Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Accelerator Applications”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Real-Time Anomaly Detection for Charge-Based Triggering in LArTPCs

Modern particle detectors, including liquid argon time projection chambers (LArTPCs), collect a vast amount of data, making it impractical to save everything for offline analysis. As a result, these experiments need to employ different down-selection techniques during data acquisition, referred to as triggering. In this talk, I will present a framework that would enable real-time, data-driven triggering for LArTPCs, using anomaly detection algorithms implemented on Field-Programmable Gate Arrays (FPGAs). Drawing on a study that makes use of collected charge data from the MicroBooNE LArTPC Public Dataset, I will discuss the overall performance of such algorithms and potential applications for future neutrino experiments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Improving galaxy cluster selection with the outskirt stellar mass of galaxies

The number density and redshift evolution of optically selected galaxy clusters offer an independent measurement of the amplitude of matter fluctuations, 𝑆 8 . However, recent results have shown that clusters chosen by the redMaPPer algorithm show richness-dependent biases that affect the weak lensing signals and number densities of clusters, increasing uncertainty in the cluster mass calibration and reducing their constraining power. Here, in this work, we evaluate an alternative cluster proxy, outskirt stellar mass, 𝑀 out , defined as the total stellar mass within a [50, 100] kpc envelope centered on a massive galaxy. This proxy exhibits scatter comparable to redMaPPer richness, 𝜆, but is less likely to be subject to projection effects. We compare the Dark Energy Survey Year 3 redMaPPer cluster catalog with a 𝑀 out selected cluster sample from the Hyper-Suprime Camera survey. We use weak lensing measurements to quantify and compare the scatter of 𝑀 out and 𝜆 with halo mass. Our results show 𝑀 out has a scatter consistent with 𝜆, with a similar halo mass dependence, and that both proxies contain unique information about the underlying halo mass. We find 𝜆-selected samples introduce features into the measured Δ⁢Σ signal that are not well fit by a log-normal scatter only model, absent in 𝑀 out selected samples. Our findings suggest that 𝑀 out offers an alternative for cluster selection with more easily calibrated selection biases, at least at the generally lower richnesses probed here. Combining both proxies may yield a mass proxy with a lower scatter and more tractable selection biases, enabling the use of lower mass clusters in cosmology. Finally, we find the scatter and slope in the 𝜆 −𝑀 out scaling relation to be 0.49 ±0.02 and 0.38 ±0.09.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Structurally flexible cloud microphysics, observationally constrained at all scales via ML-accelerated Bayesian inference

We discuss the challenge of developing observationally informed parameterizations of microphysics for use at a hierarchy of modeling scales. Our proposed approach is applicable to any domain that suffers from a two-fold parameterization problem, where physical processes are not resolved at the model scale (the first problem), and those processes are uncertain at any scale (the second problem). For such problems, a physical approach facilitates modeling across scales, as well as systematic observational inference accelerated by machine learning (ML) surrogate models, and quantification of physical uncertainties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

PERLE: A novel facility for ERL development and applications in multi-turn configuration and high-power regime

The development of ERLs has been recognized as one of the five main pillars of accelerators R&D in support of the European Strategy for Particle Physics (ESPP). The international panel in charge of the ERL Roadmap definition recognized PERLE project as “a central part of the roadmap for the development of energy-recovery linacs”, with milestones to be achieved by the next ESPP in 2026. PERLE project is aiming at the construction of a novel ERL facility for the development and application of the energy recovery technique in multi-turn configuration, high current and large energy regime. It will operate in a 3-turns mode, first at 250 MeV, then upgraded to 500 MeV with 20mA beam current. Such challenging parameters make PERLE a unique multi-turn ERL facility operating at an unexplored operational power regime (10MW), studying and validating a broad range of accelerator phenomena, paving the way for the future larger scale ERLs. PERLE will be the necessary demonstrator for the future HEP machine (LHeC / FCC-eh), with which it shares the same technological choices and beam parameters. Furthermore, PERLE opens a new frontier for the physics of “the electromagnetic probe”. It will be the first ERL dedicated to Nuclear Physics for studying the eN interaction with radioactive nuclei. Here we will report on the project status, introduce the main ongoing achievements and describe the staged strategy we will adopt toward the construction of PERLE machine at its nominal performances.

Kaabi, Walid↗
DOE OSTI2026

The mechanism of hydroxyapatite coatings degradation at high substrate temperatures

Physical vapor deposition methods used for hydroxyapatite (HA) coatings typically require elevated substrate temperatures and post-deposition annealing to induce crystallization. However, such thermal treatments can degrade both the mechanical integrity and bioactivity of the coating, particularly when substrate temperatures exceed 500 °C. The mechanisms underlying these phenomena remain insufficiently understood. In this study, HA thin films were deposited on silicon and Ti6Al4V substrates using pulsed laser deposition and were systematically characterized to elucidate these mechanisms. XPS and SIMS analyses revealed a temperature-dependent loss of OH − and PO 4 3− groups, an increased Ca/P ratio, and the formation of interfacial oxides, all of which contribute to weakened adhesion. To clarify the temperature-dependent decline in bioactivity, protein adsorption behavior was analyzed using a Kramers-type kinetic framework; the fitted desorption kinetics indicate that coatings deposited near ∼500 °C provide the most stable protein attachment, whereas higher temperatures accelerate desorption due to dehydroxylation and carbonate substitution. Together, these findings provide mechanistic insight into the thermal degradation of HA coatings and offer a framework for optimizing deposition parameters to preserve stoichiometry, adhesion, and bioactivity for long-term biomedical applications.

Kylychbekov, Salizhan [Univ. of Oxford (United Kin↗
DOE OSTI2022

Accelerated Lifetime Test of the SRF Dressed Cavity/Tuner System for LCLS II HE Project

The off-frequency detune method is being considered for application in the LCLS-II-HE superconducting linac to produce multi-energy electron beams for supporting multiple undulator lines simultaneously [1]. Design of the tuner has been changed to deliver roughly 3 times larger frequency tuning range. Working requirements for off-frequency operation (OFO) state that cavities be tuned at least twice a month. This specification requires the in-crease of the tuner longevity by 20 times compared with LCLS-II demands. Accelerated longevity tests of the LCLS-II HE dressed cavity with tuner were conducted at FNAL's HTS. Detail analysis of wearing and impacts on performances of the tuner's piezo and stepper motor actuators will be presented. Additionally, results of longevity testing of the dressed cavity bellow, when cooled down to 2 K and compressed by 2.6 mm for roughly 2000 cycles, will be presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

SYCL for Performance Portability: Application Experience with Coupled Cluster Formalism in Quantum Chemistry on Exascale Systems

The exascale computing has brought unprecedented heterogeneity in node architectures, with systems such as Frontier and Aurora featuring diverse GPU accelerators, network connectivity among others. Ensuring performance portability across these platforms is a key challenge. To address this, we employ the SYCL programming model to develop portable, high-performance quantum chemistry workloads. As a representative application, we focus on the non-iterative Triples component of the coupled-cluster CCSD(T) method, a key driver in quantum chemistry. In this work, we report on our experience deploying SYCL-based implementations using both DPC++ and AdaptiveCPP across two flagship exascale platforms: OLCF Frontier with AMD MI250X GPUs and ALCF Aurora with Intel GPUs. Our results demonstrate that SYCL enables efficient, single-source implementations that scale to thousands of nodes, delivering performance on par with vendor-optimized HIP solutions. We highlight key insights into runtime behavior, kernel portability, and scaling characteristics, showing that SYCL offers a viable path for performance-portable computing.

Bagusetty, Abhishek [Argonne National Laboratory (↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗
DOE OSTI2026

Design of a 915 MHz conduction-cooled cryomodule

High-power, compact, continuous-wave (CW) linear electron accelerators with beam energies of up to 10 MeV are being considered for possible industrial applications. Conduction-cooled, superconducting radio-frequency (SRF) technology allows operating such machines at high electrical efficiency, thereby reducing the operating cost significantly. A prototype conduction-cooled SRF cryomodule has been designed and components are currently being manufactured. The cryomodule features a two-cell, 915 MHz SRF cavity, two cryocoolers, a fundamental power coupler, two magnetic shields, a thermal shield and warm-to-cold transitions. The cryomodule has been designed to be able to provide an energy gain of 3.5 MeV to a CW electron beam with a current of 5 mA. This contribution focusses on thermal and mechanical design aspects of the cryomodule.

Ciovati, G. [Old Dominion Univ., Norfolk, VA (Unit↗
DOE OSTI2025

Design of a 915 MHz conduction-cooled cryomodule

High-power, compact, continuous-wave (CW) linear electron accelerators with beam energies of up to 10 MeV are being considered for possible industrial applications. Conduction-cooled, superconducting radio-frequency (SRF) technology allows operating such machines at high electrical efficiency, thereby reducing the operating cost significantly. A prototype conduction-cooled SRF cryomodule has been designed and components are currently being manufactured. The cryomodule features a two-cell, 915 MHz SRF cavity, two cryocoolers, a fundamental power coupler, two magnetic shields, a thermal shield and warm-to-cold transitions. The cryomodule has been designed to be able to provide an energy gain of 3.5 MeV to a CW electron beam with a current of 5 mA. This contribution focusses on thermal and mechanical design aspects of the cryomodule.

Ciovati, G. [Old Dominion Univ., Norfolk, VA (Unit↗
DOE OSTI2021

RPI LINAC refurbishment and upgrade project

The Electron Linear Accelerator at Rensselaer Polytechnic Institute (RPI) was constructed in the late 1950s and started operation in 1961 [1]. The facility was designed and used primarily for measurements of Nuclear Data (ND) with emphasis on the resonance energy region. As such it was designed to produce short pulses of neutrons (5-5000 ns) and equipped with detection stations at different neutron flight path distances from the source (15 m-250 m). When the LINAC started operation it was one of the most powerful accelerators in the world for high energy-resolution measurements in the resonance region. The original LINAC with some upgrades is still in operation but no longer provides world class capabilities for measurements with short pulses. In 2011 discussions between the RPI ND group, Naval Reactors, and the Nuclear Criticality Safety Program about the future of the LINAC concluded that maintaining the capability to perform world-class nuclear data measurements at RPI was desirable. To that end, it was decided to refurbish the facility and upgrade the accelerator capabilities to enable high accuracy measurement in the resonance region with narrow neutron pulse and high electron beam power. Located at a major US technical university, this project provides a needed US nuclear data capability for both research and education, and also includes external users and industrial applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Democratizing uncertainty quantification

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.

Benchmarks↗
DOE OSTI2025

Pointing stabilization of a 1 Hz high-power laser via machine learning

Abstract High-power lasers are vital for particle acceleration, imaging, fusion and materials processing, requiring precise control and high-energy delivery. Laser plasma accelerators (LPAs) demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders. Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs. We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam. By preemptively adjusting a correction mirror, this approach overcomes traditional feedback limits. Demonstrated on the BELLA petawatt laser operating at the terawatt level (30 mJ amplification), our method achieved root mean square pointing stabilization of 0.34 and 0.59 $\unicode{x3bc} \mathrm{rad}$ in the x and y directions, reducing jitter by 65% and 47%, respectively. This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems, paving the way for full-energy petawatt lasers and transformative advances across science, industry and security.

Amodio, Alessio↗
DOE OSTI2023

Significant reduction in the low-field magnetization of Nb 3 Sn superconducting strands using the internal oxidation APC approach

Nb 3 Sn superconductors are promising for building accelerator magnets for future energy-frontier circular colliders. A critical factor for this application is the low-field persistent-current magnetization because it leads to several critical issues: e.g. low-field instability (including flux jumps), hysteresis loss, and field errors in magnet bores. Suppression of low-field magnetization requires reduction of low-field critical current density (J c ) or effective subelement size (d eff ). However, reduction of deff of state-of-the-art Nb 3 Sn conductors—the restacked-rod-process (RRP ® ) type—below 40–50 μm without a pronounced decrease in high-field J c is difficult. On the other hand, the internal oxidation method which forms artificial pinning centers (APC) in Nb 3 Sn offers an alternative approach to reducing the low-field magnetization. Compared with a conventional Nb 3 Sn conductor whose flux pinning force versus field (F p –B) curve peaks at ~20% of its irreversibility field (B irr ), the F p –B curve peaks of APC conductors shift to higher fields due to the point pinning effect, leading to flattening of the J c –B curves. The goal of this paper is to quantitatively study how much the APC approach can reduce the low-field magnetization. Here we measured the J c –B curves of an RRP ® conductor and two APC conductors (reacted at 700 °C) from zero field to B irr using a high-field vibrating sample magnetometer. Here the results showed that the APC conductors have higher non-Cu J c at high fields (e.g. 32%–41% higher at 16 T) and simultaneously lower non-Cu Jc at low fields (e.g. 28%–34% lower at 1 T) compared with the RRP ® . This effect is due to a competition between their Nb3Sn layer fraction ratios and layer F p ratios. Suppose they reach the same 16 T non-Cu J c , then the 1 T non-Cu J c and magnetization of the APC conductors are only half or even less compared with the RRP ® conductor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Design Considerations for GPU-based Mixed Integer Programming on Parallel Computing Platforms

Mixed Integer Programming (MIP) is a powerful abstraction in combinatorial optimization that finds real-life application across many significant sectors. The recent proliferation of graphical processing unit (GPU)-based accelerated computing architectures in large-scale parallel computing or supercomputing presents new opportunities as well as challenges in the advancement of MIP solver technology to effectively use the new accelerated computing platforms and scale to large parallel systems. Here, we recount the conventional processor-based strategies and focus on configurations where the most promising intersection lies between parallel MIP solver approaches and the specific strengths of accelerated parallel platforms. We note that the best potential lies in solving problems whose individual matrix sizes (of the linear program relaxation) fit entirely within one accelerator's memory and whose branch-and-bound (or branch-and-cut) trees cannot be fully contained within a small number of computational nodes. Additionally, we identify ideal features of computational linear algebra support on GPU accelerators that would help advance this direction of scalable parallel solution of MIP problems on GPU-based accelerated computing architectures.

Perumalla, Kalyan↗
DOE OSTI2026

Goated: goal-oriented tensor decompositions in python

SAND2026-20464O Goated performs goal-oriented tensor decompositions in Python, enabling efficient compression of multi-dimensional simulation data. It extends common tensor decomposition methods by incorporating domain-specific knowledge, such as conservation laws in physics, through a penalty term in the optimization process. This approach improves data compression and modeling accuracy across various applications, including physics simulations, by using specialized algorithms and structure-aware subroutines to accelerate solver performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗