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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Precise neutron inelastic cross section measurements

The design of a new generation of nuclear reactors requires the development of a very precise neutron cross section database. Ongoing experiments performed at dedicated facilities aim to the measurement of such cross sections with an unprecedented uncertainty of the order of 5% or even smaller. We give an overview of such a facility: the Gamma Array for Inelastic Neutron Scattering (GAINS) installed at the GELINA neutron source of IRMM, Belgium. Some of the most challenging difficulties of the experimental approach are emphasized and recent results are shown.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests. The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Impact of n > 1 neoclassical tearing modes on fast ions, plasma rotation, and the onset of disruptive tearing modes in DIII-D ITER baseline scenario

We present integrated TRANSP-kick analyses quantitatively characterizing how n > 1 magnetic islands redistribute fast ions (FIs) and modify momentum balance in low-torque DIII-D H-mode scenarios operated with the ITER normalized parameter set and shape (ITER baseline scenario, or IBS). In this plasma scenario, disruptive neoclassical tearing modes (NTMs) are most commonly seeded by nonlinear 3-wave coupling when the differential rotation between the q = 1 and q = 2 surfaces ($δf_{1, 2}$) approaches zero. Analysis of a DIII-D IBS database of shots unstable to the 2/1 NTM demonstrates that the flattening rotation profile is correlated with n > 1 NTM amplitude growth, with a strong drop in $δf_{1, 2}$ occurring when the radial magnetic perturbation amplitude at the rational surface ($δB$ r s ) is estimated to be about 20 G. The interpretive TRANSP-kick simulations show that the experimentally observed reduction in core rotation is due to the fast-ion kicks. Nonlinearity in momentum losses versus NTM amplitude is found to be correlated with overlap of FI island chains, occurring when $δB$ r s is about 35 G, in rough agreement with the experimental results. This agreement suggests the primary mechanism for the conductive momentum loss in the core is due to chaotic FI orbits and FI losses developing from overlapping resonant FI island chains.

ITER baseline scenario↗
DOE OSTI2020

Improved Models of Long-Term Creep Behavior of High Performance Structural Alloys

In this program, QuesTek Innovations LLC, a leader in the field of computational materials design, proposes to develop a robust creep-modeling toolkit that expands its computational Materials by Design® technology, in order to predict the long-term creep performance of materials for base alloys and weldments in fossil energy systems under wide thermal and mechanical conditions. The Material Database Group of NIMS (National Institute for Material Science, JAPAN) provides reliable public data for long-term creep behavior over 300,000 hours (> 34 years) for a variety of materials including high Cr steels along with seminal work performed by EPRI (Electric Power Research Institute) on creep failure of these steels. QuesTek would rely on these premier institutions for experimental data needed to calibrate models. The developed tool has wider applications than the state-of-the-art modeling tools. It includes the effects of chemistry variations, microstructure variation (weldments) etc .which is lacking in many available models requiring the model to be calibrated to large number of datasets for accurate predictions. A model based on fundamental mechanism has promises in application to different materials, other than the demonstrated material (Grade 91 steels) in the current program. As a result of such an effort, we envision greatly advancing the state-of-the-art modeling tools for creep life assessments of different materials.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2003

Thermal Response of Cooled Silicon Nitride Plate Due to Thermal Conductivity Effects Analyzed

Lightweight, strong, tough high-temperature materials are required to complement efficiency improvements for next-generation gas turbine engines that can operate with minimum cooling. Because of their low density, high-temperature strength, and high thermal conductivity, ceramics are being investigated as materials to replace the nickelbase superalloys that are currently used for engine hot-section components. Ceramic structures can withstand higher operating temperatures and a harsh combustion environment. In addition, their low densities relative to metals help reduce component mass (ref. 1). To complement the effectiveness of the ceramics and their applicability for turbine engine applications, a parametric study using the finite element method is being carried out. The NASA Glenn Research Center remains very active in conducting and supporting a variety of research activities related to ceramic matrix composites through both experimental and analytical efforts (ref. 1). The objectives of this work are to develop manufacturing technology, develop a thermal and environmental barrier coating (TBC/EBC), develop an analytical modeling capability to predict thermomechanical stresses, and perform a minimal burner rig test on silicon nitride (Si3N4) and SiC/SiC turbine nozzle vanes under simulated engine conditions. Moreover, we intend to generate a detailed database of the material s property characteristics and their effects on structural response. We expect to offer a wide range of data since the modeling will account for other variables, such as cooling channel geometry and spacing. Comprehensive analyses have begun on a plate specimen with Si3N4 cooling holes.

Baaklini, George Y.↗
NASA NTRS2014

Advanced Modeling and Uncertainty Quantification for Flight Dynamics; Interim Results and Challenges

As part of the NASA Vehicle Systems Safety Technologies (VSST), Assuring Safe and Effective Aircraft Control Under Hazardous Conditions (Technical Challenge #3), an effort is underway within Boeing Research and Technology (BR&T) to address Advanced Modeling and Uncertainty Quantification for Flight Dynamics (VSST1-7). The scope of the effort is to develop and evaluate advanced multidisciplinary flight dynamics modeling techniques, including integrated uncertainties, to facilitate higher fidelity response characterization of current and future aircraft configurations approaching and during loss-of-control conditions. This approach is to incorporate multiple flight dynamics modeling methods for aerodynamics, structures, and propulsion, including experimental, computational, and analytical. Also to be included are techniques for data integration and uncertainty characterization and quantification. This research shall introduce new and updated multidisciplinary modeling and simulation technologies designed to improve the ability to characterize airplane response in off-nominal flight conditions. The research shall also introduce new techniques for uncertainty modeling that will provide a unified database model comprised of multiple sources, as well as an uncertainty bounds database for each data source such that a full vehicle uncertainty analysis is possible even when approaching or beyond Loss of Control boundaries. Methodologies developed as part of this research shall be instrumental in predicting and mitigating loss of control precursors and events directly linked to causal and contributing factors, such as stall, failures, damage, or icing. The tasks will include utilizing the BR&T Water Tunnel to collect static and dynamic data to be compared to the GTM extended WT database, characterizing flight dynamics in off-nominal conditions, developing tools for structural load estimation under dynamic conditions, devising methods for integrating various modeling elements into a real-time simulation capability, generating techniques for uncertainty modeling that draw data from multiple modeling sources, and providing a unified database model that includes nominal plus increments for each flight condition. This paper presents status of testing in the BR&T water tunnel and analysis of the resulting data and efforts to characterize these data using alternative modeling methods. Program challenges and issues are also presented.

Hyde, David C.↗
NASA NTRS2019

Experimental Aerodynamic Simulation of Scallop Ice Accretion on a Swept Wing

Understanding the aerodynamic impact of swept-wing ice accretions is a crucial component of the design of modern aircraft. Computer-simulation tools are commonly used to approximate ice shapes, so the necessary level of detail or fidelity of those simulated ice shapes must be understood relative to high-fidelity representations of the ice. Previous tests were performed in the NASA Icing Research Tunnel to acquire high-fidelity ice shapes. From this database, full-span artificial ice shapes were designed and manufactured for both an 8.9%-scale and 13.3%-scale semispan wing model of the CRM65 which has been established as the full-scale baseline for this swept-wing project. These models were tested in the Walter H. Beech wind tunnel at Wichita State University and at the ONERA F1 facility, respectively. The data collected in the Wichita St. University wind tunnel provided a low-Reynolds number baseline study while the pressurized F1 facility produced data over a wide range of Reynolds and Mach numbers with the highest Reynolds number studied being approximately Re=11.9x106. Past work focused on only three different fidelity variations for ice shapes based on multiple icing conditions. This work presents a more detailed investigation into several fidelity representations of a single highly three-dimensional scallop ice accretion. Sensitivity to roughness size and application technique on a low-fidelity smooth ice shape is described. The data indicate that the aerodynamic performance is not especially sensitive to the grit variations. An ice accretion code was also used to generate ice shapes for aerodynamic testing and comparisons. These ice shapes have a general appearance like the low-fidelity smooth ice shapes, but in this case, the computer-generated ice shape is significantly smaller. As such, the impact of that ice shape on the aerodynamic performance of the wing is reduced compared to the smooth ice shape based on the icing experiment for those same conditions. Spanwise discontinuities were also introduced to a low-fidelity ice shape in an attempt to quantify the impact of those variation in the high-fidelity ice shape. While the lift data indicate good agreement between the high-fidelity ice shapes and the low-fidelity ice shapes and the low-fidelity ice shapes with spanwise discontinuities, a closer investigation of the data suggests potential, significant differences in the flowfield. These results were similar at both facilities over the wide range of test conditions utilized.

Woodard, Brian↗
DOE OSTI2019

Investigation of in situ high temperature sensor based on the direct absorption spectroscopy signal of ammonia gas for coal-fired power plant

The selective catalytic reduction and non-selective catalytic reduction (SCR/SNCR) are the most popular de-NOx processes for coal-fired power plant, where the real-time temperature is a significant parameter. A new developed tunable diode laser spectroscopy used for measuring the temperature of ammonia (NH{sub 3}) in the process of SCR/SNCR influenced by strong exhaust gas matrices CO{sub 2} and H{sub 2}O was presented in this paper. Two lines near 6605 cm{sup −1} were selected, with rather weak temperature dependency and minimal interface from CO{sub 2} and H{sub 2}O according to HITRAN12 database. A homemade heating equipment for high temperature laser spectroscopy measurement was developed based on an ARM microcontroller. The temperature calibration experiments of absorption lines were carried out at variable concentrations under different temperatures. The spectral signals of 2.5%, 3.5% and 4.5% NH{sub 3} were observed for validation of the generalization and robustness of the sensor. The calibration and validation experimental results show that the maximum measurement error and global average error of the temperature sensor with the temperature ranging from 453 to 653 K are less than 2% and 1.38%, respectively. It demonstrates that our proposed sensor with high accuracy and linearity, and can be utilized to measure the temperature in SNCR/SCR process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Nuclear Data Sheets for A = 192

Experimental structure and decay data for all nuclei with mass A=192 (Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb, Bi, Po, At) have been evaluated. This evaluation, covering data received by 15 June 2012, supersedes the 1998 evaluation by C. M. Baglin (Nuclear Data Sheets84, 717 (1998), literature cutoff August 1998) and the subsequent inclusion in the ENSDF database of the new nuclide {sup 192}At (C. M. Baglin, literature cutoff 16 May 2006). It also incorporates the current evaluation of superdeformed-band information by B. Singh. Since the last publication, {sup 192}Ta, {sup 192}W and {sup 192}At have been observed, and an isomeric state has been identified in {sup 192}Re. The {epsilon} decay of {sup 192}Au has been studied using a multidetector array resulting in an extensively revised level scheme for {sup 192}Pt.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Universal fragment descriptors for predicting properties of inorganic crystals

Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction’s accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules.

Science & Technology - Other Topics↗
DOE OSTI2021

Data-driven profile prediction for DIII-D

A new, fully data-driven algorithm has been developed that uses neural networks to predict plasma pro les on a scale of τ E into the future given actuators and the present plasma state. The model was trained and tested on DIII-D data from the 2013-2018 experimental campaigns. The model is accurate on average, with q predictions the worst and pressure predictions the best. The model can run in milliseconds and is very simple to use. This makes it a potentially useful tool for operators and physicists when planning plasma scenarios. It also is a candidate for doing phase-space exploration without going through the DIIID database or complicated and computationally expensive simulation codes. Here, a reduced model using only realtime diagnostics has also been developed and formed the basis for a model-predictive control algorithm implemented and successfully tested on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

KOMPASS: Compaction of crushed salt for the safe containment

In Germany, rock salt formations are a possible host rock taken into account for the safe disposal of heat-emitting radioactive waste. With respect to crushed salt will be used in the repository for backfilling of open cavitied (using dry material). With time, the crushed salt will be compacted by the convergence of the host rock and reaches porosities comparable with the rock salts. The compaction behaviour of crushed salt has been investigated within the last 40 years, however, its behaviour at low porosities and the resulting low permeabilities becomes relevant with the introduction of the approach of the containment providing rock zone. In the current state, the database and process understanding have some important gaps in knowledge referring the material behaviour, existing laboratory and numerical models, especially for the porosity range. The objective of this project was the development of methods and strategies for the reduction of deficits in the prediction of crushed salt compaction leading to an improvement of the prognosis quality. It includes the development of experimental methods for determining crushed salt properties in the range of low porosities, the enhancement of process understanding and the investigation and development of existing numerical models.

Crushed salt compaction↗
DOE OSTI2020

ENDF/B-VIII.0 Augmented Covariance Data The first iteration [Slides]

Nuclear data are necessary for reliable modeling and simulation of the next generation of nuclear reactors. However, the variation in the ratio of the computed to experimental values (C/E) for certain types of nuclear systems is much less than predicted by evaluated nuclear data file (ENDF)/B covariances. Figure 1 provides an example of a set of metal-plutonium-fueled, fast-spectrum (PU-MET-FAST) integral experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) in the Oak Ridge National Laboratory (ORNL) VALID database. The variation in the C/E values, shown with one standard deviation error bars, is 100% covered by both the SCALE and ENDB/VIII.0 covariance data. This is due to the comparisons to integral data that are essential during the evaluation process. However, the ENDF evaluations represent uncertainties and correlations in differential data only; they do not reflect the impact of the comparison to integral data in the covariance evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

ENDF/B-VIII.0 Augmented Covariance Data The first iteration [Slides]

Nuclear data are necessary for reliable modeling and simulation of the next generation of nuclear reactors. However, the variation in the ratio of the computed to experimental values (C/E) for certain types of nuclear systems is much less than predicted by evaluated nuclear data file (ENDF)/B covariances. Figure 1 provides an example of a set of metal-plutonium-fueled, fast-spectrum (PU-MET-FAST) integral experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) in the Oak Ridge National Laboratory (ORNL) VALID database. The variation in the C/E values, shown with one standard deviation error bars, is 100% covered by both the SCALE and ENDB/VIII.0 covariance data. This is due to the comparisons to integral data that are essential during the evaluation process. However, the ENDF evaluations represent uncertainties and correlations in differential data only; they do not reflect the impact of the comparison to integral data in the covariance evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2013

UV Lidar Receiver Analysis for Tropospheric Sensing of Ozone

A simulation of a ground based Ultra-Violet Differential Absorption Lidar (UV-DIAL) receiver system was performed under realistic daytime conditions to understand how range and lidar performance can be improved for a given UV pulse laser energy. Calculations were also performed for an aerosol channel transmitting at 3 W. The lidar receiver simulation studies were optimized for the purpose of tropospheric ozone measurements. The transmitted lidar UV measurements were from 285 to 295 nm and the aerosol channel was 527-nm. The calculations are based on atmospheric transmission given by the HITRAN database and the Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological data. The aerosol attenuation is estimated using both the BACKSCAT 4.0 code as well as data collected during the CALIPSO mission. The lidar performance is estimated for both diffuseirradiance free cases corresponding to nighttime operation as well as the daytime diffuse scattered radiation component based on previously reported experimental data. This analysis presets calculations of the UV-DIAL receiver ozone and aerosol measurement range as a function of sky irradiance, filter bandwidth and laser transmitted UV and 527-nm energy

Pliutau, Denis↗
DOE OSTI2019

ENDF/B-VIII.0 Augmented Covariance Data: The first iteration

Nuclear data are necessary for reliable modeling and simulation of the next generation of nuclear reactors. However, the variation in the ratio of the computed to experimental values (C/E) for certain types of nuclear systems is much less than predicted by evaluated nuclear data file (ENDF)/B covariances. Figure 1 provides an example of a set of metal-plutonium-fueled, fast-spectrum (PU-MET-FAST) integral experiments from the International Criticality Safety Benchmark Evaluation Project (ICSBEP) in the Oak Ridge National Laboratory (ORNL) VALID database. The variation in the C/E values, shown with one standard deviation error bars, is 100% covered by both the SCALE and ENDB/VIII.0 covariance data. This is due to the comparisons to integral data that are essential during the evaluation process. However, the ENDF evaluations represent uncertainties and correlations in differential data only; they do not reflect the impact of the comparison to integral data in the covariance evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Corrigendum to “Experimental Determination of Solubilities of Di-calcium Ethylenediaminetetraacetic Acid Hydrate [Ca 2 C 10 H 12 N 2 O 8 •7H 2 O(s)] in NaCl and MgCl 2 Solutions to High Ionic Strengths and Its Pitzer Model: Applications to Geological Disposal of Nuclear Waste and Other Low Temperature Environments”

In the published version (Xiong et al., 2017), there was an error for the reaction coefficient for the dissolution reaction of Ca 2 C 10 H 12 N 2 O 8 •7H 2 O(s) in the database used for the modeling. In the database for the modeling, the coefficient for water (i.e., 7H 2 O) was inadvertently omitted.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Advancing AI-Driven Analysis in X-ray Absorption Spectroscopy: Spectral Domain Mapping and Universal Models

In recent years, rapid progress has been made in developing artificial intelligence (AI) and machine learning (ML) methods for X-ray absorption spectroscopy (XAS) analysis. Compared to traditional XAS analysis methods, AI/ML approaches offer dramatic improvements in efficiency and help eliminate human bias. To advance this field, we advocate an AI-driven XAS analysis pipeline that features several interconnected key building blocks: benchmarks, workflows, databases, and AI/ML models. Specifically, we present two case studies for XAS ML. In the first study, we demonstrate the importance of reconciling the discrepancies between simulation and experiment using spectral domain mapping (SDM). Our ML model, which is trained solely on simulated spectra, predicts an incorrect oxidation state trend for Ti atoms in a combinatorial zinc titanate film. After transforming the experimental spectra into a simulation-like representation using SDM, the same model successfully recovers the correct oxidation state trend. In the second study, we explore the development of universal XAS ML models that are trained on the entire periodic table, which enables them to leverage common trends across elements. Looking ahead, we envision that an AI-driven pipeline can unlock the potential of real-time XAS analysis to accelerate scientific discovery.

36 MATERIALS SCIENCE↗