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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nanotomography for Quantitative 3D Particle Reconstruction

Particulates are ubiquitous across fuel cycle operations and carry critical information about particle formation, processing, and potential proliferation-related activities. Traditional analytical techniques, including micro-Raman spectroscopy and standard electron microscopy, are often limited in spatial resolution or dimensionality, particularly when used to examine metallic or submicron-scale features. Understanding particle morphology, phase distribution, and internal porosity is essential for constraining formation conditions, thermodynamic environments, and material transport behavior. In this report, we demonstrate the application of plasma focused ion beam nanotomography to reconstruct micron-scale particulates at nanoscale resolution. Using high-resolution backscattered electron imaging and Avizo software, we obtained 3D reconstructions that enabled quantitative analysis of particle morphology, phase composition, and internal voids. Representative examples include a Ta particle with a large central void and a composite particle with embedded tetrahedral crystalline structures. These reconstructions reveal structural and compositional details that are inaccessible through conventional 2D imaging. The results demonstrate that nanotomography provides both qualitative and quantitative insights into particle formation and behavior. Using nanotomography, porosity and phase distributions can be quantified to inform models of particle density, transport, and solidification conditions. Beyond technical insights, the workflow developed here establishes a transferable capability for analyzing heterogeneous particles and has potential applications in bulk materials studies via x-ray computed tomography or other volumetric imaging modalities. Ongoing efforts are focused on optimizing the workflow to process multiple particles simultaneously, increasing throughput and statistical robustness. Overall, this work illustrates the power of nanotomography as a tool for connecting particulate morphology to formation mechanisms, composition, and transport, thereby strengthening analytical capabilities for nuclear forensics, fuel cycle analysis, and related scientific investigations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

Ambient and Cryogenic Alignment Verification and Performance of the Infrared Multi-Object Spectrometer

The Infrared Multi-Object Spectrometer (IRMOS) is a facility instrument for the Kitt Peak National Observatory 4 and 2.1 meter telescopes. IRMOS is a near-IR (0.8 - 2.5 micron) spectrometer with low- to mid-resolving power (R = 300 - 3000). IRMOS produces simultaneous spectra of approximately 100 objects in its 2.8 x 2.0 arc-min field of view using a commercial Micro Electro-Mechanical Systems (MEMS) Digital Micro-mirror Device (DMD) from Texas Instruments. The IRMOS optical design consists of two imaging subsystems. The focal reducer images the focal plane of the telescope onto the DMD field stop, and the spectrograph images the DMD onto the detector. We describe ambient breadboard subsystem alignment and imaging performance of each stage independently, and the ambient and cryogenic imaging performance of the fully assembled instrument. Interferometric measurements of subsystem wavefront error serve to venfy alignment, and are accomplished using a commercial, modified Twyman-Green laser unequal path interferometer. Image testing provides further verification of the optomechanical alignment method and a measurement of near-angle scattered light due to mirror small-scale surface error. Image testing is performed at multiple field points. A mercury-argon pencil lamp provides spectral lines at 546.1 nm and 1550 nm, and a CCD camera and IR camera are used as detectors. We use commercial optical modeling software to predict the point-spread function and its effect on instrument slit transmission and resolution. Our breadboard test results validate this prediction. We conclude with an instrument performance prediction for first light.

Connelly, Joseph A.↗
NASA NTRS2016

Full Field X-Ray Fluorescence Imaging Using Micro Pore Optics for Planetary Surface Exploration

Many planetary surface processes leave evidence as small features in the sub-millimetre scale. Current planetary X-ray fluorescence spectrometers lack the spatial resolution to analyse such small features as they only provide global analyses of areas greater than 100 mm(exp 2). A micro-XRF spectrometer will be deployed on the NASA Mars 2020 rover to analyse spots as small as 120m. When using its line-scanning capacity combined to perpendicular scanning by the rover arm, elemental maps can be generated. We present a new instrument that provides full-field XRF imaging, alleviating the need for precise positioning and scanning mechanisms. The Mapping X-ray Fluorescence Spectrometer - "Map-X" - will allow elemental imaging with approximately 100μm spatial resolution and simultaneously provide elemental chemistry at the scale where many relict physical, chemical and biological features can be imaged in ancient rocks. The arm-mounted Map-X instrument is placed directly on the surface of an object and held in a fixed position during measurements. A 25x25 mm(exp 2) surface area is uniformly illuminated with X-rays or alpha-particles and gamma-rays. A novel Micro Pore Optic focusses a fraction of the emitted X-ray fluorescence onto a CCD operated at a few frames per second. On board processing allows measuring the energy and coordinates of each X-ray photon collected. Large sets of frames are reduced into 2d histograms used to compute higher level data products such as elemental maps and XRF spectra from selected regions of interest. XRF spectra are processed on the ground to further determine quantitative elemental compositions. The instrument development will be presented with an emphasis on the characterization and modelling of the X-ray focussing Micro Pore Optic. An outlook on possible alternative XRF imaging applications will be discussed.

micro-XRF spectrometer↗
NASA NTRS2004

Alignment and Performance of the Infrared Multi-Object Spectrometer

The Infrared Multi-Object Spectrometer (IRMOS) is a principle investigator class instrument for the Kitt Peak National Observatory 4 and 2.1 meter telescopes. IRMOS is a near-IR (0.8 - 2.5 micron) spectrometer with low-to mid-resolving power (R = 300 - 3000). IRMOS produces simultaneous spectra of approximately 100 objects in its 2.8 x 2.0 arc-min field of view (4 m telescope) using a commercial Micro Electro-Mechanical Systems (MEMS) micro-mirror array (MMA) from Texas Instruments. The IRMOS optical design consists of two imaging subsystems. The focal reducer images the focal plane of the telescope onto the MMA field stop, and the spectrograph images the MMA onto the detector. We describe ambient breadboard subsystem alignment and imaging performance of each stage independently, and ambient imaging performance of the fully assembled instrument. Interferometric measurements of subsystem wavefront error serve as a qualitative alignment guide, and are accomplished using a commercial, modified Twyman-Green laser unequal path interferometer. Image testing provides verification of the optomechanical alignment method and a measurement of near-angle scattered light due to mirror small-scale surface error. Image testing is performed at multiple field points. A mercury-argon pencil lamp provides a spectral line at 546.1 nanometers, a blackbody source provides a line at 1550 nanometers, and a CCD camera and IR camera are used as detectors. We use commercial optical modeling software to predict the point-spread function and its effect on instrument slit transmission and resolution. Our breadboard and instrument level test results validate this prediction. We conclude with an instrument performance prediction for cryogenic operation and first light in late 2003.

Connelly, Joseph A.↗
NASA NTRS2017

Small Ion Channel Linking Molecular Simulations and Electrophysiology

Ion channels are pore-forming protein assemblies that mediate the transport of small ions across cell membranes. Otherwise, membrane bilayers would be almost impermeable to ions incapable to traverse the low dielectric constant, hydrophobic membrane core. Ion channels are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses, cardiac functions, muscle contraction and apoptosis. On the other extreme of biological complexity, viral ion channels (viroporins) influence many stages of the virus infection cycle either through regulating virus replication, such as entry, assembly and release or modulating the electrochemical balance in the subcellular compartments of host cells. Ion channels were crucial components of protocells. Their emergence facilitated adaptation of nascent life to different environmental conditions. The earliest ion channels must have been much simpler than most of their modern ancestors. Viral channels are among only a few naturally occurring models to study the structure, function and evolution of primordial channels. Experimental studies of these properties are difficult and often unreliable. In principle, computational methods, and molecular dynamics (MD) simulations in particular, can aid in providing information about both the structure and the function of ion channels. However, MD suffers from its own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. It is, therefore, essential to determine the reliability of MD simulations. We propose to do so on the basis of two criteria. One is channel stability on time scales that extend for several microseconds or longer. The other is the ability to reproduce the measured ionic conductance as a function of applied voltage. If both the stability and the calculated ionic conductance are satisfactory it will greatly increase our confidence that the structure and the function of a channel are described sufficiently accurately. To our knowledge, long time scale stability (approx.10 micro-sec) and the correct electrophysiology have been shown so far for only one channel - the synthetic LS3 hexamer). In this presentation, this approach will be discussed in application to two viral channels - Vpu, encoded by the HIV-1 genome and p7 of hepatitis C.

Pohorille, Andrzej↗
DOE OSTI2022

Regulation of Alfvén Eigenmodes by Microturbulence in Fusion Plasmas

Global gyrokinetic simulations of mesoscale reversed shear Alfven eigenmodes (RSAE) excited by energetic particles (EP) in fusion plasmas find that RSAE amplitude and EP transport are much higher than experimental levels at nonlinear saturation, but quickly diminish to very low levels after the saturation when background microturbulence is artificially suppressed. In contrast, in simulations coupling micro-meso scales, the RSAE amplitude and EP transport decrease drastically at the initial saturation but later increases to the experimental levels in the quasi-steady state with bursty dynamics due to regulation by thermal ion temperature gradient (ITG) microturbulence. The quasi-steady state EP transport is larger for a stronger microturbulence. Here, the RSAE amplitude in the quasi-steady state ITG-RSAE turbulence from gyrokinetic simulations, for the first time, agrees very well with experimental measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning

This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. Additionally, the diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is iteratively fitted to model evaluations to characterize the model parameter space with respect to observed empirical data. We demonstrate the feasibility of using high-performance computing and active learning model exploration techniques to characterize large parameter spaces; by partitioning the parameter space into potentially viable and non-viable regions, we rule out regions of space where simulation output is implausible to observed empirical data. We argue that such methods are necessary to enable model exploration in complex computational models that incorporate increasingly available micro-level behavior data. We provide public access to the model and high-performance computing experimentation code.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Solar wind conditions in the outer heliosphere and the distance to the termination shock

The Plasma Science experiment on the Voyager 2 spacecraft has measured the properties of solar wind protons from 1 to 40.4 AU. We use these observations to discuss the probable location and motion of the termination shock of the solar wind. Assuming that the interstellar pressure is due to a 5 micro-G magnetic field draped over the upstream face of the heliopause, the radial variation of ram pressure implies that the termination shock will be located at an average distance near 89 AU. This distance scales inversely as the assumed field strength. There are also large variations in ram pressure on time scales of tens of days, due primarily to large variations in solar wind density at a given radius. Such rapid changes in the solar wind ram pressure can cause large perturbations in the location of the termination shock. We study the nonequilibrium location of the termination shock as it responds to these ram pressure changes. The results of this study suggest that the position of the termination shock can vary by as much as 10 AU in a single year, depending on the nature of variations in the ram pressure, and that multiple crossings of the termination shock by a given outer heliosphere spacecraft are likely. After the first crossing, such models of shock motion will be useful for predicting the timing of subsequent crossings.

Belcher, John W.↗
DOE OSTI2023

Milone eTape Liquid Level Sensor Laboratory Calibration with a Commercial 12.2 cm HS-Flume and 3D Printed 4 cm Micro-HS-Flumes

The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Prior to field deployment, H-flume discharge and the corresponding Milone eTape Liquid Level Sensor (eTape) resistance values were measured in the laboratory so that discharge measurements from the NGEE Arctic Rainfall Simulator could be automated. eTape resistance was measured with increasing fluid heights for the full range of the eTape to calculate sensor detection limits and resolution. The eTape was calibrated to both a commercially available 12.2 cm HS-flume and a 3D printed 4 cm Micro-HS-flume. This data package contains two .csv files, one for the eTape calibration and the other for the flume calibrations, and two .stl files to 3D print the 4 cm Micro-HS-Flume design with a 1 cm x 3.6 cm stilling well opening. The .stl files can be opened in most 3D printing or CAD programs/software. Two .kml files of the laboratory location and broader area where testing was conducted are also included in this data package.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tailoring Carbide Dispersed Steels: A Path to Increased Strength and Hydrogen Tolerance

The use of transition metal carbides is reported for use as a hydrogen trapping mechanism for ferritic and austenitic steel materials. The program combined computational modeling and simulations to guide experiments towards candidate metal carbide traps, both for interfacial and interior trapping. It was found that interfacial trapping is less effective than interior trapping, with the group IVB transition metal carbides being the most effect internal traps with a loss of carbon. The sub-stoichiometric rocksalt structure accommodate the hydrogen atoms in its octahedral interstices. Using percolation theory, carbon loss of approximately 25% or more was sufficient to ensure an interconnected network of vacancies for such trapping from the surface to the internal sites within the carbide. Using this as a guide, the program developed a means to provide a uniform dispersion of ZrC nanoparticles with either Fe or 304L micron-scale powders which was then consolidated by direct current sintering. Electrolytic hydrogen diffusivity studies confirmed the reduction of hydrogen diffusion in the matrix with increasing ZrC content, which was a linear response over the sample range studied (0.01 to 1.0 wt.%). The consolidated material was micro-tensile tested in either a non-hydrogen or hydrogen charge condition and compared to a control with no carbides. Additions up to 0.05 wt.% ZrC increased the yield strength with no loss in ductility in either the non-hydrogen or hydrogen tested condition. ZrC concentrations above this amount further increased the yield strength at the expense of ductility. While these samples had a lower absolute ductility value prior to failure, the relative change in ductility between the non-hydrogen and hydrogen charge states was less for the carbides than that of the control. Metal-rich ZrC nanoparticles were fabricated through a conformal coating process yielding ZrC0.66 particles that were then incorporated into a metal matrix. Notch fatigue testing in a hydrogen environment was conducted where the number of cycles to failure was found to be less in the control than that of the carbide addition. However, the spread in experimental data and the number of samples tested limits a conclusive outcome based on defects noticed in the gauge section of all the powder processed samples. The collective outcomes of this report provide further insight into the mechanisms by which carbides act as hydrogen traps; a means to process such carbides through powder metallurgy; and their associated mechanical performance in either a non-hydrogen or hydrogen-charged condition.

08 HYDROGEN↗
DOE OSTI2026

Multi-task Parallelism for Robust Pre-training of Graph Foundation Models on Multi-source, Multi-fidelity Atomistic Modeling Data

Graph foundation models using graph neural networks promise sustainable, efficient atomistic modeling. To tackle challenges of processing multi-source, multi-fidelity data during pre-training, recent studies employ multi-task learning, in which shared message passing layers initially process input atomistic structures regardless of source, then route them to multiple decoding heads that predict data-specific outputs. This approach stabilizes pre-training and enhances a model’s transferability to unexplored chemical regions. Preliminary results on approximately four million structures are encouraging, yet questions remain about generalizability to larger, more diverse datasets and scalability on supercomputers. We propose a multi-task parallelism method that distributes each head across computing resources with GPU acceleration. Implemented in the open-source HydraGNN architecture, our method was trained on over 24 million structures from five datasets and tested on the Perlmutter, Aurora, and Frontier supercomputers, demonstrating efficient scaling on all three highly heterogeneous super-computing architectures.

Lupo Pasini, Massimiliano [ORNL] (ORCID:0000000249↗
NASA NTRS2022

Machine-Learning Reveals Climate Forcing From Aerosols is Dominated by Increased Cloud Cover

Aerosol-cloud interactions have a potentially large impact on climate, but are poorly quantified and thus contribute a significant and long-standing uncertainty in climate projections. The impacts derived from climate models are poorly constrained by observations, because retrieving robust large-scale signals of aerosol-cloud interactions are frequently hampered by the considerable noise associated with meteorological co-variability. The Iceland-Holuhraun effusive eruption in 2014 resulted in a massive aerosol plume in an otherwise near-pristine environment and thus provided an ideal natural experiment to quantify cloud responses to aerosol perturbations. Here we disentangle significant signals from the noise of meteorological co-variability using a satellite-based machine-learning approach. Our analysis shows that aerosols from the eruption increased cloud cover by approximately 10%, and this appears to be the leading cause of climate forcing, rather than cloud brightening as previously thought. We find that volcanic aerosols do brighten clouds by reducing droplet size, but this has a significantly smaller radiative impact than changes in cloud fraction. These results add substantial observational constraints on the cooling impact of aerosols. Such constraints are critical for improving climate models, which still inadequately represent the complex macro-physical and micro-physical impacts of aerosol-cloud interactions.

Aerosols↗
DOE OSTI2021

Understanding Carbon Dioxide Transfer in Direct Methanol Fuel Cells Using a Pore-Scale Model

Abstract The gas flow of carbon dioxide from the catalyst layer (CL) through the microporous layer (MPL) and gas diffusion layer (GDL) has great impacts on the water and fuel management in direct methanol fuel cells (DMFCs). This work has developed a liquid–vapor two-phase model considering the counter flow of carbon dioxide gas, methanol, and water liquid solution in porous electrodes of DMFC. The model simulation includes the capillary pressure as well as the pressure drop due to flow resistance through the fuel cell components. The pressure drop of carbon dioxide flow is found to be about two to three orders of magnitude higher than the pressure drop of the liquid flow. The big difference between liquid and gas pressure drops can be explained by two reasons: volume flowrate of gas is three orders of magnitude higher than that of liquid; only a small fraction of pores (<5%) in hydrophilic fuel cell components are available for gas flow. Model results indicate that the gas pressure and the mass transfer resistance of liquid and gas are more sensitive to the pore size distribution than the thickness of porous components. To buildup high gas pressure and high mass transfer resistance of liquid, the MPL and CL should avoid micro-cracks during manufacture. Distributions of pore size and wettability of the GDL and MPL have been designed to reduce the methanol crossover and improve fuel efficiency. The model results provide design guidance to obtain superior DMFC performance using highly concentrated methanol solutions or even pure methanol.

Electrochemistry↗
DOE OSTI2024

Relating Hydro–Mechanical and Elastodynamic Properties of Dynamically Stressed Tensile–Fractured Rock in Relation to Applied Normal Stress, Fracture Aperture, and Contact Area

We exploit nonlinear elastodynamic properties of fractured rock to probe the micro-scale mechanics of fractures and understand the relation between fluid transport and fracture aperture under dynamic stressing. Experiments were conducted on rough, tensile-fractured Westerly granite subject to triaxial stresses. We measure fracture permeability for steady-state fluid flow with deionized water. Pore pressure oscillations are applied at amplitudes ranging from 0.2 to 1 MPa at 1 Hz frequency. During dynamic stressing we transmit ultrasonic signals through the fracture using an array of piezoelectric transducers (PZTs) to monitor evolution of interface properties. We examine the influence of fracture aperture and contact area by conducting measurements at effective normal stresses of 10–20 MPa. Additionally, the evolution of contact area with stress is characterized using pressure sensitive film. These experiments are conducted separately with the same fracture and map contact area at stresses from 9 to 21 MPa. The measurements are a proxy for “true” contact area for the fracture surface and we relate them to elastic properties using the calculated PZT sensor footprints via numerical modeling of Fresnel zones. We compare the elastodynamic response of the fracture using the stress-induced changes in ultrasonic wave velocities for transmitter-receiver pairs to image spatial variations in contact properties. We show that nonlinear elasticity and permeability enhancement decrease with increasing normal stress. Additionally, post-oscillation wave velocity and permeability exhibit quick recoveries toward pre-oscillation values. Estimates of fracture contact area (global and local) demonstrate that the elastodynamic and permeability responses are dominated by fracture topology.

58 GEOSCIENCES↗
DOE OSTI2022

Small-scale mechanical testing and characterization of fuel cladding chemical interaction between HT9 cladding and advanced U-based metallic fuel alloy

Fuel cladding chemical interactions (FCCI) occurred on the interface between the nuclear metal fuel and cladding is the primary cause of cladding wastage, weakening cladding mechanical integrity, and placing fuel and cladding at risk. Although the microstructural and phase information of FCCI has been fairly understood, mechanical properties remain less studied due to limited reaction volume. Here, through a combining of advanced electron microscopy characterizations and small-scale mechanical testing techniques, including indentation and micro-tensile testing, this study investigated the microscale mechanical properties of FCCI between the ferritic/martensitic (F/M) HT9 cladding and an advanced Uranium (U)-based metallic fuel irradiated at the Advanced Test Reactor to 2.2% FIMA with peak inner cladding temperature reached to 650 °C. Mechanical testing results show significant hardening and embrittlement in the FCCI region. The brittle fracture of FCCI specimen is mainly attributed to the formation of nano-crystallized intermetallic σ-FeCr phase. Whereas mechanical softening was revealed in the unreacted HT9 matrix due to irradiation-induced microstructural and microchemical evolution, specifically, the disappearance of martensitic lath structure and the formation of Fe 2 Mo Laves phase precipitation which consumed the solid solution strengthening Mo from the F/M HT9 matrix. Due to the achieved high cladding temperature, this fuel pin is of particular significance for revealing the high-temperature irradiation effect on the mechanical properties of HT9 cladding. Therefore, the outcomes of this study are expected to contribute to the development of multi-scale mechanical behavior modeling of HT9 cladding for Generation IV reactors which requires cladding to run at higher temperature (above 600 ?).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

NASA Tech Briefs, January 2003

Topics covered include: Optoelectronic Tool Adds Scale Marks to Photographic Images; Compact Interconnection Networks Based on Quantum Dots; Laterally Coupled Quantum-Dot Distributed-Feedback Lasers; Bit-Serial Adder Based on Quantum Dots; Stabilized Fiber-Optic Distribution of Reference Frequency; Delay/Doppler-Mapping GPS-Reflection Remote-Sensing System; Ladar System Identifies Obstacles Partly Hidden by Grass; Survivable Failure Data Recorders for Spacecraft; Fiber-Optic Ammonia Sensors; Silicon Membrane Mirrors with Electrostatic Shape Actuators; Nanoscale Hot-Wire Probes for Boundary-Layer Flows; Theodolite with CCD Camera for Safe Measurement of Laser-Beam Pointing; Efficient Coupling of Lasers to Telescopes with Obscuration; Aligning Three Off-Axis Mirrors with Help of a DOE; Calibrating Laser Gas Measurements by Use of Natural CO2; Laser Ranging Simulation Program; Micro-Ball-Lens Optical Switch Driven by SMA Actuator; Evaluation of Charge Storage and Decay in Spacecraft Insulators; Alkaline Capacitors Based on Nitride Nanoparticles; Low-EC-Content Electrolytes for Low-Temperature Li-Ion Cells; Software for a GPS-Reflection Remote-Sensing System; Software for Building Models of 3D Objects via the Internet; "Virtual Cockpit Window" for a Windowless Aerospacecraft; CLARAty Functional-Layer Software; Java Library for Input and Output of Image Data and Metadata; Software for Estimating Costs of Testing Rocket Engines; Energy-Absorbing, Lightweight Wheels; Viscoelastic Vibration Dampers for Turbomachine Blades; Soft Landing of Spacecraft on Energy-Absorbing Self-Deployable Cushions; Pneumatically Actuated Miniature Peristaltic Vacuum Pumps; Miniature Gas-Turbine Power Generator; Pressure-Sensor Assembly Technique; Wafer-Level Membrane-Transfer Process for Fabricating MEMS; A Reactive-Ion Etch for Patterning Piezoelectric Thin Film; Wavelet-Based Real-Time Diagnosis of Complex Systems; Quantum Search in Hilbert Space; Analytic Method for Computing Instrument Pointing Jitter; and Semiselective Optoelectronic Sensors for Monitoring Microbes.

Source record↗
DOE OSTI2025

Insights from Optimizing HPL Performance on Exascale Systems: A Comparative Analysis of Panel Factorization

High performance LINPACK (HPL) remains the primary benchmark for evaluating supercomputing performance. It includes many parts with substantial internal complexity, and its performance is affected by a large number of parameters that interact in ways that are difficult to predict on large-scale heterogeneous supercomputer systems. We present a comprehensive performance analysis of HPL on Frontier, the world’s first exascale supercomputer, which achieved HPL performance of 1.35 exaflops. Through empirical parameter tuning, detailed modeling, and comparative evaluation, we uncover critical performance insights, share lessons learned, and outline best practices for effective parameter tuning on exascale systems. We introduce and evaluate two novel PDFACT strategies: a dedicated-thread (DT) variant and a GPU-based variant (GPUPDFACT) implementation using HIP cooperative groups, demonstrating that GPU-based factorization outperforms conventional CPU-based PDFACT on Frontier’s architecture. Our findings establish key performance factors for HPL on exascale systems and offer valuable guidance for future high-performance computing and benchmarking efforts.

Lu, Hao [ORNL] (ORCID:000000018941870X)↗