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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 1,063 records · Page 59
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DOE OSTI2015

POD/DEIM reduced-order strategies for efficient four dimensional variational data assimilation

This work studies reduced order modeling (ROM) approaches to speed up the solution of variational data assimilation problems with large scale nonlinear dynamical models. It is shown that a key requirement for a successful reduced order solution is that reduced order Karush–Kuhn–Tucker conditions accurately represent their full order counterparts. In particular, accurate reduced order approximations are needed for the forward and adjoint dynamical models, as well as for the reduced gradient. New strategies to construct reduced order based are developed for proper orthogonal decomposition (POD) ROM data assimilation using both Galerkin and Petrov–Galerkin projections. For the first time POD, tensorial POD, and discrete empirical interpolation method (DEIM) are employed to develop reduced data assimilation systems for a geophysical flow model, namely, the two dimensional shallow water equations. Numerical experiments confirm the theoretical framework for Galerkin projection. In the case of Petrov–Galerkin projection, stabilization strategies must be considered for the reduced order models. The new reduced order shallow water data assimilation system provides analyses similar to those produced by the full resolution data assimilation system in one tenth of the computational time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Certified dual-corrected radiation patterns of phased antenna arrays by offline–online order reduction of finite-element models

This paper presents a fast numerical method for computing certified far-field patterns of phased antenna arrays over broad frequency bands as well as wide ranges of steering and look angles. The proposed scheme combines finite-element analysis, dual-corrected model-order reduction, and empirical interpolation. To assure the reliability of the results, improved a posteriori error bounds for the radiated power and directive gain are derived. Both the reduced-order model and the error-bounds algorithm feature offline–online decomposition. A real-world example is provided to demonstrate the efficiency and accuracy of the suggested approach.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Simplex-stochastic collocation method with improved scalability

The Simplex-Stochastic Collocation (SSC) method is a robust tool used to propagate uncertain input distributions through a computer code. However, it becomes prohibitively expensive for problems with dimensions higher than 5. The main purpose of this paper is to identify bottlenecks, and to improve upon this bad scalability. In order to do so, we propose an alternative interpolation stencil technique based upon the Set-Covering problem, and we integrate the SSC method in the High-Dimensional Model-Reduction framework. In addition, we address the issue of ill-conditioned sample matrices, and we present an analytical map to facilitate uniformly-distributed simplex sampling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations

We extend the reduced basis (RB) accelerated Bayesian inversion methods for affine-parametric, linear operator equations which are considered in [16,17] to non-affine, nonlinear parametric operator equations. We generalize the analysis of sparsity of parametric forward solution maps in [20] and of Bayesian inversion in [48,49] to the fully discrete setting, including Petrov–Galerkin high-fidelity (“HiFi”) discretization of the forward maps. We develop adaptive, stochastic collocation based reduction methods for the efficient computation of reduced bases on the parametric solution manifold. The nonaffinity and nonlinearity with respect to (w.r.t.) the distributed, uncertain parameters and the unknown solution is collocated; specifically, by the so-called Empirical Interpolation Method (EIM). For the corresponding Bayesian inversion problems, computational efficiency is enhanced in two ways: first, expectations w.r.t. the posterior are computed by adaptive quadratures with dimension-independent convergence rates proposed in [49]; the present work generalizes [49] to account for the impact of the PG discretization in the forward maps on the convergence rates of the Quantities of Interest (QoI for short). Second, we propose to perform the Bayesian estimation only w.r.t. a parsimonious, RB approximation of the posterior density. Based on the approximation results in [49], the infinite-dimensional parametric, deterministic forward map and operator admit N-term RB and EIM approximations which converge at rates which depend only on the sparsity of the parametric forward map. In several numerical experiments, the proposed algorithms exhibit dimension-independent convergence rates which equal, at least, the currently known rate estimates for N-term approximation. We propose to accelerate Bayesian estimation by first offline construction of reduced basis surrogates of the Bayesian posterior density. The parsimonious surrogates can then be employed for online data assimilation and for Bayesian estimation. They also open a perspective for optimal experimental design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

A 4DCT imaging-based breathing lung model with relative hysteresis

To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

A two-stage adaptive stochastic collocation method on nested sparse grids for multiphase flow in randomly heterogeneous porous media

A new computational method is proposed for efficient uncertainty quantification of multiphase flow in porous media with stochastic permeability. For pressure estimation, it combines the dimension-adaptive stochastic collocation method on Smolyak sparse grids and the Kronrod–Patterson–Hermite nested quadrature formulas. For saturation estimation, an additional stage is developed, in which the pressure and velocity samples are first generated by the sparse grid interpolation and then substituted into the transport equation to solve for the saturation samples, to address the low regularity problem of the saturation. Numerical examples are presented for multiphase flow with stochastic permeability fields to demonstrate accuracy and efficiency of the proposed two-stage adaptive stochastic collocation method on nested sparse grids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies

We propose a Bayesian approach for seismic inversion to estimate acoustic impedance, porosity and lithofacies within the reservoir conditioned to post-stack seismic and well data. The link between elastic and petrophysical properties is given by a joint prior distribution for the logarithm of impedance and porosity, based on a rock-physics model. The well conditioning is performed through a background model obtained by well log interpolation. Two different approaches are presented: in the first approach, the prior is defined by a single Gaussian distribution, whereas in the second approach it is defined by a Gaussian mixture to represent the well data multimodal distribution and link the Gaussian components to different geological lithofacies. The forward model is based on a linearized convolutional model. For the single Gaussian case, we obtain an analytical expression for the posterior distribution, resulting in a fast algorithm to compute the solution of the inverse problem, i.e. the posterior distribution of acoustic impedance and porosity as well as the facies probability given the observed data. For the Gaussian mixture prior, it is not possible to obtain the distributions analytically, hence we propose a Gibbs algorithm to perform the posterior sampling and obtain several reservoir model realizations, allowing an uncertainty analysis of the estimated properties and lithofacies. Both methodologies are applied to a real seismic dataset with three wells to obtain 3D models of acoustic impedance, porosity and lithofacies. The methodologies are validated through a blind well test and compared to a standard Bayesian inversion approach. Using the probability of the reservoir lithofacies, we also compute a 3D isosurface probability model of the main oil reservoir in the studied field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Gradient-based constrained optimization using a database of linear reduced-order models

A methodology grounded in model reduction is presented for accelerating the gradient-based solution of a family of linear or nonlinear constrained optimization problems where the constraints include at least one linear Partial Differential Equation (PDE). A key component of this methodology is the construction, during an offline phase, of a database of pointwise, linear, Projection-based Reduced-Order Models (PROM)s associated with a design parameter space and the linear PDE(s). A parameter sampling procedure based on an appropriate saturation assumption is proposed to maximize the efficiency of such a database of PROMs. A real-time method is also presented for interpolating at any queried but unsampled parameter vector in the design parameter space the relevant sensitivities of a PROM. The practical feasibility, computational advantages, and performance of the proposed methodology are demonstrated for several realistic, nonlinear, aerodynamic shape optimization problems governed by linear aeroelastic constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Conservative remapping of material-dependent fields between possibly misaligned material regions

In this work, we propose an interpolation or remapping algorithm of material-dependent fields on polyhedral meshes where any source or target cell contains only one material. It is conservative and it preserves sharp material boundaries on the target mesh, even if the source and target regions delineating the same material are slightly misaligned. If those material regions are aligned, then the algorithm is also linearity-preserving and bounds-preserving. For a given material, it consists of a conservative field reconstruction on a target mesh part from a source mesh part associated with that material, followed by a repair step in case of misaligned boundaries. No assumption is made regarding the topology of the input meshes

36 MATERIALS SCIENCE↗
DOE OSTI2022

Proper orthogonal decomposition based reduced-order modeling of flux-Limited gray thermal radiation

Here, in this work, a proper orthogonal decomposition (POD) based reduced-order model (ROM) is developed to solve gray, flux-limited thermal radiation diffusion. We focus on the variable opacity radiation penetration benchmark posed by Olson, Auer, and Hall. The T -3 relationship for opacity in conjunction with high-temperature radiation penetrating an initially cold material produces a strong thermal radiation shock. This class of problems is particularly challenging for standard POD-based reduced-order modeling due to the nonlinearities presented by 1) the T 4 source term, and 2) flux-limited diffusion operator. To address these challenges and develop a cost competitive ROM, we employ a “hyper-reduction” technique through discrete empirical interpolation (DEIM) and allow for adaptive reduced-order projections through principal interval decomposition (PID). Performance of the proposed methodology is quantified by comparing the cost savings and accuracy relative to a full-order computation. Reference solutions and snapshot data are obtained through a full-order calculation performed by the University of Chicago maintained astrophysics code, FLASH. For consistency and potential extensibility, the developed ROM is also implemented in FLASH. We find that in the initialization regime, where the thermal radiation wave is initially created by the warming of the material, this class of problems is highly reducible and suitable for POD-based ROMs. However, the strong convective nature of the wave propagation regime is less reducible and more challenging to create an efficient ROM.

42 ENGINEERING↗
DOE OSTI2020

A continuum damage mechanics (CDM) based Wilshire model for creep deformation, damage, and rupture prediction

In this report, a new constitutive model is derived that combines the Wilshire equations with continuum damage mechanics (CDM) to enable the long-term prediction of creep deformation, damage, and rupture. The Wilshire equations have been demonstrated to accurately extrapolate the stress-rupture, minimum-creep-strain-rate, and time-to-strain of various alloys across decade of life. Recently, the time-to-creep-strain equation has been rearranged to predict creep deformation curves; however, the resulting equation is difficult to calibrate and does not track damage. The CDM-based Sinh constitutive model accurately predicts creep deformation, damage, and stress-rupture for a variety of alloys; however, it lacks an explicit description of stress and temperature co-dependence which limits interpolation and extrapolation ability. In this study, the Wilshire and the CDM-based Sinh equations are combined to create the “WCS” model. The WCS model combines the best features of each model while eliminating their deficiencies. Experimental data for alloy P91 is gathered and the WCS model is calibrated to the data. The WCS model accurately predicts the stress rupture, minimum-creep-strain-rate, creep deformation, and damage of alloy P91 across the experimental stress and temperature range as well as consistency in parametric simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Nuclear Data Sheets for A = 215

The evaluated spectroscopic data are presented for 12 known nuclides of mass 215 (Hg, Tl, Pb, Bi, Po, At, Rn, Fr, Ra, Ac, Th, Pa). For {sup 215}Hg, {sup 215}Tl, {sup 215}Pb, and {sup 215}Pa nuclei, no excited states are known. The decay characteristics of {sup 215}Hg and {sup 215}Tl are unknown. The decay scheme of {sup 215}Pb is considered as incomplete. Ordering of γ cascades in the decay of 36.9–s isomer of {sup 215}Bi and for high–spin states above 2251 keV in {sup 215}Fr are not established. High–spin excitations, including several isomeric states, are well known in {sup 215}Bi, {sup 215}Po, {sup 215}Rn, {sup 215}Fr, {sup 215}Ra, and {sup 215}Ac. No particle–transfer reaction data are available for any of the A=215 nuclei. The rms charge radii for {sup 215}Pb, {sup 215}Bi, {sup 215}Po, {sup 215}Rn, {sup 215}Fr and {sup 215}Ra have been evaluated by Daniel Abriola, from extrapolation or interpolation of available evaluated data in 2013An02 for radii of respective Z chains using formula 9 in 2004An14. This evaluation was carried out as part of ENSDD–workshop at VECC, Kolkata for Nuclear Structure and Decay Data, organized and hosted by VECC and Board of Research in Nuclear Sciences (BRNS) in Kolkata, India, November 26–29, 2012. This work supersedes the previous A = 215 evaluation (2001Br31) published by E. Browne which covered literature prior to May 2001.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Spectral analysis of shielded gamma ray sources using precalculated library data

In this paper, an approach has been developed for determining the intensity of a shielded source by first determining the thicknesses of three different shielding materials from a passively collected gamma-ray spectrum by making comparisons with predetermined shielded spectra. These evaluations are dependent on the accuracy and validity of the predetermined library spectra which were created by changing the thicknesses of the three chosen materials lead, aluminum and wood that are used to simulate any actual shielding. Each of the spectra produced was generated using MCNP5 with a sufficiently large number of histories to ensure a low relative error at each channel. The materials were held in the same respective order from source to detector, where each material consisted of three individual thicknesses and a null condition. This then produced two separate data sets of 27 total shielding material situations and subsequent predetermined libraries that were created for each radionuclide source used. The technique used to calculate the thicknesses of the materials implements a Levenberg–Marquardt nonlinear search that employs a tri-linear interpolation with the respective predetermined libraries within each channel for the supplied input unknown spectrum. Given that the nonlinear parameters require an initial guess for the calculations, the approach demonstrates first that when the correct values are input, the correct thicknesses are found. It then demonstrates that when multiple trials of random values are input for each of the nonlinear parameters, the average of the calculated solutions that successfully converges also produced the correct thicknesses. Under situations with sufficient information known about the detection situation at hand, the method was shown to behave in a manner that produces reasonable results and can serve as a good preliminary solution. Finally, this technique has the capability to be used in a variety of full spectrum inverse analysis problems including homeland security issues.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Electrons to Reactors Multiscale Modeling: Catalytic CO Oxidation over RuO 2

First-principles kinetic Monte Carlo (1p-kMC) simulations for CO oxidation on two RuO 2 facets, RuO 2 (110) and RuO 2 (111), were coupled to the computational fluid dynamics (CFD) simulations package MFIX, and reactor-scale simulations were then performed. 1p-kMC coupled with CFD has recently been shown as a feasible method for translating molecular scale mechanistic knowledge to the reactor scale, enabling comparisons to in situ and online experimental measurements. Only a few studies with such coupling have been published. This work incorporates multiple catalytic surface facets into the scale-coupled simulation, and three possibilities were investigated: the two possibilities of each facet individually being the dominant phase in the reactor, and also the possibility that both facets were present on the catalyst particles in the ratio predicted by an ab initio thermodynamics-based Wulff construction. When lateral interactions between adsorbates were included in the 1p-kMC simulations, the two surfaces, RuO 2 (110) and RuO 2 (111), were found to be of similar order-of-magnitude in activity for the pressure range of 1 × 10 –4 bar to 1 bar, with the RuO 2 (110) surface-termination showing more simulated activity than the RuO 2 (111) surface-termination. Coupling between the 1p-kMC and CFD was achieved with a lookup table generated by the error-based modified Shepard interpolation scheme. Isothermal reactor scale simulations were performed and compared to two separate experimental studies, conducted with reactant partial pressures of ≤0.1 bar. Simulations without an isothermality restriction were also conducted and showed that the simulated temperature gradient across the catalytic reactor bed is <0.5 K, which validated the use of the isothermality restriction for investigating the reactor-scale phenomenological temperature dependences. The approach with the Wulff construction based reactor simulations reproduced a trend similar to one experimental data set relatively well, with the (110) surface being more active at higher temperaures; in contrast, for the other experimental data set, our reactor simulations achieve surprisingly and perhaps fortuitously good agreement with the activity and phenomenological pressure dependence when it is assumed that the (111) facet is the only active facet present. Lastly, the active phase of catalytic CO oxidation over RuO 2 remains unsettled, but the present study presents proof of principle (and progress) toward more accurate multiscale modeling from electrons to reactors and new simulation results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Adjustments to the ICVGT scale of INRIM

At the 8{sup th} Temperature Symposium the results have been presented for the Interpolating Constant Volume Gas thermometer at INRIM (then IMGC), featuring a cryogenic pressure transducer, with an expanded uncertainty of less then 1.5 mK. However, for its fixed points this scale still relied on a NPL calibration as carried by rhodium-iron thermometer 232324. After the clarification, in 2005, by the Consultative Committee on Thermometry (CCT) of the definition of the equilibrium hydrogen (e-H2) triple point this scale was due to be adjusted for the isotopic content in the e-H2 fixed point cell. Only when this thermometer was re-calibrated in 2010 at INRIM at the three fixed points of the ICVGT was this adjustment performed, being the isotopic composition of the hydrogen cell known. With the start of the Neon Project in 2005, it became clear that a second adjustment would soon be needed, once the CCT will have decided on the way to deal with the isotopic composition of neon. The paper presents the experimental data of 2010, discusses the stability of the thermometer, and the size of the correction at the hydrogen point and of the likely correction (and its uncertainty) to be applied to the neon point, the isotopic composition of this cell being known as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Multiscale multiphysics and multidomain models—Flexibility and rigidity

The emerging complexity of large macromolecules has led to challenges in their full scale theoretical description and computer simulation. Multiscale multiphysics and multidomain models have been introduced to reduce the number of degrees of freedom while maintaining modeling accuracy and achieving computational efficiency. A total energy functional is constructed to put energies for polar and nonpolar solvation, chemical potential, fluid flow, molecular mechanics, and elastic dynamics on an equal footing. The variational principle is utilized to derive coupled governing equations for the above mentioned multiphysical descriptions. Among these governing equations is the Poisson-Boltzmann equation which describes continuum electrostatics with atomic charges. The present work introduces the theory of continuum elasticity with atomic rigidity (CEWAR). The essence of CEWAR is to formulate the shear modulus as a continuous function of atomic rigidity. As a result, the dynamics complexity of a macromolecular system is separated from its static complexity so that the more time-consuming dynamics is handled with continuum elasticity theory, while the less time-consuming static analysis is pursued with atomic approaches. We propose a simple method, flexibility-rigidity index (FRI), to analyze macromolecular flexibility and rigidity in atomic detail. The construction of FRI relies on the fundamental assumption that protein functions, such as flexibility, rigidity, and energy, are entirely determined by the structure of the protein and its environment, although the structure is in turn determined by all the interactions. As such, the FRI measures the topological connectivity of protein atoms or residues and characterizes the geometric compactness of the protein structure. As a consequence, the FRI does not resort to the interaction Hamiltonian and bypasses matrix diagonalization, which underpins most other flexibility analysis methods. FRI's computational complexity is of O(N{sup 2}) at most, where N is the number of atoms or residues, in contrast to O(N{sup 3}) for Hamiltonian based methods. We demonstrate that the proposed FRI gives rise to accurate prediction of protein B-Factor for a set of 263 proteins. We show that a parameter free FRI is able to achieve about 95% accuracy of the parameter optimized FRI. An interpolation algorithm is developed to construct continuous atomic flexibility functions for visualization and use with CEWAR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗