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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 NTRS1985

A review of fracture mechanics life technology

Current lifetime prediction technology for structural components subjected to cyclic loads was reviewed. The central objectives of the project were to report the current state of and recommend future development of fracture mechanics-based analytical tools for modeling and forecasting subcritical fatigue crack growth in structures. Of special interest to NASA was the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. A survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology were conducted. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include: development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Thomas, J. M.↗
NASA NTRS1986

A review of fracture mechanics life technology

Lifetime prediction technology for structural components subjected to cyclic loads is examined. The central objectives of the project are: (1) to report the current state of the art, and (2) recommend future development of fracture mechanics-based analytical tools for modeling subcritical fatigue crack growth in structures. Of special interest is the ability to apply these tools to practical engineering problems and the developmental steps necessary to bring vital technologies to this stage. The authors conducted a survey of published literature and numerous discussions with experts in the field of fracture mechanics life technology. One of the key points made is that fracture mechanics analyses of crack growth often involve consideration of fatigue and fracture under extreme conditions. Therefore, inaccuracies in predicting component lifetime will be dominated by inaccuracies in environment and fatigue crack growth relations, stress intensity factor solutions, and methods used to model given loads and stresses. Suggestions made for reducing these inaccuracies include development of improved models of subcritical crack growth, research efforts aimed at better characterizing residual and assembly stresses that can be introduced during fabrication, and more widespread and uniform use of the best existing methods.

Besuner, P. M.↗
NASA NTRS1985

Preliminary study: Moisture-polymer interaction. Stuby objectives

The problems associated with mathematically modeling water-module interaction phenomena, including sorption and desorption, diffusion, and permeation are discussed. With reliable analytical models, an extensive materials data base, and solar radiation surface meteorological observations (SOLMET) weather data, predicting module lifetimes in realistic environments can become a practical reality. The status of the present techniques of simulating the various transport mechanisms was reported. The Dent model (a modified Brunauer-Emmet-Teller) approach represented polyvinyl butyral (PVB) sorption data. A 100-layer material model and Fick's diffusion model gave diffusivity values exhibiting adequate agreement with those measured for PVB. Diffusivity of PVB is concentration dependent, decreasing as the water content in PVB increases. The temperature dependence of diffusion in PVB is well modeled by the Arrhenius rate equation. Equilibrium conductivity and leakage current data are well represented by Hearle's model for bulk ionic conductivity. A nodal network analysis using the Systems Improved Numerical Differencing Analyzer (SINDA) Thermal Analyzer gave reasonable correlation with measurable data. It is concluded that realistic lifetime predictions seem to be feasible.

Wen, L. C.↗
DOE OSTI2025

Damage modeling of power tower receiver tubes using the SRLIFE tool

Concentrating Solar Power (CSP) molten-salt central receivers are subject to high, transient incident flux during daily operation. The resulting creep-fatigue damage impacts the receiver’s reliability and restricts the permissible incident flux distribution for a given receiver. This paper aims to reduce CSP plants’ levelized cost of electricity by developing a methodology to predict lifetime and identifies the primary damage mechanism (creep vs fatigue) for any given fluid temperature and temperature gradient. Results are presented in the form of a damage map that serves as a valuable operation guide and design tool. Damage maps can be used to reduce maintenance costs by improving reliability and reduce receiver capital costs by better utilizing the receiver area. FEA simulation and damage modeling of tubes subject to asymmetrical flux conditions is performed in the open-source receiver design tool srlife. Parametric studies are performed over a range of inner tube temperatures and thermal gradients for A230, 316H, 740H, A282, A617, and 800H high temperature alloys. Damage maps are presented for each alloy. A parametric, FEA-based methodology is presented for comparison of fatigue-creep ratios and prediction of tube lifetime based on the critical thermal operating conditions. Fatigue is found to be negligible compared to creep for almost every case. Here, this finding suggests that fatigue effects associated with cloud events are insignificant compared to creep at these high temperature operating conditions. Additionally, lifetime predictions identify thermal conditions where small changes in operating conditions can result in large changes in predicted lifetime.

14 SOLAR ENERGY↗
DOE OSTI2022

High energy X-ray diffraction and small-angle scattering measurements of hydrogen fatigue damage in AISI 4130 steel

Accurate lifetime predictions are critical for repurposing existing pipelines for hydrogen transmission as well as for developing novel steels which are minimally susceptible to lifetime degradation by hydrogen. Ultimately, lifetime prediction models assess the amount of damage a material undergoes during a typical service cycle and the cumulative damage a material can withstand prior to failure. However, not all damage processes are equal, and neither is the manner in which mechanical loading translates to damage the same when materials are in inert environments compared to in hydrogen environments. For example, in the three leading proposed mechanisms of hydrogen embrittlement (Hydrogen-Enhanced Decohesion (HEDE), the Hydrogen-Enhanced Localized Plasticity (HELP), and the Nano-Void Coalescence (NVC)), hydrogen is proposed to enhance the manifestation of grain separation, dislocation generation/movement, and void coalescence, respectively. A full understanding of the damage modes requires a measurement capable of probing all three mechanisms at once. Here we present simultaneous High Energy X-ray Diffraction (HEXRD) and Small-Angle X-ray Scattering (SAXS) during fatiguing of steel in hydrogen. HEXRD measurements probe strain and dislocation density; SAXS measurements probe nano-pore generation and coalescence. We will discuss the differences in damage modes between steels fatigued in air and in hydrogen and the role these difference play in lifetime predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Long-Term Creep-Rupture Behavior of Alloy Inconel 740/740H

To explore potential application of Ni-based alloys for power generation at the higher temperatures and pressures needed to achieve high thermal to electrical-energy conversion efficiency, an extensive creep-rupture dataset covering up to 875 °C and almost 70,000 h for Inconel 740/740H was analyzed using Larson–Miller parameter and Wilshire approaches. The results were used to assess the relative effectiveness of the two analytical methods, both in describing the experimental data and, because of the breadth of the dataset, using analyses of its shorter-time data to make creep lifetime predictions for much more extended times, which were then directly compared to the measured rupture times. The respective methods were also used to predict creep-limited lifetimes relevant to power production (that is, 100,000 h or greater). Despite the complexity of the precipitation-strengthened Inconel 740/740H alloy and the generalized parametric approach of these methodologies, the predictions based on such were reasonably accurate when the entire dataset was analyzed. However, when the analysis was confined to only data for conditions yielding creep-rupture times < 5,000 h( about 65 % of the entire dataset), the Wilshire correlation yielded better prediction for longer time lifetimes due to the inherent instability of the specific Larson–Miller formalism used in this analysis when extrapolated significantly outside its analysis range.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Predictive Battery Lifetime Modeling at the National Renewable Energy Laboratory

Overview of the development of algebraic battery lifetime modeling efforts within NREL's Electrochemical Energy Storage group within the Energy Conversion and Storage Systems Center. Traditional approaches to developing battery lifetime models are compared with a new methodology incorporating machine learning to autonomously identify parsimonious model equations.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing

The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.

high-performance computing↗
DOE OSTI2025

An accelerated framework for predicting creep rupture lifetimes in engineering alloys

Confidently predicting high-temperature deformation, including creep and creep rupture, is paramount for the design and commercialization of candidate materials for advanced nuclear energy systems. To accelerate creep quantification, we introduce a framework that enables rapid, cost-effective, and reliable prediction of creep rupture lifetimes, minimizing reliance on time-intensive bulk creep testing. Unlike conventional creep analysis, which requires extensive time and resources, our method leverages a maximum of four short-term bulk creep tests as training data for prediction. This framework combines high-throughput nanoindentation up to 700 °C with these targeted bulk tests to inform our creep rupture model in order to predict rupture lifetimes. The strong agreement between our predictions and conventional experimental data demonstrates the effectiveness of our approach for accelerated creep analysis and lifetime prediction of structural components in high-temperature applications. Our multi-pronged approach motivates further integration of computational tools and advanced instrumentation to establish a universal framework for understanding high-temperature material responses.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spatiotemporal Learning in Power Modules: Wavelet-Enhanced Forecasting of Thermomechanical Degradation

Detecting internal defects in power electronics packages is critical for their performance and reliability, especially under extreme operating conditions, as these defects can lead to catastrophic failure if not properly addressed. Confocal scanning acoustic microscopy (C-SAM) plays a key role in the nondestructive evaluation of bond layer degradation within a power electronics package by detecting defects such as delamination, voids, and cracks. However, accurately quantifying and predicting these defects from C-SAM images remains a significant challenge due to the low noise-to-signal ratio, which typically arises from both imaging process and bond patterns itself. In this paper, we explore machine learning strategies for processing C-SAM images and providing predictive models of defect growth. We use C-SAM images of sintered copper and sintered silver samples, which are obtained under accelerated thermal experiments, as the representative dataset for our study. We investigate the effect of Fourier transforms and wavelet transforms on these datasets to remove high-frequency noise and address noise across multiple scales with histogram equalization to enhance the contrast and improve the visibility of defects. As a result, defect boundaries can be clearly distinguished, enabling more accurate tracking of their growth over time. We then employ different time-series forecasting algorithms on the denoised images to formulate an image-based lifetime prediction model. Statistical models and deep-learning techniques are trained on images obtained in the early stages of thermal shock, and defect growth in the later stages is predicted. Our work serves as a preliminary attempt to improve the accuracy of lifetime prediction models of power electronics packages, which is critical under extreme operating environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Probabilistic Prediction of Lifetimes of Ceramic Parts

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Nemeth, Noel N.↗
DOE OSTI2021

Predictive Battery Lifetime Modeling at NREL [Slides]

Battery lifetime models are used to extrapolate data from accelerated aging tests to simulate degradation in real-world applications such as electric vehicles and battery energy storage systems. Methods developed at NREL utilize both expert domain-knowledge and machine-learning to identify models, using statistical methods such as cross-validation and bootstrap resampling to interrogate model performance and quantify uncertainty. These models can be utilized in systems level simulations to predict battery performance or technoeconomic models to estimate the lifetime cost of battery systems.

25 ENERGY STORAGE↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1991

Design of the solid cryogen dewar for the Near-Infrared Camera and Multi-Object Spectrometer

A multipurpose, second-generation HST instrument for imaging and spectroscopy in the 1 to 2.5 microns wavelength region is being developed. The Near-Infrared Camera Multi-Object Spectrometer (NICMOS) is unique since it is the only HST instrument operating in the NIR and cryogenically cooled. The NICMOS detector arrays are cooled to 58 K by a solid-nitrogen (SN2) dewar with a predicted lifetime of nearly five years. To obtain this long lifetime, a hybrid cooling approach using thermoelectric coolers (TECs) is employed to reduce the parasitic heat load on the SN2. The design features used to promote long life, the predicted lifetime improvements provided by the TECs, and the performance degradation in the event of TEC failure(s) are discussed.

Oonk, Rodney L.↗
NASA NTRS2015

Accelerated Test Method for Corrosion Protective Coatings Project

This project seeks to develop a new accelerated corrosion test method that predicts the long-term corrosion protection performance of spaceport structure coatings as accurately and reliably as current long-term atmospheric exposure tests. This new accelerated test method will shorten the time needed to evaluate the corrosion protection performance of coatings for NASA's critical ground support structures. Lifetime prediction for spaceport structure coatings has a 5-year qualification cycle using atmospheric exposure. Current accelerated corrosion tests often provide false positives and negatives for coating performance, do not correlate to atmospheric corrosion exposure results, and do not correlate with atmospheric exposure timescales for lifetime prediction.

Technology Portfolio System↗