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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 1,099 records · Page 61

Integration Testing of a Modular Discharge Supply for NASA's High Voltage Hall Accelerator Thruster

NASA s In-Space Propulsion Technology Program is developing a high performance Hall thruster that can fulfill the needs of future Discovery-class missions. The result of this effort is the High Voltage Hall Accelerator thruster that can operate over a power range from 0.3 to 3.5 kW and a specific impulse from 1,000 to 2,800 sec, and process 300 kg of xenon propellant. Simultaneously, a 4.0 kW discharge power supply comprised of two parallel modules was developed. These power modules use an innovative three-phase resonant topology that can efficiently supply full power to the thruster at an output voltage range of 200 to 700 V at an input voltage range of 80 to 160 V. Efficiencies as high as 95.9 percent were measured during an integration test with the NASA103M.XL thruster. The accuracy of the master/slave current sharing circuit and various thruster ignition techniques were evaluated.

Pinero, Luis R.↗

A critical examination of expansion tunnel performance

An experimental study of the performance of the expansion tunnel for various test gases and range of quiescent acceleration section and nozzle pressure, nozzle geometric area ratio, and nozzle axial station has been performed. Flow diagnostics used to examine expansion tunnel flow characteristics were time histories and profiles of pitot pressure and axial component of flow velocity. The purpose of this study was to determine experimentally what limitations might restrict predicted operational flexibility and the advantages and disadvantages of this mode of operation as compared to the expansion tube. Results are presented which demonstrate the expansion tunnel offers several advantages over the expansion tube, but the severity of the disadvantages of the tunnel makes the expansion tube mode of operation the more desirable for performing hypersonic-hypervelocity aerothermodynamic studies of proposed entry configurations.

Miller, C. G.↗

Beam test results of the Intermediate Silicon Tracker for sPHENIX

The Intermediate Silicon Tracker (INTT), a two-layer barrel silicon strip tracker, is a key component of the tracking system for sPHENIX at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. The INTT is designed to enable the association of reconstructed tracks with individual RHIC bunch crossings. To evaluate the performance of preproduction INTT ladders and the readout chain, a beam test was conducted at the Research Center for Accelerator and Radioisotope Science, Tohoku University, Japan. This paper presents the performance of the INTT evaluated through studies of the signal-to-noise ratio, residual distribution, spatial resolution, hit-detection efficiency, and multiple track reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Unified Computational Model for Solar and Stellar Flares

We present a unified computational framework that can be used to describe impulsive flares on the Sun and on dMe stars. The models assume that the flare impulsive phase is caused by a beam of charged particles that is accelerated in the corona and propagates downward depositing energy and momentum along the way. This rapidly heats the lower stellar atmosphere causing it to explosively expand and dramatically brighten. Our models consist of flux tubes that extend from the sub-photosphere into the corona. We simulate how flare-accelerated charged particles propagate down one-dimensional flux tubes and heat the stellar atmosphere using the Fokker-Planck kinetic theory. Detailed radiative transfer is included so that model predictions can be directly compared with observations. The flux of flare-accelerated particles drives return currents which additionally heat the stellar atmosphere. These effects are also included in our models. We examine the impact of the flare-accelerated particle beams on model solar and dMe stellar atmospheres and perform parameter studies varying the injected particle energy spectra. We find the atmospheric response is strongly dependent on the accelerated particle cutoff energy and spectral index.

radiative transfer↗

ExaSGD: 2022 Kernel Thrust Activities

The Kernel Thrust milestone ADSE22-407 covers the development of device-capable optimization algorithms and solvers technologies required by the ExaSGD project’s software stack in order to solve security-constrained alternating current optimal power flow (SC-ACOPF) problems on emerging exascale architectures. To this extent, in FY22 the main objective of the Kernel Thrust was (i) provide sparse optimization solver that runs efficiently on hardware accelerator devices (i.e., NVIDIA and AMD GPUs) to perform intra-node computations, (ii) strengthen the reliability and increase the performance of the mixed-dense sparse (MDS) solver of HiOp for deployment on the FY22 target architectures, Summit and Crusher, and (iii) increase performance by improving the mathematical algorithm and refining the parallel MPI-based implementation of the coarse-grain parallel solver HiOp-PriDec for capabilities deployment on the FY22 target architectures, Summit and Crusher. This document presents the developments and contributions done by the Kernels Thrust Team in FY22 toward completion of the above-mentioned objectives. These contributions progressed along four main development (sub)thrusts: (1) Design and implementation of a sparse optimization solver for use on hardware accelerators; (2) Improvement of the mathematical algorithm and of the parallel implementation of HiOp-PriDec to ensure readiness and efficient coarse-grain parallelism for FY23 target exascale machine; and (3) Support Software and Application Development Thrusts of the exaSGD project in their deployment of the project’s software stack on AMD- and NVIDIA-based architectures. The development of the sparse optimization solver (thrust 1 above) was new in FY22 and resulted in a new sparse solver in HiOp (available as of version 0.6). The second development thrust was a continuation of the efforts from FY21 and improved the mathematical algorithm and the communication strategy of the HiOp-PriDec solver. The last developement thrust is a large collaborative effort. Namely, the project’s teams from multiple labs (LLNL, PNNL, ORNL, and NREL) performed large-scale demonstration of the ExaSGD software stack, namely the optimization solvers of HiOp interfaced with the modeling front-end ExaGO and the stochastic sampler PowerScenarios. These demonstration efforts solved large-scale instances of the SC-ACOPF challenge problem of medium network sizes (10, 000-bus system) and large number of contingencies on Summit (NVIDIA accelerators) and Crusher (AMD accelerators) systems at ORNL.

97 MATHEMATICS AND COMPUTING↗

Dual Channel Dual Staging: Hierarchical and Portable Staging for GPU-Based In-Situ Workflow

In-situ workflows have emerged as an attractive approach for addressing data movement challenges at very large scales. Since GPU-based architectures dominate the HPC landscapes, porting these in-situ workflows, and, specifically, the inter-application data exchange, to GPU-based systems can be challenging. Technologies such as GPUDirect RDMA (GDR), which is typically used for I/O in GPU applications as an optimization that circumvents the CPU overhead, can be leveraged to support bulk data exchanges between GPU applications. However, current GDR design often lacks performance portability across HPC clusters built with different hardware configurations. Furthermore, the local CPU may also be effectively used as an auxiliary communication mechanism to offload data exchanges. In this paper, we present a dual channel dual staging approach for efficient, scalable, and performance-portable inter-application data exchange for in-situ workflows. This approach exploits the data access pattern within in-situ workflows along with the inherent execution asynchrony to accelerate data exchanges and, at the same time, improve performance portability. Specifically, the dual channel dual staging method leverages both the local CPU and the remote data staging server to build a hierarchical joint staging area and uses this staging area to transform blocking inter-application bulk data exchanges into best-effort local data movements between GPU and CPU. The dual channel dual staging is implemented as a portability extension of the Dataspaces-GPU staging framework. We present an experimental evaluation of its performance, portability, and scalability using this implementation on three leadership GPU clusters. The evaluation results demonstrate that the dual channel dual staging method saves up to 75% in data-exchange time compared to host-based, GDR, and alternate portable designs, while maintaining scalability (up to 512 GPUs) and performance portability across the three platforms.

Zhang, Bo [University of Utah]↗

Machine Learning Thermodynamics And Kinetics of Defects For Accelerated Materials Discovery

Atomistic defects play a pivotal role in functional and structural materials’ performance across a myriad of technology applications. Quantitative prediction of the thermodynamics and kinetics of defect formation and migration, respectively, typically requires accurate but expensive first-principles approaches, such as density functional theory (DFT). Their computational expense limits the throughput needed to perform high-throughput materials discovery/screening exercises or to perform materials modeling tasks relying on extensive sampling techniques. Therefore, in this Sandia National Laboratories Laboratory Directed Research and Development (LDRD) project (Project #229366), we developed a variety of machine learning techniques, trained on density functional theory calculations, to accelerate the discovery and modeling of materials in which vacancy and interstitial defects primarily dictate material performance. These include applications such as metal oxides for water-splitting or mixed ionic-electronic conduction, metal hydrides for hydrogen storage, and transition metal dichalcogenides for electronics, and the approaches developed herein can further be applied to many other domains that similarly depend on materials’ thermodynamic and kinetic defect properties for their desired functionality.

36 MATERIALS SCIENCE↗

Investigation of boosted proton energies through proton radiography of target normal sheath acceleration fields in the multi-ps regime

Multi-kilojoule, multi-picosecond short-pulse lasers, such as the National Ignition Facility-Advanced Radiographic Capability laser and the OMEGA-Extended Performance laser, which have been constructed over the last two decades, enable exciting opportunities to produce high-brightness, high-energy laser-driven proton sources for applications in high-energy-density science like proton fast ignition for inertial fusion energy, particle radiography, and materials science studies. Results on these platforms have demonstrated enhanced accelerated proton energies and electron temperatures when compared to established scaling laws. Recent work has developed a new scaling for proton TNSA in the multi-ps regime. However, this new physics in the multi-ps regime motivates the need to understand the origin of the enhancement in proton energies. Toward this goal, here this work presents the first measurements of the TNSA accelerating sheath field in the multi-ps regime for pulse durations of 0.6, 5, and 10 ps. This measurement was achieved by using a separate TNSA proton source to radiograph the spatiotemporal profile of the accelerating sheath that is responsible for proton acceleration. The use of stacked radiochromic film detectors allows for a discrete time profile of the radiographs, thus enabling the measurement of the temporal and spatial evolution of the accelerating field. In performing this measurement, we extract quantities such as the sheath strength as a function of time and pulse duration, which shows that longer pulse durations sustain a stronger electric field for a longer duration when compared to sub-ps laser pulses, which may enable the observed boosted proton energies and proton conversion efficiencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Grain-boundary structure and segregation in Nb 3 Sn coatings on Nb for high-performance superconducting radiofrequency cavity applications

Here, we report on atomic-scale analyses of grain boundary (GB) structures and segregation in Nb 3 Sn coatings on Nb, prepared by the vapor-diffusion process, for superconducting radiofrequency (SRF) cavity applications, utilizing atom-probe tomography, high-resolution scanning transmission electron-microscopy and first-principles calculations. We demonstrate that the chemical composition of Nb 3 Sn GBs is correlated strongly with the diffusion of Sn and Nb at GBs during the coating process. In a sample coated with a relatively large Sn flux, we observe an interfacial width of Sn segregation at a GB of ~3 nm, with a maximum concentration of ~35 at.%. After post-annealing at 1100 °C for 3 h, the Sn segregated at GBs disappears and Nb segregation is observed subsequently at GBs, indicating that Nb diffused into the Nb3Sn GBs from the Nb substrate. It is also demonstrated that the amount of Sn segregation in a Nb 3 Sn coating can be controlled by: (i) Sn flux; and (ii) the temperatures of the Nb substrates and Sn source, which may affect the overall kinetics including GB diffusion of Sn and Nb. An investigation of the correlation between the chemical compositions of GBs and Nb 3 Sn SRF cavity performance reveals that the Nb 3 Sn SRF cavities with the best performance (high-quality factors at high accelerating electric-field gradients) do not exhibit Sn segregation at GBs. Our results suggest that the chemical compositions of GBs in Nb 3 Sn coatings for SRF cavities can be controlled by GB engineering and can be utilized to optimize fabrication of high-quality Nb 3 Sn coatings for SRF cavities.

36 MATERIALS SCIENCE↗

The detrimental ratio ( ρ ): A critical metric complementing coulombic loss for long calendar-life silicon-based lithium-ion batteries

Silicon (Si) is a promising high-capacity anode in lithium-ion batteries but suffers from chronic chemical degradation and capacity fading during calendar aging, greatly hindering its automobile applications. Electrolyte engineering currently relies on conventional evaluation criteria of reducing coulombic consumption, which implicitly presume its equivalence to irreversible capacity loss and complicates battery development. Here, we introduce the detrimental ratio p to quantify the fraction of parasitic species that permanently degrades active material. This metric is independent and crucially complements total coulombic consumption for accurate performance evaluation. We systematically investigate multiple electrolyte formulations using high-precision leakage current measurements, open-circuit-voltage experiments, and post-mortem characterizations. Although some electrolytes exhibit similarly low coulombic consumption, they diverge significantly incapacity retention and p. Especially, dimethyl-carbonate-based localized-high concentration electrolyte can synergically achieve low coulombic consumption and detrimental ratio p during calendar aging, owing to its chemically inert and structurally resilient solidelectrolyte interface with minimal isolated Si material. By contrast, increasing fluoroethylene carbonate (FEC) additive content suppresses electrolyte breakdown but suffers aggravated chemical degradation of more LixSi isolation for irreversible capacity loss with arising p. This study critically reveals that the chemistry-characteristic detrimental ratio p establishes physically informed performance evaluation to pave the way for accelerating battery development.

Calendar aging↗

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗

Multiscale modeling and cinematic visualization of photosynthetic energy conversion processes from electronic to cell scales

We report conversion of sunlight into chemical energy, namely photosynthesis, is the primary energy source of life on Earth. A visualization depicting this process, based on multiscale computational models from electronic to cell scales, is presented in the form of an excerpt from the fulldome show Birth of Planet Earth. This accessible visual narrative shows a lay audience, including children, how the energy of sunlight is captured, converted, and stored through a chain of proteins to power living cells. The visualization is the result of a multi-year collaboration among biophysicists, visualization scientists, and artists, which, in turn, is based on a decade-long experimental-computational collaboration on structural and functional modeling that produced an atomic detail description of a bacterial bioenergetic organelle, the chromatophore. Software advancements necessitated by this project have led to significant performance and feature advances, including hardware-accelerated cinematic ray tracing and instanced visualizations for efficient cell-scale modeling. The energy conversion steps depicted feature an integration of function from electronic to cell levels, spanning nearly 12 orders of magnitude in time scales. This atomic detail description uniquely enables a modern retelling of one of humanity’s earliest stories—the interplay between light and life.

97 MATHEMATICS AND COMPUTING↗

Unit-cell-thick zeolitic imidazolate framework films for membrane application

Zeolitic imidazolate frameworks (ZIFs) are a subset of metal–organic frameworks with more than 200 characterized crystalline and amorphous networks made of divalent transition metal centres (for example, Zn 2+ and Co 2+ ) linked by imidazolate linkers. ZIF thin films have been intensively pursued, motivated by the desire to prepare membranes for selective gas and liquid separations. To achieve membranes with high throughput, as in ångström-scale biological channels with nanometre-scale path lengths, ZIF films with the minimum possible thickness—down to just one unit cell—are highly desired. However, the state-of-the-art methods yield membranes where ZIF films have thickness exceeding 50 nm. Here we report a crystallization method from ultradilute precursor mixtures, which exploits registry with the underlying crystalline substrate, yielding (within minutes) crystalline ZIF films with thickness down to that of a single structural building unit (2 nm). The film crystallized on graphene has a rigid aperture made of a six-membered zinc imidazolate coordination ring, enabling high-permselective H 2 separation performance. The method reported here will probably accelerate the development of two-dimensional metal–organic framework films for efficient membrane separation.

36 MATERIALS SCIENCE↗

Global tuning of hadronic interaction models with accelerator-based and astroparticle data

In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.

Albrecht, J. [Ruhr U., Bochum, RAPP Ctr.; Ruhr U.,↗

Towards High-Performance AI4NP Applications on Modern GPU Platforms

The evolution of modern heterogeneous accelerators, such as GPUs, has significantly advanced the landscape of artificial intelligence (AI). There is a notable surge to adopt AI within the nuclear physics domain (AI4NP). While most AI4NP studies focus on feasibility analysis, our attention is directed towards evaluating their performance on contemporary GPUs that integrate tensor cores. We first benchmark the throughput of hyperparameterized multi-layer perceptron (MLP) models. We then examine the performance of an AI4NP application: Hydra. We assess the performance gain and accuracy loss caused by the tensor cores for low-precision floating-point operations. Our experiments encompass the PyTorch and TensorFlow Keras frameworks on NVIDIA’s T4 and A100 GPUs. We explore the behavior of different GPU hardware platforms and AI software tools. This study can be a valuable resource for guiding the performance optimization of larger-scale deployments of AI4NP applications.

Mei, Xinxin↗

Low-damage electron beam lithography for nanostructures on Bi 2 Te 3 -class topological insulator thin films

Nanostructured topological insulators (TIs) have the potential to impact a wide array of condensed matter physics topics, ranging from Majorana physics to spintronics. However, the most common TI materials, the Bi 2 Se 3 family, are easily damaged during nanofabrication of devices. In this paper, we show that electron beam lithography performed with a 30 or 50 kV accelerating voltage—common for nanopatterning in academic facilities—damages both nonmagnetic TIs and their magnetically doped counterparts at unacceptable levels. We additionally demonstrate that electron beam lithography with a 10 kV accelerating voltage produces minimal damage detectable through low-temperature electronic transport. In conclusion, although reduced accelerating voltages present challenges in creating fine features, we show that with careful choice of processing parameters, particularly the resist, 100 nm features are reliably achievable.

42 ENGINEERING↗

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Direct integration of atomic precision advanced manufacturing into middle-of-line silicon fabrication

Atomic precision advanced manufacturing (APAM) dopes silicon with enough carriers to change its electronic structure and can be used to create novel devices by defining metallic regions whose boundaries have single-atom abruptness. Incompatibility with the thermal and lithography process requirements for gated silicon transistor manufacturing have inhibited exploration of both how APAM can enhance CMOS performance and how transistor manufacturing steps can accelerate the discovery of new APAM device concepts. In this work, we introduce an APAM process that enables direct integration into the middle of a transistor manufacturing workflow. We show that a process that combines sputtering and annealing with a hardmask preserves a defining characteristic of APAM, a doping density far in excess of the solid solubility limit, while trading another, the atomic precision, for compatibility with manufacturing. The electrical characteristics of a chip combining a transistor with an APAM resistor show that the APAM module has only affected the transistor through the addition of a resistance and not by altering the transistor. This proof-of-concept demonstration also outlines the requirements and limitations of a unified APAM tool, which could be introduced into manufacturing environments, greatly expanding access to this technology and inspiring a new generation of devices with it.

Chemical vapor deposition↗