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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Recent H - ion source research and development at the Oak Ridge National Laboratory

The U.S. Spallation Neutron Source (SNS) is a state-of-the-art neutron scattering facility delivering the world's most intense pulsed neutron beams to a wide array of instruments which are used to conduct investigations in many fields of science and engineering. Neutrons are produced from spallation of liquid Hg by bombardment of short (~1 μs), intense (~35 A) pulses of protons delivered at 60 Hz by a storage ring which is fed by a high-intensity, ~1 GeV H - LINAC. This facility has operated almost continuously since 2006, with ion source performance increasing over those years, and currently providing 50–60 mA of H - ions with a duty-factor of 6% for maintenance-free runs of several months with near 100% availability. Ion source research and development at ORNL has played a key role in enabling and supporting this success: this report provides an update on some of the ongoing ion source research and development efforts which have been undertaken since the previous Negative Ion Beams and Sources (NIBS) conference in 2020. These include significant improvements to H - beam current by extraction from a larger source outlet aperture and improvements to the electron dumping system which should eliminate the gradual loss of electrode voltage over the course of a run which has occasionally impacted SNS operations. Improvement and simplification of the plasma ignition system for the external antenna ion source, a long-standing problem, was also realized. Lastly, RF coupling efficiency was measured for both the SNS internal and external antenna ion sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

β decay of neutron-rich 76 Cu and the structure of 76 Zn

In this work, the β decay of 76 Cu to the levels of 76 Zn was studied at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Lab (ORNL). A purified 76 Cu beam was developed and data were recorded for the decay of the A=76 decay chain using four high-purity germanium (HPGe) clover detectors at the Low-energy Radioactive Ion Beam Spectroscopy Station (LeRIBSS). In this measurement, data on γ-ray emission following β decay, including βγ and γγ coincidences, were collected and γγ spectra were analyzed to identify the statistically significant coincidences. From this analysis, we propose a level scheme for 76 Zn which contains a total of 59 energy levels up to 6.0 MeV containing 105 γ rays. We have identified an additional 53 γ rays associated with this decay which could not be place in the decay scheme due to insufficient coincidence information or no energy match to identified levels. No γ rays from states in 75 Zn fed in the delayed-neutron branch were observed even though other γ rays in the A=75 decay chain were observed. Spin and parity assignments are proposed for some levels based on comparison to systematics and shell model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A 20-kW DC Oak Ridge Converter with Integrated AC & DC Sources for Grid Services and Energy Storage Systems

This paper proposes a wireless power transfer (WPT) platform with integrated energy conversion that has the capability for 1) recharging the energy storage systems (ESSs) from the grid systems, including renewable energy sources such as wind, solar, etc., 2) off grid systems recharging the ESSs from dc grid systems, 3) grid recharging of electric vehicles (EVs), and 4) off grid recharging of EVs from ESSs. The unique aspect of the method is the use of multi-interface power electronic converter for the grid and ESSs and EVs that can support a range of applications with ac / dc and dc / dc energy conversion ability in a single converter system. The key enabling technology to achieve these functionalities is Oak Ridge Converter (ORC) with polyphase coupler coil system both developed at ORNL. This new technology enables higher power density WPT systems while allowing the coils to interface from ac grid at 60 Hz frequency or dc source directly merging with 85 kHz operating frequency of switching component. The experimental results of the proposed system are presented for 20 kW output power with the system overall efficiency around 95.4% from dc source and 93% overall efficiency from ac grid achieving 9-10% current total harmonic distortion (THD) and 0.98-0.99 power factor (PF).

Asa, Erdem↗
DOE OSTI2023

TOWARDS RAPID RESPONSE UPDATES OF POPULATIONS AT RISK

Understanding population at risks has been a focus of the LandScan program through its development of population estimates. With advancements in computer vision, deep learning technologies and access to High Performance Computing (HPC) and high resolution imagery, population estimates are now modeled at the building level. However, when those patterns are disrupted, rapid updates to population distribution estimates are needed to support humanitarian aid and response. Oak Ridge National Laboratory (ORNL) recently adapted an existing deep learning building footprint extraction model in development of a scalable approach to Building Damage Assessments (BDA). This new opportunity opens the possibility of automating BDA to support rapid population distribution estimate updates for geographic areas involved in geopolitical conflicts or natural events for humanitarian aid and response or where to focus recovery efforts. In addition, incorporate social surveys to further model human behavior under conflict or other scenarios that disrupt normal patterns of life.

Urban, Marie↗
DOE OSTI2020

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Learning to Scale the Summit: AI for Science on a Leadership Supercomputer

The Summit system at Oak Ridge National Lab-oratory (ORNL) has been the world's top AI for science su-percomputer for several years, ranked world's fastest computer at its 2018 launch and currently top system in the US and #2 on the TOP5OO list. Summit's purposeful design to handle both conventional modeling and simulation science and emerging AI workloads has made it a leading destination for AI-powered computational science. We report here on AI for science usage on Summit near the midpoint of its lifespan. We review AI usage across the many science projects that have used Summit. We then examine in detail a set of applications scaling AI to full system as well as projects implementing AI-coordinated science discovery workflows on Summit. Finally, we offer some observations regarding the future of advancing scientific knowledge and understanding via AI, especially in the context of leadership-class scientific computing.

Joubert, Wayne↗
DOE OSTI2020

Review of Safety and Exposure Limits of Electromagnetic Fields (EMF) in Wireless Electric Vehicle Charging (WEVC) Applications

This study reviews the exposure limits and safety of intermediate frequency (IF) electromagnetic field (EMF) emissions for wireless electric vehicle charging (WEVC) applications. A review of the electromagnetic field exposure limits identified in international guidelines are presented. An overview of the electromagnetic field shielding technologies is provided including recommended geometries, materials, and performances of the methods available in the literature. Available laboratory results of EMF emissions are summarized considering several wireless power transfer studies in different power levels. Possible EMF reduction techniques are discussed with shielding practices and ORNL case studies. Also, living object detection (LOD) and foreign object detection (FOD) methods are reviewed from a safety aspect.

Asa, Erdem↗
DOE OSTI2023

Optimal Power Sharing Speed Compensation in On-road Wireless EV Charging Systems

Dynamic wireless charging of electric vehicles (EV) is an emerging technology with the potential to address range anxiety and reduce the size of batteries or provide charge-sustaining operation. Charging demand for dynamic wireless charging systems (DWCS) varies greatly in response to location-specific traffic behaviors including the number and speed of vehicles. This paper highlights the potential reduction of load variation with speed compensation and simulates opportunities to maximize the number of cars charged concurrently through “power sharing” or altering power output to slower cars while maintaining a maximum delivered energy. An improved sub-minute model for synthetic traffic is proposed to effectively model DWCS load on high speed roadways and a power electronics model is created based on an existing prototype developed by ORNL to investigate the potential for power sharing. Reductions in the average speed of traffic can greatly increase instantaneous DWCS load by as much as 26%, complicating capacity sizing. Parametric studies with a LCC-S power electronics model shows feasible power reduction of more than 20%, while maintaining a maximum achievable efficiency greater than 90%. Speed compensation on a roadway with large speed variation can reduce average power expected by 21% and increase the maximum number of cars charged simultaneously by 30%. The application of power sharing may significantly reduce load variability due to speed, allow for increased car hosting capability, and guarantee a maximum energy delivered.

Lewis, Donovin D.↗
DOE OSTI2021

Progress in development of pulsed resonant charging power supply for the Spallation Neutron Source extraction kicker PFN system

A conceptual design of the pulsed resonant charging power supply (RCPS) for the beam extraction system of the Spallation Neutron Source (SNS) at the Oak Ridge National Laboratory (ORNL) was previously reported at the 2019 IEEE Pulsed Power & Plasma Science Conference (PPPS 2019) [1]. Development and testing of the prototype supply continued through the year to finalize the design ahead of the Proton Power Upgrade (PPU). Testing revealed reliability issues with the original resonant charging scheme related to the step-up transformer core. Additional components were incorporated into the system, and some of the original prototype components were replaced to improve performance and reliability of the power supply. This paper describes the changes in the resonant charging scheme, presents the results of testing of the improved prototype at full power level, and shows the final design of the RCPS.

Peplov, Vladimir↗
DOE OSTI2025

Oakridge PPU Magnets: Results and Measurements

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is being upgraded from 1.0 GeV to 1.3 GeV (or 1.4 to 2.8 MW). Several water-cooled magnets have been upgraded to transport 30% higher beam energy. Fermilab contributed the magnet design for the new chicane magnets and injection/extraction septum. Designing the magnets was a challenging task because the new magnets required good combined integrated field quality and needed to occupy the old magnets space but with about 20% greater integrated magnetic field. Additional strong requirements applied to the magnets fringe field so as not to disturb the circulating beam. After fabrication of the magnets, an extensive measurement campaign was developed and performed at Fermilab’s Magnet Test Facility. The measurements needed to assess magnet performance and provide comparison to design calculations. These included verification of field strength and harmonics along an 8 m length and 200 mm good field diameter for the chicane dipoles, end-field Hall probe mapping of these magnets, and measurements along two differently curved trajectories within the ∼3 m septum gradient magnet. Details of the measurements and systems are presented along with results and comparison to field models.

DiMarco, J. [Fermilab] (ORCID:0000000228400036)↗
DOE OSTI2022

High Flux Isotope Reactor Neutron Spectrum Shape Estimation From Activation Experiment Data

Here, this article provides a comprehensive review of historical irradiation dosimetry available for different locations within the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). This article includes a summary of the available measured activation target data covering a span of over 15 years and 39 experimental campaigns, including 200 individual sample locations evaluated. Using this broad set of data, we reconstruct historic average neutron spectra shapes for HFIR at various locations, including within the flux trap region, beryllium reflectors, and hydraulic tube (HT) regions, at both the 100- and 85-MW operational power. Our findings indicate that the general axial flux distribution shows a relatively small change in transition from 100- to 85-MW operating power, with differences of -6% to +15% for the thermal energy range and around -16% to +8% for the fast range, indicating a sharper drop-off of the thermal neutron flux away from the axial center. Compared with historical dosimetry estimates of the HFIR flux shape, we generally find a moderately broader axial profile shape for thermal neutrons in the interior target regions for the 100-MW samples evaluated but relatively close agreement for the present 85-MW flux shape for both thermal and fast fluxes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

History of Pu-238 Production Restart Efforts at Idaho National Laboratory and Oak Ridge National Laboratory

In the early 2010s, efforts to restart production in the U.S. of plutonium-238 heat source (HSPu) material for NASA deep space missions were initiated. Processes, procedures, hardware, and chemical separations were developed and implemented to enable the production of heat source material at Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL). Here, this review provides an overview of the timeline and efforts associated with the restart of production, as well as upcoming efforts to increase production.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Design and Performance Characterization of RADICAL-Pilot on Leadership-Class Platforms

Many extreme scale scientific applications have workloads comprised of a large number of individual highperformance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders and late-binding. As such, suitable implementations of the Pilot abstraction can support the collective execution of large number of tasks on supercomputers. We introduce RADICAL-Pilot (RP) as a portable, modular and extensible Pilot enabled runtime system. We describe RP's design, architecture and implementation. We characterize its performance and show its ability to scalably execute workloads comprised of tens of thousands heterogeneous tasks on DOE and NSF leadership-class HPC platforms. Specifically, we investigate RP's weak/strong scaling with CPU/GPU, single/multi core, (non)MPI tasks and python functions when using most of ORNL Summit and TACC Frontera. RADICAL-Pilot can be used stand-alone, as well as the runtime for third-party workflow systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Design of a Continuous Pellet Fueling System for Wendelstein 7-X

A continuous pellet fueling system (CPFS) is currently being designed at the Oak Ridge National Laboratory (ORNL) for the long pulse operation of the Wendelstein 7-X (W7-X) stellarator. The purpose of the CPFS is to provide deep continuous fueling for feedback-controlled high-density operation and mitigation of predicted hollow density profiles. As described here, the system will provide the capability to inject cylindrical pellets of solid hydrogen or deuterium into the plasma core, with flexibility to vary the pellet size, velocity, and injection frequency. Pellets are nominally of 3 mm in diameter and have a length between 1 and 4 mm. The heart of the CPFS is a vertically oriented, twin-screw extruder, cooled by three Gifford-McMahon cryocoolers in parallel, designed to form a continuous filament of hydrogen or deuterium. The filament width, which determines the pellet length, can be adjusted by means of a variable nozzle driven by a linear actuator at the base of the extruder. Coupled to the nozzle is a solenoid-operated gas gun and cutter assembly. A pneumatic propellant valve pulses a burst of ~60 bar helium to accelerate the cut pellet into W7-X. Three gaps in the guide tubes provide pumping locations to remove the helium propellant before it reaches the plasma. The maximum velocity of the pellet is limited by its ability to survive navigating the guide tube trajectory intact. A microwave cavity located within the guide tube provides the capability to measure the pellet size and velocity. The mechanical and thermal designs of the W7-X extruder, adjustable nozzle, and gun and cutter assembly design are described. A guide tube design and experimental pellet survivability test results are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Deep Learning for Intelligent Bubble Size Detection in the Spallation Neutron Source Visual Target

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) will undergo proton power upgrade (PPU), increasing the proton beam power from 1.4 MW to 2.8 MW. From 2.8 MW, 2.0 MW will go to the current First Target Station and the rest will go to the future Second Target Station (STS). The First Target Station uses a liquid mercury target that is contained in a 316L stainless steel vessel. The proton beam is pulsed at 60 Hz, with a pulse of about 0.7μs. When the proton beam hits the target, the intense energy deposition leads to a rapid rise in temperature in the mercury. This temperature rise creates pressure waves that propagate through the mercury and cause cavitation erosion. The power upgrade will cause stronger pressure waves that will further increase damage because of cavitation. Injecting small helium bubbles in the mercury has been an efficient method of mitigating the pressure wave at 1.4 MW. However, at higher power, additional mitigation is necessary. Therefore, the 2 MW target vessel will be equipped with swirl bubblers and an additional gas injection port near the nose to inject more gas in the target. To develop a gas injection strategy and design, flow visualization in water with a transparent prototypical target (“visual target”) was performed. Bubble sizes and their spatial distribution in the flow loop are crucial to understanding the effectiveness of the bubbles in mitigating pressure waves. Bubbles were generated in the visual target under varied conditions of input pressures with helium and air. Images were captured using a high-speed camera at varied frame rates at different positions away from the swirl bubbler and different depths in the flow loop under varying lighting conditions. Initially, methods such as circular Hough transforms were applied after a series of images processing to obtain a general distribution of bubble sizes. Bubbles smaller than 500 μm are preferred to effectively mitigate the effect of pressure waves, which demands an accurate bubble detection and sizing system. Intelligent detection and identification of bubble sizes alleviate misdetection and improves accuracies. Employing neural networks, intelligent detection of bubble sizes and their distribution was developed and provides a robust alternative to traditional techniques. Human intervention was employed to label in-focus and out-of-focus bubbles in the set of training images. An object detection network using a pretrained convolutional neural network was created that extracted the features from the training images. Data augmentation was used to improve network accuracy through a random transformation of the original data.

Rasheed, Fayaz↗
DOE OSTI2020

Post-Irradiation Evaluation of Eurofer97 Fracture Toughness Using Miniature Multinotch Bend Bar Specimens

In this study, we performed fracture toughness characterization of ten neutron-irradiated Eurofer97 variants using precracked miniature multi-notch bend bar (M4CVN) specimens based on the Master Curve method in the ASTM E1921 standard. The neutron irradiation was performed in the flux trap position of the High Flux Isotope Reactor (HFIR) of the Oak Ridge National Laboratory (ORNL) with the nominal irradiation temperature of 300°C and irradiation dose of 2.5 displacements per atom (dpa). Depending on the irradiation temperature and materials, we observed different degrees of irradiation hardening and embrittlement for ten Eurofer97 variants. The upper shift in the Master Curve reference temperature T0Q vs. the increase in Vickers microhardness values showed a liner relationship for only a few materials indicating different irradiation responses of the Eurofer97 variants.

Chen, Xiang↗
DOE OSTI2023

Shifting Layer Heights for Closed-Loop Contours in Additive Manufacturing

Traditional slicing for 3D printing involves a planar cross-sectioning process to create layers. These layers are stacked one on top of the next representing a butt-joint, which is typically the weakest direction for loading a 3D printed part. Because the layers are printed sequentially, no material or reinforcement connects from one layer to the next. This clean layer line between layers is easy to break or separate. To fix this, the authors have implemented a new approach to shift the height of every other closed-loop contour toolpath such that a clean layer line no longer exists. This bead shifting approach involves moving every other contour by half a layer height, after the cross-sectioning step, so that a straight line cannot be drawn between layers. To maintain the original object geometry, a half height layer is printed for the first and last layer to create a flat top and bottom surface. This functionality has been implemented and tested as part of ORNL Slicer 2, an open-source toolpathing software package.

Roschli, Alex↗
DOE OSTI2023

Uncertainty Quantification of Metal Additive Manufacturing Processing Conditions Through the use of Exascale Computing

Metal additive manufacturing (AM) is a disruptive manufacturing technology that opens the design space for parts outside those possible from traditional manufacturing methods. In order to accelerate industry and R&D needs to certify AM parts, the Exascale Additive Manufacturing project (ExaAM) has developed a suite of exascale-ready computational tools to model the process-to-structure-to-properties (PSP) relationship for additively manufactured metal components. One such tool is an uncertainty quantification (UQ) pipeline to quantify the effect that uncertainty in processing conditions has on local mechanical responses. We present an overview of this pipeline and its required simulation and workflow codes. Using the Oak Ridge National Laboratory’s (ORNL) exascale computer, Frontier, we utilize this pipeline to cross multiple length and time scales to predict the local mechanical response of a location within a complex AM bridge part, AMB2018-01 produced by the National Institute of Standards and Technology (NIST) as part of their 2018 AM-Bench test series. Our results are then compared to experimental mechanical tests of parts from the NIST build to quantify the error in the ExaAM UQ workflow.

Carson, Robert↗