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At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Fractal Analysis of Visual Search Activity for Mass Detection During Mammographic Screening

Purpose: The objective of this study was to assess the complexity of human visual search activity during mammographic screening using fractal analysis and to investigate its relationship with case and reader characteristics. Methods: The study was performed for the task of mammographic screening with simultaneous viewing of four coordinated breast views as typically done in clinical practice. Eye-tracking data and diagnostic decisions collected for 100 mammographic cases (25 normal, 25 benign, 50 malignant) and 10 readers (three board certified radiologists and seven radiology residents), formed the corpus data for this study. The fractal dimension of the readers’ visual scanning patterns was computed with the Minkowski–Bouligand box-counting method and used as a measure of gaze complexity. Individual factor and group-based interaction ANOVA analysis was performed to study the association between fractal dimension, case pathology, breast density, and reader experience level. The consistency of the observed trends depending on gaze data representation was also examined. Results: Case pathology, breast density, reader experience level, and individual reader differences are all independent predictors of the visual scanning pattern complexity when screening for breast cancer. No higher order effects were found to be significant. Conclusions: Fractal characterization of visual search behavior during mammographic screening is dependent on case properties and image reader characteristics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2017

Global reconstructed daily surge levels from the 20th Century Reanalysis (1871–2010)

Studying the effect of global patterns of wind and pressure gradients on the sea level variation (storm surge) is a key issue in understanding the recent climate change effect on the dynamical state of the ocean. The analysis of the spatial and temporal variability of storm surges from observations is a difficult task to accomplish since observations are not homogeneous in time, scarce in space, and moreover, their temporal coverage is limited. A recent global surge database developed by AVISO (DAC, Dynamic Atmospheric Correction) fulfilled the lack of data in terms of spatial coverage, but not regarding time extent, since it only includes the last two decades (1992–2014). In this work, we use the 20th Century Reanalysis V2 (20CR), which spans the years 1871 to 2010, to statistically reconstruct daily maximum surge levels at a global scale. A multivariate linear regression model is fitted between daily mean ERA-interim sea level pressure fields and daily maximum surge levels from DAC. Following, the statistical model is used to reconstruct daily surges using mean sea level pressure fields from 20CR. The verification of the statistical model shows good agreements between DAC levels and the reconstructed surge levels from the 20CR. The validation of the reconstructed surge with tide gauges, distributed throughout the domain, shows good accuracy both in terms of high correlations and small errors. A time series comparison is also depicted at specific tide gauges for the beginning of the 20th century, showing a high concordance. Therefore, this work provides to the scientific community, a daily database of maximum surge levels; which correspond to an extension of the DAC database, from 1871 to 2010. This database can be used to improve the knowledge on historical storm surge conditions, allowing the study of their temporal and spatial variability.

Geology↗

DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗

DOE OSTI2014

New tools for the systematic analysis and visualization of electronic excitations. II. Applications

The excited states of a diverse set of molecules are examined using a collection of newly implemented analysis methods. These examples expose the particular power of three of these tools: (i) natural difference orbitals (the eigenvectors of the difference density matrix) for the description of orbital relaxation effects, (ii) analysis of the one-electron transition density matrix in terms of an electron-hole picture to identify charge resonance and excitonic correlation effects, and (iii) state-averaged natural transition orbitals for a compact simultaneous representation of several states. Furthermore, the utility of a wide array of additional analysis methods is highlighted. Five molecules with diverse excited state characteristics are chosen for these tasks: pyridine as a prototypical small heteroaromatic molecule, a model system of six neon atoms to study charge resonance effects, hexatriene in its neutral and radical cation forms to exemplify the cases of double excitations and spin-polarization, respectively, and a model iridium complex as a representative metal organic compound. Using these examples a number of phenomena, which are at first sight unexpected, are highlighted and their physical significance is discussed. Moreover, the generality of the conclusions of this paper is verified by a comparison of single- and multireference ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Metagenomic Methods for Addressing NASA's Planetary Protection Policy Requirements on Future Missions: A Workshop Report

Molecular biology methods and technologies have advanced substantially over the past decade. These new molecular methods should be incorporated among the standard tools of planetary protection (PP) and could be validated for incorporation by 2026. To address the feasibility of applying modern molecular techniques to such an application, NASA conducted a technology workshop with private industry partners, academics, and government agency stakeholders, along with NASA staff and contractors. The technical discussions and presentations of the Multi-Mission Metagenomics Technology Development Workshop focused on modernizing and supplementing the current PP assays. The goals of the workshop were to assess the state of metagenomics and other advanced molecular techniques in the context of providing a validated framework to supplement the bacterial endospore-based NASA Standard Assay and to identify knowledge and technology gaps. In particular, workshop participants were tasked with discussing metagenomics as a stand-alone technology to provide rapid and comprehensive analysis of total nucleic acids and viable microorganisms on spacecraft surfaces, thereby allowing for the development of tailored and cost-effective microbial reduction plans for each hardware item on a spacecraft. Workshop participants recommended metagenomics approaches as the only data source that can adequately feed into quantitative microbial risk assessment models for evaluating the risk of forward (exploring extraterrestrial planet) and back (Earth harmful biological) contamination. Participants were unanimous that a metagenomics workflow, in tandem with rapid targeted quantitative (digital) PCR, represents a revolutionary advance over existing methods for the assessment of microbial bioburden on spacecraft surfaces. The workshop highlighted low biomass sampling, reagent contamination, and inconsistent bioinformatics data analysis as key areas for technology development. Finally, it was concluded that implementing metagenomics as an additional workflow for addressing concerns of NASA's robotic mission will represent a dramatic improvement in technology advancement for PP and will benefit future missions where mission success is affected by backward and forward contamination.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Time-Resolved Stochastic Dynamics of Quantum Thermal Machines

Steady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. However, at the level of discrete stochastic realizations, heat flow is unraveled as a series of abrupt quantum jumps, each representing an exchange of finite quanta with the environment. Here, in this work, we present a framework that resolves the dynamics of quantum thermal machines into cycles classified as enginelike, coolinglike, or idle. We analyze the statistics of individual cycle types and their durations, enabling us to determine both the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles of a given type. Central to our analysis is the notion of intermittency, which captures the operational consistency of the machine by assessing the frequency and distribution of idle cycles. Our framework offers a novel approach to characterizing thermal machines, with significant relevance to experiments involving mesoscopic transport through quantum dots.

full counting statistics↗

DOE OSTI2022

Performance of an Astrophysical Radiation Hydrodynamics Code under Scalable Vector Extension Optimization

We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. Here, we performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a “deeper dive” into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Oxide

Oxide is a modular framework for feature extraction and analysis of executable files. Oxide is useful in a variety of reverse engineering and categorization tasks relating to executable content.

Burton, David↗

DOE OSTI2021

molecule-tda v0.1.0

A general framework to extract topological information (via topological data analysis) from some type of point cloud data, to be used in downstream machine learning tasks.

Krishnapriyan, Aditi↗

DOE OSTI2025

ForceFinder

SAND2025-11750O ForceFinder extends the Structural Dynamics Python Libraries (SDynPy) with comprehensive tools for inverse source estimation (ISE) tasks via frequency response function (FRF) matrix inversion. The software is designed for transfer path analysis and multiple-input/multiple-output (MIMO) vibration control problems. It allows users to estimate sources through various algorithms, from the basic Moore-Penrose pseudo-inverse to statistical learning methods such as Tikhonov regularization via an L-curve and elastic net regularization via an information criterion. ForceFinder uses an object-oriented framework, where all components of the ISE problem—such as FRFs, responses, and transformations—are stored in a "SourcePathReceiver" object. This software can be applied to any noise and vibration problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Carter, Steven [Sandia National Lab. (SNL-CA), Liv↗

DOE OSTI2012

Glycolic-Nitric Acid Flowsheet Demonstration of the DWPF Chemical Process Cell with Sludge and Supernate Simulants

Savannah River Remediation (SRR) is evaluating changes to its current Defense Waste Processing Facility (DWPF) flowsheet to improve processing cycle times. This will enable the facility to support higher canister production while maximizing waste loading. Higher throughput is needed in the Chemical Process Cell (CPC) since the installation of the bubblers into the melter has increased melt rate. Due to the significant maintenance required for the DWPF gas chromatographs (GC) and the potential for production of flammable quantities of hydrogen, reducing or eliminating the amount of formic acid used in the CPC is being developed. Earlier work at Savannah River National Laboratory has shown that replacing formic acid with an 80:20 molar blend of glycolic and formic acids has the potential to remove mercury in the SRAT without any significant catalytic hydrogen generation. This report summarizes the research completed to determine the feasibility of processing without formic acid. In earlier development of the glycolic-formic acid flowsheet, one run (GF8) was completed without formic acid. It is of particular interest that mercury was successfully removed in GF8, no formic acid at 125% stoichiometry. Glycolic acid did not show the ability to reduce mercury to elemental mercury in initial screening studies, which is why previous testing focused on using the formic/glycolic blend. The objective of the testing detailed in this document is to determine the viability of the nitric-glycolic acid flowsheet in processing sludge over a wide compositional range as requested by DWPF. This work was performed under the guidance of Task Technical and Quality Assurance Plan (TT&QAP). The details regarding the simulant preparation and analysis have been documented previously.

08 HYDROGEN↗

DOE OSTI2012

Computational Mechanics Research and Support for Aerodynamics and Hydraulics at TFHRC, Year 2 Quarter 4 Progress Report

The computational fluid dynamics (CFD) and computational structural mechanics (CSM) focus areas at Argonne’s Transportation Research and Analysis Computing Center (TRACC) initiated a project to support and compliment the experimental programs at the Turner-Fairbank Highway Research Center (TFHRC) with high performance computing based analysis capabilities in August 2010. The project was established with a new interagency agreement between the Department of Energy and the Department of Transportation to provide collaborative research, development, and benchmarking of advanced three-dimensional computational mechanics analysis methods to the aerodynamics and hydraulics laboratories at TFHRC for a period of five years, beginning in October 2010. The analysis methods employ well benchmarked and supported commercial computational mechanics software. Computational mechanics encompasses the areas of Computational Fluid Dynamics (CFD), Computational Wind Engineering (CWE), Computational Structural Mechanics (CSM), and Computational Multiphysics Mechanics (CMM) applied in Fluid-Structure Interaction (FSI) problems. The major areas of focus of the project are wind and water effects on bridges — superstructure, deck, cables, and substructure (including soil), primarily during storms and flood events — and the risks that these loads pose to structural failure. For flood events at bridges, another major focus of the work is assessment of the risk to bridges caused by scour of stream and riverbed material away from the foundations of a bridge. Other areas of current research include modeling of the salt spray transport into bridge girders to address suitability of using weathering steel in bridges, CFD analysis of the operation of the wind tunnel in the TFHRC wind engineering laboratory, and coupling of CFD and CSM software to solve fluid structure interaction problems, primarily analysis of bridge cables in wind. This quarterly report documents technical progress on the project tasks for the period of July through September 2012.

42 ENGINEERING↗

DOE OSTI2013

Computational Mechanics Research and Support for Aerodynamics and Hydraulics at TFHRC (Year 3 Quarter 2 Progress Report)

Lottes, S. A.↗

DOE OSTI2013

Study of Air Ingress Across the Duct During the Accident Conditions

The goal of this project is to study the fundamental physical phenomena associated with air ingress in very high temperature reactors (VHTRs). Air ingress may occur due to a rupture of primary piping and a subsequent breach in the primary pressure boundary in helium-cooled and graphite-moderated VHTRs. Significant air ingress is a concern because it introduces potential to expose the fuel, graphite support rods, and core to a risk of severe graphite oxidation. Two of the most probable air ingress scenarios involve rupture of a control rod or fuel access standpipe, and rupture in the main coolant pipe on the lower part of the reactor pressure vessel. Therefore, establishing a fundamental understanding of air ingress phenomena is critical in order to rationally evaluate safety of existing VHTRs and develop new designs that minimize these risks. But despite this importance, progress toward development these predictive capabilities has been slowed by the complex nature of the underlying phenomena. The combination of inter-diffusion among multiple species, molecular diffusion, natural convection, and complex geometries, as well as the multiple chemical reactions involved, impose significant roadblocks to both modeling and experiment design. The project team will employ a coordinated experimental and computational effort that will help gain a deeper understanding of multiphased air ingress phenomena. This project will enhance advanced modeling and simulation methods, enabling calculation of nuclear power plant transients and accident scenarios with a high degree of confidence. The following are the project tasks: Perform particle image velocimetry measurement of multiphase air ingresses; and, Perform computational fluid dynamics analysis of air ingress phenomena.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2018

Evaluation of CASL boiling model for DNB performance in full scale 5x5 fuel bundle with spacer grids

As one of main tasks for FY17 CASL-THM activity, Evaluation study on applicability of the CASL baseline boiling model for 5x5 DNB application is conducted and the predictive capability of the DNB analysis is reported here. While the baseline CASL-boiling model (GEN- 1A) approach has been successfully implemented and validated with a single pipe application in the previous year’s task, the extended DNB validation for realistic sub-channels with detailed spacer grid configurations are tasked in FY17. The focus area of the current study is to demonstrate the robustness and feasibility of the CASL baseline boiling model for DNB performance in a full 5x5 fuel bundle application. A quantitative evaluation of the DNB predictive capability is performed by comparing with corresponding experimental measurements (i.e. reference for the model validation). The reference data are provided from the Westinghouse Electricity Company (WEC). Two different grid configurations tested here include Non-Mixing Vane Grid (NMVG), and Mixing Vane Grid (MVG). Thorough validation studies with two sub-channel configurations are performed at a wide range of realistic PWR operational conditions.

42 ENGINEERING↗

DOE OSTI2018

R&D Roadmap for Enhanced Resilient Plant Systems, Metrics, Scenarios, Risk Analysis, and Modeling and Simulation

The nuclear industry and the U.S. Department of Energy are jointly developing accident tolerant fuel (ATF) which has the potential to greatly improve the safety and economic performance of the current fleet of NPPs. The combination of ATF with the optimal use of FLEX equipment (deployed as an industry response to the Fukushima Daiichi Nuclear Power Plant (NPP) accident in 2012), enhancements on plant components and systems, incorporation of augmented cooling systems or new passive cooling systems, and improvements in fuel cycle efficiency, have the potential to render the NPPs more efficient and resilient to events (both internally and externally initiated) that have the potential to challenge the integrity of the fuel or plant containment. In this report, combinations of these plant improvements are called Enhanced Resilient Plant Systems. In order to accelerate the development and deployment of the components that comprise Enhanced Resilient Plant Systems, a well-integrated toolkit that is fuel/clad-, fuel cycle-, systems-, and scenario-centric is required to provide a ready platform for the analysis of the advanced ATF fuel and cladding materials that are being developed, as well as plant systems modifications to achieve enhanced resiliency. Since the deployment of these enhancements will comprise a risk/benefit tradeoff of their impacts on plant safety and economics, the envisioned toolkit will need to be capable to characterizing the multidimensional aspects associated with these evaluations and provide decision-makers with information that can optimize the technological, economic, and safety benefits that are to be obtained. The Risk-Informed Systems Analysis (RISA) Pathway of the DOE Light Water Reactor Sustainability (LWRS) Program initiated several research tasks to develop analytical capabilities to support the industry in the transition to the ATF and Enhanced Resilient Plant Systems. The general idea behind the initiative is the development of an integrated evaluation approach which combines the plant probabilistic risk assessment (PRA) models with Multi-Physics Best Estimate Plus Uncertainty (MP-BEPU) analyses in a seamless fashion. The integrated evaluation framework aims at enabling plant system configuration variations to be studied with speed and precision, including detailed risk and benefit assessments of introducing ATF and Enhanced Resilient Plant Systems into current LWR plants to achieve both safety and operational performance enhancements. The focus of this report is to present an integrated research and development (R&D) roadmap to identify and perform high value evaluations of proposed ATF and Enhanced Resilient Plant Systems concepts to identify both the technical (e.g. benefits to risk, safety, and operational margins) and the economic (i.e. business and cost) elements associated with industry adoption of the technology. The integrated evaluation approach will be developed to support the development, testing, qualification, licensing, and deployment of ATF and Enhanced Resilient Plant Systems technology that is capable of achieving substantial safety and economic improvements as well as timely widespread adoption by the US nuclear industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗