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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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NASA Earth Exchange – Current overview of climate and wildfire-oriented works

NASA Earth Exchange (NEX) combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing petabyte-scale datasets covering large regions, continents, or the globe. As an accessible platform, NEX can accelerate fundamental research, develop new applications, and reduce overall project costs by providing the research community with data, software, and high-end computing power. Two research thrusts for the NEX community are developing and distributing the NEX-GDDP-CMIP6 downscaled climate dataset and the community-driven wildfire research. NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The wildfire research thrust leverages geostationary and low earth orbit remote sensing platforms and advanced modeling (WRF). We present a high-level overview of the NEX community, discuss relevant datasets and show several visualization techniques of data used in the wildfire research activity.

NEX↗
DOE OSTI2015

Plasma driven neutron/gamma generator

An apparatus for the generation of neutron/gamma rays is described including a chamber which defines an ion source, said apparatus including an RF antenna positioned outside of or within the chamber. Positioned within the chamber is a target material. One or more sets of confining magnets are also provided to create a cross B magnetic field directly above the target. To generate neutrons/gamma rays, the appropriate source gas is first introduced into the chamber, the RF antenna energized and a plasma formed. A series of high voltage pulses are then applied to the target. A plasma sheath, which serves as an accelerating gap, is formed upon application of the high voltage pulse to the target. Depending upon the selected combination of source gas and target material, either neutrons or gamma rays are generated, which may be used for cargo inspection, and the like.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Experimental Demonstration of the Henon-Heiles Quasi-Integrable System at IOTA

IOTA is a research electron and proton storage ring recently commissioned at Fermilab to test novel techniques for improving bea m stability and quality, notably the concept of non -linear integrable optics . We present the first results of experimental investigation of a quasi -integrable system with one invariant of motion, a Henon Henon-Heiles type system implemented with octupole magnets . Good agreement with simulations is demonstrated on key parameters of achievable tune spread and dynamic aperture preservation . Resilience to perturbations and imperfections in the lattice is shown. We also outline research plans and discuss applicability to future high intensity accelerators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Autonomous Coupler Alignment Using Position-Based Visual Servoing in a ROS 2 Framework

As robotic arms are becoming increasingly common alongside humans as collaborative robots, their high precision in motion enables tasks to be performed at significantly higher speeds with reduced disruption in the environment. The Fermi National Accelerator Laboratory is exploring this application by incorporating a UR16e from Universal Robots in a cleanroom setting during assembly of couplers to superconducting radio frequency cavities as part of the PIP-II project. The goal of the robotic assembly process is to precisely position the UR16e robot so that the coupler flange, mounted on the robot’s end-effector, is accurately aligned with and pressed against the cavity flange, requiring only final fastening by a lab technician. This thesis builds upon an initial system in which the robotic process was limited to the alignment phase using position-based visual servoing with an eye-in-hand camera to only align the coupler to the cavity with an offset distance. The objective of this thesis is to further advance autonomous robotic assembly by extending the process. To this end, the entire software framework was reconstructed, as the previous development environment posed significant challenges in modifying the software and adapting to hardware changes. The main contributions of this thesis are as follows: (i) a modular and scalable software framework based on ROS~2 was developed to facilitate performance expansion and interchangeability of software and hardware components; (ii) the desired alignment position for position-based visual servoing was parameterized to enable flexible configuration; and (iii) a methodology was developed to close the offset distance between the coupler and cavity utilizing the internal force-torque sensing capability of the UR16e, as visual feedback is not available during the offset-closing phase. The proposed autonomous robotic assembly reduces assembly time and technician involvement, thereby minimizing the risk of airborne particulate contamination, which is essential in the cleanroom setting. Moreover, the ROS~2-based framework provides a foundation for further expansion and continued advancement of robotic automation in Fermilab.

Giffen, Nickolas [Northern Illinois U.]↗
DOE OSTI2022

Data-driven linear time advance operators for the acceleration of plasma physics simulation

In this study, we demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Pulsed-focusing recirculating linacs for muon acceleration

Since the muon has a short lifetime, fast acceleration is essential for high-energy applications such as muon colliders, Higgs factories, or neutrino factories. The best one can do is to make a linear accelerator with the highest possible accelerating gradient to make the accelerating time as short as possible. However, the cost of such a single linear accelerator is prohibitively large due to expensive power sources, cavities, tunnels, and related infrastructure. As was demonstrated in the Thomas Jefferson Accelerator Facility (Jefferson Lab) Continuous Electron Beam Accelerator Facility (CEBAF), an elegant solution to reduce cost is to use magnetic return arcs to recirculate the beam through the accelerating RF cavities many times, where they gain energy on each pass. In such a Recirculating Linear Accelerator (RLA), the magnetic focusing strength diminishes as the beam energy increases in a conventional linac that has constant strength quadrupoles. After some number of passes the focusing strength is insufficient to keep the beam from going unstable and being lost. In this project, the use of fast pulsed quadrupoles in the linac sections was considered for stronger focusing as a function of time to allow more successive passes of a muon beam in a recirculating linear accelerator. In one simulation, it was shown that the number of passes could be increased from 8 to 12 using pulsed magnet designs that have been developed and tested. This could reduce the cost of linac sections of a muon RLA by 8/12, where more improvement is still possible. The expense of a greater number of passes and corresponding number of return arcs was also addressed in this project by exploring the use of ramped or FFAG-style magnets in the return arcs. A better solution, invented in this project, is to use combined-function dipole-quadrupole magnets to simultaneously transport two beams of different energies through one magnet string to reduce costs of return arcs by almost a factor of two. A patent application was filed for this invention and a detailed report published in Physical Review Special Topics. A scaled model using an electron beam was developed and proposed to test the concept of a dog bone RLA with combined-function return arcs. The efforts supported by this grant were reported in a series of contributions to particle accelerator conferences that are reproduced in the appendices and summarized in the body of this report.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Performance tuning of CEED software and 1st and 2nd wave apps

The goal of this milestone was the performance tuning of the CEED software, as well as the use and tuning of CEED to accelerate the first and second wave of targeted ECP applications. In this milestone, the CEED team developed optimization techniques and tuned for performance the CEED software to accelerate the first and second wave target ECP applications. Specifically, the focus was on the following: (1) Efficient use of the memory sub-system for managing data motion and interactions among different physics packages and libraries; this included integration of the new developments in a libCEED 0.5 software release; (2) Enhancing the CEED libraries with GPU and AMD GPU support in close interaction with vendors; (3) Optimal data locality and motion, and enhanced scalability and parallelism; this included vendors interactions for improvements in data motion and making strong scaling easier and more efficient; and (4) Continue boosting performance for the first-wave and second-wave of ECP target applications, including ExaSMR, ExaWind, Urban, MARBL, E3SM, and ExaAM. A main part of this milestone was the performance tuning of the CEED first-wave and second-wave ECP applications. This included the ExaSMR application – Coupled Monte Carlo Neutronics and Fluid Flow Simulation of Small Modular Reactors (ORNL), the MARBL application – Next-Gen Multi-physics Simulation Code (LLNL), and the ExaAM ExaConstit – a miniapp for the Transforming Additive Manufacturing through Exascale Simulation applications project (ExaAM), as well as ExaWind, Urban, and E3SM. The artifacts delivered include performance improvements in CEED’s 1st and 2nd wave of applications, and tuned CEED software for various architectures through a number of backends, freely available in the CEED’s repository on GitHub. See the CEED website, http://ceed.exascaleproject.org and the CEED GitHub organization, http://github.com/ceed for more details. In addition to details and results from the above R&D efforts, in this document we are also reporting on other project-wide activities performed in Q4 of FY19 including: CEED’s third annual meeting, MFEM GPU kernels scaling improvements, libCEED 0.5 and NekRS releases, an overview paper covering latest results on a set of bake-off high-order finite element problems (BPs), and other outreach efforts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Rotating wind solution and the acceleration of the cosmic radio jets

A wind-type solution is obtained in an axisymmetric spacetime in the case when matter has angular momentum. An application of the solution in understanding the acceleration of matter in radio jets as it flows along the funnel of a thick accretion disk is suggested. It is observed that the location of the critical point depends strongly upon the angular momentum of the wind. Apart from the usual acceleration of matter due to the expansion of the flow tube, the energy due to the rotational motion is found to contribute to the poloidal motion, hence enhancing the flow speed.

Chakrabarti, S. K.↗
NASA NTRS1959

Human Tolerance to Rapidly Applied Accelerations: A Summary of the Literature

The literature is surveyed to determine human tolerance to rapidly applied accelerations. Pertinent human and animal experiments applicable to space flight and to crash impact forces are analyzed and discussed. These data are compared and presented on the basis of a trapezoidal pulse. The effects of body restraint and of acceleration direction, onset rate, and plateau duration on the maximum tolerable and survivable rapidly applied accelerations are shown. Results of the survey indicate that adequate torso and extremity restraint is the primary variable in tolerance to rapidly applied accelerations. The harness, or restraint system, must be arranged to transmit the major portion of the accelerating force directly to the pelvic structure and not via the vertebral column. When the conditions of adequate restraint have been met, then the other variables, direction, magnitude, and onset rate of rapidly applied accelerations, govern maximum tolerance and injury limits. The results also indicate that adequately stressed aft-faced passenger seats offer maximum complete body support with minimum objectionable harnessing. Such a seat, whether designed for 20-, 30-, or 40-G dynamic loading, would include lap strap, chest (axillary) strap, and winged-back seat to increase headward and lateral G protection, full-height integral head rest, arm rests (load-bearing) with recessed hand-holds and provisions to prevent arms from slipping either laterally or beyond the seat back, and leg support to keep the legs from being wedged under the seat. For crew members and others whose duties require forward-facing seats, maximum complete body support requires lap, shoulder, and thigh straps, lap-belt tie-down strap, and full-height seat back with integral head support.

Eiband, A. Martin↗
DOE OSTI2021

Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs

Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.

Thavappiragasam, Mathialakan↗
DOE OSTI2020

Computational Methods to Accelerate Development of Corrosion Resistant Coatings for Industrial Gas Turbines

Oxidation resistant overlay coatings protect the underlying superalloy component in industrial gas turbines from oxidation attack. Rate of depletion of the Al-rich β-phase in the bond coat governs the lifetime of these coatings. The applicability of a computational method in accelerating the development of corrosion resistant coatings and significantly reducing the extensive experimental effort to predict coating lifetimes and microstructural changes in three-coated Ni-based superalloys for real operational durations (20–40 kh) was undertaken in the present study. Scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and electron microprobe analysis (EPMA) were employed to characterize MCrAlY-coated superalloy substrates (1483, 247 and X4) after exposure at 900 °C in air + 10% H 2 O for up to 20,000 h. The model predicted the longest coating lifetime for the coating on X4 substrate. Precipitation of γ' in the coatings was correctly predicted for all three coating systems. Additionally, the model was able to predict the formation of topologically close packed (TCP)-phases in the investigated coating systems.

Pillai, Rishi R.↗
DOE OSTI2025

Analytical and numerical studies of dark current in radiofrequency structures for short-pulse high-gradient acceleration

High-gradient acceleration is a key research area that could enable compact linear accelerators for future colliders, light sources, and other applications. In the pursuit of high-gradient operation, rf breakdown limits the attainable accelerating gradient in normal-conducting rf structures. Recent experiments at the Argonne Wakefield Accelerator suggest a promising approach: using short rf pulses with durations of a few nanoseconds. Experimental studies show that these 𝒪⁡(1⁢ ⁢ns) rf pulses can mitigate breakdown limitations, resulting in higher gradients. For example, an electric field of nearly 400 MV/m was achieved in an 𝑋-band photoemission gun driven by 6-ns-long rf pulses, with rapid rf conditioning and low dark current observed. Despite these promising results, the short-pulse regime remains an underexplored parameter space, and rf breakdown physics under nanosecond-long pulses requires further investigation. In this paper, we present analytical and numerical simulations of dark current dynamics in accelerating cavities operating in the short-pulse regime. We study breakdown-associated processes spanning different time scales, including field emission, multipacting, and plasma formation, using simulations of the 𝑋-band photogun cavities. The results reveal the advantages of using short rf pulses to reduce dark current and mitigate rf breakdown, offering a path toward a new class of compact accelerators with enhanced performance and reduced susceptibility to breakdown.

Linear accelerators↗
DOE OSTI2014

Applying Nonlinear Diffusion Acceleration to Fixed-Source Problems with Anisotropic Scattering - Paper 15

Work over the last several years has demonstrated the impressive performance gains that can be attained by using Moment-Based Acceleration (MBA), or High-Order/Low-Order (HOLO), methods in a variety of transport applications. In the field of neutronics, Nonlinear Diffusion Acceleration (NDA) has been used to accelerate the solution to the fixed-source problem and the k-eigenvalue problem. These methods efficiently move a major portion of the computational work out of the full phase-space (high-order (HO)) domain into a reduced phase-space (low-order (LO)) setting. In previous implementations, NDA has only been applied to isotropic scattering problems. In this paper, we will extend this methodology to anisotropic scattering. This initial work on anisotropic scattering will focus on the 1-D multi-group neutron transport equation. This summary focuses on a fixed-source problem, but the extension to criticality problems is straight-forward via NDA-NCA. Within this paper, we have described a method for extending Nonlinear Diffusion Acceleration to solve problems with anisotropic scattering. We demonstrated that a consistent low-order system, resembling the low-order system from, could be constructed. We demonstrated that the NDA method performed exceptionally in the presence of anisotropic scattering. NDA reduced the number of iterations required to meet the convergence tolerance by a factor of 500 over source iteration for a one fixed-source problem and by 3.5-50 x for the Henyey-Greenstein problems. This method is equally well-suited for eigenvalue problems. The NDA method allows us to transition the eigenvalue iteration to the low-order domain.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗