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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Performance Analysis of PIConGPU: Particle-in-Cell on GPUs using NVIDIA’s NSight Systems and NSight Compute

PIConGPU, Particle In Cell on GPUs, is an open source simulations framework for plasma and laser-plasma physics used to develop advanced particle accelerators for radiation therapy of cancer, high energy physics and photon science. While PIConGPU has been optimized for at least 5 years to run well on NVIDIA GPU-based clusters, there has been limited exploration by the development team of potential scalability bottlenecks using recently updated and new tools including NVIDIA’s NVProf tool and the brand-new NVIDIA NSight Suite (Systems and Compute) tools. PIConGPU is a highly optimized application that runs production jobs at scale on a system Oak Ridge Leadership Facility’s (OLCF) Summit supercomputer (using the full machine at 4600 nodes; at 98% of GPU utilization on all ~28000 NVIDIA Volta GPUs). PIConGPU has been selected as one of the the eight applications for OLCF’s coveted Center for Accelerated Application Readiness (CAAR) program aimed at the facility’s Frontier supercomputer (OLCF’s first exascale system to launch in 2021), to partner with our vendors (primary vendors: AMD and Cray/HPE) ensuring that Frontier will be able to perform large-scale science when it opens to users in 2022. To this effect, performance engineers on the PIConGPU team wanted to dive deep into the application to understand at the finest granularity, which portions of the code could be further optimized to exploit the hardware on Summit at it’s maximum potential and also to elucidate which key kernels should be tracked and optimized for the CAAR effort to port this code to Frontier. Any bottlenecks that are observed via performance profiling on Summit are likely to also impact scalability on the Frontier-dev system and the Frontier Early Access (EA) system. Additionally, the engineers wanted to take a closer look at the newest NVIDIA profiling tools which allows us to identify the most useful features on these tools and will provide an opportunity to compare it to new AMD and Cray’s performance analysis tool releases and provide feedback to our vendor partners on what features are most important and mission critical for CAAR efforts. The primary goal of this report is to focus on the evaluation of PIConGPU’s most time-intensive kernels using NVProf and NSight Suite. Three kernels, Current Deposition (also known as Compute Current), Particle Push (Move and Mark), and Shift Particles are known to be some of the most time-consuming kernels in PIConGPU. The Current xi Deposition kernel and Particle Push kernel both set up the particle attributes for running any physics simulation with PIConGPU, so it is crucial to improve the performance of these two kernels. In this report, we measure single GPU metrics for the three kernels, offer high level takeaways from the conducted analysis, and compare the profiling data from NSight Compute to that of NVProf. This analysis was performed using a grid size of 240 x 272 x 224, and 10 time steps with the Mid-November Figure of Merit (FOM) run setup. The Traveling Wave Electron Acceleration (TWEAC) science case used in this run is a representative science case for PIConGPU. This execution can also be used for baseline analysis on AMD MI50/ MI60 systems. As of the time of writing, the PIConGPU application has limited use for features of NSight Systems, so this report will mainly focus on insights garnered from NSight Compute. For this analysis, we run the “full” metric set available in NSight Compute version 2020.1.2 and use NSight Systems version 2020.3.1 to generate the application timeline.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗
NASA NTRS1992

Ground and flight calibration assessment of HiRAP accelerometer data from missions STS-35 and STS-40

A method of removing non-aerodynamic signals and calibrating the High Resolution Accelerometer Package (HiRAP) flight data was developed and is discussed for Shuttle Orbiter missions STS-35 and STS-40. These two mission data sets were analyzed using ground (dynamic) calibration data and flight calibrations using a flight calibration technique that was developed and refined over the HiRAP operational lifetime. This technique evolved early in the flight program, since it was recognized that ground calibration factors are insufficient to determine absolute low acceleration levels. The application of flight calibration factors to the data sets from these missions produced calibrated acceleration levels within an accuracy of less than plus or minus 1.5 micro-g of zero during a time in the flight when the acceleration level was known to be less than 1 micro-g. This analysis further confirms the theory that flight calibrations are required in order to obtain the absolute measurement of low-frequency, low-acceleration flight signals.

Blanchard, Robert C.↗
NASA NTRS1993

Flight calibration assessment of HiRAP accelerometer data

A flight derived method of calibrating the High Resolution Accelerometer Package (HiRAP) flight data has been developed and is discussed for Shuttle Orbiter missions STS-35 and STS-40. These two mission data sets have been analyzed using ground calibration factors and flight derived calibration factors. This flight technique evolved early in the flight program when it was recognized that ground calibration factors are insufficient to determine absolute low-acceleration levels. The application of flight calibration factors to the data sets from these missions produced calibrated acceleration levels within an accuracy of less than +/- 1.5 microgravity of zero during a time in the flight when the acceleration level was known to be less than 1.0 microgravity. This analysis further confirms the theory that flight calibrations are required in order to obtain the absolute measurement of low-frequency, low-acceleration flight signals.

Blanchard, Robert C.↗
NASA NTRS1975

A technique for accelerating iterative convergence in numerical integration, with application in transonic aerodynamics

A technique is described for the efficient numerical solution of nonlinear partial differential equations by rapid iteration. In particular, a special approach is described for applying the Aitken acceleration formula (a simple Pade approximant) for accelerating the iterative convergence. The method finds the most appropriate successive approximations, which are in a most nearly geometric sequence, for use in the Aitken formula. Simple examples are given to illustrate the use of the method. The method is then applied to the mixed elliptic-hyperbolic problem of steady, inviscid, transonic flow over an airfoil in a subsonic free stream.

Martin, E. D.↗
NASA NTRS1976

A technique for accelerating iterative convergence in numerical integration, with application in transonic aerodynamics

A technique is described for the efficient numerical solution of nonlinear partial differential equations by rapid iteration. In particular, a special approach is described for applying the Aitken acceleration formula (a simple Pade approximant) for accelerating the iterative convergence. The method finds the most appropriate successive approximations, which are in a most nearly geometric sequence, for use in the Aitken formula. Simple examples are given to illustrate the use of the method. The method is then applied to the mixed elliptic-hyperbolic problem of steady, inviscid, transonic flow over an airfoil in a subsonic free stream.

Martin, E. D.↗
NASA NTRS1982

Electric rail gun projectile acceleration to high velocity

Electric rail accelerators are being investigated for application in electric propulsion systems. Several electric propulsion applications require that the rail accelerator be capable of launching projectiles at velocities above 10 km/s. An experimental program was conducted to develop rail accelerator technology for high velocity projectile launch. Several 6 mm bore, 3 m long rail accelerators were fabricated. Projectiles with a mass of 0.2 g were accelerated by plasmas, carrying currents up to 150 kA. Experimental design and results are described. Results indicate that the accelerator performed as predicted for a fraction of the total projectile acceleration. The disparity between predicted and measured results are discussed.

Bauer, D. P.↗
DOE OSTI2020

GPU Direct I/O with HDF5

Exascale HPC systems are being designed with accelerators, such as GPUs, to accelerate parts of applications. In machine learning workloads as well as large-scale simulations that use GPUs as accelerators, the CPU (or host) memory is currently used as a buffer for data transfers between GPU (or device) memory and the file system. If the CPU does not need to operate on the data, then this is sub-optimal because it wastes host memory by reserving space for duplicated data. Furthermore, this “bounce buffer” approach wastes CPU cycles spent on transferring data. A new technique, NVIDIA GPUDirect Storage (GDS), can eliminate the need to use the host memory as a bounce buffer. Thereby, it becomes possible to transfer data directly between the device memory and the file system. This direct data path shortens latency by omitting the extra copy and enables higher-bandwidth. To take full advantage of GDS in existing applications, it is necessary to provide support with existing I/O libraries, such as HDF5 and MPI-IO, which are heavily used in applications. In this paper, we describe our effort of integrating GDS with HDF5, the top I/O library at NERSC and at DOE leadership computing facilities. We design and implement this integration using a HDF5 Virtual File Driver (VFD). The GDS VFD provides a file system abstraction to the application that allows HDF5 applications to perform I/O without the need to move data between CPUs and GPUs explicitly. We compare performance of the HDF5 GDS VFD with explicit data movement approaches and demonstrate superior performance with the GDS method.

Ravi, J↗
DOE OSTI2022

Considerations for a TeV collider based on dielectric laser accelerators

Particle acceleration in dielectric microstructures powered by infrared lasers, or "dielectric laser acceleration" (DLA), is a promising area of advanced accelerator research with the potential to enable more affordable and higher-gradient accelerators for energy frontier science and a variety of other applications. DLA leverages well-established industrial fabrication capabilities and the commercial availability of tabletop lasers to reduce cost, with axial accelerating fields in the GV/m range. Further, desirable luminosities would be obtained by operating with very low charge per bunch but at extremely high repetition rates. And as a consequence of its unique operating parameter regime, coupling of the laser to the accelerator can potentially be in the 50% range and with low beamstrahlung energy loss due at the interaction point, making DLA a promising approach for a future multi-TeV linear collider.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

CALPHAD-based Bayesian optimization to accelerate alloy discovery for high-temperature applications

Two crucial properties influencing the performance of high-temperature alloys are coefficient of thermal expansion (CTE) and phase constitution. It is desirable to have alloys with low CTE, which reduces CTE mismatch with the surface oxide and the likelihood of oxide spallation. Reducing the amount of brittle intermetallic phases such as Sigma (σ) enhances alloy ductility and processability. Here, we propose a multi-objective Bayesian Optimization (BO) model to simultaneously minimize CTE (at an operational temperature of 1150 °C) and T σ (temperature when the Sigma phase completely dissolves in the metal matrix), properties which are obtained from high-throughput CALculation of PHAse Diagrams (CALPHAD). The model successfully identifies several alloys with CTE ≤ 2 × 10 –5 /K and T σ ≤ 500 °C by exploring just 7% of the nickel–chromium–cobalt–aluminum–iron (Ni–Cr–Co–Al–Fe) composition space. Such multi-objective alloy design frameworks can be used to inform additive manufacturing experiments and accelerate alloy discovery for high-temperature energy applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nb 3 Sn multicell cavity coating system at Jefferson Lab

Superconducting radio frequency niobium cavities are the building blocks of modern accelerators for scientific applications. Lower surface resistance, higher fields, and high operating temperatures advance the reach of the future accelerators for scientific discovery as well as potentially enabling cost-effective industrial solutions. We describe the design and performance of an Nb 3 Sn coating system that converts the inner surface of niobium cavities to an Nb 3 Sn film. The niobium surface, heated by radiation from the niobium retort, is exposed to Sn and SnCl 2 vapor during the heat cycle, which results in about 2 μm Nb 3 Sn film on the niobium surface. Film composition and structure as well as radio frequency properties with 1-cell R&D cavities and 5-cell practical accelerator cavities are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Accelerator Real-time Edge AI for Distributed Systems (READS) (Proposal)

Over the last decade, Machine Learning (ML) technologies have slowly made their way into the accelerator community. Rapid advances in recent years in deep learning, particularly reinforcement learning for control system applications and the accessibility of deep learning in embedded hardware, have generated renewed interest and spawned a number of applications. The Fermilab Accelerator Complex, shown in Fig. 1, has provided High Energy Physics (HEP) experiments with proton beams for nearly fifty years. The current focus of the laboratory is its world-class experimental program at the intensity frontier. While increasing beam intensity certainly presents its own challenges, preserving beam size while minimizing beam losses – particles lost through interactions with the beam vacuum pipe – turns out to be, in many ways, the main challenge. The accelerator is controlled via a complex system of hundreds of thousands of devices. Enabling fine tuning and real-time optimization of their parameters using ML methods and stepping beyond experience-based reasoning of human operators are key to the success of future intensity upgrades. Our objective will be to integrate ML into accelerator operations and furthermore, provide an accessible framework, which can also be used by a broad range of other accelerator systems with dynamic tuning needs.

43 PARTICLE ACCELERATORS↗
NASA NTRS1976

Accelerated test techniques for micro-circuits: Evaluation of high temperature (473 k - 573 K) accelerated life test techniques as effective microcircuit screening methods

The application of high temperature accelerated test techniques was shown to be an effective method of microcircuit defect screening. Comprehensive microcircuit evaluations and a series of high temperature (473 K to 573 K) life tests demonstrated that a freak or early failure population of surface contaminated devices could be completely screened in thirty two hours of test at an ambient temperature of 523 K. Equivalent screening at 398 K, as prescribed by current Military and NASA specifications, would have required in excess of 1,500 hours of test. All testing was accomplished with a Texas Instruments' 54L10, low power triple-3 input NAND gate manufactured with a titanium- tungsten (Ti-W), Gold (Au) metallization system. A number of design and/or manufacturing anomalies were also noted with the Ti-W, Au metallization system. Further study of the exact nature and cause(s) of these anomalies is recommended prior to the use of microcircuits with Ti-W, Au metallization in long life/high reliability applications. Photomicrographs of tested circuits are included.

Johnson, G. M.↗
NASA NTRS1998

A Review of Microgravity Levels on Ten OARE Shuttle Missions

The Orbital Acceleration Research Experiment (OARE) is an accelerometer package with nano-g sensitivity and on-orbit bias calibration capabilities. The OARE consists of a three axis miniature electrostatic accelerometer (MESA), a full in-flight bias and scale factor calibration station, and an on-board microprocessor for experiment control and data storage. Originally designed to measure and record the aerodynamic acceleration environment of the NASA Space Shuttles during re-entry, the OARE has been used on ten shuttle missions to measure the quasi-steady acceleration environment (<1 Hz) of the Orbiter while in low-Earth orbit. The effects on the quasi-steady acceleration environment from Orbiter systems, Orbiter attitude, Orbiter altitude, and crew activity are well understood as a result of these ten shuttle missions. This knowledge of the quasi-steady acceleration realm has direct application to understanding the quasi-steady acceleration environment expected for the International Space Station (ISS). This paper will summarize the more salient aspects of this quasi-steady acceleration knowledge base.

McPherson, Kevin M.↗
NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗
DOE OSTI2025

Progress in $Nb_3Sn$ SRF Technology: Opportunities and Outlook

Nb3Sn superconducting radiofrequency (SRF) cavities can expand performance capabilities of particle accelerators for both the fundamental research and the industrial applications. The technology holds a great appeal especially to small-scale applications, where it can enable a turn-key compact cryocooler operation eliminating the need for complex sub-atmospheric liquid helium cryogenic plants. Since the research into Nb3Sn SRF coatings using vapor diffusion technique restarted in 2009 at Cornell University, there has been a growing number of SRF groups around the world developing this technology with a steady increase in cavity performance and system complexity. In this talk, after a short overview of SRF technology, I will present on some of the recent developments in Nb3Sn SRF cavities, focusing on recent efforts to complete the first-of-its-kind Nb3Sn 2-cavity CEBAF-type cryomodule, which was assembled and tested last year. The talk will conclude with a short overview on some of the ongoing projects and the future possibilities for Nb3Sn cavities in accelerator applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

RECORD FAST CYCLING ACCELERATOR MAGNET BASED ON HIGH TEMPERATURE SUPERCONDUCTOR

We report on the High Temperature Superconductor (HTS) based prototype accelerator magnet capable to operate at 12 T/s B-field ramping rate with a very low supporting cryogenic cooling power thus indicating a feasibility of its application in the accelerator requiring high repetition rate and high average beam power. The magnet is designed to simultaneously accelerate two particle beams in the separate beam gaps energized by a single conductor. The design, construction and the power test of the prototype fast-cycling HTS based accelerator magnet is presented while the more detailed description and power test data analysis s given in [1]. As example, the measured cryogenic power loss limit is discussed in terms of the feasibility of application of such a magnet for the construction of the 8 GeV dual proton beam Booster.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Beamline for E-beam processing at UITF

Electron beam irradiation is a method that has shown a good potential to reduce several pollutants in wastewater. One of the main challenges towards wider adoption of this method is the need for compact, reliable, cost-effective, high-power accelerators. Jefferson Lab is working on the design and prototyping of accelerator components, based on superconducting radio-frequency (SRF) technology, aiming at accelerators for industrial applications. The LDRD project aimed at designing, procuring, installing, and commissioning a beamline at the Upgraded Injector Test Facility (UITF) accelerator to allow electron-beam irradiation studies of different materials, beginning with wastewater. The availability of such beamline allows exploring the ability of electron-beam radiation to reduce or eliminate so-called “forever chemicals” that can be found in wastewater or industrial sites. After successful commissioning, the beamline was used to irradiate wastewater samples with different concentrations of 1,4-dioxane, in collaboration with Hampton Roads Sanitation District (HRSD).

42 ENGINEERING↗