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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PIP-II 800 MeV Proton Linac Beam Pattern Generator

The PIP2 IT Beam Pattern Generator is the system that synchronizes beam injection and the RF systems between the PIP2 LINAC to the Booster. The RF frequencies of these two accelerator systems are not harmonically related. Synchronization is accomplished by controlling two MEBT Beam Choppers, which select 162.5MHz beam bunches from the LEBT and RFQ to produce an appropriate reduced beam bunch pattern that enables bucket-to-bucket transfer to the Booster RF at 46.46MHz (84th harmonic). This chopping pattern also reduces the beam current to an average of 2mA over the Booster injection, matching the Linac nominal beam current. The BPG also generates the RF frequency/phase reference which the Booster will phase lock to during injection. The BPG is fully programmable, allowing for arbitrary beam patterns with adjustable timing parameters, having a fine adjustment resolution of 38ps. The latter is accomplished using digital signal processing techniques. This paper discusses the design of the BPG, its construction, test results, and operational experience after being integrated into the PIP2 IT test accelerator and concludes with a discussion of the system’s performance and future plans.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Ion acceleration from microstructured targets irradiated by high-intensity picosecond laser pulses

Structures on the front surface of thin foil targets for laser-driven ion acceleration have been proposed to increase the ion source maximum energy and conversion efficiency. While structures have been shown to significantly boost the proton acceleration from pulses of moderate-energy fluence, their performance on tightly focused and high-energy lasers remains unclear. Here, we report the results of laser-driven three-dimensional (3D)-printed microtube targets, focusing on their efficacy for ion acceleration. Using the high-contrast (~10 12) PHELIX laser (150 J, 10 21 W / cm 2 ), we studied the acceleration of ions from 1-μm-thick foils covered with micropillars or microtubes, which we compared with flat foils. The front-surface structures significantly increased the conversion efficiency from laser to light ions, with up to a factor of 5 higher proton number with respect to a flat target, albeit without an increase of the cutoff energy. An optimum diameter was found for the microtube targets. Our findings in this work are supported by a systematic particle-in-cell modeling investigation of ion acceleration using 2D simulations with various structure dimensions. Simulations reproduce the experimental data with good agreement, including the observation of the optimum tube diameter, and reveal that the laser is shuttered by the plasma filling the tubes, explaining why the ion cutoff energy was not increased in this regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A New Route to Improve the Material Quality of Nb3Sn with Zr Inclusion

Nb3Sn superconducting material promises significant potential to exceed the performance of niobium based superconducting radio frequency (SRF) accelerator cavities. With the aim of advancing the ongoing R&D efforts in improving the material quality of Nb3Sn SRF cavities, we studied how the inclusion of Zr in Nb3Sn matrix via co-sputtering process effects the microscopic structure and superconducting properties. Our results suggest co-sputtered Nb3SnZr alloy as a new prospective material platform to further advance the performance limits of SRF cavities.

Tripathi, Malvika [Fermilab]↗
DOE OSTI2026

Towards a More Predictive Framework for Laser-Driven Particle Sources through Experimental Data-Informed Models

Laser-driven particle acceleration (LDPA) has emerged as a critical technology for high-energydensity physics applications since its discovery at Lawrence Livermore National Laboratory twenty years ago. However, realizing the full potential of these particle sources requires understanding the fundamental acceleration mechanisms and developing enhanced target designs for improved performance. This research addressed the need for controllable, high-performance laser-driven proton sources through two complementary approaches: experimentally investigating sheath field dynamics in multi-picosecond laser regimes and developing novel three-dimensional printed microstructured targets to achieve enhanced particle acceleration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗
DOE OSTI2022

Impact of electron transport models on capillary discharge plasmas

Magnetohydrodynamics (MHD) can be used to model capillary discharge waveguides in laser-wakefield accelerators. However, the predictive capability of MHD can suffer due to poor microscopic closure models. Here, we study the impact of electron heating and thermal conduction on the capillary waveguide performance as part of an effort to understand and quantify uncertainties in modeling and designing next-generation plasma accelerators. To do so, we perform two-dimensional high-resolution MHD simulations using an argon-filled capillary discharge waveguide with three different electron transport coefficients models. The models tested include (i) Davies et al., (ii) Spitzer, and (iii) Epperlein–Haines (EH). We found that the EH model overestimates the electron temperature inside the channel by over 20% while predicting a lower azimuthal magnetic field. Furthermore, the Spitzer model, often used in MHD simulations for plasma-based accelerators, predicts a significantly higher electron temperature than the other models suggest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

OpenACC Unified Programming Environment for Multi-hybrid Acceleration with GPU and FPGA

Accelerated computing in HPC such as with GPU, plays a central role in HPC nowadays. However, in some complicated applications with partially different performance behavior is hard to solve with a single type of accelerator where GPU is not the perfect solution in these cases. We are developing a framework and transpiler allowing the users to program the codes with a single notation of OpenACC to be compiled for multi-hybrid accelerators, named MHOAT (Multi-Hybrid OpenACC Translator) for HPC applications. MHOAT parses the original code with directives to identify the target accelerating devices, currently supporting NVIDIA GPU and Intel FPGA, dispatching these specific partial codes to background compilers such as NVIDIA HPC SDK for GPU and OpenARC research compiler for FPGA, then assembles binaries for the final object with FPGA bitstream file. In this paper, we present the concept, design, implementation, and performance evaluation of a practical astrophysics simulation code where we successfully enhanced the performance up to 10 times faster than the GPU-only solution.

Boku, Taisuke↗
DOE OSTI2024

Developing And Scaling an OpenFOAM Model to Study Turbulent Flow in a HFIR Coolant Channel

Improving the understanding of how computational fluid dynamics (CFD) direct numerical simulations (DNS) of flows in the High Flux Isotope Reactor (HFIR) perform when run in parallel using the high performance computing (HPC) platform Summit at the Oak Ridge Leadership Computing Facility (OLCF) is of particular importance to boost the computational tools used to support HFIR conversion to low enriched fuel (LEU). Evaluation of scaling performance was driven by the increasing importance of graphics processing unit (GPU) usage in HPC, which is becoming the standard for modern supercomputers such as Summit. The desired results are to obtain a strong positive correlation between the computational resources dedicated to a problem and the relative speed-up of the simulation in comparison to a benchmark. This capability will allow substantially improvement in HFIR flow analytical capabilities, specifically when predicting turbulence properties at high Reynolds numbers. The study leverages previous simulation results performed with code PHASTA (finite element) on HPC platforms Cori (NERSC) and Theta (ALCF) [1] with computing options provided in the computing platform OpenFOAM (finite volume) at OLCF. Transitioning from PHASTA to OpenFOAM will (1) eliminate dependence on third-party software for mesh generation and manipulation, (2) reduce resource needs by employing modern architectures, and (3) build expertise for future modeling of HFIR-specific problems like heat transfer in involute geometry, entrance effects, flow structure in channel corners, and so on—all important issues when defining the available thermal margins in the transition to LEU. CPUs and GPUs differ significantly in their architecture and utilization, as discussed in the literature [2]. The most important differences are in the approach to computations and their memory. A single GPU contains a large quantity of cores, enabling it to perform with a much higher throughput than a CPU, but execution requires a different approach. GPU codes execute instructions using the Single-Instruction Multiple-Thread (SIMT) approach in which a single instruction is used for groups of threads called warps. A warp typically consists of 32 threads which must execute the same set of instructions, although on separate threads. Alternately, a CPU has far fewer cores that are much more flexible in their operation, excelling at quickly performing more complex serial computations. This is why GPUs have greater throughput when properly utilized. The second important difference is seen when comparing their memory spaces. Limited memory allocations and CPU–GPU communications cause a significant bottleneck in GPU-accelerated programs. Further study was required to properly take advantage of GPU resources. A comprehensive analysis of code performance and the model-specific features of turbulence constitutes the core of this work. In this study, a DNS simulation of HFIR channel turbulence was performed with the finite volume CFD code OpenFOAM v2112 and CUDA v11.0 on Red Hat Enterprise Linux v8.2. The OpenFOAM installation had AMGx integrated to enable GPU acceleration and utilizes the PETSc4FOAM library. The computational resources and the problem size were scaled on CPU and CPU + GPU architectures to gain a better understanding of the performance of a DNS problem on modern computing hardware. The study aimed to analyze the scaling of the code exclusively on CPUs and then to examine the scaling of the codes with GPU acceleration enabled. Scaling studies included CPU and GPU acceleration on a mesh of varying resolution to analyze the impact of problem size relative to computational resources. In the course of preparing the GPU configuration on Summit, mainly using the AMGX solvers, difficulties were encountered stemming from constant changes resulting from extensive ongoing development activities and the changing environment. This resulted in the inability to complete the GPU portion of the work. The code was compiled and tested, but production runs to assess acceleration were not performed because the used discretional compute time allocation expired as year-end approached. The Summit HPC platform is scheduled for decommissioning in 2024, making it unattractive for future use with Nvidia-based GPUs. Therefore, the work will be moved onto NERSC machines in FY24. An application was prepared and submitted, and sufficient node-hours were awarded to continue the research in the next calendar year. This report summarizes work performed thus far, which mostly focused on CPU OpenFOAM computing.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A differentiable simulation package for performing inference of synchrotron-radiation-based diagnostics

The direction of particle accelerator development is ever-increasing beam quality, currents and repetition rates. This poses a challenge to traditional diagnostics that directly intercept the beam due to the mutual destruction of both the beam and the diagnostic. An alternative approach is to infer beam parameters non-invasively from the synchrotron radiation emitted in bending magnets. However, inferring the beam distribution from a measured radiation pattern is a complex and computationally expensive task. To address this challenge we present SYRIPY ( SYnchrotron Radiation In PYthon ), a software package intended as a tool for performing inference of synchrotron-radiation-based diagnostics. SYRIPY has been developed using PyTorch , which makes it both differentiable and able to leverage the high performance of GPUs, two vital characteristics for performing statistical inference. The package consists of three modules: a particle tracker, Lienard–Wiechert solver and Fourier optics propagator, allowing start-to-end simulation of synchrotron radiation detection to be carried out. SYRIPY has been benchmarked against SRW , the prevalent numerical package in the field, showing good agreement and up to a 50× speed improvement. Finally, we have demonstrated how SYRIPY can be used to perform Bayesian inference of beam parameters using stochastic variational inference.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Counting Calories: Light Yield Studies with ADRIANO2 Calorimeter Prototype

Precision in measuring particle energies is crucial to understand the intricacies of high-energy physics beyond the standard model. For the REDTOP experiment to detect η/η´ mesons potentially decaying into dark-matter particles not yetdiscovered, it is essential to have accurate measurements through sophisticated and innovative detector technology built with special properties. The ADRIANO2 (A Dual Readout Integrally Active Non-segmented Option) Calorimeter Prototype plays a pivotal role in advancing detection capabilities, offering the potential to enhance the particle identification procedure. This study delves into the characterization of the ADRIANO2 prototype’s light yield with the ultimate goal of contributing to broader high-energy physics objectives. To estimate the light yield for the ADRIANO2 prototype, we must calibrate the light sensors as well as collect data from beams of known properties. Several prototypes of the ADRIANO2 detector have been tested at the Mtest Facility at Fermi National Accelerator Laboratory in the last few years. This paper attempts to summarize the calibration of one such ADRIANO2 prototype to estimate its experimental performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Challenges and Lessons Learned from fabrication, testing and analysis of eight MQXFA Low Beta Quadrupole magnets for HL-LHC

By the end of October 2022, the US HL-LHC Accelerator Upgrade Project (AUP) had completed fabrication of ten MQXFA magnets and tested eight of them. The MQXFA magnets are the low beta quadrupole magnets to be used in the Q1 and Q3 Inner Triplet elements of the High Luminosity LHC. This AUP effort is shared by BNL, Fermilab, and LBNL, with strand verification tests at NHMFL. An important step of the AUP QA plan is the testing of MQXFA magnets in a vertical cryostat at BNL. The acceptance criteria that could be tested at BNL were all met by the first four production magnets (MQXFA03-MQXFA06). Subsequently, two magnets (MQXFA07 and MQXFA08) did not meet some criteria and were disassembled. Lessons learned during the disassembly of MQXFA07 caused a revision to the assembly specifications that were used for MQXFA10 and subsequent magnets. In this paper, we present a summary of: 1) the fabrication and test data of all the MQXFA magnets; 2) the analysis of MQXFA07/A08 test results with characterization of the limiting mechanism; 3) the outcome of the investigation, including the lessons learned during MQXFA07 disassembly; and 4) the finite element analysis correlating observations with test performance.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

The heterogeneous nature of mechanically accelerated grain growth

Abstract While grain growth is traditionally viewed as a purely thermally driven process, nanocrystalline metals can undergo grain growth under mechanical loads, even at room temperature. We performed a detailed atomistic study of the heterogeneous nature of mechanically accelerated grain growth in a polycrystalline Pt nanowire. Using molecular dynamics simulations, we compared the grain-growth behavior of individual grains during tensile and shear cyclic loading, for three different equivalent strain levels, and at two temperatures. Pure thermal grain growth with no mechanical loading provided a baseline reference case. On average, grains that were already susceptible to thermal grain growth were stimulated to grow faster with mechanical loading, as expected. However, when analyzed on a grain-by-grain basis, the results were far more complex: grains that grew fastest under one stimuli were less accelerated under other stimuli. Even when the magnitude of loading changed, the relative growth of individual grains was distorted. We interpret this complexity from the perspective of superimposed growth mechanisms.

Chen, Elton Y.↗
DOE OSTI2022

Influence of point defect accumulation on in-pile thermal conductivity degradation: Fuel rod defect distribution and deviation between in-pile and post irradiation thermal conductivity

As nuclear fuel burn-up increases, its thermal conductivity degrades due to the accumulation of defects that lead to increased phonon scattering rates. This results in a rise in the centerline temperature of the fuel rod, whereby heat generation must be decreased to avoid undesired behavior such as fuel melting and extensive fission gas release. Fuel performance codes are utilized to optimize the fuel's operational conditions; while they are based on established physical principles, their empirical nature limits their predictive capabilities. Recently, an effort has been made to develop predictive fuel performance codes for commonly used nuclear fuels, as well as accelerated qualification of advanced nuclear fuels. In this report, we elaborate on the importance of careful analysis of point defects’ impact on thermal conductivity in fuel performance analysis. Further, a model is presented where point defect concentration is estimated based on Rate Theory modeling and used as input to the Klemens-Callaway model to calculate their contribution to the degradation of thermal conductivity in UO 2 under prototypical irradiation conditions. This analysis suggests that point defect concentration is significant at the rim of the fuel pellet and neglecting this leads to underestimation of the centerline temperature, which may have consequences on fission gas behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

GPU-accelerated multitiered iterative phasing algorithm for fluctuation X-ray scattering

The multitiered iterative phasing (MTIP) algorithm is used to determine the biological structures of macromolecules from fluctuation scattering data. It is an iterative algorithm that reconstructs the electron density of the sample by matching the computed fluctuation X-ray scattering data to the external observations, and by simultaneously enforcing constraints in real and Fourier space. This paper presents the first ever MTIP algorithm acceleration efforts on contemporary graphics processing units (GPUs). The Compute Unified Device Architecture (CUDA) programming model is used to accelerate the MTIP algorithm on NVIDIA GPUs. The computational performance of the CUDA-based MTIP algorithm implementation outperforms the CPU-based version by an order of magnitude. Furthermore, the Heterogeneous-Compute Interface for Portability (HIP) runtime APIs are used to demonstrate portability by accelerating the MTIP algorithm across NVIDIA and AMD GPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Accelerating high-order continuum kinetic plasma simulations using multiple GPUs

Kinetic plasma simulations solve the Vlasov-Poisson or Vlasov-Maxwell equations to evolve scalar-variable distribution functions in position-velocity phase space and vector-variable electromagnetic fields in configuration space. The immense computational cost of evolving high-dimensional variables, and their large number of degrees of freedom, often limits the utility of continuum kinetic simulations and presents a challenge when it comes to accurately simulating real-world physical phenomena. To address this challenge, we present techniques that accelerate and minimize the computational work required for a scalable Vlasov-Poisson solver. We show theoretical hardware compute and communication bounds for solving a fourth-order finite-volume Vlasov-Poisson system. These bounds are then used to inform and evaluate the design of performance portable algorithms for a multiple graphics processing unit (GPU) accelerated version of the Vlasov-Poisson solver VCK-CPU [1]. We demonstrate that the multi-GPU Vlasov solver implementation, VCK-GPU, simultaneously minimizes required inter-process data transfer while also being bounded by the machine network performance limits. This results in an overall strong scaling speedup per timestep of up to 40x in three-dimensional phase space (one position, two velocity coordinates) and 54x in four dimensional phase space (two position, two velocity coordinates) and a 341x increase in simulation throughput of the GPU accelerated code over the existing CPU code. The GPU code is also able to weak scale up to 256 compute nodes and 1024 GPUs. In conclusion, we demonstrate that the improved compute performance enables exploring configurations which were previously computationally infeasible, including resolving fine-scale distribution function filamentation and multi-species dynamics with realistic electron-proton mass ratios.

Continuum kinetics↗
DOE OSTI2025

Long-term thermal aging behavior and strength reduction in a laser powder bed fusion 316H stainless steel

The long-term thermal stability of structural alloys is essential for ensuring the safe and reliable operation of nuclear reactors and other power plants. While extensive research has explored the effects of thermal aging on conventional stainless steels, the behavior of additively manufactured (AM) alloys remains less understood. This study examines the thermal aging response of laser powder bed fusion (LPBF) 316H stainless steel (SS) at temperatures ranging from 550 °C to 750 °C over durations of up to 10,000 h (approximately 1.14 years). Advanced characterization techniques, including electron microscopy and synchrotron X-ray diffraction, were used to investigate dislocation recovery and phase evolution. Based on these findings, a time-temperature-precipitation (TTP) diagram was developed for LPBF 316H SS, revealing a 10- to100-fold acceleration in precipitation kinetics compared to wrought 316H SS. A physics-informed model was calibrated using the short-term experimental data, enabling predictions of average precipitate sizes, volume fractions of M 23 C 6 and Laves phases, and changes in molybdenum solute concentration for aging up to 1 × 10⁶ h (114 years). These microstructural insights were further utilized to estimate yield strength and extrapolate strength reduction factors over the extended aging period. Despite the accelerated aging kinetics, LPBF 316H SS demonstrated superior yield strength retention compared to its wrought counterpart. In conclusion, this study establishes a framework for evaluating long-term performance using short-term experimental data and supports the accelerated qualification of AM materials for high-temperature structural applications.

Laser powder bed fusion↗