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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 415 records · Page 23

Application of machine learning techniques for fast MeV x-ray spectra unfolding from filter stack spectrometer data

Recovery of MeV x-ray spectra from detector signals is difficult because the response matrix inversion is ill-conditioned and current methods are too slow for high-repetition-rate experiments. In this work, we make use of neural networks to unfold MeV x-ray spectra from measurements obtained with a filter stack spectrometer at rates of near 40 Hz. The neural network was trained on synthetic data and tested on both synthetic and experimental data, the latter obtained in two separate experiments performed at the Omega EP laser facility. We show here that this unfolding method has good performance on synthetic data and that it is a promising option for experimental data of up to 40 MeV. The accuracy on experimental data is verified by using a simple forward model to compare against measured values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nuclear Structure and Decay Data for A=169 Isobars

Experimental data pertaining to all nuclei with mass number A=169 (Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, Hf, Ta, W, Re, Os, Ir, Pt) have been evaluated. Level schemes from both radioactive decay and reaction studies are presented, along with associated tables of experimental data and adopted properties for levels and γ rays. The present evaluation for A=169 supersedes the 2008 evaluation, 2008Ba31, by C.M. Baglin. A few highlights of this evaluation: More extensive work on ε decay from 169W is needed and new experimental work will be required to resolve a discrepancy between the J π values deduced for a 180-keV level in 169Ta based on extensive band structure from (HI,xnγ) work (J π =1/2−) and TDPAD measurements (J=5/2). Low lying states of 169Os were studied via fine structure of 173Pt α decay in 2014ThZZ. The Eαs feeding the g.s. of 169Os in 2008Ba31 are separated well into two consistent groups to feed the g.s. and the newly proposed state at 34.84 keV. Based on the studies of 2014ThZZ and 2021Zh52, the g.s. spin-parity assignment of 169Os has been proposed to be (7/2−) from (5/2−). The 169Ir g.s. half-life and alpha emission branching reported in 2012Th13 from 173Au α decay measurements are preferred over the values in 2005Sc22. The reported half-life value in 2005Sc22 for 169Ir g.s. is discrepant and the research work was carried out in the same lab of 2012Th13.

Basunia, M Shamsuzzoha↗

Comprehensive Assessment of the Accuracy of the Ideal Adsorbed Solution Theory for Predicting Binary Adsorption of Gas Mixtures in Porous Materials

Quantifying the adsorption of chemical mixtures in porous adsorbents is critical to developing these materials for useful separation applications. The ideal adsorbed solution theory (IAST) is the most widely applied mixing theory for predicting mixture adsorption using single-component adsorption data, but a perceived lack of experimental data has limited previous efforts to explore the accuracy of IAST in a systematic way. In this paper, we take advantage of a large collection of binary experimental data for gas adsorption that became available recently to tackle this issue. Specifically, we identify more than 400 examples in which binary adsorption data and single-component data are available in the same publication and apply IAST to all these examples. This analysis includes experimental data from 63 gas mixtures of 37 different molecular species and 174 different adsorbents. In addition to being the most systematic evaluation to date of the accuracy of IAST for gas adsorption, these data will be valuable for future efforts to test or develop mixing theories that improve upon IAST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resolving Discrepancies between State-of-the-Art Theory and Experiment for HO 2 + HO 2 via Multiscale Informatics

Recent high-level theoretical calculations predict a mild temperature dependence for HO 2 + HO 2 inconsistent with state-of-the-art experimental determinations that upheld the stronger temperature dependence observed in early experiments. Via MultiScale Informatics analysis of the theoretical and experimental data, we identified an alternative interpretation of the raw experimental data that uses HO 2 + HO 2 rate constants nearly identical to theoretical predictions---implying that the theoretical and experimental data are actually consistent, at least when considering the raw data from experimental studies. Here, similar analyses of typical signals from low-temperature experiments indicate that an HOOOOH intermediate---identified by recent theory but absent from earlier interpretations---yields modest effects that are smaller than, but may have contributed to, the scatter in data among different experiments. More generally, the findings demonstrate that modern chemical theories and experiments have progressed to a point where meaningful comparison requires joint consideration of their data simultaneously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗

A Semi-Detailed Pyrolytic Gas-Phase Kinetic Model for the Volatiles of Polyethylene Thermal Degradation

This work presents a semi-detailed kinetic model to address the pyrolytic gas-phase reactivity of volatiles formed during thermal degradation of polyethylene (PE). The model builds on a validated multi-step condensed-phase model and employs validated lumping approaches. Short-chain compounds are modelled with high detail, while long-chain ones are described by surrogate species representative of diesel-cuts (NC16H32) and waxes (NC30H60). The reactivity of short chains is described through the comprehensive CRECK kinetic model, updated to align C5-C7 olefins based on recent literature experimental data. Due to the lack of experimental data for longer olefins, their reactivity is modeled by analogy to the shorter ones, ensuring an asymptotic behavior with increasing carbon numbers. The semi-detailed model is validated through experimental data on PE pyrolysis, assuming an instantaneous mixing of the inert inlet flow with released volatiles, followed by a segregated plug-flow behavior. Validation across different reactor setups confirms the model’s capability to predict detailed product distributions. Despite minor discrepancies, the proposed model effectively captures experimental trends. Further work will address modelling the reactivity in oxygen-containing environments.

kinetics↗

Computational Simulations of Convergent Nozzles for the AIAA 1st Propulsion Aerodynamics Workshop

Computational Fluid Dynamics (CFD) simulations were completed for a series of convergent nozzles in participation of the American Institute of Aeronautics and Astronautics (AIAA) 1st Propulsion Aerodynamics Workshop. The simulations were performed using the Wind-US flow solver. Discharge and thrust coefficients were computed for four axisymmetric nozzles with nozzle pressure ratios (NPR) ranging from 1.4 to 7.0. The computed discharge coefficients showed excellent agreement with available experimental data; the computed thrust coefficients captured trends observed in the experimental data, but over-predicted the thrust coefficient by 0.25 to 1.0 percent. Sonic lines were computed for cases with NPR >= 2.0 and agreed well with experimental data for NPR >= 2.5. Simulations were also performed for a 25 deg. conic nozzle bifurcated by a flat plate at NPR = 4.0. The jet plume shock structure was compared with and without the splitter plate to the experimental data. The Wind-US simulations predicted the shock structure well, though lack of grid resolution in the plume reduced the sharpness of the shock waves. Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations and Detached Eddy Simulations (DES) were performed at NPR = 1.6 for the 25 deg conic nozzle with splitter plate. The simulations predicted vortex shedding from the trailing edge of the splitter plate. However, the vortices of URANS and DES solutions appeared to dissipate earlier than observed experimentally. It is believed that a lack of grid resolution in the region of the vortex shedding may have caused the vortices to break down too soon

DES↗

Comparisons of two-dimensional shock-expansion theory with experimental aerodynamic data for delta-planform wings at high supersonic speeds

An investigation has been conducted to explore the potential for optimizing airfoil shape at high supersonic speeds by utilizing the two-dimensional shock-expansion method. Theoretical and experimental force and moment coefficients are compared for four delta-planform semispan wings having a leading-edge sweep angle of 65 deg and incorporating modified diamond airfoils with a thickness-chord ratio of 0.06. The wings differ only in airfoil maximum-thickness position and camber. The experimental data are obtained at Mach numbers of 3.95 and 4.63 and at a Reynolds number of 9.84 million per meter. A relatively simple method is developed for predicting, in terms of lift-drag ratio, the optimum modified diamond airfoil at high supersonic and hypersonic speeds.

Jernell, L. S.↗

The nucleardatapy toolkit for simple access to experimental nuclear data, astrophysical observations, and theoretical predictions

Systematic comparisons across theoretical predictions for the properties of dense matter, nuclear physics data, and astrophysical observations (also called meta-analyses) are performed. Existing predictions for symmetric nuclear and neutron matter properties are considered, and they are shown in this paper as an illustration of the present knowledge. Asymmetric matter is constructed assuming the isospin asymmetry quadratic approximation. It is employed to predict the pressure at twice saturation energy-density based only on nuclear-physics constraints, and we find it compatible with the one from the gravitational-wave community. To make our meta-analysis transparent, updated in the future, and to publicly share our results, the Python toolkit nucleardatapy is described and released here. Hence, this paper accompanies nucleardatapy, which simplifies access to nuclear-physics data, including theoretical calculations, experimental measurements, and astrophysical observations. This Python toolkit is designed to easily provide data for: (i) predictions for uniform matter (from microscopic or phenomenological approaches); (ii) correlation among nuclear properties induced by experimental and theoretical constraints; (iii) measurements for finite nuclei (nuclear chart, charge radii, neutron skins or nuclear incompressibilities, etc.) and hypernuclei (single particle energies); and (iv) astrophysical observations. This toolkit provides data in a unified format for easy comparison and provides new meta-analysis tools. It will be continuously developed, and we expect contributions from the community in our endeavor.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗

Computational Fluid Dynamics Simulations of the Transonic Dynamics Tunnel Airstream Oscillator System

This paper presents a Computational Fluid Dynamics (CFD) model of the flow in the NASA Langley Research Center Transonic Dynamics Tunnel (TDT) with the Airstream Oscillator System (AOS) in operation. The TDT is a continuous-flow, closed circuit wind tunnel with a 16- by 16-foot slotted test section with cropped corners. The tunnel was originally built as the 19-ft Pressure Tunnel in 1938, but it was converted to the current transonic tunnel in the 1950s, with capabilities to use either air or heavy gas (R-134a) as the test medium. The TDT was also fitted with an AOS which can be used to create a gust field in the test section. To date, no computational analyses of the TDT involving the AOS have been performed. In this study, experimental data acquired of an oscillating airstream in the tunnel will be used to calibrate the computational analyses. A significant motivation of this work is to attempt to compare computational gust velocities to those recorded in the TDT literature. In addition to a validation of this model with experimental data, it may also be possible to supplement the experimental data with computational data. The experimental data is rather sparse and at only a few Mach numbers. Computational results may be able to expand the AOS data set. Another motivation for this work is that the Integrated Adaptive Wing Technology Maturation (IAWTM) semi-span model of the high-aspect-ratio CRM with 10 trailing edge control surfaces is currently being fabricated and will be delivered to the NASA Langley Transonic Dynamics Tunnel (TDT) for testing in late 2020. Among tests to be conducted, gust load alleviation (GLA) will be demonstrated at transonic conditions using the AOS.

Computational Fluid Dynamics↗

SPRUCE Outflow Chemistry Data for Experimental Plots Beginning in 2016

This data set includes the chemistry of outflow waters in the SPRUCE experiment plots located in the S1 bog of the USDA Forest Service Marcell Experimental Forest (MEF) in northern Minnesota, 40 km north of Grand Rapids. These data are post-treatment data from the warming and elevated carbon dioxide (CO2) treatments associated with the SPRUCE experiment. There are ten experimental plots in SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). Sample collection and analyses started in March of 2016 and will continue for the duration of the experiment. Samples were analyzed for pH, specific conductivity, anion concentrations (chloride, sulfate), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), and total organic carbon (TOC) concentrations. Subsets of the samples have been analyzed for natural-abundance stable isotopes of water (δ18O-H2O and δD-H2O), dissolved carbon dioxide (δ13C-CO2), and dissolved methane (δ13C-CH4), and concentrations of total mercury (Thg), methylmercury (MeHg), ferrous iron (Fe2+), ferric iron (Fe3+), dissolved inorganic carbon (DIC), and dissolved methane (CH4).

54 ENVIRONMENTAL SCIENCES↗

Thermoelastic vibration test techniques

The structural integrity of proposed high speed aircraft can be seriously affected by the extremely high surface temperatures and large temperature gradients throughout the vehicle's structure. Variations in the structure's elastic characteristics as a result of thermal effects can be observed by changes in vibration frequency, damping, and mode shape. Analysis codes that predict these changes must be correlated and verified with experimental data. The experimental modal test techniques and procedures used to conduct uniform, nonuniform, and transient thermoelastic vibration tests are presented. Experimental setup and elevated temperature instrumentation considerations are also discussed. Modal data for a 12 by 50 inch aluminum plate heated to a temperature of 475 F are presented. These data show the effect of heat on the plate's modal characteristics. The results indicated that frequency decreased, damping increased, and mode shape remained unchanged as the temperature of the plate was increased.

Kehoe, Michael W.↗

Thermoelastic vibration test techniques

The structural integrity of proposed high speed aircraft can be seriously affected by the extremely high surface temperatures and large temperature gradients throughout the vehicle's structure. Variations in the structure's elastic characteristics as a result of thermal effects can be observed by changes in vibration frequency, damping, and mode shape. Analysis codes that predict these changes must be correlated and verified with experimental data. The experimental modal test techniques and procedures used to conduct uniform, nonuniform, and transient thermoelastic vibration tests are presented. Experimental setup and elevated temperature instrumentation considerations are also discussed. Modal data for a 12 by 50 inch aluminum plate heated to a temperature of 475 F are presented. These data show the effect of heat on the plate's modal characteristics. The results indicated that frequency decreased, damping increased, and mode shape remained unchanged as the temperature of the plate was increased.

Kehoe, Michael W.↗

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

7075-T6 and 2024-T351 Aluminum Alloy Fatigue Crack Growth Rate Data

Experimental test procedures for the development of fatigue crack growth rate data has been standardized by the American Society for Testing and Materials. Over the past 30 years several gradual changes have been made to the standard without rigorous assessment of the affect these changes have on the precision or variability of the data generated. Therefore, the ASTM committee on fatigue crack growth has initiated an international round robin test program to assess the precision and variability of test results generated using the standard E647-00. Crack growth rate data presented in this report, in support of the ASTM roundrobin, shows excellent precision and repeatability.

Forth, Scott C.↗

Assessing the ASME Section III, Division 5, Class A Primary Load Design Rules Against Creep Notch Effects

This report assesses the ASME Section III, Division 5, Subsection HB, Subpart B rules covering the design and construction of high temperature Class A nuclear reactor components for their robustness against creep notch effects. The creep notch effect combines the effect of multiaxial stresses on material creep deformation and damage. This report considers both effects, including the potential for creep mechanism shifts affecting the extrapolation of design data from high stress, short-time experimental data to low stress, long time operating component conditions. The report summarizes the history of and literature on multiaxial creep and surveys the current ASME design rules dealing with multiaxial effects. The report then describes the results of two dedicated numerical studies, one assessing the robustness of the ASME rules against uncertainty in extrapolating from uniaxial creep test data to multiaxial component conditions and a second study examining the potential effects of a mechanism shift from high stress, dislocation-mediated creep to diffusion-dominated creep at lower stresses. The final conclusion of the report is that the ASME rules adequately guard against multiaxial creep failure, though there are several aspects of the Code that could be optimized to provide less over-conservative design predictions or to provide a more consistent design margin as a function of temperature and stress. In a few areas, particularly the potential for mechanism shifts outside the currently-available experimental data, the Code rules should be revaluated as additional experimental data and new modeling and simulation results become available

22 GENERAL STUDIES OF NUCLEAR REACTORS↗