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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 OSTI2021

Exploring the Interaction Between Head-Supported Mass, Posture, and Visual Stress on Neck Muscle Activation

Objective Assess neck muscle activity for varying interactions between helmet, posture, and visual stress in a simulated “helo-hunch” posture. Background Military aviators frequently report neck pain (NP). Risk factors for NP include head-supported mass, awkward postures, and mental workload. Interactions between these factors could induce constant low-level muscle activation during helicopter flight and better explain instances of NP. Method Interactions between physical loading (helmet doffed/donned), posture (symmetric/asymmetric), and visual stress (low/high contrast) were studied through neck muscle electromyography (EMG), head kinematics, subjective discomfort, perceived workload, and task performance. Subjects ( n = 16) performed eight 30-min test conditions (varied physical loading, posture, and visual stress) while performing a simple task in a simulated “helo-hunch” seating environment. Results Conditions with a helmet donned had fewer EMG median frequency cycles (which infer motor unit rotation for rest/recovery, where more cycles are better) in the left cervical extensor and left sternocleidomastoid. Asymmetric posture (to the right) resulted in higher normalized EMG activity in the right cervical extensor and left sternocleidomastoid and resulted in less lateral bending compared with neutral across all conditions. Conditions with high visual stress also resulted in fewer EMG cycles in the right cervical extensor. Conclusion A complex interaction exists between the physical load of the helmet, postural stress from awkward postures, and visual stress within a simulated “helo-hunch” seating environment. Application These results provide insight into how visual factors influence biomechanical loading. Such insights may assist future studies in designing short-term administrative controls and long-term engineering controls.

Behavioral Sciences↗
DOE OSTI2018

Enforcing End-to-end I/O Policies for Scientific Workflows using Software-Defined Storage Resource Enclaves

Data-intensive knowledge discovery requires scientific applications to run concurrently with analytics and visualization codes executing in situ for timely output inspection and knowledge extraction. Consequently, I/O pipelines of scientific workflows can be long and complex because they comprise many stages of analytics across different layers of the I/O stack of high-performance computing systems. Performance limitations at any I/O layer or stage can cause an I/O bottleneck resulting in greater than expected end-to-end I/O latency. In this paper, we present the design and implementation of a novel data management infrastructure called Software-Defined Storage Resource Enclaves (SIREN) at system level to enforce end-to-end policies that dictate an I/O pipeline's performance. SIREN provides an I/O performance interface for users to specify the desired storage resources in the context of in-situ analytics. If suboptimal performance of analytics is caused by an I/O bottleneck when data are transferred between simulations and analytics, schedulers in different layers of the I/O stack automatically provide the guaranteed lower bounds on I/O throughput. Lastly, our experimental results demonstrate that SIREN provides performance isolation among scientific workflows sharing multiple storage servers across two I/O layers (burst buffer and parallel file systems) while maintaining high system scalability and resource utilization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Soft X‐ray Ptychographic Imaging and Morphological Quantification of Calcium Silicate Hydrates (C–S–H)

Morphological details of calcium silicate hydrate (C–S–H) stemming from the hydration process of Portland cement ( PC ) phases are crucial for understanding the PC ‐based systems but are still only partially known. Here we introduce the first soft X‐ray ptychographic imaging of tricalcium silicate (C 3 S) hydration products. The results are compared using both scanning transmission X‐ray and electron transmission microscopy data. The evidence shows that ptychography is a powerful method to visualize the details of outer and inner product C–S–H of fully hydrated C 3 S, which have fibrillar and an interglobular structure with average void sizes of 20 nm, respectively. The high‐resolution ptychrography image enables us to perform morphological quantification of C–S–H, and, for the first time, to possibly distinguish the contributions of inner and outer product C–S–H to the small angle scattering of cement paste. The results indicate that the outer product C–S–H is mainly responsible for the q −3 regime, whereas the inner product C–S–H transitions to a q −2 regime. Various hypotheses are discussed to explain these regimes.

Bae, Sungchul↗
DOE OSTI2016

Assessment of metal artifact reduction methods in pelvic CT

Purpose: Metal artifact reduction (MAR) produces images with improved quality potentially leading to confident and reliable clinical diagnosis and therapy planning. In this work, the authors evaluate the performance of five MAR techniques for the assessment of computed tomography images of patients with hip prostheses. Methods: Five MAR algorithms were evaluated using simulation and clinical studies. The algorithms included one-dimensional linear interpolation (LI) of the corrupted projection bins in the sinogram, two-dimensional interpolation (2D), a normalized metal artifact reduction (NMAR) technique, a metal deletion technique, and a maximum a posteriori completion (MAPC) approach. The algorithms were applied to ten simulated datasets as well as 30 clinical studies of patients with metallic hip implants. Qualitative evaluations were performed by two blinded experienced radiologists who ranked overall artifact severity and pelvic organ recognition for each algorithm by assigning scores from zero to five (zero indicating totally obscured organs with no structures identifiable and five indicating recognition with high confidence). Results: Simulation studies revealed that 2D, NMAR, and MAPC techniques performed almost equally well in all regions. LI falls behind the other approaches in terms of reducing dark streaking artifacts as well as preserving unaffected regions (p < 0.05). Visual assessment of clinical datasets revealed the superiority of NMAR and MAPC in the evaluated pelvic organs and in terms of overall image quality. Conclusions: Overall, all methods, except LI, performed equally well in artifact-free regions. Considering both clinical and simulation studies, 2D, NMAR, and MAPC seem to outperform the other techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Enabling Command-and-Control in Advanced In Situ Workflows

Scientific discovery is progressing towards autonomous science with the combination of scientific instruments, high-performance computing, and artificial intelligence in complex workflows. This evolution introduces new requirements for managing scientific workflows, including feedback loops, near real-time constraints, and the ability to dynamically control workflow execution. In situ workflows that analyze and visualize data as it is generated are well-suited to satisfy stringent time constraints and their iterative nature offers greater opportunities for command-and-control. However, only a few of the many workflow management systems available have been specifically designed to manage in situ workflows and often lack support for automated feedback loops that allow analysis and visualization components to interact with the main scientific data producer. To address this need, we present in this paper how to add command-and-control capabilities to a workflow management system. We identify the functional design requirements of such a command-and-control system, detail its architecture, interface, and core mechanisms, and illustrate how advanced in situ workflows can leverage command-and-control in three use cases: graceful termination with checkpoint, dynamic and adaptive data reduction, and event-triggered analysis.

Mehta, Kshitij [ORNL] (ORCID:0000000297149981)↗
DOE OSTI2021

VTK-m User's Guide (V.1.6)

High-performance computing relies on ever finer threading. Advances in processor technology include ever greater numbers of cores, hyperthreading, accelerators with integrated blocks of cores, and special vectorized instructions, all of which require more software parallelism to achieve peak performance. Traditional visualization solutions cannot support this extreme level of concurrency. Extreme scale systems require a new programming model and a fundamental change in how we design algorithms. To address these issues we created VTK-m: the visualization toolkit for multi-/many-core architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Preparation and Analysis of Austenitic Steel Samples Irradiated at Very High Damage Doses

This report describes the preliminary results of the visual inspection, cutting, preparation for IASCC (irradiation-assisted stress corrosion cracking) testing, and property evaluation of austenitic stainless steel specimens irradiated at very-high-damage doses (up to 125 dpa) in the BOR-60 fast reactor. Work was performed at Oak Ridge National Laboratory using the Irradiated Materials Examination and Testing (hot cell) Facility and the Low Activation Materials Development and Analysis (LAMDA) laboratory. Report sections describe specific aspects of the research activity. Section 1 reviews the general background, material, and specimen origin, and provides detailed information on material composition and damage dose level. Section 2 describes operations performed with irradiated specimens at the hot cell facility and LAMDA laboratory. At the moment, tensile specimen preparation is complete, and the tensile bars are ready for shipment to the University of Michigan for stress corrosion cracking testing. Section 3 discusses the microstructure of archive alloys and post-irradiation material properties; because of the very limited timeframe, only selected results are given on the magnetic properties of the irradiated specimens. Section 4 summarizes the work performed, presents conclusions, and discusses future activities within the line of research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Large language model evaluation for high–performance computing software development

We apply AI-assisted large language model (LLM) capabilities of GPT-3 targeting high-performance computing (HPC) kernels for (i) code generation, and (ii) auto-parallelization of serial code in C ++, Fortran, Python and Julia. Our scope includes the following fundamental numerical kernels: AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG, and language/programming models: (1) C++ (e.g., OpenMP [including offload], OpenACC, Kokkos, SyCL, CUDA, and HIP), (2) Fortran (e.g., OpenMP [including offload] and OpenACC), (3) Python (e.g., numpy, Numba, cuPy, and pyCUDA), and (4) Julia (e.g., Threads, CUDA.jl, AMDGPU.jl, and KernelAbstractions.jl). Kernel implementations are generated using GitHub Copilot capabilities powered by the GPT-based OpenAI Codex available in Visual Studio Code given simple + + prompt variants. To quantify and compare the generated results, we propose a proficiency metric around the initial 10 suggestions given for each prompt. For auto-parallelization, we use ChatGPT interactively giving simple prompts as in a dialogue with another human including simple “prompt engineering” follow ups. Results suggest that correct outputs for C++ correlate with the adoption and maturity of programming models. For example, OpenMP and CUDA score really high, whereas HIP is still lacking. We found that prompts from either a targeted language such as Fortran or the more general-purpose Python can benefit from adding language keywords, while Julia prompts perform acceptably well for its Threads and CUDA.jl programming models. Finally, we expect to provide an initial quantifiable point of reference for code generation in each programming model using a state-of-the-art LLM. Overall, understanding the convergence of LLMs, AI, and HPC is crucial due to its rapidly evolving nature and how it is redefining human-computer interactions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Evaluation of flow patterns and elongated bubble characteristics during the flow boiling of halocarbon refrigerants in a micro-scale channel

In the present study, quasi-diabatic two-phase flow pattern visualizations and measurements of elongated bubble velocity, frequency and length were performed. The tests were run for R134a and R245fa evaporating in a stainless steel tube with diameter of 2.32 mm, mass velocities ranging from 50 to 600 kg/m{sup 2} s and saturation temperatures of 22 C, 31 C and 41 C. The tube was heated by applying a direct DC current to its surface. Images from a high-speed video-camera (8000 frames/s) obtained through a transparent tube just downstream the heated sections were used to identify the following flow patterns: bubbly, elongated bubbles, churn and annular flows. The visualized flow patterns were compared against the predictions provided by Barnea et al. (1983), Felcar et al. (2007), Revellin and Thome (2007) and Ong and Thome (2009). From this comparison, it was found that the methods proposed by Felcar et al. (2007) and Ong and Thome (2009) predicted relatively well the present database. Additionally, elongated bubble velocities, frequencies and lengths were determined based on the analysis of high-speed videos. Results suggested that the elongated bubble velocity depends on mass velocity, vapor quality and saturation temperature. The bubble velocity increases with increasing mass velocity and vapor quality and decreases with increasing saturation temperature. Additionally, bubble velocity was correlated as linear functions of the two-phase superficial velocity. (author)

42 ENGINEERING↗
DOE OSTI2013

Surveying the agents of galaxy evolution in the tidally stripped, low metallicity small Magellanic Cloud (SAGE-SMC). III. Young stellar objects

The Spitzer Space Telescope Legacy Program SAGE-SMC allows global studies of resolved stellar populations in the SMC in a different environment than our Galaxy. Using the SAGE-SMC IRAC (3.6-8.0 μm) and MIPS (24 and 70 μm) catalogs and images combined with near-infrared (JHK {sub s}) and optical (UBVI) data, we identified a population of ∼1000 intermediate- to high-mass young stellar objects (YSOs) in the SMC (three times more than previously known). Our method of identifying YSO candidates builds on the method developed for the Large Magellanic Cloud by Whitney et al. with improvements based on what we learned from our subsequent studies and techniques described in the literature. We perform (1) color-magnitude cuts based on five color-magnitude diagrams (CMDs), (2) visual inspection of multi-wavelength images, and (3) spectral energy distribution (SED) fitting with YSO models. For each YSO candidate, we use its photometry to calculate a measure of our confidence that the source is not a non-YSO contaminant, but rather a true YSO, based on the source's location in the color-magnitude space with respect to non-YSOs. We use this CMD score and the SED fitting results to define two classes of sources: high-reliability YSO candidates and possible YSO candidates. We found that, due to polycyclic aromatic hydrocarbon emission, about half of our sources have [3.6]-[4.5] and [4.5]-[5.8] colors not predicted by previous YSO models. The YSO candidates are spatially correlated with gas tracers.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2011

Advanced Simulation Capability for Environmental Management (ASCEM): Early Site Demonstration

The U.S. Department of Energy Office of Environmental Management, Technology Innovation and Development (EM-32), is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high performance computing tool will facilitate integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. As part of the initial development process, a series of demonstrations were defined to test ASCEM components and provide feedback to developers, engage end users in applications, and lead to an outcome that would benefit the sites. The demonstration was implemented for a sub-region of the Savannah River Site General Separations Area that includes the F-Area Seepage Basins. The physical domain included the unsaturated and saturated zones in the vicinity of the seepage basins and Fourmile Branch, using an unstructured mesh fit to the hydrostratigraphy and topography of the site. The calculations modeled variably saturated flow and the resulting flow field was used in simulations of the advection of non-reactive species and the reactive-transport of uranium. As part of the demonstrations, a new set of data management, visualization, and uncertainty quantification tools were developed to analyze simulation results and existing site data. These new tools can be used to provide summary statistics, including information on which simulation parameters were most important in the prediction of uncertainty and to visualize the relationships between model input and output.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

An Uncertainty Quantification Framework for Studying the Effect of Spatial Heterogeneity in Reservoir Permeability on CO2 Sequestration

In this paper, we introduce an uncertainty quantification (UQ) software framework for carbon sequestration, focused on the effect of spatial heterogeneity of reservoir properties on CO2 migration. We use a sequential Gaussian method (SGSIM) to generate realizations of permeability fields with various spatial statistical attributes. To deal with the computational difficulties, we integrate the following ideas/approaches. First, we use three different sampling approaches (probabilistic collocation, quasi-Monte Carlo, and adaptive sampling) to reduce the number of forward calculations while trying to explore the parameter space and quantify the input uncertainty. Second, we use eSTOMP as the forward modeling simulator. eSTOMP is implemented with the Global Arrays toolkit that is based on one-sided inter-processor communication and supports a shared memory programming style on distributed memory platforms, providing a highly-scalable performance. Third, we built an adaptive system infrastructure to select the best possible data transfer mechanisms, to optimally allocate system resources to improve performance and to integrate software packages and data for composing carbon sequestration simulation, computation, analysis, estimation and visualization. We demonstrate the framework with a given CO2 injection scenario in heterogeneous sandstone reservoirs.

Carbon sequestration, uncertainty quantification, ↗
DOE OSTI2024

Uncertainty quantification and propagation in lithium-ion battery electrodes using bayesian convolutional neural networks

The complex nature of manufacturing processes stipulates electrodes to possess high variability with increased heterogeneity during production. X-ray computed tomography imaging has proved to be critical in visualizing the complicated stochastic particle distribution of as-manufactured electrodes in lithium-ion batteries. However, accurate prediction of their electrochemical performance necessitates precise evaluation of kinetic and transport properties from real electrodes. Image segmentation that characterizes voxels to particle/pore phase is often meticulous and fraught with subjectivity owing to a myriad of unconstrained choices and filter algorithms. Here we utilize a Bayesian convolutional neural network to tackle segmentation subjectivity and quantify its pertinent uncertainties. Otsu inter-variance and Blind/Referenceless Imaging Spatial Quality Evaluator are used to assess the relative image quality of grayscale tomograms, thus evaluating the uncertainty in the derived microstructural attributes. We analyze how image uncertainty is correlated with the uncertainties and magnitude of kinetic and transport properties of an electrode, further identifying pathways of uncertainty propagation within microstructural attributes. The coupled effect of spatial heterogeneity and microstructural anisotropy on the uncertainty quantification of transport parameters is also understood. This work demonstrates a novel methodology to extract microstructural descriptors from real electrode images through quantification of associated uncertainties and discerning the relative strength of their propagation, thus facilitating feedback to manufacturing processes from accurate image based electrochemical simulations.

25 ENERGY STORAGE↗
DOE OSTI2026

Magnetic brightening and nanoscale imaging of spin-polarized helical edge modes in ZrTe 5

Efficient charge transport remains a fundamental challenge for nanoelectronic devices, as their performance is constrained by high dissipation and the impedance mismatch between high-frequency signal sources and nanoscale circuit interfaces. Although topologically protected helical edge modes offer a dissipationless and backscattering-resilient alternative, achieving nanoscale control over these modes requires direct visualization of their spatial electrodynamics, especially under high-frequency operation. Here, by utilizing cryogenic magneto-infrared scattering-type scanning near-field optical microscopy (cm-IR-sSNOM), we image spin-polarized helical edge channels in ZrTe 5 at the nanoscale, revealing magnetic-field-induced brightening as a high-frequency electrodynamic signature of robust topological edge modes. Operating at 1.8 K and under a magnetic field of up to 5 T, we observe the emergence of edge-state polarizability at infrared frequencies that is notably resilient to the magnetic gaps that typically quench d.c. and microwave edge transport. Our results reveal a topological ‘two-lane’ spatial reorganization in which an external magnetic field induces a spin-population imbalance between counterpropagating edge modes. Favoured helical branches are confined against physical boundaries to activate a net infrared near-field contrast. This electrodynamic response scales linearly with the number of atomic layers, which confirms that individual layers in ZrTe 5 preserve their discrete quantum spin Hall identities. These findings may be useful for developing topological spintronic devices, as the magnetic infrared tunability of helical edge channels provides a pathway for low-loss nanoscale interconnects and high-speed information processing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC↗
DOE OSTI2015

Compartmentalized microchannel array for high-throughput analysis of single cell polarized growth and dynamics

Here, interrogating polarized growth is technologically challenging due to extensive cellular branching and uncontrollable environmental conditions in conventional assays. Here we present a robust and high-performance microfluidic system that enables observations of polarized growth with enhanced temporal and spatial control over prolonged periods. The system has built-in tunability and versatility to accommodate a variety of science applications requiring precisely controlled environments. Using the model filamentous fungus, Neurospora crassa , this microfluidic system enabled direct visualization and analysis of cellular heterogeneity in a clonal fungal cell population, nuclear distribution and dynamics at the subhyphal level, and quantitative dynamics of gene expression with single hyphal compartment resolution in response to carbon source starvation and exchange experiments. Although the microfluidic device is demonstrated on filamentous fungi, our technology is immediately extensible to a wide array of other biosystems that exhibit similar polarized cell growth with applications ranging from bioenergy production to human health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Simultaneous imaging and diffraction in the dynamic diamond anvil cell

The ability to visualize a sample undergoing a pressure-induced phase transition allows for the determination of kinetic parameters, such as the nucleation and growth rates of the high-pressure phase. For samples that are opaque to visible light (such as metallic systems), it is necessary to rely on x-ray imaging methods for sample visualization. Here, we present an experimental platform developed at beamline P02.2 at the PETRA III synchrotron radiation source, which is capable of performing simultaneous x-ray imaging and diffraction of samples that are dynamically compressed in piezo-driven diamond anvil cells. This setup utilizes a partially coherent monochromatic x-ray beam to perform lensless phase contrast imaging, which can be carried out using either a parallel- or focused-beam configuration. The capabilities of this platform are illustrated by experiments on dynamically compressed Ga and Ar. Melting and solidification were identified based on the observation of solid/liquid phase boundaries in the x-ray images and corresponding changes in the x-ray diffraction patterns collected during the transition, with significant edge enhancement observed in the x-ray images collected using the focused-beam. These results highlight the suitability of this technique for a variety of purposes, including melt curve determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗