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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

SU-D-210-05: The Accuracy of Raw and B-Mode Image Data for Ultrasound Speckle Tracking in Radiation Therapy

Purpose: For ultrasound speckle tracking there is some evidence that the envelope-detected signal (the main step in B-mode image formation) may be more accurate than raw ultrasound data for tracking larger inter-frame tissue motion. This study investigates the accuracy of raw radio-frequency (RF) versus non-logarithmic compressed envelope-detected (B-mode) data for ultrasound speckle tracking in the context of image-guided radiation therapy. Methods: Transperineal ultrasound RF data was acquired (with a 7.5 MHz linear transducer operating at a 12 Hz frame rate) from a speckle phantom moving with realistic intra-fraction prostate motion derived from a commercial tracking system. A normalised cross-correlation template matching algorithm was used to track speckle motion at the focus using (i) the RF signal and (ii) the B-mode signal. A range of imaging rates (0.5 to 12 Hz) were simulated by decimating the imaging sequences, therefore simulating larger to smaller inter-frame displacements. Motion estimation accuracy was quantified by comparison with known phantom motion. Results: The differences between RF and B-mode motion estimation accuracy (2D mean and 95% errors relative to ground truth displacements) were less than 0.01 mm for stable and persistent motion types and 0.2 mm for transient motion for imaging rates of 0.5 to 12 Hz. The mean correlation for all motion types and imaging rates was 0.851 and 0.845 for RF and B-mode data, respectively. Data type is expected to have most impact on axial (Superior-Inferior) motion estimation. Axial differences were <0.004 mm for stable and persistent motion and <0.3 mm for transient motion (axial mean errors were lowest for B-mode in all cases). Conclusions: Using the RF or B-mode signal for speckle motion estimation is comparable for translational prostate motion. B-mode image formation may involve other signal-processing steps which also influence motion estimation accuracy. A similar study for respiratory-induced motion would also be prudent. This work is support by Cancer Research UK Programme Grant C33589/A19727.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Traversing large graphs on GPUs with unified memory

Due to the limited capacity of GPU memory, the majority of prior work on graph applications on GPUs has been restricted to graphs of modest sizes that fit in memory. Recent hardware and software advances make it possible to address much larger host memory transparently as a part of a feature known as unified virtual memory. While accessing host memory over an interconnect is understandably slower, the problem space has not been sufficiently explored in the context of a challenging workload with low computational intensity and an irregular data access pattern such as graph traversal. We analyse the performance of breadth first search (BFS) for several large graphs in the context of unified memory and identify the key factors that contribute to slowdowns. Next, we propose a lightweight offline graph reordering algorithm, HALO (Harmonic Locality Ordering), that can be used as a pre-processing step for static graphs. HALO yields speedups of 1.5x-1.9x over baseline in subsequent traversals. Our method specifically aims to cover large directed real world graphs in addition to undirected graphs whereas prior methods only account for the latter. Additionally, we demonstrate ties between the locality ordering problem and graph compression and show that prior methods from graph compression such as recursive graph bisection can be suitably adapted to this problem.

Gera, Prasun↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2026

Model-Based Investigation of Multi-Fault Interactions and Performance Degradation in Residential Heat Pump Systems

Faults in heat pump systems can significantly degrade performance, reduce efficiency, and accelerate component wear, leading to higher operating costs and maintenance demands. While numerous studies have investigated the impact of individual faults, the interactions between multiple concurrent faults remain insufficiently understood, despite their common occurrence in real-world operation. This study conducts a comprehensive simulation analysis of multiple simultaneous faults in a vapor compression heat pump using a validated heat pump design model (HPDM) tool. Detailed component-level modeling methods are implemented to examine performance sensitivity under combinations of refrigerant flow and heat exchanger faults. The results reveal complex fault interactions that can mask or amplify system deviations, challenging conventional diagnostic approaches. Findings from this work provide meaningful insights for the development of more robust fault detection and diagnosis algorithms, supporting improved reliability and energy efficiency in next-generation heat pump technologies.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2020

Modeling of the thermo-mechanical response and texture evolution of WE43 Mg alloy in the dynamic recrystallization regime using a viscoplastic self-consistent formulation

This paper presents a microstructure sensitive model for predicting mechanical response and texture evolution of metals in the dynamic recrystallization regime. A recently proposed viscoplastic self-consistent (VPSC) formulation for the prediction of recrystallization driven by strain energy and intragranular misorientation is extended to hexagonal close-packed (hcp) metals. The model is applied to the dynamic recrystallization of magnesium alloy WE43 at different temperatures and strain rates. Model predictions in terms of stress-strain response and texture evolution are compared to the experimental measurements and acceptable agreement is achieved. According to the model predictions, superplastic behavior of nuclei was found to be the dominant softening mechanism at high temperatures and low strain rates. High concentration of precipitates at the grain boundaries and presence of alloying elements are the likely causes of low boundary mobility, resulting in nucleation dominated dynamic recrystallization. Relatively strong basal compression textures indicate dominant activity of basal slip, which can be achieved only through large difference in slip resistance between soft basal and hard prismatic and pyramidal modes.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Population of 224 realistic human subject-based computational breast phantoms

Purpose: To create a database of highly realistic and anatomically variable 3D virtual breast phantoms based on dedicated breast computed tomography (bCT) data. Methods: A tissue classification and segmentation algorithm was used to create realistic and detailed 3D computational breast phantoms based on 230 + dedicated bCT datasets from normal human subjects. The breast volume was identified using a coarse three-class fuzzy C-means segmentation algorithm which accounted for and removed motion blur at the breast periphery. Noise in the bCT data was reduced through application of a postreconstruction 3D bilateral filter. A 3D adipose nonuniformity (bias field) correction was then applied followed by glandular segmentation using a 3D bias-corrected fuzzy C-means algorithm. Multiple tissue classes were defined including skin, adipose, and several fractional glandular densities. Following segmentation, a skin mask was produced which preserved the interdigitated skin, adipose, and glandular boundaries of the skin interior. Finally, surface modeling was used to produce digital phantoms with methods complementary to the XCAT suite of digital human phantoms. Results: After rejecting some datasets due to artifacts, 224 virtual breast phantoms were created which emulate the complex breast parenchyma of actual human subjects. The volume breast density (with skin) ranged from 5.5% to 66.3% with a mean value of 25.3% ± 13.2%. Breast volumes ranged from 25.0 to 2099.6 ml with a mean value of 716.3 ± 386.5 ml. Three breast phantoms were selected for imaging with digital compression (using finite element modeling) and simple ray-tracing, and the results show promise in their potential to produce realistic simulated mammograms. Conclusions: This work provides a new population of 224 breast phantoms based on in vivo bCT data for imaging research. Compared to previous studies based on only a few prototype cases, this dataset provides a rich source of new cases spanning a wide range of breast types, volumes, densities, and parenchymal patterns.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

ECP Milestone Memo WBS 2.3.4.13 ECP/VTK-m FY19Q1 [MS-19/01-03] ZFP / Release / Clip STDA05-17

The STDA05-17 milestone comprises the following 3 deliverables. VTK-m Release 2 We will provide a release of VTK-m software and associated documentation. The source code repository will be tagged at a stable state, and, at a minimum, tarball captures of the source code will be made available from the web site. A version of the VTK-m User's Guide documenting this release will also be made available. Productionize zfp compression The "ZFP: Compressed Floating-Point Arrays" project (WBS 1.3.4.13) is creating an implementation of ZFP compression in VTK-m. Their implementation will be focused on operating in CUDA. The VTK-m project will assist by generalizing the implementation to other devices (such as multi-core CPUs). We will also assist in productionizing the code such that it can be used by external projects and products. Clip Clip operations intersect meshes with implicit functions. It is the foundation of spatial subsetting algorithms, such as "box," and the foundation of data-based subsetting, such as "isovolume." The algorithm requires considering thousands of possible cases, and is thus quite difficult to implement. This milestone will implement clipping to be sufficient for Visit's and ParaView's needs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Systematic Study on the Dynamic Softening Behavior of a Heat-Resistant Alloy Considering Thermal and Microstructural Effects

Deep understanding of the relationships among flow softening behaviors, microstructure evolution and process parameters is an essential issue due to the varied strain rate and temperature in industrial hot working schedules. In this research, substantial hot compression tests of a SNCrW heat-resistant alloy were conducted to quantitatively investigate the extrinsic dynamic flow softening behaviors and intrinsic grain size evolution. The thermal softening ratio (TSR) and microstructural softening ratio (MSR) were introduced to, respectively, characterize the degree of deformation heating-induced thermal softening and dynamic recrystallization-induced microstructural softening, respectively. To obtain more accurate results, the TSR was calculated with an improved algorithm that considered strain effects. Additionally, a 3D TSR map and MSR map of the SNCrW heat-resistant alloy were constructed to study the response relationships between thermal softening or microstructural softening and the deformation parameters. In addition, a superimposed contour map of the average grain size on the MSR map was developed to reveal the relationships between microstructural evolution and the macromechanical response. The results show that the grain size of the SNCrW heat-resistant alloy exhibits an inverse correlation with the MSR and is slightly correlated with thermal softening.

36 MATERIALS SCIENCE↗
DOE OSTI2015

CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field

Here we report that proper treatment of nonbonded interactions is essential for the accuracy of molecular dynamics (MD) simulations, especially in studies of lipid bilayers. The use of the CHARMM36 force field (C36 FF) in different MD simulation programs can result in disagreements with published simulations performed with CHARMM due to differences in the protocols used to treat the long-range and 1-4 nonbonded interactions. In this study, we systematically test the use of the C36 lipid FF in NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM. A wide range of Lennard-Jones (LJ) cutoff schemes and integrator algorithms were tested to find the optimal simulation protocol to best match bilayer properties of six lipids with varying acyl chain saturation and head groups. MD simulations of a 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) bilayer were used to obtain the optimal protocol for each program. MD simulations with all programs were found to reasonably match the DPPC bilayer properties (surface area per lipid, chain order parameters, and area compressibility modulus) obtained using the standard protocol used in CHARMM as well as from experiments. The optimal simulation protocol was then applied to the other five lipid simulations and resulted in excellent agreement between results from most simulation programs as well as with experimental data. AMBER compared least favorably with the expected membrane properties, which appears to be due to its use of the hard-truncation in the LJ potential versus a force-based switching function used to smooth the LJ potential as it approaches the cutoff distance. The optimal simulation protocol for each program has been implemented in CHARMM-GUI. This protocol is expected to be applicable to the remainder of the additive C36 FF including the proteins, nucleic acids, carbohydrates, and small molecules.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Chemical Pressure-Driven Enhancement of the Hydrogen Evolving Activity of Ni 2 P from Nonmetal Surface Doping Interpreted via Machine Learning

The activity of Ni 2 P catalysts for the hydrogen evolution reaction (HER) is currently limited by strong H adsorption at the Ni 3 -hollow site. We investigate the effect of surface nonmetal doping on the HER activity of the Ni 3 P 2 termination of Ni 2 P(0001), which is stable at modest electrochemical conditions. Using density functional theory (DFT) calculations, we find that both 2p nonmetals and heavier chalcogens provide nearly thermoneutral H adsorption at moderate surface doping concentrations. We also find, however, that only chalcogen substitution for surface P is exergonic. For intermediate surface concentrations of S, the free energy of H adsorption at the Ni 3 -hollow site is -0.11 eV, which is significantly more thermoneutral than the undoped surface (-0.45 eV). We use the regularized random forest machine learning algorithm to discover the relative importance of structure and charge descriptors, extracted from the DFT calculations, in determining the HER activity of Ni 2 P(0001) under different doping concentrations. Here, we discover that the Ni–Ni bond length is the most important descriptor of HER activity, which suggests that the nonmetal dopants induce a chemical pressure-like effect on the Ni 3 -hollow site, changing its reactivity through compression and expansion.

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

Temporal feedback control of high-intensity laser pulses to optimize ultrafast heating of atomic clusters

We describe how active feedback routines can be applied at a limited repetition rate (5 Hz) to optimize high-power (>10 TW) laser interactions with clustered gases. Optimization of x-ray production from an argon cluster jet, using a genetic algorithm, approximately doubled the measured energy through temporal modification of the 150 mJ driving laser pulse. This method achieved an increased radiation yield through exploration of a multi-dimensional parameter space, without requiring detailed a priori knowledge of the complex cluster dynamics. The optimized laser pulses exhibited a slow rising edge to the intensity profile, which enhanced the laser energy coupling into the cluster medium, compared to the optimally compressed FWHM pulse (40 fs). This report suggests that this technique can be more widely utilized for control of intense pulsed secondary radiation from petawatt-class laser systems.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

A Conservative Finite-Volume Based Interface-Tracking Algorithm Using the Signed Distance Function

Methods for tracking an interface between two fluid phases are developed to ensure desired fluid properties, conservation, and stability are preserved in a finitevolume (FV) discretization. Here, the interface is tracked using a level set method where the signed distance function implicitly defines the interface. Marching methods are used to evaluate the value of the signed distance function, including a novel initialization method to initialize any implicit function to the signed distance function around sharp corners in the level set. Global conservation and consistency with a set of governing equations is enforced by a compression coefficient that measures the volumetric compression or expansion due to inaccuracies in the level set evaluation. A redistribution method is integrated into the volume correction to eliminate the small-cell instability while maintaining global conservation. This suite of methods is implemented and tested using static uniform velocity, and potential flow cases with multiple interface geometries. Results show these methods achieve up to second order accuracy, and are conservative. The application for these methods is intended to track the interface of a 3D printing filament in a finite-volume discretization of the all-speed Navier-Stokes equations.

42 ENGINEERING↗
DOE OSTI2015

Geomechanical and Fluid Transport Properties

Complex changes to fluid and mechanical properties of a pyrolyzing formation could lead to significant subsidence. Capturing subsidence requires accounting for changes in porosity due to generation and drainage of fluid. Pores, permeability and pore pressure are generated during pyrolysis of kerogen into oil and gas. In a series reaction scheme, oil is an intermediate product of pyrolysis. A large portion of oil-range fluids may be lost in an in-situ operation if the oil produced cannot be drained quickly enough. Petroleum fluid quality and production are highly dependent on the relative rates of creation, destruction, and transport of oil and gas in a given volume. All of these are dependent on the heating rate of oil shale. If oil shale is heated quickly, fluid flow may increase, but at a cost to the amount of oil that is finally extracted. To account for the effect of pore fluid on mechanical deformation, an elastic model was combined with a Mohr-Coulomb failure criterion and Biot’s linear consolidation model. The overall model is poroelastic, because it accounts for rock deforming by considering the response of the bulk system and the pore fluids it contains. Biot’s linear model includes all ways that pore fluid volume can change in a system, including stress-strain interactions between pores and the bulk material. Additionally, the model captures the distinction between fluid and solid matrix compression and describes how bulk deformation is affected by fluid drainage. The fluid response to changing stress is affected by changes in pore pressure, while the bulk material responds to effective stress changes. To capture all of these effects, a number of theoretical and empirical models were employed in FLAC3D™, a rock-mechanics software package produced by Itasca Consulting Group. The basic capabilities of FLAC3D™ have been supplemented by customized algorithms for the simulation package. The most important contribution has been to develop a methodology for describing poro-thermo-mechanical properties of oil shale across the complete chronology of in situ pyrolysis. This report highlights those methods and results for inferring realistic oil shale properties.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2025

FedEFsz: Fair Cross-Silo Federated Learning System With Error-Bounded Lossy Compression

Cross-Silo federated learning systems have been identified as an efficient approach to scaling DNN training across geographically-distributed data silos to preserve the privacy of the training data. Communication efficiency and fairness are two major issues that need to be both satisfied when federated learning systems are deployed in practice. Simultaneously guaranteeing both of them, however, is exceptionally difficult because simply combining communication reduction and fairness optimization approaches often causes non-converged training or drastic accuracy degradation. Here, to bridge this gap, we propose FedEFsz. On the one hand, it integrates the state-of-the-art error-bounded lossy compressor SZ3 into cross-silo federated learning systems to significantly reduce communication traffic during the training. On the other hand, it achieves a high fairness (i.e., rather consistent model accuracy and performance across different clients) through a carefully designed heuristic algorithm that can tune the error-bound of SZ3 for different clients during the training. Extensive experimental results based on a GPU cluster with 65 GPU cards show that FedEFsz improves the fairness across different benchmarks by up to 60.88% and meanwhile reduces the communication traffic by up to 315×.

Cross-Silo Federated Learning Systems↗
DOE OSTI2016

A Note on Alternating Minimization Algorithm for the Matrix Completion Problem

Here, we consider the problem of reconstructing a low-rank matrix from a subset of its entries and analyze two variants of the so-called alternating minimization algorithm, which has been proposed in the past.We establish that when the underlying matrix has rank one, has positive bounded entries, and the graph underlying the revealed entries has diameter which is logarithmic in the size of the matrix, both algorithms succeed in reconstructing the matrix approximately in polynomial time starting from an arbitrary initialization.We further provide simulation results which suggest that the second variant which is based on the message passing type updates performs significantly better.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Stochastic reconstruction and microstructure modeling of SMC chopped fiber composites

Here, to establish an integrated Processing-Microstructure-Property workflow for the prediction of material behaviors, this paper presents a new stochastic pseudo-3D microstructure reconstruction method for Sheet Molding Compounds (SMC) chopped fiber composites. The proposed method captures the bi-level microstructural features of SMC composites. At the higher level, a Voronoi diagram-based algorithm is developed to reconstruct the unique substructure features of SMC fiber tows. The geometry of Voronoi cells is adjusted by a Simulated Annealing (SA) algorithm to match the geometrical statistics of the real fiber tows. At the lower level, the algorithm assigns fiber orientation to each Voronoi cell (which represents a fiber tow). The fiber orientation angles are recovered from a statistical fiber orientation tensor. The proposed method is employed to establish a multi-layer pseudo-3D SMC Representative Volume Element (RVE) model for Finite Element Analysis (FEA) of SMC microstructure. This model enables the prediction of mechanical properties based on the material processing information (e.g. fiber orientation tensor obtained from compression molding simulation), and the microstructure information obtained from microscopic imaging for an SMC composite. Lastly, the predicted properties are successfully validated by experimental tensile tests.

36 MATERIALS SCIENCE↗
DOE OSTI2017

A High Performance Block Eigensolver for Nuclear Configuration Interaction Calculations

As on-node parallelism increases and the performance gap between the processor and the memory system widens, achieving high performance in large-scale scientific applications requires an architecture-aware design of algorithms and solvers. We focus on the eigenvalue problem arising in nuclear Configuration Interaction (CI) calculations, where a few extreme eigenpairs of a sparse symmetric matrix are needed. Here, we consider a block iterative eigensolver whose main computational kernels are the multiplication of a sparse matrix with multiple vectors (SpMM), and tall-skinny matrix operations. We then present techniques to significantly improve the SpMM and the transpose operation SpMM T by using the compressed sparse blocks (CSB) format. We achieve 3-4× speedup on the requisite operations over good implementations with the commonly used compressed sparse row (CSR) format. We develop a performance model that allows us to correctly estimate the performance of our SpMM kernel implementations, and we identify cache bandwidth as a potential performance bottleneck beyond DRAM. We also analyze and optimize the performance of LOBPCG kernels (inner product and linear combinations on multiple vectors) and show up to 15× speedup over using high performance BLAS libraries for these operations. The resulting high performance LOBPCG solver achieves 1.4× to 1.8× speedup over the existing Lanczos solver on a series of CI computations on high-end multicore architectures (Intel Xeons). We also analyze the performance of our techniques on an Intel Xeon Phi Knights Corner (KNC) processor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Engine Combustion System Optimization Using Computational Fluid Dynamics and Machine Learning: A Methodological Approach

Gasoline compression ignition (GCI) engines are considered an attractive alternative to traditional spark-ignition and diesel engines. Here, a Machine Learning-Grid Gradient Ascent (ML-GGA) approach was developed to optimize the performance of internal combustion engines. ML offers a pathway to transform complex physical processes that occur in a combustion engine into compact informational processes. The developed ML-GGA model was compared with a recently developed Machine Learning-Genetic Algorithm (ML-GA). Detailed investigations of optimization solver parameters and variable limit extension were performed in the present ML-GGA model to improve the accuracy and robustness of the optimization process. Detailed descriptions of the different procedures, optimization tools, and criteria that must be followed for a successful output are provided here. The developed ML-GGA approach was used to optimize the operating conditions (case 1) and the piston bowl design (case 2) of a heavy-duty diesel engine running on a gasoline fuel with a research octane number (RON) of 80. The ML-GGA approach yielded >2% improvements in the merit function, compared with the optimum obtained from a thorough computational fluid dynamics (CFD) guided system optimization. The predictions from the ML-GGA approach were validated with engine CFD simulations. This study demonstrates the potential of ML-GGA to significantly reduce the time needed for optimization problems, without loss in accuracy compared with traditional approaches.

33 ADVANCED PROPULSION SYSTEMS↗