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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 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A robust hierarchical solver for ill-conditioned systems with applications to ice sheet modeling

A hierarchical solver is proposed for solving sparse ill-conditioned linear systems in parallel. The solver is based on a modification of the LoRaSp method, but employs a deferred-compression technique, which provably reduces the approximation error and significantly improves efficiency. Moreover, the deferred-compression technique introduces minimal overhead and does not affect parallelism. As a result, the new solver achieves linear computational complexity under mild assumptions and excellent parallel scalability. To demonstrate the performance of the new solver, we focus on applying it to solve sparse linear systems arising from ice sheet modeling. The strong anisotropic phenomena associated with the thin structure of ice sheets creates serious challenges for existing solvers. To address the anisotropy, we additionally developed a customized partitioning scheme for the solver, which captures the strong-coupling direction accurately. In general, the partitioning can be computed algebraically with existing software packages, and thus the new solver is generalizable for solving other sparse linear systems. Our results show that ice sheet problems of about 300 million degrees of freedom have been solved in just a few minutes using a thousand processors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Design and application of a kinetic model of lipid metabolism in Saccharomyces cerevisiae

Lipid biosynthesis plays a vital role in living cells and has been increasingly engineered to overproduce various lipid-based chemicals. However, owing to the tightly constrained and interconnected nature of lipid biosynthesis, both understanding and engineering of lipid metabolism remain challenging, even with the help of mathematical models. Here we report the development of a kinetic metabolic model of lipid metabolism in Saccharomyces cerevisiae that integrates fatty acid biosynthesis, glycerophospholipid metabolism, sphingolipid metabolism, storage lipids, lumped sterol synthesis, and the synthesis and transport of relevant target-chemicals, such as fatty acids and fatty alcohols. The model was trained on lipidomic data of a reference S. cerevisiae strain, single knockout mutants, and lipid overproduction strains reported in literature. The model was used to design mutants for fatty alcohol overproduction and the lipidomic analysis of the resultant mutant strains coupled with model-guided hypothesis led to discovery of a futile cycle in the triacylglycerol biosynthesis pathway. In addition, the model was used to explain successful and unsuccessful mutant designs in metabolic engineering literature. Thus, this kinetic model of lipid metabolism can not only enable the discovery of new phenomenon in lipid metabolism but also the engineering of mutant strains for overproduction of lipids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Landmark-embedded Gaussian process with applications for functional data modeling

In practice, we often need to infer the value of a target variable from functional observation data. A challenge in this task is that the relationship between the functional data and the target variable is very complex: the target variable not only influences the shape but also the location of the functional data. In addition, due to the uncertainties in the environment, the relationship is probabilistic, that is, for a given fixed target variable value, we still see variations in the shape and location of the functional data. To address this challenge, we present a landmark-embedded Gaussian process model that describes the relationship between the functional data and the target variable. A unique feature of the model is that landmark information is embedded in the Gaussian process model so that both the shape and location information of the functional data are considered simultaneously in a unified manner. Gibbs-Metropolis-Hasting algorithm is used for model parameters estimation and target variable inference. The performance of the proposed framework is evaluated by extensive numerical studies and a case study of nano-sensor calibration.

42 ENGINEERING↗
DOE OSTI2023

Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization

Obtaining lightweight and accurate approximations of discretized objective functional Hessians in inverse problems governed by partial differential equations (PDEs) is essential to make both deterministic and Bayesian statistical large-scale inverse problems computationally tractable. The cubic computational complexity of dense linear algebraic tasks, such as Cholesky factorization, that provide a means to sample Gaussian distributions and determine solutions of Newton linear systems is a computational bottleneck at large-scale. These tasks can be reduced to log-linear complexity by utilizing hierarchical off-diagonal low-rank (HODLR) matrix approximations. In this work, we show that a class of Hessians that arise from inverse problems governed by PDEs are well approximated by the HODLR matrix format. In particular, we study inverse problems governed by PDEs that model the instantaneous viscous flow of ice sheets. In these problems, we seek a spatially distributed basal sliding parameter field such that the flow predicted by the ice sheet model is consistent with ice sheet surface velocity observations. Here, we demonstrate the use of HODLR Hessian approximation to efficiently sample the Laplace approximation of the posterior distribution with covariance further approximated by HODLR matrix compression. Computational studies are performed which illustrate ice sheet problem regimes for which the Gauss–Newton data-misfit Hessian is more efficiently approximated by the HODLR matrix format than the low-rank (LR) format. We then demonstrate that HODLR approximations can be favorable, when compared to global LR approximations, for large-scale problems by studying the data-misfit Hessian associated with inverse problems governed by the first-order Stokes flow model on the Humboldt glacier and Greenland ice sheet.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Changes in polarization dictate necessary approximations for modeling electronic deexcitation intensity: Application to x-ray emission

Accurate simulation of electronic excitations and deexcitations are critical for complementing complex spectroscopic experiments and can provide validation to theoretical approaches. Here, using a generalized framework, we contrast the accuracy and validity of orbital-constrained and linear-response approaches that build upon Kohn-Sham density functional theory (DFT) to simulate emission spectra of electronic origin and propose an efficient approximation, named many-body x-ray emission spectroscopy or MBXES, for simulating such processes. We show analytically as well as with computed examples that for electronic (de)excitation leading to an appreciable change in polarization (i.e., density rearrangement), the adiabatic approximation in a response-based formalism will be inadequate for the calculation of oscillator strength. Thus, such a change (e.g., in the net electrostatic dipole moment of a finite system) can be used as a metric for evaluating the applicability of the adiabatic response-based approach and can be particularly valuable in x-ray emission spectroscopy. On the other hand, MBXES, the flexible method introduced in this paper, can compute oscillator strengths accurately at a much lower computational expense on the basis of two DFT-based self-consistent field calculations. Using illustrative examples of emission spectra, the efficacy of the MBXES method is demonstrated by comparison with its parent theory, orbital-optimized DFT, and with experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Distribution-Level Phasor Measurement Units Application to Composite Load Model Validation

The paper presents the results of composite load model validation based on the distribution level micro- phasor measurement units (PMU) measurements. The actual micro-PMU measurements from the distribution feeders are collected by Lawrence Berkley National Laboratory (LBNL). The composite load model parameters are initially generated using the load model data tool developed by Pacific Northwest National Laboratory (PNNL). The generated load models are calibrated to match the performances with the micro-PMU measurements using disturbance records “play-in” capabilities available in a GE PSLF simulation package. A trial-and-error approach based on engineering judgement is proposed in this paper to benchmark the generated load model parameters and is implemented in the prototype of load model validation tool, which would be a supplement to the load model data tool.

Liu, Yuan↗