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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

TOUGH3: A new efficient version of the TOUGH suite of multiphase flow and transport simulators

The TOUGH suite of nonisothermal multiphase flow and transport simulators has been updated by various developers over many years to address a vast range of challenging subsurface problems. The increasing complexity of the simulated processes as well as the growing size of model domains that need to be handled call for an improvement in the simulator's computational robustness and efficiency. Moreover, modifications have been frequently introduced independently, resulting in multiple versions of TOUGH that (1) led to inconsistencies in feature implementation and usage, (2) made code maintenance and development inefficient, and (3) caused confusion to users and developers. TOUGH3—a new base version of TOUGH—addresses these issues. It consolidates both the serial (TOUGH2 V2.1) and parallel (TOUGH2-MP V2.0) implementations, enabling simulations to be performed on desktop computers and supercomputers using a single code. New PETSc parallel linear solvers are added to the existing serial solvers of TOUGH2 and the Aztec solver used in TOUGH2-MP. The PETSc solvers generally perform better than the Aztec solvers in parallel and the internal TOUGH3 linear solver in serial. TOUGH3 also incorporates many new features, addresses bugs, and improves the flexibility of data handling. So due to the improved capabilities and usability, TOUGH3 is more robust and efficient for solving tough and computationally demanding problems in diverse scientific and practical applications related to subsurface flow modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Free-energy calculations for semi-flexible macromolecules: Applications to DNA knotting and looping

We present a method to obtain numerically accurate values of configurational free energies of semiflexible macromolecular systems, based on the technique of thermodynamic integration combined with normal-mode analysis of a reference system subject to harmonic constraints. Compared with previous free-energy calculations that depend on a reference state, our approach introduces two innovations, namely, the use of internal coordinates to constrain the reference states and the ability to freely select these reference states. As a consequence, it is possible to explore systems that undergo substantially larger fluctuations than those considered in previous calculations, including semiflexible biopolymers having arbitrary ratios of contour length L to persistence length P. To validate the method, high accuracy is demonstrated for free energies of prime DNA knots with L/P = 20 and L/P = 40, corresponding to DNA lengths of 3000 and 6000 base pairs, respectively. We then apply the method to study the free-energy landscape for a model of a synaptic nucleoprotein complex containing a pair of looped domains, revealing a bifurcation in the location of optimal synapse (crossover) sites. This transition is relevant to target-site selection by DNA-binding proteins that occupy multiple DNA sites separated by large linear distances along the genome, a problem that arises naturally in gene regulation, DNA recombination, and the action of type-II topoisomerases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Entanglement propagation and typicality of measurements in the quantum Kac ring

We study the time evolution of entanglement in a new quantum version of the Kac ring, where two spin chains become dynamically entangled by quantum gates, which are used instead of the classical markers. The features of the entanglement evolution are best understood by using knowledge about the behavior of an ensemble of classical Kac rings. For instance, the recurrence time of the quantum many-body system is twice the length of the chain and “thermalization” only occurs on time scales much smaller than the dimension of the Hilbert space. The model thus elucidates the relation between the results of measurements in quantum and classical systems: While in classical systems repeated measurements are performed over an ensemble of systems, the corresponding result is obtained by measuring the same quantum system prepared in an appropriate superposition repeatedly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Derivative-free optimization for parameter estimation in computational nuclear physics

We consider optimization problems that arise when estimating a set of unknown parameters from experimental data, particularly in the context of nuclear density functional theory. We examine the cost of not having derivatives of these functionals with respect to the parameters. We show that the POUNDERS code for local derivative-free optimization obtains consistent solutions on a variety of computationally expensive energy density functional calibration problems. We also provide a primer on the operation of the POUNDERS software in the Toolkit for advanced optimization.

Wild, Stefan M. (ORCID:0000000260992772)↗
NASA NTRS2002

A Uniform Ontology for Software Interfaces

It is universally the case that computer users who are not also computer specialists prefer to deal with computers' in terms of a familiar ontology, namely that of their application domains. For example, the well-known Windows ontology assumes that the user is an office worker, and therefore should be presented with a "desktop environment" featuring entities such as (virtual) file folders, documents, appointment calendars, and the like, rather than a world of machine registers and machine language instructions, or even the DOS command level. The central theme of this research has been the proposition that the user interacting with a software system should have at his disposal both the ontology underlying the system, as well as a model of the system. This information is necessary for the understanding of the system in use, as well as for the automatic generation of assistance for the user, both in solving the problem for which the application is designed, and for providing guidance in the capabilities and use of the system.

Feyock, Stefan↗
DOE OSTI2026

Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning

We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A survey of nonlinear robust optimization

Robust optimization (RO) has attracted great attention from the optimization community over the past decade. RO is dedicated to solving optimization problems subject to uncertainty: design constraints must be satisfied for all the values of the uncertain parameters within a given uncertainty set. Uncertainty sets may be modeled as deterministic sets (boxes, polyhedra, ellipsoids), in which case the RO problem may be reformulated via worst-case analysis, or as families of distributions. The challenge of RO is to reformulate or approximate robust constraints so that the uncertain optimization problem is transformed into a tractable deterministic optimization problem. Most reformulation methods assume linearity of the robust constraints or uncertainty sets of favorable shape, which represents only a fraction of real-world applications. This survey addresses nonlinear RO and includes problem formulations and applications, solution approaches, and available software with code samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Photo-acoustic spectroscopy and quantum efficiency of Yb{sup 3+} doped alumino silicate glasses

In this contribution, we analyze the effect of several preparation methods of Yb{sup 3+} doped alumino silicate glasses on their quantum efficiency by using photo-acoustic measurements in comparison to standard measurement methods including the determination via the fluorescence lifetime and an integrating sphere setup. The preparation methods focused on decreasing the OH concentration by means of fluorine-substitution and/or applying dry melting atmospheres, which led to an increase in the measured fluorescence lifetime. However, it was found that the influence of these methods on radiative properties such as the measured fluorescence lifetime alone does not per se give exact information about the actual quantum efficiency of the sample. The determination of the quantum efficiency by means of fluorescence lifetime shows inaccuracies when refractive index changing elements such as fluorine are incorporated into the glass. Since fluorine not only eliminates OH from the glass but also increases the “intrinsic” radiative fluorescence lifetime, which is needed to calculate the quantum efficiency, it is difficult to separate lifetime quenching from purely radiative effects. The approach used in this contribution offers a possibility to disentangle radiative from non-radiative properties which is not possible by using fluorescence lifetime measurements alone and allows an accurate determination of the quantum efficiency of a given sample. The comparative determination by an integrating sphere setup leads to the well-known problem of reabsorption which embodies itself in the measurement of too low quantum efficiencies, especially for samples with small quantum efficiencies.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Self-interacting inelastic dark matter: a viable solution to the small scale structure problems

Self-interacting dark matter has been proposed as a solution to the small-scale structure problems, such as the observed flat cores in dwarf and low surface brightness galaxies. If scattering takes place through light mediators, the scattering cross section relevant to solve these problems may fall into the non-perturbative regime leading to a non-trivial velocity dependence, which allows compatibility with limits stemming from cluster-size objects. However, these models are strongly constrained by different observations, in particular from the requirements that the decay of the light mediator is sufficiently rapid (before Big Bang Nucleosynthesis) and from direct detection. A natural solution to reconcile both requirements are inelastic endothermic interactions, such that scatterings in direct detection experiments are suppressed or even kinematically forbidden if the mass splitting between the two-states is sufficiently large. Using an exact solution when numerically solving the Schrödinger equation, we study such scenarios and find regions in the parameter space of dark matter and mediator masses, and the mass splitting of the states, where the small scale structure problems can be solved, the dark matter has the correct relic abundance and direct detection limits can be evaded.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

TAO 3.10 Users Manual

The Toolkit for Advanced Optimization (TAO) focuses on the development of algorithms and software for the solution of large-scale optimization problems on high-performance architectures. Areas of interest include unconstrained and bound-constrained optimization, nonlinear least squares problems, optimization problems with partial differential equation constraints, and variational inequalities and complementarity constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Postoperative 3D spine reconstruction by navigating partitioning manifolds

Purpose: The postoperative evaluation of scoliosis patients undergoing corrective treatment is an important task to assess the strategy of the spinal surgery. Using accurate 3D geometric models of the patient’s spine is essential to measure longitudinal changes in the patient’s anatomy. On the other hand, reconstructing the spine in 3D from postoperative radiographs is a challenging problem due to the presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. Methods: This paper describes the reconstruction problem by searching for the optimal model within a manifold space of articulated spines learned from a training dataset of pathological cases who underwent surgery. The manifold structure is implemented based on a multilevel manifold ensemble to structure the data, incorporating connections between nodes within a single manifold, in addition to connections between different multilevel manifolds, representing subregions with similar characteristics. Results: The reconstruction pipeline was evaluated on x-ray datasets from both preoperative patients and patients with spinal surgery. By comparing the method to ground-truth models, a 3D reconstruction accuracy of 2.24 ± 0.90 mm was obtained from 30 postoperative scoliotic patients, while handling patients with highly deformed spines. Conclusions: This paper illustrates how this manifold model can accurately identify similar spine models by navigating in the low-dimensional space, as well as computing nonlinear charts within local neighborhoods of the embedded space during the testing phase. This technique allows postoperative follow-ups of spinal surgery using personalized 3D spine models and assess surgical strategies for spinal deformities.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

Evaluation of multiple reduced-order models to enhance confidence in global sensitivity analyses

Variance-based global sensitivity analysis (e.g., the Sobol' sensitivity index) can be used to identify the important parameters over the entire parameter space. However, one often cannot afford the computational costs of sampling-based approaches in combination with expensive high-fidelity forward models. Reduced-order models (ROM) can substantially accelerate calculation of these sensitivities. However, it is usually difficult to determine what type of ROM should be used and how accurately the ROM represents the high-fidelity model (HFM) results. Here in this paper, we propose to concurrently use multiple ROMs as a way to assess the robustness of the model-reduction method. Two sets of HFM simulations are needed, one set for building ROMs and the other for validating ROMs. Our goal is to keep the total number of HFM simulations to a minimum. Ideally some of the HFM simulations in the first set can be shared by different ROMs. Based on validation results, the ROMs can be combined with different schemes. We demonstrate that we can achieve the goal by using four different ROMs and still considerably save computational time compared to using traditional HFM simulation for calculating sensitivity indices. We apply the approach to an example problem of a large-scale geological carbon dioxide storage system, in which the objective is to calculate a sensitivity index to identify important parameters. For this problem, the locally best ROM provides better estimates than the weighted average from all ROMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

GPU accelerated fully space and time resolved numerical simulations of self-focusing laser beams in SBS-active media

A computer cluster equipped with Graphics Processing Units (GPUs) is used for simulating nonlinear optical wave packets undergoing Kerr self-focusing and stimulated Brillouin scattering in fused silica. We first recall the model equations in full (3+1) dimensions. These consist of two coupled nonlinear Schrödinger equations for counterpropagating optical beams closed with a source equation for light-induced acoustic waves seeded by thermal noise. Compared with simulations on a conventional cluster of Central Processing Units (CPUs), GPU-based computations allow us to use a significant (16 times) larger number of mesh points within similar computation times. Reciprocally, simulations employing the same number of mesh points are between 3 and 20 times faster on GPUs than on the same number of classical CPUs. Performance speedups close to 45 are reported for isolated functions evaluating, e.g., the optical nonlinearities. Since the field intensities may reach the ionization threshold of silica, the action of a defocusing electron plasma is also addressed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Single-view phase retrieval of an extended sample by exploiting edge detection and sparsity

We propose a new approach to robustly retrieve the exit wave of an extended sample from its coherent diffraction pattern by exploiting sparsity of the sample's edges. This approach enables imaging of an extended sample with a single view, without ptychography. We introduce nonlinear optimization methods that promote sparsity, and we derive update rules to robustly recover the sample's exit wave. We test these methods on simulated samples by varying the sparsity of the edge-detected representation of the exit wave. Finally, our tests illustrate the strengths and limitations of the proposed method in imaging extended samples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1988

On the size and composition of particles in polar stratospheric clouds

Attenuation measurements of the solar radiation between 1.5 and 15 micron wavelengths were performed with the airborne (DC-8) JPL MARK 4 interferometer during the 1987 Antarctic Expedition. The opacities not only provide information about the abundance of stratospheric gases but also about the optical depths of polar stratospheric clouds (PSCs) at wavelengths of negligible gas absorption (windows). The optical depth of PSCs can be determined for each window once the background attenuation, due to air-molecules and aerosol has been filtered out with a simple extinction law. The ratio of optical thicknesses at different wavelengths reveals information about particle size and particle composition. Among the almost 700 measured spectra only a few PSC cases exist. PSC events are identified by sudden reductions in the spectrally integrated intensity value and are also verified with backscattering data from an upward directed lidar instrument, that was mounted on the DC-8. For the selected case on September 21st at 14.40 GMT, lidar data indicate an optically thin cloud at 18k and later an additional optically thick cloud at 15 km altitude. All results still suffer from: (1) often arbitrary definitions of a clear case, that often already may have contained PSC particles and (2) noise problems that restrict the calculations of optical depths to values larger than 0.001. Once these problems are handled, this instrument may become a valuable tool towards a better understanding of the role PSCs play in the Antarctic stratosphere.

Kinne, Stefan↗
DOE OSTI2019

Derivative-free optimization methods

In many optimization problems arising from scientific, engineering and artificial intelligence applications, objective and constraint functions are available only as the output of a black-box or simulation oracle that does not provide derivative information. Such settings necessitate the use of methods for derivative-free, or zeroth-order, optimization. We provide a review and perspectives on developments in these methods, with an emphasis on highlighting recent developments and on unifying treatment of such problems in the non-linear optimization and machine learning literature. We categorize methods based on assumed properties of the black-box functions, as well as features of the methods. We first overview the primary setting of deterministic methods applied to unconstrained, non-convex optimization problems where the objective function is defined by a deterministic black-box oracle. We then discuss developments in randomized methods, methods that assume some additional structure about the objective (including convexity, separability and general non-smooth compositions), methods for problems where the output of the black-box oracle is stochastic, and methods for handling different types of constraints.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Neural nets on the MPP

The Massively Parallel Processor (MPP) is an ideal machine for computer experiments with simulated neural nets as well as more general cellular automata. Experiments using the MPP with a formal model neural network are described. The results on problem mapping and computational efficiency apply equally well to the neural nets of Hopfield, Hinton et al., and Geman and Geman.

Hastings, Harold M.↗
NASA NTRS2004

Adaptive Multi-Agent Systems for Constrained Optimization

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Macready, William↗