Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Gaussian process”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Influence of source batch S{sub K} dispersion on dosimetry for prostate cancer treatment with permanent implants

Purpose: In clinical practice, specific air kerma strength (S{sub K}) value is used in treatment planning system (TPS) permanent brachytherapy implant calculations with {sup 125}I and {sup 103}Pd sources; in fact, commercial TPS provide only one S{sub K} input value for all implanted sources and the certified shipment average is typically used. However, the value for S{sub K} is dispersed: this dispersion is not only due to the manufacturing process and variation between different source batches but also due to the classification of sources into different classes according to their S{sub K} values. The purpose of this work is to examine the impact of S{sub K} dispersion on typical implant parameters that are used to evaluate the dose volume histogram (DVH) for both planning target volume (PTV) and organs at risk (OARs). Methods: The authors have developed a new algorithm to compute dose distributions with different S{sub K} values for each source. Three different prostate volumes (20, 30, and 40 cm{sup 3}) were considered and two typical commercial sources of different radionuclides were used. Using a conventional TPS, clinically accepted calculations were made for {sup 125}I sources; for the palladium, typical implants were simulated. To assess the many different possible S{sub K} values for each source belonging to a class, the authors assigned an S{sub K} value to each source in a randomized process 1000 times for each source and volume. All the dose distributions generated for each set of simulations were assessed through the DVH distributions comparing with dose distributions obtained using a uniform S{sub K} value for all the implanted sources. The authors analyzed several dose coverage (V{sub 100} and D{sub 90}) and overdosage parameters for prostate and PTV and also the limiting and overdosage parameters for OARs, urethra and rectum. Results: The parameters analyzed followed a Gaussian distribution for the entire set of computed dosimetries. PTV and prostate V{sub 100} and D{sub 90} variations ranged between 0.2% and 1.78% for both sources. Variations for the overdosage parameters V{sub 150} and V{sub 200} compared to dose coverage parameters were observed and, in general, variations were larger for parameters related to {sup 125}I sources than {sup 103}Pd sources. For OAR dosimetry, variations with respect to the reference D{sub 0.1cm{sup 3}} were observed for rectum values, ranging from 2% to 3%, compared with urethra values, which ranged from 1% to 2%. Conclusions: Dose coverage for prostate and PTV was practically unaffected by S{sub K} dispersion, as was the maximum dose deposited in the urethra due to the implant technique geometry. However, the authors observed larger variations for the PTV V{sub 150}, rectum V{sub 100}, and rectum D{sub 0.1cm{sup 3}} values. The variations in rectum parameters were caused by the specific location of sources with S{sub K} value that differed from the average in the vicinity. Finally, on comparing the two sources, variations were larger for {sup 125}I than for {sup 103}Pd. This is because for {sup 103}Pd, a greater number of sources were used to obtain a valid dose distribution than for {sup 125}I, resulting in a lower variation for each S{sub K} value for each source (because the variations become averaged out statistically speaking)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

The Poisson tensor completion parametric estimator

We introduce the Poisson tensor completion (PTC) estimator that exploits inter-sample relationships to compute a low-rank Poisson tensor decomposition of the frequency histogram for samples of a multivariate distribution. Our crucial observation is that the histogram bins are an instance of a space partitioning of counts and thus can be identified with a spatial non-homogeneous Poisson process. The Poisson tensor decomposition leads to a completion of the mean measure over all bins—including those containing few to no samples—and leads to our proposed estimator. A Poisson tensor decomposition models the underlying distribution of the count data and guarantees non-negative estimated values obviating the need for additional constraints to ensure non-negativity. Furthermore, we demonstrate that our PTC estimator is a substantial improvement over standard histogram-based estimators for sub-Gaussian probability distributions because of the concentration of norm phenomenon.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2005

Interstellar Isomers: The Importance of Bonding Energy Differences

We present strong detections of methyl cyanide (CH3CN), vinyl cyanide (CH2CHCN), ethyl cyanide (CH3CH2CN) and cyanodiacetylene (HC4CN) molecules with the Green Bank Telescope (GBT) toward the Sgr B2(N) molecular cloud. Attempts to detect the corresponding isocyanide isomers were only successful in the case of methyl isocyanide (CH3NC) for its J(sub K) = 1(sub 0) - 0(sub 0) transition, which is the first interstellar report of this line. To determine the spatial distribution of CH3NC, we used archival Berkeley-Illinois-Maryland Association (BIMA) array data for the J(sub K) = 1(sub 0) - 0(sub 0) transitions but no emission was detected. From ab initio calculations, the bonding energy difference between the cyanide and isocyanide molecules is greater than 8500 per centimeter (greater than 12,000 K). Thus, cyanides are the more stable isomers and would likely be formed more preferentially over their isocyanide counterparts. That we detect CH3NC emission with a single antenna (Gaussian beamsize(omega(sub B))=1723 arcsec(sup 2)) but not with an interferometer (omega(sub b)=192 arcsec(sup 2)), strongly suggests that CH3NC has a widespread spatial distribution toward the Sgr B2(N) region. Other investigators have shown that CH3CN is present both in the LMH hot core of Sgr B2(N) and in the surrounding medium, while we have shown that CH3NC appears to be deficient in the LMH hot core. Thus, largescale, non-thermal processes in the surrounding medium may account for the conversion of CH3CN to CH3NC while the LMH hot core, which is dominated by thermal processes, does not produce a significant amount of CH3NC. Ice analog experiments by other investigators have shown that radiation bombardment of CH3CN can produce CH3NC, thus supporting our observations. We conclude that isomers separated by such large bonding energy differences are distributed in different interstellar environments, making the evaluation of column density ratios between such isomers irrelevant unless it can be independently shown that these species are co-spatial.

Remijan, Anthony J.↗
DOE OSTI2016

Development of TDLAS for Water Vapor Concentration Measurement during VHTR Steam Ingress

Very-high-temperature reactors (VHTR) utilize a graphite-moderated, helium-cooled design that provides higher efficiencies and a low-carbon source of process heat (>700 deg. C) for many industrial applications. Safety concerns have led to extensive accident condition investigations. Steam generator heat-exchanger tube rupture accidents (SGTR) can lead to increased reactor core steam density, which causes neutron slowing-down and chemical corrosion of the graphite fuel elements and structural columns. It is important to be able to computationally model the propagation of steam throughout the lower plenum and nuclear reactor core, but experimental data is needed to validate such models. The primary objective of this project is to instrument a scaled down experiment of a VHTR designed by Ohio State University (OSU), with tunable diode laser absorption spectroscopy (TDLAS) diagnostics to measure steam concentration changes and map how water vapor propagates through the test facility's lower plenum and core. The basic principle of absorption spectroscopy is based on a molecular species ability to absorb photons of specific energies. A collimated laser beam of known energy is passed through a test section containing a sample gas. When a transition of the absorbing gas species resonates with the laser frequency, a certain amount of energy will be absorbed based on the rovibrational characteristics of the molecule. The intensity of the transmitted laser light can be measured by a detector after exiting the test section. The Beer-Lambert Law of absorbance is used to recover this information relating beam attenuation to the system dimensions, gas composition, pressure, and temperature. The line-strength is a function of temperature alone and relates the fraction of molecules in a given rovibrational state through the partition function. The partition function describes the statistical properties of a system in thermodynamic equilibrium where the states obey a Boltzmann distribution. Thus, the number density of molecules in a particular state can be determined from the total internal partition function at a particular temperature. The lineshape function of a given absorption transition is derived from the physical interaction between the absorbing species and is dependent on temperature and pressure. Random thermal motion of absorbing molecules result in broadening of the linewidth, called Doppler broadening, which follows a Gaussian distribution. Molecular collisions result in broadening and shifting of the linewidth, called pressure broadening, which follows a Lorentzian distribution. The overall lineshape results in a Voigt profile, which is a convolution of the Gaussian and Lorentzian distributions. The Voigt profile does not have a simple analytical form and is most often calculated numerically or approximated by complex functions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Using Statistical Multivariable Models to Understand the Relationship Between Interplanetary Coronal Mass Ejecta and Magnetic Flux Ropes

In-situ measurements of interplanetary coronal mass ejections (ICMEs) display a wide range of properties. A distinct subset, "magnetic clouds" (MCs), are readily identifiable by a smooth rotation in an enhanced magnetic field, together with an unusually low solar wind proton temperature. In this study, we analyze Ulysses spacecraft measurements to systematically investigate five possible explanations for why some ICMEs are observed to be MCs and others are not: i) An observational selection effect; that is, all ICMEs do in fact contain MCs, but the trajectory of the spacecraft through the ICME determines whether the MC is actually encountered; ii) interactions of an erupting flux rope (PR) with itself or between neighboring FRs, which produce complex structures in which the coherent magnetic structure has been destroyed; iii) an evolutionary process, such as relaxation to a low plasma-beta state that leads to the formation of an MC; iv) the existence of two (or more) intrinsic initiation mechanisms, some of which produce MCs and some that do not; or v) MCs are just an easily identifiable limit in an otherwise corntinuous spectrum of structures. We apply quantitative statistical models to assess these ideas. In particular, we use the Akaike information criterion (AIC) to rank the candidate models and a Gaussian mixture model (GMM) to uncover any intrinsic clustering of the data. Using a logistic regression, we find that plasma-beta, CME width, and the ratio O(sup 7) / O(sup 6) are the most significant predictor variables for the presence of an MC. Moreover, the propensity for an event to be identified as an MC decreases with heliocentric distance. These results tend to refute ideas ii) and iii). GMM clustering analysis further identifies three distinct groups of ICMEs; two of which match (at the 86% level) with events independently identified as MCs, and a third that matches with non-MCs (68 % overlap), Thus, idea v) is not supported. Choosing between ideas i) and iv) is more challenging, since they may effectively be indistinguishable from one another by a single in-situ spacecraft. We offer some suggestions on how future studies may address this.

Riley, P.↗
DOE OSTI2018

Trajectory-based understanding of the quantum–classical transition for barrier scattering

The quantum–classical transition of wave packet barrier scattering is investigated using a hydrodynamic description in the framework of a nonlinear Schrödinger equation. The nonlinear equation provides a continuous description for the quantum–classical transition of physical systems by introducing a degree of quantumness. Based on the transition equation, the transition trajectory formalism is developed to establish the connection between classical and quantum trajectories. The quantum–classical transition is then analyzed for the scattering of a Gaussian wave packet from an Eckart barrier and the decay of a metastable state. Computational results for the evolution of the wave packet and the transmission probabilities indicate that classical results are recovered when the degree of quantumness tends to zero. Classical trajectories are in excellent agreement with the transition trajectories in the classical limit, except in some regions where transition trajectories cannot cross because of the single-valuedness of the transition wave function. As the computational results demonstrate, the process that the Planck constant tends to zero is equivalent to the gradual removal of quantum effects originating from the quantum potential. This study provides an insightful trajectory interpretation for the quantum–classical transition of wave packet barrier scattering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Redshift-space distortions in simulations of the 21-cm signal from the cosmic dawn

ABSTRACT The 21-cm signal from the Cosmic Dawn (CD) is likely to contain large fluctuations, with the most extreme astrophysical models on the verge of being ruled out by observations from radio interferometers. It is therefore vital that we understand not only the astrophysical processes governing this signal, but also other inherent processes impacting the signal itself, and in particular line-of-sight effects. Using our suite of fully numerical radiative transfer simulations, we investigate the impact on the redshifted 21-cm from the CD from one of these processes, namely the redshift-space distortions (RSDs). When RSDs are added, the resulting boost to the power spectra makes the signal more or equally detectable for our models for all redshifts, further strengthening hopes that a power spectra measurement of the CD will be possible. RSDs lead to anisotropy in the signal at the beginning and end of the CD, but not while X-ray heating is underway. The inclusion of RSDs, however, decreases detectability of the non-Gaussianity of fluctuations from inhomogeneous X-ray heating as measured by the skewness and kurtosis. On the other hand, mock observations created from all our simulations that include telescope noise corresponding to 1000 h of observation with the Square Kilometre Array telescope show that we may be able to image the CD for all heating models considered and suggest RSDs dramatically boost fluctuations coming from the inhomogeneous Ly α background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

VeloxChem: A Python-driven density-functional theory program for spectroscopy simulations in high-performance computing environments

An open-source program named VeloxChem has been developed for the calculation of electronic real and complex linear response functions at the levels of Hartree–Fock and Kohn–Sham density functional theories. With an object-oriented program structure written in a Python/C++ layered fashion, VeloxChem enables time-efficient prototyping of novel scientific approaches without sacrificing computational efficiency, so that molecular systems involving up to and beyond 500 second-row atoms (or some 10,000 contracted and in part diffuse Gaussian basis functions) can be routinely addressed. In addition, VeloxChem is equipped with a polarizable embedding scheme for the treatment of the classical electrostatic interactions with an environment that in turn is modeled by atomic site charges and polarizabilities. The underlying hybrid message passing interface (MPI)/open multiprocessing (OpenMP) parallelization scheme makes VeloxChem suitable for execution in high-performance computing cluster environments, showing even slightly beyond linear scaling for the Fock matrix construction with use of up to 16,384 central processing unit (CPU) cores. An efficient—with respect to convergence rate and overall computational cost—multifrequency/gradient complex linear response equation solver enables calculations not only of conventional spectra, such as visible/ultraviolet/X-ray electronic absorption and circular dichroism spectra, but also time-resolved linear response signals as due to ultra-short weak laser pulses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. Furthermore, the combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Detecting perceptual groupings in textures by continuity considerations

A generalization is presented for the second derivative of a Gaussian D(sup 2)G operator to apply to problems of perceptual organization involving textures. Extensions to other problems of perceptual organization are evident and a new research direction can be established. The technique presented is theoretically pleasing since it has the potential of unifying the entire area of image segmentation under the mathematical notion of continuity and presents a single algorithm to form perceptual groupings where many algorithms existed previously. The eventual impact on both the approach and technique of image processing segmentation operations could be significant.

Greene, Richard J.↗
NASA NTRS2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗
DOE OSTI2023

Multiple emission components in the Cygnus cocoon detected from Fermi -LAT observations

Star-forming regions may play an important role in the life cycle of Galactic cosmic rays (CRs), notably as home to specific acceleration mechanisms and transport conditions. Gamma-ray observations of Cygnus X have revealed the presence of an excess of hard-spectrum gamma-ray emission, possibly related to a cocoon of freshly accelerated particles. We seek an improved description of the gamma-ray emission from the cocoon using ~13 yr of observations with the Fermi-Large Area Telescope (LAT) and use it to further constrain the processes and objects responsible for the young CR population. We developed an emission model for a large region of interest, including a description of interstellar emission from the background population of CRs and recent models for other gamma-ray sources in the field. Thus, we performed an improved spectro-morphological characterisation of the residual emission including the cocoon. The best-fit model for the cocoon includes two main emission components: an extended component FCES G78.74+1.56, described by a 2D Gaussian of extension r 68 = 4.4° ± 0.1° -0.1° +0.1° and a smooth broken power law spectrum with spectral indices 1.67 ± 0.05 -0.01 +0.02 and 2.12 ± 0.02 -0.01 +0.00 below and above 3.0 ± 0.6 -0.2 +0.0 GeV, respectively; and a central component FCES G80.00+0.50, traced by the distribution of ionised gas within the borders of the photo-dissociation regions and with a power law spectrum of index 2.19 ± 0.03 -0.01 +0.00 that is significantly different from the spectrum of FCES G78.74+1.56. An additional extended emission component FCES G78.83+3.57, located on the edge of the central cavities in Cygnus X and with a spectrum compatible with that of FCES G80.00+0.50, is likely related to the cocoon. For the two brightest components FCES G80.00+0.50 and FCES G78.74+1.56, spectra and radial-azimuthal profiles of the emission can be accounted for in a diffusion-loss framework involving one single population of non-thermal particles with a flat injection spectrum. Particles span the full extent of FCES G78.74+1.56 as a result of diffusion from a central source, and give rise to source FCES G80.00+0.50 by interacting with ionised gas in the innermost region. For this simple diffusion-loss model, viable setups can be very different in terms of energetics, transport conditions, and timescales involved, and both hadronic and leptonic scenarios are possible. The solutions range from long-lasting particle acceleration, possibly in prominent star clusters such as Cyg OB2 and NGC 6910, to a more recent and short-lived release of particles within the last 10–100 kyr, likely from a supernova remnant. The observables extracted from our analysis can be used to perform detailed comparisons with advanced models of particle acceleration and transport in star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The order of three lowest-energy states of the six-electron harmonium at small force constant

The order of low-energy states of six-electron harmonium is uncertain in the case of strong correlation, which is not a desired situation for the model system being considered for future testing of approximate methods of quantum chemistry. The computational study of these states has been carried out at the frequency parameter ω = 0.01, using the variational method with the basis of symmetry-projected, explicitly correlated Gaussian (ECG) lobe functions. It has revealed that the six-electron harmonium at this confinement strength is an octahedral Wigner molecule, whose order of states is different than in the strong confinement regime and does not agree with the earlier predictions. The results obtained for ω = 0.5 and 10 are consistent with the findings based on the Hund’s rules for the s{sup 2}p{sup 4} electron configuration. Substantial part of the computations has been carried out on the graphical processing units and the efficiency of these devices in calculation of the integrals over ECG functions has been compared with traditional processors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1987

Detection of signals by weighted integrate-and-dump filter

A Weighted Integrate and Dump Filter (WIDF) is presented that results in reducing those losses in telemetry symbol signal to noise ratio (SNR) which occur in digital Integrate and Dump Filters (IDFs) when the samples are not phase locked to the input data symbol clock. The Minimum Mean Square Error (MMSE) criterion is used to derive a set of weights for approximating the analog integrate and dump filter, which is the matched filter for detection of signals in additive white Gaussian noise. This new digital matched filter results in considerable performance improvement compared to unweighted digital matched filters. An example is presented for a sampling rate of four times the symbol rate. As the sampling offset (or phase) varies with respect to the data symbol boundaries, the output SNR varies 1 dB for an unweighted IDF, but only 0.3 dB for the optimum WIDF, averaged over random data patterns. This improvement in performance relative to unweighted IDF means that significantly lower sampling and processing rates can be used for given telemetry symbol rates, resulting in reduced system cost.

Sadr, R.↗
NASA NTRS1995

The Barberplaid illusion: Even Perceived Plaid Motion is Biased by Asymmetric Apertures

Our results show that the perceived direction of motion of plaids windowed by asymmetric spatial Gaussians is biased toward the long axis of the window. The bias increases as the relative angle between the plaid motion and the window increases, peaks at a relative angle of about 40 degrees, and then decreases. The peak bias was 14 degrees for a spatial frequency of 0.6 cpd and a window aspect ratio of 4.0. The biases increase as the window is elongated and decrease as the component spatial frequency increases. We tested the predictions of several models of human motion processing (cross correlation, motion energy, intersection of constraints, and vector sum), and show that none of these can predict our data. These results suggest that spatial integration of motion signals plays a crucial role in the perception of plaid motion.

Beutter, Brent↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗