, Tsan-Hsing↗

Surface Instability of Liquid Propellants in Microgravity During Pulsed Settling Operations

Pulsing reaction control system (RCS) thrusters, vent valves, or other propulsion devices can preserve propellant resources in space, but this operation also effectively introduces a vibration to the vehicle. When the vibration is perpendicular to the liquid propellant surface, Faraday waves may be generated at the liquid-vapor interface. These Faraday instabilities can perturb or break up the liquid surface of cryogenic tanks, leading to inefficiencies in thermal management or even ullage collapse. Drawing from theory and experiments, an engineering model defining the allowable design regions for pulsed settling in microgravity was assembled and verified with computational fluid dynamics (CFD) simulations. A traditional settling metric, the Bond number, was also overlaid in the model to indicate which duty cycles were insufficient to overcome surface tension and aggregate propellant. Mission planners and engineers can consult the tool to rapidly evaluate the stability of a liquid-vapor interface given the pulse frequency and the excitation acceleration. Expressions developed for Faraday waves induced by a sinusoidal forcing input at standard gravity were found to provide excellent predictive capabilities for pulsed, or rectangular, waveforms in the absence of a consistent gravitational acceleration. This study extends the usage of these equations to an alternative forcing function and microgravity environments for the purpose of estimating natural frequencies, surface mode shapes, surface wave amplitudes, and the onset of droplet ejection. CFD simulations with the Loci/STREAM-VoF (Volume of Fluid) solver were initially validated against experimental results in standard gravity. Discrete points on the design map were then investigated with CFD and confirmed that the engineering model reliably indicates surface stability and most Faraday wave characteristics without requiring higher-fidelity tools. The engineering model is highly extensible and can be adapted for various propellant fill fractions, fluid properties, and tank sizes.

Faraday Waves↗

Surface Instability of Liquid Propellants in Microgravity During Pulsed Settling Operations

Pulsing reaction control system (RCS) thrusters, vent valves, or other propulsion devices can preserve propellant resources in space, but this operation also effectively introduces a vibration to the vehicle. When the vibration is perpendicular to the liquid propellant surface, Faraday waves may be generated at the liquid-vapor interface. These Faraday instabilities can perturb or break up the liquid surface of cryogenic tanks, leading to inefficiencies in thermal management or even ullage collapse. Drawing from theory and experiments, an engineering model defining the allowable design regions for pulsed settling in microgravity was assembled and verified with computational fluid dynamics (CFD) simulations. A traditional settling metric, the Bond number, was also overlaid in the model to indicate which duty cycles were insufficient to overcome surface tension and aggregate propellant. Mission planners and engineers can consult the tool to rapidly evaluate the stability of a liquid-vapor interface given the pulse frequency and the excitation acceleration. Expressions developed for Faraday waves induced by a sinusoidal forcing input at standard gravity were found to provide excellent predictive capabilities for pulsed, or rectangular, waveforms in the absence of a consistent gravitational acceleration. This study extends the usage of these equations to an alternative forcing function and microgravity environments for the purpose of estimating natural frequencies, surface mode shapes, surface wave amplitudes, and the onset of droplet ejection. CFD simulations with the Loci/STREAM-VoF (Volume of Fluid) solver were initially validated against experimental results in standard gravity. Discrete points on the design map were then investigated with CFD and confirmed that the engineering model reliably indicates surface stability and most Faraday wave characteristics without requiring higher-fidelity tools. The engineering model is highly extensible and can be adapted for various propellant fill fractions, fluid properties, and tank sizes.

Faraday Waves↗

Software reliability studies

There are many software reliability models which try to predict future performance of software based on data generated by the debugging process. Our research has shown that by improving the quality of the data one can greatly improve the predictions. We are working on methodologies which control some of the randomness inherent in the standard data generation processes in order to improve the accuracy of predictions. Our contribution is twofold in that we describe an experimental methodology using a data structure called the debugging graph and apply this methodology to assess the robustness of existing models. The debugging graph is used to analyze the effects of various fault recovery orders on the predictive accuracy of several well-known software reliability algorithms. We found that, along a particular debugging path in the graph, the predictive performance of different models can vary greatly. Similarly, just because a model 'fits' a given path's data well does not guarantee that the model would perform well on a different path. Further we observed bug interactions and noted their potential effects on the predictive process. We saw that not only do different faults fail at different rates, but that those rates can be affected by the particular debugging stage at which the rates are evaluated. Based on our experiment, we conjecture that the accuracy of a reliability prediction is affected by the fault recovery order as well as by fault interaction.

Hoppa, Mary Ann↗

Ion Storage Ring Measurements of Low Temperature Dielectronic Recombination Rate Coefficients for Modeling X-Ray Photoionized Cosmic Plasmas

Low temperature dielectronic recombination (DR) is the dominant recombination mechanism for most ions in X-ray photoionized cosmic plasmas. Reliably modeling and interpreting spectra from these plasmas requires accurate low temperature DR rate Coefficients. Of particular importance are the DR rate coefficients for the iron L-shell ions (Fe XVII-Fe XXIV). These ions are predicted to play an important role in determining the thermal structure and line emission of X-ray photoionized plasmas, which form in the media surrounding accretion powered sources such as X-ray binaries (XRBs), active galactic nuclei (AGN), and cataclysmic variables (Savin et al., 2000). The need for reliable DR data of iron L-shell ions has become particularly urgent after the launches of Chandra and XMM-Newton. These satellites are now providing high-resolution X-ray spectra from a wide range of X-ray photoionized sources. Interpreting the spectra from these sources requires reliable DR rate coefficients. However, at the temperatures relevant, for X-ray photoionized plasmas, existing theoretical DR rate coefficients can differ from one another by factors of two to orders of magnitudes.

Savin, D. W.↗

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗

Foundational Research for Fusion Systems Safety Assessment Overview

Presentation detailing work package to develop comprehensive fusion device safety models over the course of the next three years, including references to a blanket, divertor and magnet design, and statistical reliability models

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimization of Debris Shields on the NISAR Mission’s L-Band Radar Instrument

The NASA-ISRO Synthetic Aperture Radar (NISAR) space mission is a collaboration between NASA and the Indian Space Research Organization (ISRO), launching in the 2020s to a polar orbit of 747km altitude. The mission will provide spatial and temporal measurements of land surface changes (e.g. ice sheets, vegetation, earthquakes). Many of the SAR electronics boxes are mounted on the exterior of the structure. Their singlewall box lids efficiently radiate heat for thermal control, but are not very efficient debris shields. The initial design showed an unacceptably high impact risk as estimated with NASA’s ORDEM3 debris model and Bumper impact analysis tool. Each box has a different role in instrument functionality, and this was captured in a reliability model used to optimize the distribution of shield mass among the boxes: total added mass was minimized while maintaining a threshold of functionality and survival probability that was acceptable to the project.

Chinn, James Z.↗

Space reliability technology - A historical perspective

The progressive improvements in reliability of launch vehicles is traced from the Vanguard rocket to the STS. The Vanguard, built with minimal redundancy and a high mass ratio, was used as an operational vehicle midway through its test program in an attempt to meet the perceived challenge represented by the Sputnik. The fourth Vanguard failed due to inadequate contamination prevention and lack of inspection ports. Automatic firing sequences were adopted for the Titan rockets, which were an order of magnitude larger than the Vanguard and therefore had room for interior inspections. Qualification testing and reporting were introduced for components, along with X ray inspection of fuel tank welds. Dual systems were added for flight critical components when the Titan became man-rated for the Gemini program. Designs incorporated full failure mode effects and criticality analyses for the Apollo program, which exposed the limits of applicability of numerical reliability models. Fault tree analyses and program milestone reviews were initiated. The worth of man-in-the-loop in space activities for reliability was demonstrated with the rescue of Skylab after solar panel and meteoroid shield failures. It is now the reliability of the payload, rather than the vehicle, that is questioned for Shuttle launches.

Cohen, H.↗