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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

First Measurements of the HCFC-142b Trend from Atmospheric Chemistry Experiment (ACE) Solar Occultation Spectra

The first measurement of the HCFC-142b (CH3CClF2) trend near the tropopause has been derived from volume mixing ratio (VMR) measurements at northern and southern hemisphere mid-latitudes for the 2004-2008 time period from spaceborne solar occultation observations recorded at 0.02/cm resolution with the ACE (atmospheric chemistry experiment) Fourier transform spectrometer. The HCFC-142b molecule is currently the third most abundant HCFC (hydrochlorofluorocarbon) in the atmosphere and ACE measurements over this time span show a continuous rise in its volume mixing ratio. Monthly average measurements at northern and southern hemisphere midlatitudes have similar increase rates that are consistent with surface trend measurements for a similar time span. A mean northern hemisphere profile for the time span shows a near constant VMR at 8-20km altitude range, consistent on average for the same time span with in situ results. The nearly constant vertical VMR profile also agrees with model predictions of a long lifetime in the lower atmosphere.

Rinsland, Curtis P.↗
NASA NTRS2007

The Relationship of Loss, Mean Age of Air and the Distribution of CFCs to Stratospheric Circulation and Implications for Atmospheric Lifetimes

Man-made molecules called chlorofluorcarbons (CFCs) are broken apart in the stratosphere by high energy light, and the reactive chlorine gases that come from them cause the ozone hole. Since the ozone layer stops high energy light from reaching low altitudes, CFCs must be transported to high altitudes to be broken apart. The number of molecules per volume (the density) is much smaller at high altitudes than near the surface, and CFC molecules have a very small chance of reaching that altitude in any particular year. Many tons of CFCs were put into the atmosphere during the end of the last century, and it will take many years for all of them to be destroyed. Each CFC has an atmospheric lifetime that depends on the amount of energy required to break them apart. Two of the gases that were made the most are CFC13 and CF2C12. It takes more energy to break apart CF2C12 than CFC13, and its lifetime is about 100 years, nearly twice as long as the lifetime for CFC13. It is hard to figure out the lifetimes from surface measurements because we don't know exactly how much was released into the air each year. Atmospheric models are used to predict what will happen to ozone and other gases as the CFCs decrease and other gases like C02 continue to increase during the next century. CFC lifetimes are used to predict future concentrations and all assessment models use the predicted future concentrations. The models have different circulations and the amount of CFC lost according to the model may not match the loss that is expected according to the lifetime. In models the amount destroyed per year depends on how fast the model pushes air into the stratosphere and how much goes to high altitudes each year. This paper looks at the way the model circulation changes the lifetimes, and looks at measurements that tell us which model is more realistic. Some models do a good job reproducing the age-of-air, which tells us that these models are circulating the stratospheric air at the right speed. These same models also do a good job reproducing the amount of CFCs in the lower atmosphere where they were measured by instruments on NASA's ER-2, a research plane that flies in the lower stratosphere. The lifetime for CFC13 that is calculated using the models that do the best job matching the data is about 25% longer than most people thought. This paper shows that using these measurements to decide which models are more realistic helps us understand why their predictions are different from each other and also to decide which predictions are more likely.

Douglass, A. R.↗
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 OSTI2024

Coupled Process/Device Modeling and Point Defect Engineering of Cu(In,Ga)Se 2 Solar Cells

Point defects directly impact solar cell device performance by limiting the carrier lifetime. In this work, density functional theory calculations are first used to determine the formation energy and diffusion energy barriers of dominant defects in Cu(In,Ga)Se 2 . Next, continuum reaction–diffusion models are developed to analyze the redistribution of defects during manufacturing processes. We estimate defect capture cross sections using a first-principles-based approach. Here, these cross sections are combined with our calculated defect profiles and trap energy levels to parameterize a Shockley–Read–Hall recombination model, which we implement into a device simulator to predict carrier lifetimes and device performance. In that way, a predictive technology computer aided design model is built to predict and optimize the performance of Cu(In,Ga)Se 2 solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

The Natural and Accelerated Evolution of EVA Adhesion Through Intermediate Exposures

Ethylene vinyl acetate (EVA) encapsulants comprise the majority of the encapsulants currently in use; much work has been done to understand and model the adhesive characteristics of EVA-encapsulated modules, but limited work has provided reliable insight into adhesion during the intermediate stages of exposure, limiting the ability to validate model predictions in this range. We provide the adhesion energy measurements for EVA adhesion after nearly six years of field aging and 10 000 h of accelerated aging. Both field and accelerated aging reveal a distinct plateau that emerges during the intermediate exposure periods (after one year in the field and after 1000 h in a chamber). At 10 000 h, adhesion within accelerated aged minimodules falls to a level generally seen after long-term field exposures (>15 years). Previous modeling predicted that adhesion would steadily decrease over the lifetime of a module, but these current results uncover an intermediate plateauing trend that is important to accurately modeling the evolution of adhesion and predicting adhesive failure. Based on these findings, three key model refinements concerning the rate of UV-radical formation and subsequent β-scission, the rate and acceleration of hydrolytic depolymerization, and the profile of the plasticity contribution over time are implemented and discussed.

14 SOLAR ENERGY↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Developing the Science Basis for Understanding Polymer Encapsulant Degradation Mechanisms: DuraMAT 2.0 Final Project Report

Polymeric encapsulants are essential materials in photovoltaic modules, protecting sensitive electronics from the environment while providing mechanical integrity to the multilayered assembly. However, these polymeric materials are susceptible to degradation processes driven by the ingress of environmental species, ultraviolet radiation, thermal stresses, and mechanical loading. In this study, we employ a combined atomistic simulation and accelerated aging experimental approach to study the molecular-scale mechanisms of encapsulant degradation. Classical molecular dynamics simulations quantify the diffusion of environmental and degradation species through the polymer matrix, producing composition-specific diffusion coefficients. Reactive simulations characterize activation energy barriers and reaction rate constants for key chemical pathways. In parallel, thermal-desorption analyses coupled with mass spectrometry monitor the emergence and concentration profiles of degradation products under controlled stressor conditions. By integrating simulation and experiment, we establish quantitative correlations between polymer composition, species diffusivity, and chemical reactivity. We anticipate that these relations and quantitative values could serve as high-fidelity inputs to reaction-diffusion models, enabling physics-informed lifetime predictions and guiding the design of more durable encapsulant materials for solar energy applications.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Fatigue strength reduction model: RANDOM3 and RANDOM4 user manual. Appendix 2: Development of advanced methodologies for probabilistic constitutive relationships of material strength models

FORTRAN programs RANDOM3 and RANDOM4 are documented in the form of a user's manual. Both programs are based on fatigue strength reduction, using a probabilistic constitutive model. The programs predict the random lifetime of an engine component to reach a given fatigue strength. The theoretical backgrounds, input data instructions, and sample problems illustrating the use of the programs are included.

Boyce, Lola↗
NASA NTRS1992

Space Cryogenics Workshop, 10th, Cleveland, OH, June 18-20, 1991, Proceedings

The present workshop on cryogenics discusses the anomalous on-orbit behavior of the Cosmic Background Explorer Dewar, the SHOOT orbital operations, cooling options for Astromag, and space IR telescope facility mission and cryogenic design. Attention is given to the design of a spaceworthy adiabatic demagnetization refrigerator, the evaluation of metal hydride compressors for applications in Joule-Thomson cryocoolers, diaphragm Stirling cryocooler developments, and a computer simulation model for Stirling refrigerators. Topics addressed include low-gravity thermal stratification of liquid helium on SHOOT, a screening program to select a resin for gravity probe-B composites, a simplified generic cryostat thermal model for predicting cryogen mass and lifetime, and the effect of gas mass flux on cryogenic liquid jet breakup. Also discussed are damping criteria for thermal acoustic oscillations in slush and liquid hydrogen systems, an STS-based cryogenic fluid management experiment, and the design and testing of a cryogenic mixer pump.

Source record↗
NASA NTRS1993

A predictive model for space-based X-ray CCD degradation

The first generation of X-ray telescopes to use Charge-Coupled Devices (CCDs) is being launched this decade. With a read noise of a few electrons, CCDs provide Fano-limited spectral resolution across the soft X-ray band (0.1 - 10 keV). However, degradation of resolution due to charge transfer losses becomes noticeable as Charge Transfer Inefficiency (CTI) increases to 10(exp -5). In this paper, we present a model which calculates the effects of radiation damage in low Earth orbit in order to predict CCD lifetimes over which good charge transfer is maintained. The model presented here considers damage mechanisms within the CCD, environmental conditions in which the CCD operates, and experiment shielding. We find that the predicted CTI approaches 10(exp -5) after a one to two year mission for the flight instruments considered here.

Antunes, Alex↗
DOE OSTI2022

Machine-Learning Assisted Identification of Accurate Battery Lifetime Models with Uncertainty

Reduced-order battery lifetime models, which consist of algebraic expressions for various aging modes, are widely utilized for extrapolating degradation trends from accelerated aging tests to real-world aging scenarios. Identifying models with high accuracy and low uncertainty is crucial for ensuring that model extrapolations are believable, however, it is difficult to compose expressions that accurately predict multivariate data trends; a review of cycling degradation models from literature reveals a wide variety of functional relationships. Here, a machine-learning assisted model identification method is utilized to fit degradation in a stand-out LFP-Gr aging data set, with uncertainty quantified by bootstrap resampling. The model identified in this work results in approximately half the mean absolute error of a human expert model. Models are validated by converting to a state-equation form and comparing predictions against cells aging under varying loads. Parameter uncertainty is carried forward into an energy storage system simulation to estimate the impact of aging model uncertainty on system lifetime. The new model identification method used here reduces life-prediction uncertainty by more than a factor of three (86% ± 5% relative capacity at 10 years for human-expert model, 88.5% ± 1.5% for machine-learning assisted model), empowering more confident estimates of energy storage system lifetime.

25 ENERGY STORAGE↗
DOE OSTI2022

Development of an Open-source Alloy Selection and Lifetime Assessment Tool for Structural Components in CSP

Lack of sufficient data on high temperature mechanical and corrosion behavior of structural materials is a huge barrier in the technological maturity of current and future Concentrating Solar Power (CSP) technologies. Rapid development and selection of materials cannot be achieved by expensive and time-consuming acquisition of experimental data. The goal of the proposed work is development of an open-source alloy selection and lifetime prediction tool that will integrate validated physics-based models to describe influence of temperature, alloy composition, environment and component geometry (thickness) on mechanical and corrosion behavior of Ni and Fe-based alloys employed in molten salts/sCO 2 heat exchangers. This one-year project leveraged the extensive dataset on the creep\corrosion behavior of candidate materials generated at ORNL through past projects and input from current collaborations with industrial partners. Based on previous experience and the feedback provided by industry (Brayton Energy and Echogen), three candidate materials of interest, Ni-based alloys 740H, 282 and 625 and application-specific operating conditions (max. temperature of 730 °C and stress of 150 MPa) were identified for the heat exchanger. An extensive corrosion and creep dataset was assimilated for the relevant operating conditions and was supported by detailed characterization of about 100 metallographic cross-sections. The corrosion dataset consisted of scanning electron microscopy images (secondary electron and backscatter electron), measured concentration profiles of alloying elements using energy dispersive X-ray spectroscopy (EDS), widths of denuded zones (dissolution of strengthening phases) and depths of attack in molten KCl-MgCl 2 mixtures using image analyses. The creep dataset comprised of creep rupture data and creep strain curves (for 740H and 282). Coupled thermodynamic-kinetic microstructure-based models were employed to predict the stress-corrosion induced compositional and phase evolutions in the alloy during operation under the identified operating conditions. Reduced order models were developed from advanced physics-based models and were integrated in a user-friendly alloy selection tool. The corrosion model was able to predict the time to a critical Cr concentration at the oxide/alloy interface (chemical lifetime) within ±10% (1 standard deviation) of typical statistical variation in corrosion tests and EDS measurement errors (±0.5 wt%). The initial scope of the project was limited to predict creep rupture times (Larson-Miller parameter). Based on the input provided by industry, the mechanical lifetime of the heat exchanger is governed by accumulated creep strains (2%) rather than creep rupture. To be able to predict the times to specific creep strains, a more extensive creep model development was undertaken largely beyond the initial scope of the project. The continuum damage mechanics creep model was able to predict times to 2% creep strain, t 2% with an accuracy of ±500h. Ultimately, a screening protocol for SiC was generated to demonstrate the pathway for integration of one of the currently immature materials from a commercial adoption standpoint in the current material evaluation tool. The modeling tool developed here is accessible to the science community and stakeholders and lays the foundation for methods that will enable a rapid evaluation of optimum materials for CSP applications and reliable prediction of material degradation thereby considerably reducing operational costs, improving reliability and increasing overhaul intervals. However, the complete potential of such a tool to include a wider range of materials and test conditions can only be realized with a more concentrated combined experimental-characterization-computation effort.

14 SOLAR ENERGY↗
NASA NTRS1993

Lifetime prediction of materials exposed to the natural space environment

The goal of this study is to model the lifetime of different types of seal materials based on results obtained from accelerated experiments. A semi-mechanistic approach was taken. Thermal aging data were taken from the literature whereas experiments were conducted at Auburn under this contract for selected environments. The seal materials of interest are Silicone 383, Silicone 650, Viton 835, and Viton 747. The relevant conditions include thermal, oxygen, inert gas, vacuum, and gamma radiation. Compression set data available from NASA were used to examine the thermal effect. Experiments were conducted at Auburn University and at NASA to isolate the role of thermal, oxygen, inert gas, vacuum, gamma irradiation, and proton irradiation. A simple discrete stress relaxation method was developed to determine the relaxation response of the elastomers. Dynamic mechanical thermal analysis was also used to characterize the mechanical response of the specimens. These provide a more meaningful correlation between mechanisms and degradation.

Zee, Ralph↗
DOE OSTI2026

Prediction of Creep-Induced Strain Using a Symbolic Regression-Based Model

Material creep under high-temperature conditions limits the lifetime and safety of structural systems such as advanced nuclear reactors. Conventional creep testing is slow and often produces inconsistent results across nominally identical experiments, making lifetime prediction uncertain. Here, to address these challenges, this work develops a data-driven symbolic regression (SR) model that consolidates results from duplicate creep tests and predicts the remaining strain-time curve of an ongoing experiment. The method uses piece-wise multi-objective SR with physical constraints to generate analytic, interpretable functions describing transient creep strain. Applied to Inconel Alloy 617 data, the approach achieved relative mean absolute errors of 1.0–9.5%, providing closed-form predictions of strain evolution. These results demonstrate a first step toward reducing the duration and cost of long-term creep testing while retaining physically interpretable model forms.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Detailed Design and Cost Estimation of a 300 MWe Oxy-Fuel sCO2 Turbine

The detailed design of a 300 MWe, utility scale oxy-fuel turbine has been completed for purposed operation in the sCO2 direct fired Allam-Fetvedt cycle, targeting near-zero emissions and a 50% LHV system efficiency. The turbine and its supporting plant aim to offer a lower levelized cost of energy than a natural gas combined cycle plant employing carbon capture. The oxy-fuel turbine conditions include an inlet temperature of 1150°C and inlet pressure of 305 bar, representing temperatures near that of a gas turbine simultaneously with pressures near an ultra-supercritical steam turbine. The combustor housing and turbine designs were completed according to the ASME BPVC; the turbine case specifically incorporates a multi-body design with inner high-pressure barrel case and low-pressure (30 bar) horizontally split outer case of low-chromium steel material. Lateral rotordynamic evaluation demonstrated acceptable vibration response for a range of imbalance conditions per API standards. The cooling flow required in the six-stage turbine flowpath for 30,000 hr. blade and stator lifetime is predicted through thermal and structural modeling of the first stage. The provided cost estimate of the turbine is formed through a combination of scaled up-costs from procured 10 MWe scale sCO2 turbomachinery hardware, and vendor provided budgetary quotes of larger components including the turbine case requiring casting, welding, and final machining processes. The performance and cost estimation of the oxy-fuel turbine predicted for the completed detailed design provides important information towards future development needs for market penetration of utility scale direct fired sCO2 power cycles.

Marshall, Michael [Southwest Research Institute, S↗
NASA NTRS2011

Limits to Mercury's Magnesium Exosphere from MESSENGER Second Flyby Observations

The discovery measurements of Mercury's exospheric magnesium, obtained by the MErcury Surface. Space ENvironment, GEochemistry. and Ranging (MESSENGER) probe during its second Mercury flyby, are modeled to constrain the source and loss processes for this neutral species. Fits to a Chamberlain exosphere reveal that at least two source temperatures are required to reconcile the distribution of magnesium measured far from and near the planet: a hot ejection process at the equivalent temperature of several tens of thousands of degrees K, and a competing, cooler source at temperatures as low as 400 K. For the energetic component, our models indicate that the column abundance that can be attributed to sputtering under constant southward interplanetary magnetic field (IMF) conditions is at least a factor of five less than the rate dictated by the measurements, Although highly uncertain, this result suggests that another energetic process, such as the rapid dissociation of exospheric MgO, may be the main source of the distant neutral component. If meteoroid and micrometeoroid impacts eject mainly molecules, the total amount of magnesium at altitudes exceeding approximately 100 km is found to be consistent with predictions by impact vaporization models for molecule lifetimes of no more than two minutes. Though a sharp increase in emission observed near the dawn terminator region can be reproduced if a single meteoroid enhanced the impact vapor at equatorial dawn, it is much more likely that observations in this region, which probe heights increasingly near the surface, indicate a reservoir of volatile Mg being acted upon by lower-energy source processes.

Sarantos, Menelaos↗
NASA NTRS2017

Monte Carlo Computational Modeling of Atomic Oxygen Interactions

Computational modeling of the erosion of polymers caused by atomic oxygen in low Earth orbit (LEO) is useful for determining areas of concern for spacecraft environment durability. Successful modeling requires that the characteristics of the environment such as atomic oxygen energy distribution, flux, and angular distribution be properly represented in the model. Thus whether the atomic oxygen is arriving normal to or inclined to a surface and whether it arrives in a consistent direction or is sweeping across the surface such as in the case of polymeric solar array blankets is important to determine durability. When atomic oxygen impacts a polymer surface it can react removing a certain volume per incident atom (called the erosion yield), recombine, or be ejected as an active oxygen atom to potentially either react with other polymer atoms or exit into space. Scattered atoms can also have a lower energy as a result of partial or total thermal accommodation. Many solutions to polymer durability in LEO involve protective thin films of metal oxides such as SiO2 to prevent atomic oxygen erosion. Such protective films also have their own interaction characteristics. A Monte Carlo computational model has been developed which takes into account the various types of atomic oxygen arrival and how it reacts with a representative polymer (polyimide Kapton H) and how it reacts at defect sites in an oxide protective coating, such as SiO2 on that polymer. Although this model was initially intended to determine atomic oxygen erosion behavior at defect sites for the International Space Station solar arrays, it has been used to predict atomic oxygen erosion or oxidation behavior on many other spacecraft components including erosion of polymeric joints, durability of solar array blanket box covers, and scattering of atomic oxygen into telescopes and microwave cavities where oxidation of critical component surfaces can take place. The computational model is a two dimensional model which has the capability to tune the interactions of how the atomic oxygen reacts, scatters, or recombines on polymer or nonreactive surfaces. In addition to the specification of atomic oxygen arrival details, a total of 15 atomic oxygen interaction parameters have been identified as necessary to properly simulate observed interactions and resulting polymer erosion that have been observed in LEO. The tuning of the Monte Carlo model has been accomplished by adjusting interaction parameters so the erosion patterns produced by the model match those from several actual LEO space experiments. Surface texturing in LEO can also be predicted by the model. Such comparison of space tests with ground laboratory experiments have enabled confidence in ground laboratory lifetime prediction of protected polymers. Results of Monte Carlo tuning, examples of surface texturing and undercutting erosion prediction, and several examples of how the model can be used to predict other LEO and Mars orbital space results are presented.

Monte Carlo Modeling↗