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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 OSTI2020

Data-driven predictive probability density function control of fiber length stochastic distribution shaping in refining process

Pulp is the most important raw material in paper in paper industries, whose Fiber Length Stochastic Distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the output FLSD shaping, which display non-Gaussian distribution properties. Therefore, the traditional control, method based on the mean and variance of fiber length is difficult to control the FLSD shaping effectively. In this paper, a novel data-driven predictive probability density function (PDF) control method is proposed for output FLSD shaping in refining process. Primarily, in order to improve the approximation accuracy of the PDF employing RBF neural network, the parameters (center value and width) of each RBF basis functions are tuned via utilizing iterative learning control (ILC) law, and the corresponding estimations of weights law can be obtained. Secondly, considering that the conventional linear model of weights vector has drawbacks of low accuracy and weak generalization ability, random vector functional link networks (RVFLNs) based data driven nonlinear modelling method is employed to characterize the prediction model between the input variables and weights vector. Finally, in order to reduce the randomness of the output FLSD, a minimum entropy control method under mean constraint is employed to design the predictive PDF controller for the output FLSD shaping with the help of the established nonlinear stochastic distribution model. Both simulations and experiments are given to illustrate the effectiveness and practicability of the proposed method.

Probability debsity function, Fiber length distrib↗
DOE OSTI2024

Accelerating the Discovery of New, Single Phase High Entropy Ceramics via Active Learning

High-entropy ceramics have garnered interest due to their remarkable hardness, compressive strength, thermal stability, and fracture toughness; yet the discovery of new high-entropy ceramics (out of a tremendous number of possible elemental permutations) still largely requires costly, inefficient, trial-and-error experimental and computational approaches. The entropy forming ability (EFA) factor was recently proposed as a computational descriptor that positively correlates with the likelihood that a 5-metal high-entropy carbide (HECs) will form the desired single phase, homogeneous solid solution; however, discovery of new compositions is computationally expensive. If you consider 8 candidate metals, the HEC EFA approach uses 49 optimizations for each of the 56 unique 5-metal carbides, requiring a total of 2744 costly density functional theory calculations. Here, we describe an orders-of-magnitude more efficient active learning (AL) approach for identifying novel HECs. To begin, we compared numerous methods for generating composition-based feature vectors (e.g., magpie and mat2vec), deployed an ensemble of machine learning (ML) models to generate an average and distribution of predictions, and then utilized the distribution as an uncertainty. Here we then deployed an AL approach to extract new training data points where the ensemble of ML models predicted a high EFA value or was uncertain of the prediction. Our approach has the combined benefit of decreasing the amount of training data required to reach acceptable prediction qualities and biases the predictions toward identifying HECs with the desired high EFA values, which are tentatively correlated with the formation of single phase HECs. Using this approach, we increased the number of 5-metal carbides screened from 56 to 15,504, revealing 4 compositions with record-high EFA values that were previously unreported in the literature. Our AL framework is also generalizable and could be modified to rationally predict optimized candidate materials/combinations with a wide range of desired properties (e.g., mechanical stability, thermal conductivity).

36 MATERIALS SCIENCE↗
NASA NTRS1971

Generation of Finite Life Distributional Goodman Diagrams for Reliability Prediction

The methodology of developing finite life distributional Goodman diagrams and surfaces is described for presenting allowable combinations of alternating stress and mean stress to the design engineer. The combined stress condition is that of an alternating bending stress and a constant shear stress. The finite life Goodman diagrams and surfaces are created from strength distributions developed at various ratios of alternating to mean stress at particular cycle life values. The conclusions indicate that the Von Mises-Hencky ellipse, for cycle life values above 1000 cycles, is an adequate model of the finite life Goodman diagram. In addition, suggestions are made which reduce the number of experimental data points required in a fatigue data acquisition program.

Kececioglu, D.↗
DOE OSTI2025

CFD modeling of natural circulation in LiCl-KCl molten salt closed loop

Characterizing flow within a molten salt closed-loop system is crucial for assessing system requirements, evaluating performance, and identifying potential flaws. Direct flow measurement using instrumentation is challenging due to extreme environmental conditions and the limitations associated with measuring molten salt flow under natural convection. Here, this study aims to provide comprehensive insights into the thermal-hydraulic behavior of a closed loop, with a particular focus on temperature distribution and velocity prediction. The Computational Fluid Dynamics (CFD) model demonstrated the capability to effectively simulate and predict both temperature distributions and flow velocities within the molten salt loop. The CFD model's predictive capability was validated by its ability to replicate temperature measurements under varying boundary conditions. The analysis revealed that the CFD model tends to underpredict temperatures in the cold leg and overpredict them in the hot leg, highlighting the need for continuous model refinement and acknowledging the limitations of using a steady-state approach. Furthermore, the potential of using external temperature measurements to estimate internal molten salt temperatures and predict flow velocity was explored, revealing that this approach could introduce up to a 5.5% error in flow velocity calculations. Line probes mapping temperature distributions across the tube's cross-section and molten salt provided valuable insights into temperature gradients, emphasizing the need for a thermal conductivity equation for molten salt with lower uncertainty to achieve more accurate temperature predictions of the system.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1980

A correlation method to predict the surface pressure distribution of an infinite plate or a body of revolution from which a jet is issuing

A correlation method to predict pressures induced on an infinite plate by a jet exhausting normal to the plate into a subsonic free stream was extended to jets exhausting at angles to the plate and to jets exhausting normal to the surface of a body revolution. The complete method consisted of an analytical method which models the blockage and entrainment properties of the jet and an empirical correlation which accounts for viscous effects. For the flat plate case, the method was applicable to jet velocity ratios up to ten, jet inclination angles up to 45 deg from the normal, and radial distances up to five diameters from the jet. For the body of revolution case, the method was applicable to a body at zero degrees angle of attack, jet velocity ratios 1.96 and 3.43, circumferential angles around the body up to 25 deg from the jet, axial distances up to seven diameters from the jet, and jet-to-body diameter ratios less than 0.1.

Perkins, S. C., Jr.↗
DOE OSTI2022

Dynamic Performance Comparison and Prediction based on Distribution-level Phasor Measurement Units

This paper introduces a new distribution level Phasor Measurement Unit (PMU) which adopts advanced hardware components and structure. The hardware parameters from the new PMU and the existing PMU are used to build a simulation model to predict the PMU performance. Therefore, a real-world testbench is built and four distribution level PMUs are tested under the steady-state and dynamic tests. The quantitative experiment result confirms the prediction model which could guide future PMU design, and also verifies the accuracy of the new PMU on the synchrophasor and frequency measurements in multiple scenarios.

Wu, Yuru↗
DOE OSTI2022

Sensitivity analysis for characterizing the impact of HNGD model on the prediction of hydrogen redistribution in Zircaloy cladding using BISON code

Hydrogen in zirconium cladding is able to precipitate into zirconium hydrides which impacts cladding integrity. The Hydride Nucleation-Growth-Dissolution (HNGD) model in the BISON code accounts for the precipitation and dissolution kinetics of hydride in Zircaloy material. This paper presents global sensitivity analyses of the HNGD model aiming to enhance our understanding of the hydride precipitation phenomena by quantifying the variance that key parameters have on the prediction of hydrogen behavior under various environmental conditions. Here, model predictions are compared to experimental data obtained under two different conditions: 1) with uniformly precharged specimens subjected to a linear thermal gradient, and 2) specimens precharged with a cathodically applied hydride rim at one end of the sample and subjected to an asymmetric thermal gradient. The Sobol sensitivity analysis identifies the key parameters in the HNGD model for both types of specimens. For linear temperature cases, the heat of transport dominates the accuracy of predictions when no precipitation occurs at the cold end, while Terminal Solid Solubility for Dissolution (TSSD) is the most important parameter when precipitation occurs. A large variation in the predicted hydrogen concentration profiles is found in the range of high TSSD due to the occurrence of precipitation. For asymmetric temperature cases, the solubility coefficient gives the largest impact on the predicted hydrogen distribution, as it determines the amount of solute hydrogen dissolved from the initially applied hydride rim. A large discrepancy in hydrogen distribution between simulations and experiments exists with the asymmetric specimens because BISON simulations fail to predict the precipitation of hydride at the cooler end. Comparative studies using former and updated models verifies the significant impact of the hydride growth mechanism on predicted hydrogen concentration profiles. In particular, when hydride initially exists, changes in TSSD generate a large variation in the predicted amount of precipitation by hydride growth, giving large uncertainty in predicting the hydrogen distribution over the sample length. The outputs characterize the significant impact of the hydride growth mechanism in the HNGD model on predicting hydrogen behavior, and improve the understanding of the precipitation of hydride in Zircaloy cladding within a range of expected environmental conditions. The analyses indicate work is still needed to improve the hydride solvus models in the BISON code to accurately predict experimentally observed hydride concentrations and distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Factorization for azimuthal asymmetries in SIDIS at next-to-leading power

Differential measurements of the semi-inclusive deep inelastic scattering (SIDIS) process with polarized beams provide important information on the three-dimensional structure of hadrons. Among the various observables are azimuthal asymmetries that start at subleading power, and which give access to novel transverse momentum dependent distributions (TMDs). Theoretical predictions for these distributions are currently based on the parton model rather than a rigorous factorization based analysis. Working under the assumption that leading power Glauber interactions do not spoil factorization at this order, we use the Soft Collinear Effective Theory to derive a complete factorization formula for power suppressed hard scattering effects in SIDIS. This yields generalized definitions of the TMDs that depend on two longitudinal momentum fractions (one of them only relevant beyond tree level), and a complete proof that only the same leading power soft function appears and can be absorbed into the TMD distributions at this order. We also show that perturbative corrections can be accounted for with only one new hard coefficient. Factorization formulae are given for all spin dependent structure functions which start at next-to-leading power. Prospects for improved subleading power predictions that include resummation are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Distribution of tessera terrain on Venus - Prediction for Magellan

Tessera terrain is the dominant tectonic unit in the northern hemisphere of Venus and is characterized by complex sets of intersecting structural trends and distinctive radar properties due to a high degree of meter and sub-meter scale (5 cm to 10 m) roughness. Based on these distinctive radar properties, a prediction of the global distribution of tessera can be made using Pioneer Venus (PV) reflectivity and roughness data. Where available, Benera 15/16 and Arecibo images and PV diffuse scattering data were used to evaluate the prediction. From this assessment, it is concluded that most of the regions with prediction values greater than 0.6 (out of 1) are likely to be tessera, and are almost certain to be techonically deformed.

Bindschadler, D. L.↗
NASA NTRS1991

Models of recurrent strike-slip earthquake cycles and the state of crustal stress

Numerical models of the strike-slip earthquake cycle, assuming a viscoelastic asthenosphere coupling model, are examined. The time-dependent simulations incorporate a stress-driven fault, which leads to tectonic stress fields and earthquake recurrence histories that are mutually consistent. Single-fault simulations with constant far-field plate motion lead to a nearly periodic earthquake cycle and a distinctive spatial distribution of crustal shear stress. The predicted stress distribution includes a local minimum in stress at depths less than typical seismogenic depths. The width of this stress 'trough' depends on the magnitude of crustal stress relative to asthenospheric drag stresses. The models further predict a local near-fault stress maximum at greater depths, sustained by the cyclic transfer of strain from the elastic crust to the ductile asthenosphere. Models incorporating both low-stress and high-stress fault strength assumptions are examined, under Newtonian and non-Newtonian rheology assumptions. Model results suggest a preference for low-stress (a shear stress level of about 10 MPa) fault models, in agreement with previous estimates based on heat flow measurements and other stress indicators.

Lyzenga, Gregory A.↗
DOE OSTI2017

A Simulation Framework for Battery Cell Impact Safety Modeling Using LS-DYNA

The development process of electrified vehicles can benefit significantly from computer-aided engineering tools that predict themultiphysics response of batteries during abusive events. A coupled structural, electrical, electrochemical, and thermal model framework has been developed within the commercially available LS-DYNA software. The finite element model leverages a three-dimensional mesh structure that fully resolves the unit cell components. The mechanical solver predicts the distributed stress and strain response with failure thresholds leading to the onset of an internal short circuit. In this implementation, an arbitrary compressive strain criterion is applied locally to each unit cell. A spatially distributed equivalent circuit model provides an empirical representation of the electrochemical responsewith minimal computational complexity.The thermalmodel provides state information to index the electrical model parameters, while simultaneously accepting irreversible and reversible sources of heat generation. The spatially distributed models of the electrical and thermal dynamics allow for the localization of current density and corresponding temperature response. The ability to predict the distributed thermal response of the cell as its stored energy is completely discharged through the short circuit enables an engineering safety assessment. A parametric analysis of an exemplary model is used to demonstrate the simulation capabilities.

25 ENERGY STORAGE↗
DOE OSTI2016

Kinetic model for the collisionless sheath of a collisional plasma

Collisional plasmas typically have mean-free-path still much greater than the Debye length, so the sheath is mostly collisionless. Once the plasma density, temperature, and flow are specified at the sheath entrance, the profile variation of electron and ion density, temperature, flow speed, and conductive heat fluxes inside the sheath is set by collisionless dynamics, and can be predicted by an analytical kinetic model distribution. These predictions are contrasted here with direct kinetic simulations, showing good agreement.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

TU-C-BRE-11: 3D EPID-Based in Vivo Dosimetry: A Major Step Forward Towards Optimal Quality and Safety in Radiation Oncology Practice

Purpose: To develop a 3D in vivo dosimetry method that is able to substitute pre-treatment verification in an efficient way, and to terminate treatment delivery if the online measured 3D dose distribution deviates too much from the predicted dose distribution. Methods: A back-projection algorithm has been further developed and implemented to enable automatic 3D in vivo dose verification of IMRT/VMAT treatments using a-Si EPIDs. New software tools were clinically introduced to allow automated image acquisition, to periodically inspect the record-and-verify database, and to automatically run the EPID dosimetry software. The comparison of the EPID-reconstructed and planned dose distribution is done offline to raise automatically alerts and to schedule actions when deviations are detected. Furthermore, a software package for online dose reconstruction was also developed. The RMS of the difference between the cumulative planned and reconstructed 3D dose distributions was used for triggering a halt of a linac. Results: The implementation of fully automated 3D EPID-based in vivo dosimetry was able to replace pre-treatment verification for more than 90% of the patient treatments. The process has been fully automated and integrated in our clinical workflow where over 3,500 IMRT/VMAT treatments are verified each year. By optimizing the dose reconstruction algorithm and the I/O performance, the delivered 3D dose distribution is verified in less than 200 ms per portal image, which includes the comparison between the reconstructed and planned dose distribution. In this way it was possible to generate a trigger that can stop the irradiation at less than 20 cGy after introducing large delivery errors. Conclusion: The automatic offline solution facilitated the large scale clinical implementation of 3D EPID-based in vivo dose verification of IMRT/VMAT treatments; the online approach has been successfully tested for various severe delivery errors.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2015

How the Assumed Size Distribution of Dust Minerals Affects the Predicted Ice Forming Nuclei

The formation of ice in clouds depends on the availability of ice forming nuclei (IFN). Dust aerosol particles are considered the most important source of IFN at a global scale. Recent laboratory studies have demonstrated that the mineral feldspar provides the most efficient dust IFN for immersion freezing and together with kaolinite for deposition ice nucleation, and that the phyllosilicates illite and montmorillonite (a member of the smectite group) are of secondary importance.A few studies have applied global models that simulate mineral specific dust to predict the number and geographical distribution of IFN. These studies have been based on the simple assumption that the mineral composition of soil as provided in data sets from the literature translates directly into the mineral composition of the dust aerosols. However, these tables are based on measurements of wet-sieved soil where dust aggregates are destroyed to a large degree. In consequence, the size distribution of dust is shifted to smaller sizes, and phyllosilicates like illite, kaolinite, and smectite are only found in the size range 2 m. In contrast, in measurements of the mineral composition of dust aerosols, the largest mass fraction of these phyllosilicates is found in the size range 2 m as part of dust aggregates. Conversely, the mass fraction of feldspar is smaller in this size range, varying with the geographical location. This may have a significant effect on the predicted IFN number and its geographical distribution.An improved mineral specific dust aerosol module has been recently implemented in the NASA GISS Earth System ModelE2. The dust module takes into consideration the disaggregated state of wet-sieved soil, on which the tables of soil mineral fractions are based. To simulate the atmospheric cycle of the minerals, the mass size distribution of each mineral in aggregates that are emitted from undispersed parent soil is reconstructed. In the current study, we test the null-hypothesis that simulating the presence of a large mass fraction of phyllosilicates in dust aerosols in the size range 2 m, in comparison to a simple model assumption where this is neglected, does not yield a significant effect on the magnitude and geographical distribution of the predicted IFN number. Results from sensitivity experiments are presented as well.

Dust↗
DOE OSTI2021

A newly proposed isotherm model to predict Cs exchange with crystalline silicotitanate in tank waste simulants

The Zheng Anthony Miller (ZAM) computer model, a multicomponent ion exchange model used to predict the exchange of Group I metals onto crystalline silicotitanate (CST), has historically been used to predict Cs distribution coefficients from Hanford and Savannah River Site (SRS) tank waste simulants. Comparison of experimentally determined Cs distribution coefficients from tank waste simulants with ZAM isotherm model predictions indicate overprediction of Cs and K distribution coefficients for simple and complex simulants with the engineered form of CST. Additionally, recent changes in chemical composition/manufacturing of IONSIV TM R9140-B have resulted in increased Cs capacity from high-salt, highly alkaline solutions. Here, this work served to assess different isotherm models and refine equilibrium parameters to develop a model that can be applied to Hanford and SRS tank waste Cs removal efforts. Toward this goal, the Campbell Westesen Peterson (CWP) model was developed. This model utilized the experimentally determined Cs capacity, and simplified ZAM equilibria expressions to include only the binary substitution of Cs + or K + on the Na + sites. Equilibrium constants for these equations were refined using experimentally determined distribution coefficients. Overall, the CWP model significantly improved our ability to predict both Cs and K loading capacity from complex matrices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1980

Predicting propulsion system drag

DONBOL computer program analytically predicts axisymmetric nozzle afterbody pressure distributions and drag. Predictions are based on Neumann solution for inviscid external flow coupled with modified Reshotko-Tucker integral boundary layer technique, control volume method of Presz for calculating flow in separated region, and inviscid one dimensional solution for jet exhaust flow. Comparisons with experimental data indicate program accurately predicts pressure distributions of boattail afterbodies for which jet exhaust plume can be simulated by solid body. For other configurations, nozzle pressure drag seems to be significantly underpredicted. Method is limited to subsonic free stream mach numbers below those for which flow over body becomes sonic.

Putnam, L. E.↗
NASA NTRS1989

Experimental and predicted pressure and heating distributions for an Aeroassist Flight Experiment vehicle in air at Mach 10

The Aeroassisted Flight Experiment vehicle for whose scale model pressure and heat-transfer rate distributions have been measured in air at Mach 10 is a 60-deg elliptic cone, raked off at a 73-percent angle, with an ellipsoid nose and a skirt added to the base of the rake plane to reduce heating. The predictions of both an inviscid flow-field code and a Navier-Stokes solver are compared with measured values. Good agreement is obtained in the case of pressure distributions; the effect of Reynolds number on heat-transfer distributions is noted to be small.

Micol, John R.↗
NASA NTRS1992

The effects of uneven fiber spacing on thermal residual stresses in a unidirectional SCS-6/Ti-15-3 laminate

High residual stresses develop in SCS-6/Ti-15-3 composites during cooldown from the fabrication temperature; these residual stresses can effect the mechanical and physical properties of the composite. Discrete fiber-matrix finite element models were used to study the residual stresses due to the temperature change during the fabrication process, including the effects of uneven fiber spacing, the free surface, and increased fiber volume fractions. To accurately model the effects of the free surface, it is only necessary to model one fiber through the thickness. Below the first ply, the analysis predicts stress distributions that are identical to the infinite array predictions. For uneven fiber space less than 0.042 mm in an interior ply, the maximum hoop stress was predicted to occur between fibers within a ply and to increase as the fiber spacing decreased. The maximum hoop stress correlated well with the observed radial cracking between fibers. For the case of touching fibers, the analysis predicted tensile radial stresses at the fiber-matrix debonding during the fabrication cooldown. Identical trends were predicted for uneven fiber spacing in surface plies with slightly greater values of maximum stresses. The analysis predicted matrix yielding to occur upon cooldown when the edge-to-edge fiber spacing was less than or equal to 0.022 mm. The stress distributions preidcted for increasing fiber volume fractions were similar to those predicted for decreasing the fiber spacing for two adjacent fibers within a ply.

Bigelow, Catherine A.↗