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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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This report discuss aging mechanisms and cycling performance of Li batteries, and considers the influence of both the passive and active materials. To achieve this aim we developed in situ coin cell and pouch cell NMR probes as well as HR-MAS NMR protocols to study cells with as a little modification as possible.
The costs of maintaining ageing aircraft are draining the existing budgets. The Specialist Meeting provided guidance on strategies for the development and implementation of technologies and logistic management processes to reduce this economic burden. The emphasis was on military aircraft, but many of the principles could be applied to other defence systems. The papers covered the entire range of ageing problems including structural integrity, corrosion, avionics, mechanical subsystems, structures and wiring as well as the role of information management. Forty-two papers addressed the safety and economic implications such as fatigue cracking, corrosion, wear and material degradation. Key technologies were discussed, including non-destructive inspection, repair, modifications, prevention analysis, and health management. The shortcomings of current were highlighted and the investment required was identified. The need for research and development was clearly identified.
Lamb waves offer a promising method of evaluating damage in composite materials. The Lamb wave velocity is directly related to the material parameters, so an effective tool exists to monitor damage in composites by measuring the velocity of these waves. The Lamb Wave Imager (LWI) uses a pulse/receive technique that excites an antisymmetric Lamb mode and measures the time-of-flight over a wide frequency range. Given the material density and plate thickness, the bending and out-of-plane shear stiffnesses are calculated from a reconstruction of the dispersion curve. In this study, the time-of-flight as well as the elastic stiffnesses D11, D22, A44, and A55 for composite samples which have undergone combined thermal and mechanical aging are obtained. The samples examined include a baseline specimen with 0 cycles, specimens which have been aged 2350 and 3530 cycles at high strain levels, and one specimen aged 3530 cycles at low strain levels.
The introduction of new, advanced composite materials into aviation systems requires a thorough understanding of the long term effects of combined thermal and mechanical loading upon those materials. Analytical methods investigating the effects of intense thermal heating combined with mechanical loading have been investigated. The damage mechanisms and fatigue lives were dependent on test parameters as well as stress levels. Castelli, et al. identified matrix dominated failure modes for out-of-phase cycling and fiber dominated damage modes for in-phase cycling. In recent years, ultrasonic methods have been developed that can measure the mechanical stiffness of composites. To help evaluate the effect of aging, a suitably designed Lamb wave measurement system is being used to obtain bending and out-of-plane stiffness coefficients of composite laminates undergoing thermal-mechanical loading. The system works by exciting an antisymmetric Lamb wave and calculating the velocity at each frequency from the known transducer separation and the measured time-of-flight. The same peak in the waveforms received at various distances is used to measure the time difference between the signals. The velocity measurements are accurate and repeatable to within 1% resulting in reconstructed stiffness values repeatable to within 4%. Given the material density and plate thickness, the bending and out-of-plane shear stiffnesses are calculated from a reconstruction of the dispersion curve. A mechanical scanner is used to move the sensors over the surface to map the time-of-flight, velocity, or stiffnesses of the entire specimen. Access to only one side of the material is required and no immersion or couplants are required because the sensors are dry coupled to the surface of the plate. In this study, the elastic stiffnesses D(sub 11), D(sub 22), A(sub 44), and A(sub 55) as well as time-of-flight measurements for composite samples that have undergone combined thermal and mechanical aging for a duration of 10,000 hours are reported.
Curves and tabular data present the results of strength tests made during and after 2 1/2 years of aging on rivets and rivet wire of 3/16-inch nominal diameter. The specimens were of aluminum alloy: 24S, 17S, and A17S of the duralumin type and 53S of the magnesium-silicide type.
Curves and tabular data present the results of strength tests made during and after 2 1/2 years of aging on rivets and rivet wire of 3/16-inch nominal diameter. The specimens were of aluminum alloy: 24s, 17s, and a17s of the duralumin type and 53s of the magnesium-silicide type.
Although localized high-concentration electrolytes (LHCEs) have been shown to improve the calendar lifetime of silicon anodes, the roles of the electrolyte constituents in calendar aging are not well understood. Here, in this work, we utilize a voltage hold protocol and an LHCE with varying molar ratios of lithium bis(fluorosulfonyl)imide (LiFSI), tetramethylene sulfone (TMS), and 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether (TTE) to probe the component roles during aging. Interestingly, the estimated calendar lifetime and irreversible lithium losses from the V-hold experiments are independent of the electrolyte formulations. Contrarily, the solid electrolyte interphase (SEI) composition depends on the electrolyte formulation. X-ray photoelectron spectroscopy shows that TMS-coordinated species decompose to form insoluble alkanes and lithium hydroxide (LiOH), while lithium fluoride (LiF) originates from the anion-coordination complex. The SEI composition does not appear to play a significant role in the silicon anode passivity, as measured by parasitic current, suggesting that the SEI-electrolyte interactions dictate the calendar aging mechanisms.
Laboratory aging campaigns benchmark and elucidate the complex degradation behavior of lithium-ion batteries, and are critical not only for developing new battery chemistries and cell designs but also for engineering reliable battery management systems. Critically, these laboratory experiments aim to quantify and capture realistic aging mechanisms. In this study, we systematically compare dynamic discharge profiles representative of electric vehicle driving to the well-accepted constant-current profiles. Surprisingly, we discovered that dynamic discharge enhances lifetime substantially compared to constant current discharge. Specifically, for the same average current and voltage window, varying the dynamic discharge profile leads to an increase of up to 38 % in equivalent full cycles at end-of-life. Explainable machine learning reveals the importance of low-frequency current pulses as well as time-induced aging under these realistic discharge conditions. Our work quantifies the importance of evaluating new battery chemistries and designs with realistic load profiles, and highlights the opportunities to revisit our understanding of aging mechanisms at the chemistry, materials, and cell levels.
Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.
This research project was a collaborative investigation between researchers at the RTX Technology Research Center (RTRC) and the University of Texas at Austin and made a significant contribution to enabling electric aircraft. The transport of electric power between the points of generation and use requires power cables. These cables must be smaller, lighter and provide a more predictable life than power cables used in stationary applications. Consequently, this investigation provided heretofore unavailable information supporting the safety and reliability of smaller lighter power cables for electrified aircraft. In addition, the research identified key additional engineering data needed to support quantitative reliability assessments. Important advances included: • Demonstrated that at least one manufacturer can make a novel, smaller, lighter power cable that is free from serious defects. • Developed and published an appropriate analytical construct to describe the life of this novel cable. This is a necessary step for use in aviation where the understanding of remaining life is critical. • Demonstrated thermal-mechanical aging that suggested 1000+ flights before the thermal-mechanical processes produced defects large enough that the defect growth was accelerated electrically. • Showed that electrical aging took place at two rates. The first possibly lasting weeks to months and the second possibly days to weeks. If robust, this provides a good diagnostic for cable replacement. • Demonstrated that the traditional electrical testing of cable materials using manufactured voids can be misleading due to the size of the voids. Emerging laser drilling technology permitted demonstration that the physics of failure in realistically small voids is different from that in the unrealistically large voids used in earlier research, which is very important for high-quality, high-performance, small aircraft cables. Although this project represents a significant contribution to the specifics of cable aging in the aircraft environment, important additional research remains to be completed, including: • Non-uniform thermal cycling by applying the heat from the center conductor to maximize thermal stress next to the core area where the electric gradient is the strongest. This builds on the uniform thermal cycling that has been completed. • The augmentation of the thermal-mechanical failure rate by electrical processes. Better understanding of these time constants strongly affects the ability to predict life. • Termination design: Terminations provide not only electrical reflection potential, but a location for a series arc fault and an area where ozone can diffuse into the center conductor and negatively affect cable insulation. • The abrasion and ozone resistance of the cable jacket. • Pressure cycling as an accelerant of thermal, mechanical, and/or electrical aging. • Possible methods for online PD detection and offline PD localization
The experimental increase in mechanical usage or overloading of the left hindlimb was produced by immobilization of the contralateral hindlimb. The right hindlimb was placed in a flexed position against the body and was immobilized using an elastic bandage. Some control animals were sacrificed initially at time zero and increased mechanical usage and age-matched control animals were sacrificed after 2, 10, 18, and 26 weeks of treatment. All animals received double bone fluorochrome labeling prior to sacrifice. Cortical bone histomorphometry and cross-sectional moments of inertia were determined. Marrow cavity enlargement and total cross-sectional area expansion represented the age-related cortical bone changes. Increased mechanical usage enhanced periosteal bone modeling in the formation mode and dampened endocortical bone remodeling and bone modeling in the resorption mode (resorption drift) to create a slight positive bone balance. These observations are in general agreement with Frost's postulate for mechanical effects on bone modeling and remodeling. The maximum moment of inertia did not change significantly in either control or overloaded tibial shafts. The minimum and polar moment of inertias in overloaded bones increases over those of controls at 18 and 26 weeks of the experiment.
The experimental increase in mechanical usage or overloading of the left hindlimb was produced by immobilization of the contralateral hindlimb. The right hindlimb was placed in a flexed position against the body and was immobilized using an elastic bandage. Some control animals were sacrificed initially at time zero and increased mechanical usage and age-matched control animals were sacrificed after 2, 10, 18, and 26 weeks of treatment. All animals received double bone fluorochrome labeling prior to sacrifice. Cortical bone histomorphometry and cross-sectional moments of inertia were determined. Marrow cavity enlargement and total cross-sectional area expansion represented the age-related cortical bone changes. Increased mechanical usage enhanced periosteal bone modeling in the formation mode and dampened endocortical bone remodeling and bone modeling in the resorption mode (resorption drift) to create a slight positive bone balance. These observations are in general agreement with Frost's postulate for mechanical effects on bone modeling and remodeling. The maximum moment of inertia did not change significantly in either control or overloaded tibial shafts. The minimum and polar moment of inertias in overloaded bones increases over those of controls at 18 and 26 weeks of the experiment.
The dynamic evolution of precipitates and second phases dictates the strength and stability of most engineering alloys. By design, or as a consequence of thermo-mechanical aging, engineering metals and alloys often form precipitates of second phases when subjecting to diverse thermal and mechanical loads. Precipitation is governed by several factors, including the alloy’s composition, processing/operating temperature, and stresses — either as a result of external loads or from residual stresses. However, state-of-the-art models for precipitate nucleation (i.e., classical nucleation theory) typically lacks consistent method to capture the effects of externally applied and/or internal stresses on nucleation; thereby severely limiting the applicability of these models to complex materials systems and to representative loading scenarios. Here, in this work, we extend upon classical nucleation theory to account for the effect of stresses on precipitation kinetics and thermodynamics. This is achieved via the use of an Eshelbian micromechanics framework keeping track of (i) the stress build up resulting from second phase formation as a function of mechanical load and, (ii) the effects of dislocations on precipitate formation. This new model is applied to σ precipitate in Fe–Cr binary alloys and M 23 C 6 precipitate in 316H stainless steel (SS). Simulations demonstrate the important role of both the remotely applied loads and dislocation pile ups on precipitate nucleation.
A rational approach to the problem of accelerated testing for material characterization of advanced polymer matrix composites is discussed. The experimental and analytical methods provided should be viewed as a set of tools useful in the screening of material systems for long-term engineering properties in aerospace applications. Consideration is given to long-term exposure in extreme environments that include elevated temperature, reduced temperature, moisture, oxygen, and mechanical load. Analytical formulations useful for predictive models that are based on the principles of time-based superposition are presented. The need for reproducible mechanisms, indicator properties, and real-time data are outlined as well as the methodologies for determining specific aging mechanisms.
Lithium-ion battery energy storage systems (BESS) packs have emerged as a leading solution for grid-scale energy storage, enhancing resiliency and balancing load fluctuations. Yet, experimental characterization of large-format LIB packs-particularly to assess performance and degradation over hundreds of cycles - demands substantial hardware investment and multi-year testing campaigns. In this work, we couple a hierarchical, physics-based modeling framework agnostic to electrode chemistries with high-performance computing to accelerate systems level evaluation by upto two orders of magnitude. Building on the open-source liionpack platform, we implement cell, module, and pack-scale electrochemical models enriched with mechanistic aging mechanisms and deploy them on an HPC cluster to simulate 150−200kWh systems over 500 - 1,000 cycles with in days. We subject these virtual B ESS to both constant-current cycling and realistic grid service profiles spanning frequency regulation, ramp-rate support, and energy arbitrage-and quantify the resulting degradation patterns. Our results reveal that localized cell aging can induce substantial nonuniformity at module and pack levels, with service-specific cycling protocols driving distinct aging modes. This rapid, multiscale modeling approach provides a powerful design-space exploration tool for optimizing electrical architecture, control strategies, and operational schedules to prolong pack lifetime and lower total cost of ownership.
Understanding aging mechanisms of electronic components is of extreme importance in the aerospace domain where they are part of numerous critical subsystems including avionics. In particular, power MOSFETs are of special interest as they are involved in high voltage switching circuits such as drivers for electrical motors. With increased use of electronics in aircraft control, it becomes more important to understand the degradation of these components in aircraft specific environments. In this paper, we present an accelerated aging methodology for power MOSFETs that subject the devices to indirect thermal overstress during high voltage switching. During this accelerated aging process, two major modes of failure were observed - latch-up and die attach degradation. In this paper we present the details of our aging methodology along with details of experiments and analysis of the results.
Increasing beneficial use of fresh or landfilled fly ash as a replacement for Portland cement can be more challenging for the construction of precast buildings or similar applications requiring rapid strength development. Therefore, the framework presented in this paper aims to reassess high-volume fly ash concretes but in the context of facilitating more sustainable precast buildings. More specifically, the framework was used to characterize strength development of concrete mixes with a target minimum 24-hour compressive strength of 24.1 MPa (3500 psi), selected as an example strength development metric to demonstrate the framework, and comprised of 40% Class C, Class F, and landfilled (harvested) fly ash – as a high-volume replacement of Type III or Type IL cement. High-early strength was driven by optimized dosages of commercial grade gypsum and accelerating admixtures, in addition to optimal aggregate packing and mix proportioning strategies. Early-age mechanical properties including compressive strength, modulus of rupture, and modulus of elasticity were reevaluated within 24 hours of batching with respect to common precast production demands. Simple data analyses were then used to highlight cases where currently accepted design provisions for the aforementioned properties are either overly-conservative or unconservative with respect to test data. Furthermore, the framework and demonstration of example mixes presented herein aim to promote confidence for using larger fractions of fresh or landfilled fly ashes for precast buildings to further enhance environmental benefits without sacrificing pertinent early-age structural performance.
The reactor pressure vessel (RPV) is a critical structural component in pressurized-water reactors, and it is designed to withstand extreme conditions, such as high pressures, elevated temperatures, and prolonged radiation exposure. Ensuring RPV integrity is essential for the safe and reliable long-term operation of nuclear power plants, especially as aging mechanisms such as fatigue and irradiation embrittlement pose increased risks. Fatigue, caused by cyclic thermal and mechanical loading, can lead to crack initiation in localized high-stress regions. Simultaneously, neutron irradiation, particularly in the beltline region, progressively reduces fracture toughness, increasing susceptibility to brittle fracture. These combined effects of fatigue and irradiation embrittlement potentially impact the RPV structural integrity, necessitating fitness-for-service assessments. This study applies the fracture toughness master curve approach to evaluate the impact of irradiation embrittlement on RPV fatigue life. A coupled thermo-mechanical stress analysis identifies critical stress locations under normal service transients, pinpointing regions most vulnerable to fatigue crack initiation and growth. Stress intensity factors for postulated flaws at these locations are calculated, enabling an assessment of fatigue life under irradiated and unirradiated conditions. The results indicate that neutron irradiation embrittlement accelerates the conditions in which a critical crack can form and lead to failure, particularly at lower temperatures. The failure occurs where reduced fracture toughness limits the material’s resistance to crack growth. Axial cracks at nozzle corners are the most life limiting without irradiation, while circumferential cracks demonstrate longer fatigue lives. The findings highlight the importance of incorporating irradiation effects into fatigue life predictions to ensure the long-term structural integrity of RPVs.