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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 19 records

Effect of Roller Profile on Cylindrical Roller Bearing Life Prediction: Comparison of Bearing Life Theories - Part 1

Four rolling-element bearing life theories were chosen for analysis and compared for a simple roller-race geometry model. The life theories were those of Weibull; Lundberg and Palmgren; Ioannides and Harris; and Zaretsky. The analysis without a fatigue limit of Ioannides and Harris is identical to the Lundberg and Palmgren analysis, and the Weibull analysis is similar to that of Zaretsky if the exponents are chosen to be identical. The resultant predicted life a each stress condition not only depends on the life equation used but also on the Weibull slope assumed. The least variation in predicted life with Weibull slope comes with the Zaretsky equation. Except for a Weibull slope of 1.11, at which the Weibull equation predicts the highest lives, the highest lives are predicted for the Zaretsky equation. For Weibull slopes of 1.5 and 2, both the Lundherg-Palmgren and Ioannides-Harris (where tau(sub u) = 0) equations predict lower lives than the ANSI/ABMA/ISO standard. Based upon the Hertz stresses for line contact, the accepted load-life exponent of 10/3 results in a maximum Hertz stress-life exponent equal to 6.6. This value is inconsistent with that experienced in the field. The assumption of as shear stress fatigue limit tau(sub u) results in Hertz stress-life exponents greater than are experimentally verifiable.

Poplawski, Joseph V.↗

Methodology for designing accelerated aging tests for predicting life of photovoltaic arrays

A methodology for designing aging tests in which life prediction was paramount was developed. The methodology builds upon experience with regard to aging behavior in those material classes which are expected to be utilized as encapsulant elements, viz., glasses and polymers, and upon experience with the design of aging tests. The experiences were reviewed, and results are discussed in detail.

Gaines, G. B.↗

Life Predicted in a Probabilistic Design Space for Brittle Materials With Transient Loads

Analytical techniques have progressively become more sophisticated, and now we can consider the probabilistic nature of the entire space of random input variables on the lifetime reliability of brittle structures. This was demonstrated with NASA s CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code combined with the commercially available ANSYS/Probabilistic Design System (ANSYS/PDS), a probabilistic analysis tool that is an integral part of the ANSYS finite-element analysis program. ANSYS/PDS allows probabilistic loads, component geometry, and material properties to be considered in the finite-element analysis. CARES/Life predicts the time dependent probability of failure of brittle material structures under generalized thermomechanical loading--such as that found in a turbine engine hot-section. Glenn researchers coupled ANSYS/PDS with CARES/Life to assess the effects of the stochastic variables of component geometry, loading, and material properties on the predicted life of the component for fully transient thermomechanical loading and cyclic loading.

Nemeth, Noel N.↗

Characterization of Precipitation-Strengthening Heat-Resistant Austenitic Stainless Steels for Life-Prediction Modeling

In this study, the role of minor alloying additions in 347H stainless steels (UNS34709, ASTM A240/240M) on creep-rupture properties at 650-750°C and microstructure evolution during isothermal exposure at 750°C has been investigated, aiming to provide the experimental dataset as boundary conditions of physics-based modeling for material/component life prediction. Four different 347H heats containing various amounts of boron and nitrogen additions were prepared and evaluated. The combined additions of B and N are found to stabilize the strengthening secondary M23C6 carbides and retarding the transition from M23C6 to sigma phase precipitates during thermal exposure. The observed kinetics of microstructure evolution reasonably explains the improvement of creep-rupture properties of 347H stainless steels with the B and N additions.

Yamamoto, Yukinori↗

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗

Life-Prediction Parameters of Sapphire Determined for the Design of a Space Station Combustion Facility Window

To characterize the stress corrosion parameters and predict the life of a sapphire window being considered for use in the International Space Station's Fluids and Combustion Facility, researchers at the NASA Glenn Research Center conducted stress corrosion tests, fracture toughness tests, and reliability analyses, as shown in the figures. Standardized test methods, developed and updated by the author under the auspices of American Society for Testing and Materials, were employed. One interesting finding is that sapphire exhibits a susceptibility to stress corrosion in water similar to that of glass. In addition to generating the stress corrosion parameters and fracture toughness data, closed-form expressions for the variances of the crack growth parameters were derived. The expressions allow confidence bands to be easily placed on life predictions of ceramic components. Brittle materials such as sapphire and quartz are required for windows in a variety of applications such as the Fluids and Combustion Facility. To minimize the launch weight of such facilities, researchers must design the windows to be as lightweight as possible. The safe use of lightweight, brittle windows in structural applications is limited by two factors: low fracture toughness and slow crack growth, or stress corrosion. Stress corrosion of these and other optical materials can occur in relatively common environments, such as humid air. Access to the data has been requested by designers for use in the life prediction of a Northrop Grumman F16 instrument window and a Jet Propulsion Laboratory instrument window. One Space Act Agreement has been formed. Future work includes the measurement of the life of subscale windows.

Salem, Jonathan A.↗

Ceramic Matrix Composites (CMC) Life Prediction Method Development

Advanced launch systems (e.g., Reusable Launch Vehicle and other Shuttle Class concepts, Rocket-Based Combine Cycle, etc.), and interplanetary vehicles will very likely incorporate fiber reinforced ceramic matrix composites (CMC) in critical propulsion components. The use of CMC is highly desirable to save weight, to improve reuse capability, and to increase performance. CMC candidate applications are mission and cycle dependent and may include turbopump rotors, housings, combustors, nozzle injectors, exit cones or ramps, and throats. For reusable and single mission uses, accurate prediction of life is critical to mission success. The tools to accomplish life prediction are very immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for a variety of space propulsion applications. This paper describes an approach to satisfy the need to develop an integrated life prediction system for CMC that addresses mechanical durability due to cyclic and steady thermomechanical loads, and takes into account the impact of environmental degradation.

Levine, Stanley R.↗

Thrust chamber life prediction

The reusable life of the Space Shuttle main engine (SSME) is influenced by the cyclic life of the regeneratively liquid cooled main combustion chamber (MCC). During an operational duty cycle the MCC liner is subjected to a large transient thermal gradient that imparts a high thermal cyclic strain to the liner hot gas wall. Life predictions of such chambers have usually been based on low cycle fatigue (LCF) evaluations. Hot-fire testing, however, has shown significant mid-channel wall deformation and thinning during accrued cyclic testing. This phenomenon is termed cyclic creep and appears to be significantly accelerated at elevated temperatures. An analytical method that models the cyclic creep phenomenon and its application to thrust chamber life prediction is presented. The chamber finite element geometry is updated periodically to account for accrued wall thinning and distortion. Failure is based on the tensile instability failure criterion. Cyclic life results for several chamber life enhancing coolant channel designs are compared to the typically used LCF analysis that neglects cyclic creep. The results show that the usable cyclic creep life is approximately 30 to 50% of the commonly used LCF life.

Kasper, H. J.↗

Bat554: Machine Learning for Accelerated Life Prediction and Cell Design

This presentation describes work associated with the early prediction of life and failure modes using machine learning. Key areas which will be highlighted are the generation of synthetic data, the use of deep learning and other machine learning models and the use of machine learning to train life prediction models.

25 ENERGY STORAGE↗

Thermal barrier coating life prediction model development

In order to fully exploit thermal barrier coatings (TBCs) on turbine components and achieve the maximum performance benefit, the knowledge and understanding of TBC failure mechanisms must be increased and the means to predict coating life developed. The proposed program will determine the predominant modes of TBC system degradation and then develop and verify life prediction models accounting for those degradation modes. The successful completion of the program will have dual benefits: the ability to take advantage of the performance benefits offered by TBCs, and a sounder basis for making future improvements in coating behavior.

Hillery, R. V.↗

Effect of Load Rate on Tensile Strength of Various CFCCs at Elevated Temperatures: An Approach to Life Prediction Testing

Strength of three continuous fiber-reinforced ceramic composites, including SiC/CAS-11, SiC/MAS-5 and SiC/SiC, was determined as a function of test rate in air at 1100 - 1200 C. All three composite materials exhibited a strong dependency of strength on test rate, similar to the behavior observed in many advanced monolithic ceramics at elevated temperatures. The application of the preloading technique as well as the prediction of life from one loading configuration (constant stress-rate) to another (constant stress loading) suggested that the overall macroscopic failure mechanism of the composites would be the one governed by a power-law tyw of damage evolution/accumulation, analogous to slow crack growth commonly observed in advanced monolithic ceramics. It was further found that constant stress-rate testing could be used as an alternative to life prediction test methodology even for the composite materials at least for the short range of lifetime.

Choi, Sung R.↗

Thermal barrier coating life-prediction model development

Life predictions are made for two types of strain-tolerant and oxidation-resistant Thermal Barrier Coating (TBC) systems produced by commercial coating suppliers to the gas turbine industry. The plasma-sprayed TBC system, composed of a low-pressure plasma spray (LPPS) applied oxidation-resistant NiCrAlY bond coating and an air-plasma-sprayed yttria (8 percent) partially stabilized zirconia insulative layer, is applied by both Chromalloy and Klock. The second type of TBC is applied by the electron-beam/physical vapor deposition process by Temescal. Thermomechanical and thermochemical testing of the program TBCs is in progress. A number of the former tests has been completed. Fracture mechanics data for the Chromalloy plasma-sprayed TBC system indicate that the cohesive toughness of the zirconia layer is increased by thermal cycling and reduced by high temperature exposure at 1150 C. Eddy current technology feasibility has been established with respect to nondestructively measuring zirconia layer thickness of a TBC system. High pressure turbine blades have been coated with program TBC systems for a piggyback test in a TFE731-5 turbofan factory engine test. Data from this test will be used to validate the TBC life models.

Strangman, T. E.↗

Ceramic Matrix Composites (CMC) Life Prediction Development - 2003

Accurate life prediction is critical to successful use of ceramic matrix composites (CMCs). The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many reusable and single mission launch vehicle propulsion and airframe applications. This paper describes an approach and progress made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation of C/SiC.

Levine, Stanley R.↗

Physical Interpretation of Early Battery Life Prediction Models

Early battery life prediction models are most useful for R&D if they help us understand the early changes in battery electrochemical response that correspond with long-term degradation and failure. Linear regression models such as Fused lasso and Partial Least Squares can fit coefficients directly to high-dimensional electrochemical data like capacity-voltage and ΔV–state-of-charge, i.e., Q(V) and ΔV(SOC) curves, learning coefficients that can be physically interpreted. We leverage the ISU-ILCC battery aging data set to learn high-dimensional coefficients for early battery life prediction from traditional slow-rate capacity check data, demonstrating learning on Q(V), d Q· d V −1 , and ΔV(SOC) curves. A thorough study on the dependence of coefficient values on train/test size and data preprocessing methods is made, demonstrating the reliability of high-dimensional regression approaches unless very small amounts of data are used for model training. For this data set, coefficients from Q(V) and d Q· d V −1 models highlight changes in electrode stoichiometry due to lithium loss, while ΔV(SOC) coefficients highlight changes in positive electrode diffusivity due to particle cracking as well as electrode stoichiometry shifts. By directly interpreting the coefficients of a regression model, we make physical insights into battery degradation mechanisms without requiring the assumptions of traditional battery data analysis methods.

25 ENERGY STORAGE↗

A Machine Learning–Based Tire Life Prediction Framework for Increasing Life of Commercial Vehicle Tires

In the commercial freight industry, tire retreading decisions are often conservative due to limited knowledge of a tire’s remaining service life. This practice leads to increased costs and material waste. This paper proposes a machine learning–based approach for estimating tire casing life and retreadability, focusing on usage data rather than wear information. This approach could extend the tire’s lifespan and reduce landfill waste. Data integration from diverse tire casing measurement sources presents challenges, including imbalanced removal data. Our methodology addresses these challenges by using historical inspection, telematics, and finite element modeling (FEM) datasets. We introduce “Tire Casing Energy” as a comprehensive usage input and apply a Variance-Reduction Synthetic Minority Oversampling Technique (VR-SMOTE) for data imbalance rectification. A random forest model is used to estimate the state of the tire casing and the casing removal probability, with Bayesian optimization applied for hyperparameter tuning, enhancing model accuracy. Here, the proposed prediction framework is able to differentiate different truck fleets and tire locations based on their usage parameters. With the aid of this machine learning model, the importance and sensitivity of different tire usage parameters can be obtained, which is beneficial to maximize tire life.

Data balancing↗

C/sic Life Prediction for Propulsion Applications

Accurate life prediction is critical to successful use of ceramic matrix composites (CMC). The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many reusable and single mission launch vehicle propulsion and airframe applications. This paper describes an approach and process made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation of C/SiC. Issues such as oxidation, steam and hydrogen effects on material behavior are discussed. Preliminary tests indicate that steam will aggressively remove SiC seal coat and matrix in line with past experience. The kinetics of water vapor reaction with carbon fibers is negligible at 600 C, but comparable to air attack at 1200 C. The mitigating effect of steam observed in fiber oxidation studies has also been observed in stress rupture tests. Detailed microscopy of oxidized specimens is being carried out to develop the oxidation model. Carbon oxidation kinetics are reaction controlled at intermediate temperatures and diffusion controlled at high temperatures (approximately 1000 C). Activation energies for T-300 and interface pyrolytic carbon were determined as key inputs to the oxidation model. Crack opening as a function of temperature and stress was calculated. Mechanical property tests to develop and verify the probabilistic life model are very encouraging except for residual strength prediction. Gage width is a key variable governing edge oxidation of seal coated specimens. Future efforts will include architectural effects, enhanced coatings, biaxial tests, and LCF. Modeling will need to account for combined effects.

Levine, Stanley R.↗

C/SIC Life Prediction for Propulsion Applications

Accurate life prediction is critical to successful use of ceramic matrix composites (CMC). The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many reusable and single mission launch vehicle propulsion and airframe applications. This paper describes an approach and progress made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation of C/SiC. Issues such as oxidation, steam and hydrogen effects on material behavior are discussed. Preliminary tests indicate that stream will aggressively remove SiC seal coat and matrix in line with past experience. The kinetics of water vapor reaction with carbon fibers is negligible at 600 C, but comparable to air attack at 1200 C. The mitigating effect of steam observed in fiber oxidation studies has also been observed in stress rupture tests. Detailed microscopy of oxidized specimens is being carried out to develop the oxidation model. Carbon oxidation kinetics are reaction controlled at intermediate temperatures and diffusion controlled at high temperatures (approx. 1000 C). Activation energies for T-300 and interface pyrolytic carbon were determined as key inputs to the oxidation model. Crack opening as a function of temperature and stress was calculated. Mechanical property tests to develop and verify the probabilistic life model are very encouraging except for residual strength prediction. Gage width is a key variable governing edge oxidation of seal coated specimens. Future efforts will include architectural effects, enhanced coatings, biaxial tests, and LCF. Modeling will need to account for combined effects.

Levine, Stanley R.↗

NASALIFE - Component Fatigue and Creep Life Prediction Program

NASALIFE is a life prediction program for propulsion system components made of ceramic matrix composites (CMC) under cyclic thermo-mechanical loading and creep rupture conditions. Although the primary focus was for CMC components, the underlying methodologies are equally applicable to other material systems as well. The program references empirical data for low cycle fatigue (LCF), creep rupture, and static material properties as part of the life prediction process. Multiaxial stresses are accommodated by Von Mises based methods and a Walker model is used to address mean stress effects. Varying loads are reduced by the Rainflow counting method or a peak counting type method. Lastly, damage due to cyclic loading and creep is combined with Minor s Rule to determine damage due to cyclic loading, damage due to creep, and the total damage per mission and the number of potential missions the component can provide before failure.

Gyekenyesi, John Z.↗