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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

An Overview of the NASA Advanced Composites Consortium High Energy Dynamic Impact Phase II Technical Path

Advanced composite structures are increasingly becoming the norm for use in military and commercial aircraft. Many of these structures are in places that are prone to high energy dynamic impact (HEDI) such as a wing or fuselage structures subjected to bird strike or a fan blade out event. Certification testing is expensive and industry currently lacks to the tools to perform reliable certification by analysis or smarter testing. As such, the NASA Advanced Composites Consortium HEDI team was formed with representatives from aerospace original equipment manufacturers, government research laboratories, and academia to advance the state-of-the-art in emerging progressive damage and failure analysis (PDFA) methods in a two phase program. These PDFA approaches have the ability to predict ply-by-ply level damage in composite structures, but to date, have not been thoroughly vetted for HEDI events. In this paper, the technical path that is used in Phase II of the program is presented.

Justusson, Brian↗
NASA NTRS2021

Reliability and Safety Assessment of Urban Air Mobility Concept Vehicles

The primary objective of this research effort is to identify failure modes and hazards associated with several configurations of multicopter concept vehicles supplied by NASA. Functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) are performed for each of the eight vehicle configurations under review. Conceptual design of notional powertrain configurations (turboshaft, electric, hybrid electric), notional thrust control systems (rpm control and collective control), and navigation control systems for the concept vehicles were to support the reliability and safety analysis and to assess whether a mission can be completed safely. Two kinds of analyses are performed: static safety analysis which enable the quantification of the likelihood of individual events, and dynamic safety analyses which allows the investigation of multiple time-dependent failures. Their objective is to quantify the likelihood of catastrophic failures.

Urban Air Mobility↗
NASA NTRS2023

Assessment of Electrical, Electronic, and Electromechanical (EEE) Parts Copper Wire Bonds for Space Programs

The NASA Electronic Parts and Packaging Program co-manager, requested the NASA Engineering and Safety Center (NESC) to compile a body of publicly available knowledge on copper (Cu) wire bonds and perform reliability testing and analysis on these bonds, including environment tests, sample destructive physical analysis, and bond pull/shear tests during environment test intervals. The goal was to understand the risks of using Cu wire bonds for space applications and develop guidelines on Cu bond pull/shear limits for NASA applications. This document contains the results of the NESC assessment.

Electrical, Electronic, and Electromechanical↗
DOE OSTI2026

Validation of the DESI DR2 Ly$α$ forest full-shape analysis

We present the validation of the Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2) Lyman-$α$ (Ly$α$) forest full-shape analysis. This analysis combines three-dimensional Ly$α$ forest auto-correlations and cross-correlations with quasars to extract information from both the baryon acoustic oscillation (BAO) feature and the broadband clustering signal, with primary emphasis on the Alcock-Paczynski (AP) measurement. Compared to the DESI DR1 analysis, the DR2 validation uses substantially larger and more realistic mock datasets, including CoLoRe 2LPT and AbacusSummit Ly$α$ forest simulations. The modeling framework is also improved through analytic marginalization over small scales ($<10$$h^{-1}$Mpc) and the impact of ultraviolet background fluctuations. The validation program was completed prior to unblinding and defines quantitative requirements for the cosmological parameters of interest, which are evaluated using hundreds of mock realizations. We further test the analysis through independent fits to the auto- and cross-correlations, multiple catalog splits, and a broad suite of analysis and modeling variations applied to both mocks and blinded observational data. We find that the BAO and AP parameters satisfy all validation requirements and remain stable across all tests. In contrast, mock studies reveal a significant bias in the inferred growth-rate parameter $fσ_8$, leading us to exclude this measurement from the final analysis. The consistency across mocks, data splits, and robustness tests demonstrates that the DR2 Ly$α$ full-shape analysis provides a reliable and substantially improved broadband AP measurement over previous Ly$α$ forest studies.

Herbold, M. [Chicago U., KICP; Ohio State U.] (ORC↗
NASA NTRS2017

Reliably Detectable Flaw Size for NDE Methods that Use Calibration

Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh1823 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

Koshti, Ajay M.↗
DOE OSTI2024

Sensitivity of fatigue reliability in wind turbines: effects of design turbulence and the Wöhler exponent

Fatigue assessment of wind turbines involves three main sources of uncertainty: material resistance, load, and the damage accumulation model. Many studies focus on increasing the accuracy of fatigue load assessment to improve the fatigue reliability. Probabilistic modeling of the wind's turbulence standard deviation is an example of an approach used for this purpose. Editions 3 and 4 of the IEC standard for the design of wind energy generation systems (IEC 61400-1) suggest different probability distributions as alternatives for the representative turbulence in the normal turbulence model (NTM) of edition 1. There are debates on whether the suggested distributions provide conservative reliability levels, as the established design safety factors are calibrated based on the representative turbulence approach. The current study addresses the debate by comparing annual reliability based on different scenarios of NTM using a probabilistic approach. More importantly, it elaborates on the relative importance of load assessment accuracy in defining the fatigue reliability. Using the DTU 10 MW reference wind turbine and the first-order reliability method (FORM), we study the changes in the annual reliability level and its sensitivity to the three main random inputs. We perform the study considering the blade root flapwise and the tower base fore–aft moments, assuming different fatigue exponents in each load channel. The results show that integration over distributions of turbulence in each mean wind speed results in less conservative annual reliability levels than representative turbulence. The difference in the reliability levels varies according to turbulence distribution and the fatigue exponent. In the case of the tower base, the difference in the annual reliability index after 20 years can be up to 50 %. However, the model and material uncertainty have much higher effects on the reliability levels compared to load uncertainty. Knowledge about such differences in the reliability levels due to the choice of turbulence distribution is especially important, as it impacts the extent of lifetime extension through reliability reassessments.

17 WIND ENERGY↗
NASA NTRS1986

Management of SSME hardware life utilization

Statistical and probabilistic reliability methodologies were developed for the determination of hardware life limits for the Space Shuttle Main Engine (SSME). Both methodologies require that a mathematical reliability model of the engine (system) performance be developed as a function of the reliabilities of the components and parts. The system reliability model should be developed from the Failute Modes and Effects Analysis/Critical Items List. The statistical reliability methodology establishes hardware life limits directly from the failure distributions of the components and parts obtained from statistically-designed testing. The probabilistic reliability methodology establishes hardware life limits from a decision analysis methodology which incorporates the component/part reliabilities obtained from a probabilistic structural analysis, a calibrated maintenance program, inspection techniques, and fabrication procedures. Probilistic structural analysis is recommended as a tool to prioritize upgrading of the components and parts. The Weibull probability distribution is presently being investigated by NASA/MSFC to characterize the failure distribution of the SSME hardware from a limited data base of failures.

Pauschke, J. M.↗
NASA NTRS2000

Software Released by LEWICE 2.0 Ice Accretion Software Development Project

Computational icing simulation methods are making the transition from the realm of research to commonplace use in design and certification. As such, standards of software management, design, validation, and documentation must be adjusted to accommodate the increased expectations of the user community with respect to accuracy, reliability, capability, and usability. With this in mind, in collaboration with Glenn's Engineering Design and Analysis Division, the Icing Branch of the NASA Glenn Research Center at Lewis Field began a software improvement project focused on the two-dimensional ice accretion simulation tool LEWICE. This project is serving as an introduction to the concepts of software management and is intended to serve as a pilot project for future icing simulation code development. The LEWICE 2.0 Software Development Project consisted of two major elements: software management and software validation. The software management element consisted of identifying features of well-designed and well-managed software that are appropriate for an analytical prediction tool such as LEWICE and applying them to a revised version of the code. This element included tasks such as identification of software requirements, development and implementation of coding standards, and implementation of software revision control practices. With the application of these techniques, the LEWICE ice accretion code became a more stable and reliable software product. In addition, the lessons learned about software development and maintenance can be factored into future software projects at the outset. The software validation activity was an integral part of our effort to make LEWICE a more accurate and reliable analysis tool. Because of the efforts taken to extensively validate this software, LEWICE 2.0 is more robust than previous releases and can reproduce results accurately across several computing platforms. It also differs from previous versions in the extensive quantitative comparisons of its results with a data base of ice shapes that were generated in Glenn's Icing Research Tunnel. The results of the shape comparisons were analyzed to determine the range of meteorological conditions under which LEWICE 2.0 is within the repeatability found for ice shapes obtained from experiments. These comparisons show that the average variation of LEWICE 2.0 from experimental data is 7.2 percent, whereas the overall variability of the experimental data is 2.5 percent. The LEWICE 2.0 Software Development Project resulted in the release, at the recent Icing Branch LEWICE Workshop, of a more useful and robust analysis tool than was previously available to the icing community. The lessons learned from this project will be applied to the Icing Branch s future software development efforts.

Potapczuk, Mark G.↗
NASA NTRS1992

Sensitivity of wildlife habitat models to uncertainties in GIS data

Decision makers need to know the reliability of output products from GIS analysis. For many GIS applications, it is not possible to compare these products to an independent measure of 'truth'. Sensitivity analysis offers an alternative means of estimating reliability. In this paper, we present a CIS-based statistical procedure for estimating the sensitivity of wildlife habitat models to uncertainties in input data and model assumptions. The approach is demonstrated in an analysis of habitat associations derived from a GIS database for the endangered California condor. Alternative data sets were generated to compare results over a reasonable range of assumptions about several sources of uncertainty. Sensitivity analysis indicated that condor habitat associations are relatively robust, and the results have increased our confidence in our initial findings. Uncertainties and methods described in the paper have general relevance for many GIS applications.

Stoms, David M.↗
NASA NTRS1996

Methodology for Physics and Engineering of Reliable Products

Physics of failure approaches have gained wide spread acceptance within the electronic reliability community. These methodologies involve identifying root cause failure mechanisms, developing associated models, and utilizing these models to inprove time to market, lower development and build costs and higher reliability. The methodology outlined herein sets forth a process, based on integration of both physics and engineering principles, for achieving the same goals.

failure analysis electronics reliability PACT (pre↗
NASA NTRS1987

Advanced probabilistic method of development

Advanced structural reliability methods are utilized on the Probabilistic Structural Analysis Methods (PSAM) project to provide a tool for analysis and design of space propulsion system hardware. The role of the effort at the University of Arizona is to provide reliability technology support to this project. PSAM computer programs will provide a design tool for analyzing uncertainty associated with thermal and mechanical loading, material behavior, geometry, and the analysis methods used. Specifically, reliability methods are employed to perform sensitivity analyses, to establish the distribution of a critical response variable (e.g., stress, deflection), to perform reliability assessment, and ultimately to produce a design which will minimize cost and/or weight. Uncertainties in the design factors of space propulsion hardware are described by probability models constructed using statistical analysis of data. Statistical methods are employed to produce a probability model, i.e., a statistical synthesis or summary of each design variable in a format suitable for reliability analysis and ultimately, design decisions.

Wirsching, P. H.↗
DOE OSTI2024

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↗
DOE OSTI2025

Reliable Integration of AI Data Centers at Scale – Analysis, Modeling and Synthetic Data Generation

This report analyzes the power consumption of large dynamic digital loads using the open-source MIT supercloud and SURF datasets. With an emphasis on the MIT data, we calculate important power consumption characteristics to help system operators improve generation planning and resource allocation. We also introduce a rudimentary model for generating synthetic load profiles.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Space Station Freedom power - A reliability, availability, and maintainability assessment of the proposed Space Station Freedom electric power system

A preliminary reliability, availability, and maintainability (RAM) analysis of the proposed Space Station Freedom electric power system (EPS) was performed using the unit reliability, availability, and maintainability (UNIRAM) analysis methodology. Orbital replacement units (ORUs) having the most significant impact on EPS availability measures were identified. Also, the sensitivity of the EPS to variations in ORU RAM data was evaluated for each ORU. Estimates were made of average EPS power output levels and availability of power to the core area of the space station. The results of assessments of the availability of EPS power and power to load distribution points in the space stations are given. Some highlights of continuing studies being performed to understand EPS availability considerations are presented.

Turnquist, S. R.↗
NASA NTRS1999

Probabilistic Analysis of Aircraft Gas Turbine Disk Life and Reliability

Two series of low cycle fatigue (LCF) test data for two groups of different aircraft gas turbine engine compressor disk geometries were reanalyzed and compared using Weibull statistics. Both groups of disks were manufactured from titanium (Ti-6Al-4V) alloy. A NASA Glenn Research Center developed probabilistic computer code Probable Cause was used to predict disk life and reliability. A material-life factor A was determined for titanium (Ti-6Al-4V) alloy based upon fatigue disk data and successfully applied to predict the life of the disks as a function of speed. A comparison was made with the currently used life prediction method based upon crack growth rate. Applying an endurance limit to the computer code did not significantly affect the predicted lives under engine operating conditions. Failure location prediction correlates with those experimentally observed in the LCF tests. A reasonable correlation was obtained between the predicted disk lives using the Probable Cause code and a modified crack growth method for life prediction. Both methods slightly overpredict life for one disk group and significantly under predict it for the other.

Melis, Matthew E.↗
NASA NTRS2008

FAA Development of Reliable Modeling Methodologies for Fan Blade Out Containment Analysis: Ballistic Impact Testing - Part 2

This report summarizes the ballistic impact testing that was conducted to provide validation data for the development of numerical models of blade out events in fabric containment systems. The ballistic impact response of two different fiber materials - Kevlar 49 (E.I. DuPont Nemours and Company) and Zylon AS (Toyobo Co., Ltd.) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation and velocity of the projectile were varied and recorded. In most cases the tests were designed such that the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models for predicting the response of fabrics under conditions simulating those of a jet engine blade release situations. In addition some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different materials.

Revilock, Duane M.↗
NASA NTRS2003

Thermo-Mechanical Modeling and Analysis for Turbopump Assemblies

Life, reliability, and cost are strongly impacted by steady and transient thermo-mechanical effect. Design cycle can suffer big setbacks when working a transient stress/deflection issue. Balance between objectives and constrains is always difficult. Requires assembly-level analysis early in the design cycle.

Platt, Mike↗
NASA NTRS1978

Data analysis of the LPSP experiment on OSO-8

The first and statistically most reliable step in the data analysis - the computation of the vertical phase lag between photospheric and chromospheric oscillations - was completed. Unfortunately, the error associated with this calculated phase lag is so great that the result has no physical significance. Since the subsequent data analysis that was originally planned would have much larger associated errors, it was concluded that the data available is insufficient to allow any meaningful results to be derived. Accordingly, the project was terminated. The reasons for the failure of the data are discussed. There are two basic reasons for this failure; (1) the very low signal to noise ratio of the raw data, and (1) the small statistical sample that resulted from the very small number of usable orbits. The final phase of data analysis is described. Finally, some comments and recommendations of a general nature are made concerning this entire contract effort. It is hoped that at least some lessons can be learned from this particular Guest Investigator project, so that future Guest Investigator programs can be pursued more effectively, and with less risk.

Frazier, E. N.↗