Search NASA⌕ Search

SEARCH · Search NASA

Results for “compute intensive problems”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Baseline suppression problems for high precision measurements using optical beam profile monitors

The use of fluorescent screens (e.g. YAG screens) and Optical Transition Radiation (OTR) screens for beam profile monitors provides a simple and widely used way to obtain detailed two dimensional intensity maps. What makes this possible is the availability of relatively inexpensive CCD cameras. For high precision measurements many possible error contributions need to be considered that have to do with properties of the fluorescent screens and of the CCDs. Saturation effects, reflections within and outside the screen, non-linearities, radiation damage, etc are often mentioned. Here we concentrate on an error source less commonly described, namely erroneous baseline subtraction, which is particularly important when fitting projected images. We show computer simulations as well as measurement results having remarkable sensitivity of the fitted profile widths to even partial suppression of the profile baseline data, which often arises from large pixel-to-pixel variations at low intensity levels. Such inadvertent baseline data suppression is very easy to miss as it is usually not obvious when inspecting projected profiles. In this report we illustrate this effect and discuss possible algorithms to automate the detection of this problem as well as some possible corrective measures.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

TomoPyUI : a user-friendly tool for rapid tomography alignment and reconstruction

The management and processing of synchrotron and neutron computed tomography data can be a complex, labor-intensive and unstructured process. Users devote substantial time to both manually processing their data ( i.e. organizing data/metadata, applying image filters etc. ) and waiting for the computation of iterative alignment and reconstruction algorithms to finish. In this work, we present a solution to these problems: TomoPyUI , a user interface for the well known tomography data processing package TomoPy . This highly visual Python software package guides the user through the tomography processing pipeline from data import, preprocessing, alignment and finally to 3D volume reconstruction. The TomoPyUI systematic intermediate data and metadata storage system improves organization, and the inspection and manipulation tools (built within the application) help to avoid interrupted workflows. Notably, TomoPyUI operates entirely within a Jupyter environment. Herein, we provide a summary of these key features of TomoPyUI , along with an overview of the tomography processing pipeline, a discussion of the landscape of existing tomography processing software and the purpose of TomoPyUI , and a demonstration of its capabilities for real tomography data collected at SSRL beamline 6-2c.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2003

Iterative pass optimization of sequence data

The problem of determining the minimum-cost hypothetical ancestral sequences for a given cladogram is known to be NP-complete. This "tree alignment" problem has motivated the considerable effort placed in multiple sequence alignment procedures. Wheeler in 1996 proposed a heuristic method, direct optimization, to calculate cladogram costs without the intervention of multiple sequence alignment. This method, though more efficient in time and more effective in cladogram length than many alignment-based procedures, greedily optimizes nodes based on descendent information only. In their proposal of an exact multiple alignment solution, Sankoff et al. in 1976 described a heuristic procedure--the iterative improvement method--to create alignments at internal nodes by solving a series of median problems. The combination of a three-sequence direct optimization with iterative improvement and a branch-length-based cladogram cost procedure, provides an algorithm that frequently results in superior (i.e., lower) cladogram costs. This iterative pass optimization is both computation and memory intensive, but economies can be made to reduce this burden. An example in arthropod systematics is discussed. c2003 The Willi Hennig Society. Published by Elsevier Science (USA). All rights reserved.

NASA Discipline Evolutionary Biology↗
DOE OSTI2018

Modeling Radiation Detection Using a Mixed-Effects Statistical Model for Background Variation

In this paper, we consider radiation source localization in an urban environment as an inverse problem and use Bayesian parameter estimation techniques to infer the source location and intensity. Since parameter estimation generally requires a large number of model evaluations, we employ a simplified photon transport model, as in a 2017 paper by Stefanescu, et al., to reduce computational requirements. However, the model in the 2017 paper does not account for the physical reality that background radiation varies with position within an urban locale. We incorporate statistical mixed-effects modeling into the simplified transport equation from the Stefanescu, et al. paper to reflect individual variation among the background radiation measurements at multiple detector locations. With our new model, we use a Bayesian DRAM-within-Gibbs technique, which incorporates the Delayed Rejection Adaptive Metropolis (DRAM) algorithm, to estimate the mixed-effects parameters. We note that without adequate prior information, we were unable to simultaneously estimate the set of parameters corresponding to the source intensity, source location, and individual background radiation counts. By calibrating the background in the absence of a source, we obtained narrow prior distributions, which permitted us to jointly infer the source intensity and location and the background radiation distribution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1978

Singularity computations

Direct descriptions of the structure of a singularity would describe the radial and angular distributions of the field quantities as explicitly as practicable along with some measure of the intensity of the singularity. This paper discusses such an approach based on recent development of numerical methods for elastoplastic flow. Attention is restricted to problems where one variable or set of variables is finite at the origin of the singularity but a second set is not.

Swedlow, J. L.↗
DOE OSTI2024

PHASM: A Toolkit for Creating AI Surrogate Models within Legacy Codebases

PHASM (“Parallel Hardware viA Surrogate Models”) is a software toolkit for creating AI-based surrogate models of scientific code. AI-based surrogate models are widely used for creating fast and inverse simulations. PHASM anticipates an additional future use case: adapting legacy code to modern hardware. While data centers are investing in heterogeneous hardware such as GPUs and FPGAs, many established scientific codebases remain unable to take advantage of the hardware’s higher parallelism without undergoing a costly rewrite. An alternative is to train a AI-based surrogate model to mimic computationally intensive functions in the code, and run the surrogate instead. PHASM formalizes a development lifecycle for such surrogate models, including discovering functions amenable to replacement with a surrogate model, predicting the resulting performance, identifying the function’s space of inputs and outputs, binding the model to the code, and managing model versions. A suite of software tools for facilitating these steps was written and validated against a set of model problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Brochure on the 2024 ASCR Workshop on Analog Computing for Science

Analog computing fundamentally differs from digital by representing data with fully continuous physical quantities, such as voltages, probabilities, chemical concentrations, or light intensities, rather than encoding values in discrete binary states. While digital computing has historically excelled in precision, scalability, and noise resistance, newer analog approaches are gaining interest for their potential to dramatically improve energy efficiency and processing speed. Analog systems can inherently solve mathematical problems through their physical behavior and offer distinct advantages in scenarios where continuous operations are more effective than Boolean logic.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Preconditioning bandgap eigenvalue problems in three-dimensional photonic crystals simulations

To explore band structures of three-dimensional photonic crystals numerically, we need to solve the eigenvalue problems derived from the governing Maxwell equations. The solutions of these eigenvalue problems cannot be computed effectively unless a suitable combination of eigenvalue solver and preconditioner is chosen. Taking eigenvalue problems due to Yee's scheme as examples, we propose using Krylov-Schur method and Jacobi-Davidson method to solve the resulting eigenvalue problems. For preconditioning, we derive several novel preconditioning schemes based on various preconditioners, including a preconditioner that can be solved by Fast Fourier Transform efficiently. We then conduct intensive numerical experiments for various combinations of eigenvalue solvers and preconditioning schemes. We find that the Krylov-Schur method associated with the Fast Fourier Transform based preconditioner is very efficient. It remarkably outperforms all other eigenvalue solvers with common preconditioners like Jacobi, Symmetric Successive Over Relaxation, and incomplete factorizations. This promising solver can benefit applications like photonic crystal structure optimization.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Plates and shells containing a surface crack under general loading conditions

Various through and part-through crack problems in plates and shells are considered. The line-spring model of Rice and Levy is generalized to the skew-symmetric case to solve surface crack problems involving mixed-mode, coplanar crack growth. Compliance functions are introduced which are valid for crack depth to thickness ratios at least up to .95. This includes expressions for tension and bending as well as expressions for in-plane shear, out-of-plane shear, and twisting. Transverse shear deformation is taken into account in the plate and shell theories and this effect is shown to be important in comparing stress intensity factors obtained from the plate theory with three-dimensional solutions. Stress intensity factors for cylinders obtained by the line-spring model also compare well with three-dimensional solution. By using the line-spring approach, stress intensity factors can be obtained for the through crack and for part-through crack of any crack front shape, without recalculation integrals that take up the bulk of the computer time. Therefore, parameter studies involving crack length, crack depth, shell type, and shell curvature are made in some detail. The results will be useful in brittle fracture and in fatigue crack propagation studies. All problems considered are of the mixed boundary value type and are reducted to strongly singular integral equations which make use of the finite-part integrals of Hadamard. The equations are solved numerically in a manner that is very efficient.

Joseph, Paul F.↗
DOE OSTI2022

TTDFT: A GPU accelerated Tucker tensor DFT code for large-scale Kohn-Sham DFT calculations

We present the Tucker tensor DFT (TTDFT) code which uses a tensor-structured algorithm with graphic processing unit (GPU) acceleration for conducting ground-state DFT calculations on large-scale systems. The Tucker tensor DFT algorithm uses a localized Tucker tensor basis computed from an additive separable approximation to the Kohn-Sham Hamiltonian. The discrete Kohn-Sham problem is solved using Chebyshev filtered subspace iteration method that relies on matrix-matrix multiplications of a sparse symmetric Hamiltonian matrix and a dense wavefunction matrix, expressed in the localized Tucker tensor basis. These matrix-matrix multiplication operations, which constitute the most computationally intensive step of the solution procedure, are GPU accelerated providing ~8-fold GPU-CPU speedup for these operations on the largest systems studied. In conclusion, the computational performance of the TTDFT code is presented using benchmark studies on aluminum nano-particles and silicon quantum dots with system sizes ranging up to ~7,000 atoms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

An ab initio model for the modulation of galactic cosmic-ray electrons

The modulation of galactic cosmic-ray electrons is studied using an ab initio three-dimensional steady state cosmic-ray modulation code in which the effects of turbulence on both the diffusion and drift of these cosmic-rays are treated as self-consistently as possible. A significant refinement is that a recent two-component turbulence transport model is used. This model yields results in reasonable agreement with observations of turbulence quantities throughout the heliosphere. The sensitivity of computed galactic electron intensities to choices of various turbulence parameters pertaining to the dissipation range of the slab turbulence spectrum, and to the choice of model of dynamical turbulence, is demonstrated using diffusion coefficients derived from the quasi-linear and extended nonlinear guiding center theories. Computed electron intensities and latitude gradients are also compared with spacecraft observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Adaptive Numerical Dissipation Control in High Order Schemes for Multi-D Non-Ideal MHD

The required type and amount of numerical dissipation/filter to accurately resolve all relevant multiscales of complex MHD unsteady high-speed shock/shear/turbulence/combustion problems are not only physical problem dependent, but also vary from one flow region to another. In addition, proper and efficient control of the divergence of the magnetic field (Div(B)) numerical error for high order shock-capturing methods poses extra requirements for the considered type of CPU intensive computations. The goal is to extend our adaptive numerical dissipation control in high order filter schemes and our new divergence-free methods for ideal MHD to non-ideal MHD that include viscosity and resistivity. The key idea consists of automatic detection of different flow features as distinct sensors to signal the appropriate type and amount of numerical dissipation/filter where needed and leave the rest of the region free from numerical dissipation contamination. These scheme-independent detectors are capable of distinguishing shocks/shears, flame sheets, turbulent fluctuations and spurious high-frequency oscillations. The detection algorithm is based on an artificial compression method (ACM) (for shocks/shears), and redundant multiresolution wavelets (WAV) (for the above types of flow feature). These filters also provide a natural and efficient way for the minimization of Div(B) numerical error.

Yee, H. C.↗
DOE OSTI2018

Nonstationary Problem of Complex Heat Transfer in a System of Semitransparent Bodies with Boundary-Value Conditions of Diffuse Reflection and Refraction of Radiation

We consider a nonstationary initial boundary-value problem describing complex (radiative-conductive) heat transfer in a system of semitransparent bodies. To describe radiation propagation, we use the radiation transfer equation with boundary-value conditions of diffuse reflection and refraction of radiation. We take into account that the radiation intensity and optical properties of bodies depend on the radiation frequency. The unique solvability of a weak solution is established. The comparison theorem is proved. A priori estimates of a weak solution as well as its regularity are obtained.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence

Particle-laden turbulent flows subject to radiative heating are relevant in many applications, for example concentrated solar power receivers. Efficient and accurate simulations provide valuable insights and enable optimization of such systems. However, as there are many uncertainties inherent in such flows, uncertainty quantification is fundamental to improve the predictive capabilities of the numerical simulations. For large-scale, multi-physics problems exhibiting high-dimensional uncertainty, characterizing the stochastic solution presents a significant computational challenge as most strategies require a large number of high-fidelity solves. This requirement might result in an infeasible number of simulations when a typical converged high-fidelity simulation requires intensive computational resources. To reduce the cost of quantifying high-dimensional uncertainties, we investigate the application of a non-intrusive, bi-fidelity approximation to estimate statistics of quantities of interest associated with an irradiated particle-laden turbulent flow. This method exploits the low-rank structure of the solution to accelerate the stochastic sampling and approximation processes by means of cheaper-to-run, lower fidelity representations. Here, the application of this bi-fidelity approximation results in accurate estimates of the quantities of interest statistics, while requiring a small number of high-fidelity model evaluations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Photoelectron Spectra of Aqueous Solutions from First Principles

We present a combined computational and experimental study of the photoelectron spectrum of a simple aqueous solution of NaCl. Measurements were conducted on microjets, and first-principles calculations were performed using hybrid functionals and many-body perturbation theory at the G0W0 level, starting with wave functions computed in ab initio molecular dynamics simulations. We show excellent agreement between theory and experiments for the positions of both the solute and solvent excitation energies on an absolute energy scale and for peak intensities. The best comparison was obtained using wave functions obtained with dielectric-dependent self-consistent and range-separated hybrid functionals. Our computational protocol opens the way to accurate, predictive calculations of the electronic properties of electrolytes, of interest to a variety of energy problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Designing Algorithms for the EMU Migrating-threads-based Architecture

The decades-old memory bottleneck problem for data-intensive applications is getting worse as the processor core counts continue to increase. Workloads with sparse memory access characteristics only achieve a fraction of a system’s total memory bandwidth. EMU architecture provides a radical approach to the issue by migrating the computational threads to the location where the data resides. The system enables access to a large PGAS-type memory for hundreds of nodes via a Cilk- based multi-threaded execution scheme.EMU architecture brings brand new challenges in application design and development. Data distribution and thread creation strategies play a crucial role in achieving optimal performance in the EMU platform. In this work, we identify several design considerations that need to be taken care of while developing applications for the new architecture and we evaluate their performance effects on the EMU-chick hardware. We also present a modified BFS algorithm for the EMU system and give experi- mental results for its execution on the platform.

Belviranli, Mehmet E.↗
DOE OSTI2016

GALACTIC COSMIC-RAY INTENSITY MODULATION BY COROTATING INTERACTION REGION STREAM INTERFACES AT 1 au

We present a new model that couples galactic cosmic-ray (GCR) propagation with magnetic turbulence transport and the MHD background evolution in the heliosphere. The model is applied to the problem of the formation of corotating interaction regions (CIRs) during the last solar minimum from the period between 2007 and 2009. The numerical model simultaneously calculates the large-scale supersonic solar wind properties and its small-scale turbulent content from 0.3 au to the termination shock. Cosmic rays are then transported through the background, and thus computed, with diffusion coefficients derived from the solar wind turbulent properties, using a stochastic Parker approach. Our results demonstrate that GCR variations depend on the ratio of diffusion coefficients in the fast and slow solar winds. Stream interfaces inside the CIRs always lead to depressions of the GCR intensity. On the other hand, heliospheric current sheet (HCS) crossings do not appreciably affect GCR intensities in the model, which is consistent with the two observations under quiet solar wind conditions. Therefore, variations in diffusion coefficients associated with CIR stream interfaces are more important for GCR propagation than the drift effects of the HCS during a negative solar minimum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗