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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Predictive numerical modeling of plasma-induced surface roughness and wettability evolution in LM-PAEK/CF tape

Plasma surface modification effectively enhances adhesion in thermoplastic composites, yet its impacts on high-performance polymers like low-melting polyaryletherketone (LM-PAEK) remain inadequately quantified. Here, this study integrates experimental analysis and numerical modeling to characterize surface roughness and wettability changes in LM-PAEK/carbon fiber composites treated with atmospheric plasma. Atomic Force Microscopy quantified surface topography (n = 10 per condition for contact angles), while static contact-angle assessments measured wettability. Roughness rapidly increased from ∼0.2 nm to 1.6 nm, and contact angle reduced from ∼90° to 24°, both stabilizing after 25–30 s of exposure. A semi-empirical, physics-informed framework was calibrated to these data, coupling surface chemistry via the Owens–Wendt decomposition with topography via the Wenzel roughness factor, and evaluated using out-of-sample (cross-validated) tests, while static contact angle assessments measured wettability. Numerical predictions matched experimental results closely (RMSE <5%, R 2 > 0.95). Incorporating material-specific parameters, the calibrated model supports plasma-treatment optimization and provides quantitative guidance for improving interfacial adhesion in thermoplastic composite manufacturing.

Atomic Force Microscopy↗
DOE OSTI2022

Solar Radiation Research Laboratory (SRRL) Final Report: Fiscal Years 2019-2021

The Solar Radiation Research Laboratory (SRRL) at the National Renewable Energy Laboratory (NREL) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m 2 ) for the United States, which is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two International Organization for Standardization (ISO)/International Electrotechincal Commission (IEC) 17025 calibration facilities that provide unique, high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop: improved methods for the calibration of solar radiometers; new standards through the ISO, the IEC, and ASTM International; models; advanced instrumentation and methods for operating solar measurement stations. The SRRL data sets are also critical for the validation of new models and data sets, such as the National Solar Radiation Database (NSRDB).

14 SOLAR ENERGY↗
DOE OSTI2025

Real-time elemental analysis of liquids for process monitoring using laser-induced breakdown spectroscopy with a liquid wheel sampling approach

This article presents an engineered sampling system that used a rotating wheel to form a thin liquid layer, permitting the use of laser-induced breakdown spectroscopy (LIBS) for in situ, real-time elemental impurity quantification during liquid processing. The sampling approach was demonstrated on eight elements from across the periodic table (Na, Al, K, Ca, Ti, Sr, Mo, and Yb). Univariate and multivariate calibrations were presented for each element. The average value for percent root mean square errors of cross-validation for the multivariate models was 3.64%, highlighting the method's strong prediction accuracy. Additionally, the limits of detection for each analyte were estimated from their univariate models: Na = 0.0532, Al = 18.5, K = 0.105, Ca = 0.273, Ti = 67.7, Sr = 0.640, Mo = 22.4, and Yb = 22.9 μg mL –1 . Finally, a test in which multivariate models were used to monitor a liquid system for 80 min was performed to investigate the real-time monitoring capabilities of this liquid LIBS sampling approach. Rigorous measurements were performed to effectively predict the absence and concentrations of multiple analytes as they were spiked and diluted. This demonstration showed the feasibility of using LIBS for real-time liquid quantification models with estimated precision ≤ 8.1%. Finally, the limitations of this approach and potential future improvements are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Cluster cosmology with anisotropic boosts: validation of a novel forward modelling analysis and application on SDSS redMaPPer clusters

We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$. We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Predicting electrical conductivity in Cu/Nb composites: A combined model-experiment study

The generation of high magnetic fields requires materials with high electric conductivity and good strength properties. Cu/Nb composites are considered to be good candidates for this purpose. In this work, we aim to predict, from theory, the dependence of electric conductivity on the microstructure, most notably on the layer thickness and grain sizes. We also conducted experiments to calibrate and validate our simulations. Bimetal interfaces and grain boundaries are confirmed to have the largest impact on conductivity in this composite material. In this approach, a distribution of the layer thickness is accounted for in order to better model the experimentally observed microstructure. Because layer thicknesses below the mean free path of Cu significantly degrade the conductivity, an average layer thickness larger than expected may be needed to meet conductivity requirements in order to minimize these smaller layers in the distribution. We also investigate the effect of variations in volume fraction of Nb and temperature on the material’s conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Comparing Compressed and Full-Modeling analyses with FOLPS: implications for DESI 2024 and beyond

The Dark Energy Spectroscopic Instrument (DESI) will provide unprecedented information about the large-scale structure of our Universe. In this work, we study the robustness of the theoretical modelling of the power spectrum of F OLPS , a novel effective field theory-based package for evaluating the redshift space power spectrum in the presence of massive neutrinos. We perform this validation by fitting the AbacusSummit high-accuracy N -body simulations for Luminous Red Galaxies, Emission Line Galaxies and Quasar tracers, calibrated to describe DESI observations. We quantify the potential systematic error budget of F OLPS finding that the modelling errors are fully sub-dominant for the DESI statistical precision within the studied range of scales. Additionally, we study two complementary approaches to fit and analyse the power spectrum data, one based on direct Full-Modelling fits and the other on the ShapeFit compression variables, both resulting in very good agreement in precision and accuracy. In each of these approaches, we study a set of potential systematic errors induced by several assumptions, such as the choice of template cosmology, the effect of prior choice in the nuisance parameters of the model, or the range of scales used in the analysis. Furthermore, we show how opening up the parameter space beyond the vanilla ΛCDM model affects the DESI observables. These studies include the addition of massive neutrinos, spatial curvature, and dark energy equation of state. We also examine how relaxing the usual Cosmic Microwave Background and Big Bang Nucleosynthesis priors on the primordial spectral index and the baryonic matter abundance, respectively, impacts the inference on the rest of the parameters of interest. This paper pathways towards performing a robust and reliable analysis of the shape of the power spectrum of DESI galaxy and quasar clustering using F OLPS .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

First Detection of the GI-type of Intrinsic Alignments of Galaxies Using the Self-calibration Method in a Photometric Galaxy Survey

Weak gravitational lensing is one of the most promising cosmological probes to constrain dark matter, dark energy, and the nature of gravity at cosmic scales. Intrinsic alignments (IAs) of galaxies have been recognized as one of the most serious systematic effects facing gravitational lensing. Such alignments must be isolated and removed to obtain a pure lensing signal. Furthermore, the alignments are related to the processes of galaxy formation, so their extracted signal can help in understanding such formation processes and improving their theoretical modeling. We report in this Letter the first detection of the gravitational shear–intrinsic shape (GI) correlation and the intrinsic shape–galaxy density (Ig) correlation using the self-calibration method in a photometric redshift survey. These direct measurements are made from the KiDS-450 photometric galaxy survey with a significance of 3.65σ in the third bin for the Ig correlation, and 3.51σ for the GI cross-correlation between the third and fourth bins. The self-calibration method uses the information available from photometric surveys without needing to specify an IA model and will play an important role in validating IA models and IA mitigation in future surveys such as the Rubin Observatory Legacy Survey of Space and Time, Euclid, and WFIRST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A review of NEST models for liquid xenon and an exhaustive comparison with other approaches

This paper discusses the microphysical simulation of interactions in liquid xenon, the active detector medium in many leading rare-event searches for new physics, and describes experimental observables useful for understanding detector performance. The scintillation and ionization yield distributions for signal and background are presented using the Noble Element Simulation Technique (NEST), a toolkit based on experimental data and simple empirical formulas, which mimic previous microphysics modeling but are guided by data. The NEST models for light and charge production as a function of the particle type, energy, and electric field are reviewed, along with models for energy resolution and final pulse areas. NEST is compared with other models or sets of models and validated against real data, with several specific examples drawn from XENON, ZEPLIN, LUX, LZ, PandaX, and table-top experiments used for calibrations.

WIMPs↗
DOE OSTI2021

FAST.Farm load validation for single wake situations at alpha ventus

The main objective of the presented work is the validation of the simulation tool FAST.Farm for the calculation of power and structural loads in single wake situations; the basis for the validation is the measurement database of the operating offshore wind farm alpha ventus. The approach is described in detail and covers the calibration of the aeroelastic turbine model, transfer of environmental conditions to simulations, and comparison between simulations and adequately filtered measurements. It is shown that FAST.Farm accurately predicts power and structural load distributions over wind direction with discrepancies of less than 10 % for most of the cases compared to the measurements. Additionally, the frequency response of the structure is investigated, and it is calculated by FAST.Farm in good agreement with the measurements. In general, the calculation of fatigue loads is improved with a wake-added turbulence model added to FAST.Farm in the course of this study.

17 WIND ENERGY↗
DOE OSTI2022

Oil Recovery Prediction for Polymer Flood Field Test of Heavy Oil on Alaska North Slope Via Machine Assisted Reservoir Simulation

The first ever polymer flood field pilot to enhance the recovery of heavy oils on the Alaska North Slope is ongoing. This study constructs and calibrates a reservoir simulation model to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding, as indicated by a significant decrease in water cut. Later, transmissibility contrasts are reinstated to replicate a water surge event observed in one of the producing wells during polymer flooding. This event may represent decreased injection conformance from fracture overextension; its anticipated occurrence in the other production well is included in the final forecast. The definition of polymer retention in the simulator incorporates the tailing effect reported in laboratory studies; this tailing effect is useful to the simultaneous history match of producing water cut and produced polymer concentration. The top 24 best-matched simulation models produced at each stage of the history matching process are used to forecast oil recovery. The final forecast clearly demonstrates that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone. This exercise displays that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the benefits of an enhanced oil recovery process such as polymer flooding. Therefore, caution is recommended in using basic waterflood simulation models to scope potential enhanced oil recovery projects.

Keith, Cody Douglas↗
DOE OSTI2023

Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti’s Theorem for Markov Chains

Conformal prediction is a widely used method to quantify uncertainty in settings where the data is independent and identically distributed (IID), or more generally, exchangeable. Conformal prediction takes in a pre-trained classifier and a calibration dataset as inputs, and returns a function which maps feature vectors to subsets of classes. The output of the returned function for a new feature vector is guaranteed to contain the true class with a pre-specified confidence. Despite its success and usefulness in IID settings, extending conformal prediction to non-exchangeable (e.g., Markovian) data in a manner that provably preserves all desirable theoretical properties has largely remained an open problem. As a solution, we extend conformal prediction to the setting of a Hidden Markov Model (HMM) with unknown parameters. The key idea behind the proposed method is to partition the non-exchangeable Markovian data from the HMM into exchangeable blocks by exploiting the de Finetti’s Theorem for Markov Chains discovered by Diaconis and Freedman (1980). The permutations of the exchangeable blocks are then viewed as randomizations of the observed Markovian data from the HMM. The proposed method provably retains all desirable theoretical guarantees offered by the classical conformal prediction framework and is general enough to be useful in many sequential prediction problems.

Nettasinghe, Don Buddhika Wijayantha↗
DOE OSTI2020

Vented and sealed cookoff of powdered and pressed ε-CL-20

In this work, we have completed a series of vented and sealed cookoff experiments of the ε-polymorph of CL-20 in our Sandia Instrumented Thermal Ignition (SITI) apparatus using both powder and pressed pellets at nominal densities of 313 ± 8 kg/m 3 and 1030 ± 4 kg/m 3 , respectively. The boundary temperature of our aluminum confinement cylinder was ramped in 10 minutes from room temperature to a prescribed set-point temperature ranging between 448 nd 468 K and held at the set-point temperature until ignition. A universal cookoff model (UCM) has been calibrated using the ε-CL-20 SITI data to predict pressurization and thermal ignition of ε-CL-20. The ignition model was validated by using one-dimensional time-to-explosion (ODTX) ignition data from a different laboratory. We found that a thirtyfold increase in the reaction rates due to liquefaction at 520 K could explain the high temperature ODTX cookoff data. The model gives a plausible explanation of why melting is important in fast cookoff events involving CL-20. Our model also gives support to 520 K as the liquefaction point of CL-20, which has different values in the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Validation of the Community Land Model Version 5 over the Contiguous United States (CONUS) using in-situ and remote sensing datasets

The Community Land Model (CLM) is an effective tool to simulate the biophysical and biogeochemical processes and their interactions with the atmosphere. Although CLM Version 5 (CLM5) constitutes various updates in these processes, its performance in simulating energy, water and carbon cycles over the Contiguous United States (CONUS) at scales which land surface changes and hydrometeorological and hydroclimatological applications are more locally relevant is yet to be assessed. In this study, we conducted three simulations at 0.125? during 1979-2018 over the CONUS using different configurations of CLM, namely CLM5-biogeochemistry (CLM5BGC), CLM4.5BGC, and CLM5-satellite phenology (CLM5SP). We validated and compared their simulations against multiple remote-sensed and in-situ datasets. Overall, the parametric and structural updates (e.g., carbon cost for nitrogen uptake, variable soil thickness, dry surface layer) in CLM5 improve its ability in capturing terrestrial biogeochemical dynamics. The low evapotranspiration in CLM5BGC is associated with biases in simulating vegetation phenological characteristics rather than soil water limitations. The mismatch between CLM5BGC-simulated peak leaf area index and reference data can be attributed to CLM5BGC's inability in simulating phenology of trees and grasses. The differences between CLM-simulated irrigation and reference estimates can be attributed to differences between processes represented in models and in reality, and uncertainties in input and validation datasets. Evaluation against observations at small catchments suggest that hydrologic parameters needed to be calibrated to improve simulations of runoff, especially subsurface runoff. Additional efforts are needed to incorporate spatially-distributed plant phenology and physiology parameters and regional-specific agricultural management practices (e.g., planting, harvest).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Accelerated Creep Test Qualification of Creep-Resistance Using the Wilshire–Cano–Stewart Constitutive Model and Stepped Isostress Method

In this paper, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire–Cano–Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing is a long-term continuous process; in fact, the ASME B&PV III requires that 10,000+ h of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The SSM has been developed, which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750 °C and predictions are compared to conventional creep testing data. The WCS model has proven to make long-term predictions for stress-rupture, MCSR, creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are postaudit validated using the National Institute of Material Science database. Similarly, the MCSR predictions are compared from previous studies. Finally, the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and industrial gas turbines.

42 ENGINEERING↗
DOE OSTI2026

Deflagration to Detonation Transition Update: XDDT Code Modularization

A legacy FORTRAN 77 implementation of the Baer–Nunziato two-phase mixture theory for deflagration-to-detonation transition (DDT) in reactive granular materials—hereafter the XDDT (eXplosive DDT) code—has been modularized to Fortran 90 with modular structure, external input files, and adaptive mesh capability. During validation, two code defects were identified and corrected: an inconsistency in the nodal solid pressure evaluation and a nonphysical burn-front tracking criterion. The ignition criterion was also corrected to use the granular surface temperature from the interface heat transfer model, matching the original Baer implementation. An initial attempt to validate against Figure 3 of the original Baer and Nunziato (1986) paper revealed that the code’s detonation velocity on a 201-node mesh (5.5 km/s) was approximately 21% below the expected Chapman–Jouguet value for 70% TMD HMX (∼7 km/s). Validation was redirected to the piston-driven DDT experiments of McAfee et al. (1989), Shot B-9036, for which well-characterized ionization-pin data are available. With the compaction-burn coefficient calibrated to 𝐶 𝛼 = 75, the XDDT code reproduces the DDT transition time to within 0.4% and produces a steady-state detonation velocity within 4% of the McAfee experimental value of 6.36 km/s. The burn model was generalized to support pressure-dependent exponents, enabling application to nitrocellulose-based ball propellants (TS3659) with a cube-root pressure dependence. Validation against the Sandusky/Baer PDC82 piston-impact experiment yielded a reactive wave velocity of 2.3–2.8 km/s, in good agreement with the experimental value of ∼2.2 km/s, and wave coalescence within 5% of the experimental timing. The mathematical model, input parameter requirements, and a roadmap for extending XDDT to PETN with an autocatalytic burn model are presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Accelerated Creep Testing of Inconel 718 Using the Stepped Isostress Method (SSM)

This paper demonstrates the stepped isostress method (SSM); an accelerated creep test (ACT) for the rapid assessment of metallic materials. The SSM test is based on the time-temperature-stress superposition principle (TTSSP) where temperature and/or stress are step increased to accelerate the time-to-rupture. The SSM test has proven successful for the ACT of polymers and polymeric composites but has yet to be proven for metallic materials. In this study, new test matrix design rules for the SSM of metals are established based on deformation mechanism, time-temperature transformation, and time-temperature precipitation maps. A test matrix of SSM and conventional creep tests (CCTs) are executed for alloy Inconel 718 at 750°C (1382°F) with stress levels ranging from 100 to 350 MPa. Validation CCT data is gathered from the Japan National Institute of Material Science (NIMS). Material constants for the Sine-hyperbolic (Sinh) constitutive model are calibrated using the SSM data and employed to predict the conventional creep response. Here, when blindly compared to the CCT data, the SSM calibrated Sinh model can accurately predict the conventional creep response across logarithmic decades and thus accelerate the capture of conventional creep data. Fractography indicates ductile fracture by transgranular microvoid coalescence (TMVC) with the same fracture mode observed in both SSM and CCT specimens. Creep cavitation is indicated by the population, smoothness, and size of microvoids.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bayesian discovery of optimal reduced order models from mechanistic and experimental data: A case study of Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles rely on a silicon carbide (SiC) layer as the primary structural material and barrier to metallic fission products (FPs) release. Accurate prediction of palladium (Pd) transport and penetration is therefore critical for qualifying TRISO fuels for advanced reactors. The empirical correlation for Pd penetration in BISON is derived from historical particle-fuel data, but cannot explain the large scatter in the experimental data that arises from varying experimental conditions. To aid fuel qualification, we previously developed a mechanistic reduced order model (ROM) using BISON that resolves these dependencies. Here, in this work we build on that mechanistic ROM and perform validation and quantify its uncertainty using Bayesian uncertainty quantification (UQ). calibration against a suite of in-pile and out-of-pile experiments spanning particle compositions, geometries, and operating conditions, and we benchmark it against the empirical correlation. Bayesian UQ identifies influential parameters, calibrates them to data, and yields predictive intervals. Results show that while the empirical correlation can be tuned to fit a single experiment type, it transfers poorly; the mechanistic ROM sustains accuracy with credible uncertainty across disparate conditions. This demonstrates a practical path—via Bayesian UQ applied to mechanistic ROMs—to leverage single-effect experiments for inferring in-reactor behavior and supporting TRISO fuel qualification.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗