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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Deposit and Evaluate Material Across Extremes of Process Windows

Additive manufacturing (AM) can be a viable pathway to fabricate near-net-shape parts for next generation nuclear reactors. Stainless steel 316H (SS 316H) has been identified as a material of interest in the Advanced Materials and Manufacturing Technologies program to accelerate the use of AM for nuclear energy applications. Heterogeneity in material performance is one of the biggest challenges to qualification of AM SS 316H for in-service applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

DenKv: Addressing Design Trade-offs of Key-value Stores for Scientific Applications

High-performance computing (HPC) facilities have employed flash-based storage tier near to compute nodes to absorb high I/O demand by HPC applications during periodic system-level checkpoints. To accelerate these checkpoints, proxy-based distributed key-value stores (PD-KVS) gained particular attention for their flexibility to support multiple backends and different network configurations. PD-KVS rely internally on monolithic KVS, such as LevelDB or RocksDB, to exploit the KV interface and query support. However, PD-KVS are unaware of the high redundancy factor in checkpoint data, which can be up to GBs to TBs, and therefore, tend to generate high write and space amplification on these storage layers. In this paper, we propose DenKv which is deduplication-extended node-local LSM-tree-based KVS. DenKv employs asynchronous partially inline dedup (APID) and aims to maintain the performance characteristics of LSM-tree-based KVS while reducing the write and space amplification problems. We implemented DenKv atop BlobDB and showed that our proposed solution maintains performance while reducing write amplification up to 2× and space amplification by 4× on average.

Khan, Awais↗
DOE OSTI2023

Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. This suppression is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate exponential acceleration of MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three phenomenological regimes as a function of drive strength. For weak drives, the system exhibits exponentially decaying tunneling rates but robust magnetic order; in the crossover regime at intermediate drive strength, we find polynomial decay of tunnelling alongside vanishing magnetic order; and at very strong drive strengths both the Rabi frequency and time-averaged magnetic order are approximately constant with increasing system size. We support these claims with extensive full wavefunction and tensor network numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers.

Grattan, George↗
DOE OSTI2021

Collaborative Research: Explosive reconnection in relativistic magnetically-dominated plasmas (Final Report)

Magnetic fields can be the dominant component of astrophysical plasmas, so that the magnetic energy density might exceed even the rest-mass energy density of matter. In this extreme (and largely unexplored) regime the magnetic field controls the overall plasma evolution, dissipation, and acceleration of non-thermal particles. This plasma regime, applicable to a variety of astrophysical sources - magnetars, pulsars and pulsar wind nebulae (PWNe), jets of Active Galactic Nuclei (AGNs) and Gamma-Ray Bursters (GRBs) - is dramatically different from laboratory plasmas, the magnetospheres of planets, and the interplanetary plasma. Relativistic astrophysical sources then provide an unique opportunity to study the fundamental plasma physics of magnetically-dominated plasmas; a novel and fast-evolving field of theoretical research which, by investigating energy conversion and particle energization processes in plasmas, is of vital importance to the Fusion Energy Sciences DoE program. Data coming from astrophysical high-energy missions, especially the Crab Nebula flares recently observed by the Fermi and AGILE satellites, suggest that the acceleration of non-thermal particles to the highest energies occurs in magnetic reconnection events - a major change of paradigm in high-energy astrophysics. Most importantly, observations demand that particle acceleration should proceed extremely fast (with accelerating electric field of the order of the magnetic field) and on macroscopic scales (much larger, e.g., than the microscopic plasma skin depth). We are conducting studies of the microphysics of magnetically-dominated plasmas focussing in particular on the highly dynamic regime of explosive reconnection and associated particle acceleration in relativistic plasmas. We are studying the stability and explosive plasma dynamics, particle acceleration and radiation production in a number of idealized plasma configurations that approximate relevant astrophysical sources (like the magnetic ABC structures and interacting flux tubes, as well as generalizations of analytical models of X-point collapse to relativistic plasmas). The well-studied case of the Crab Nebula is taken as a prototypical example for the application of the model. We are combining analytical studies of explosive magnetic dynamics and dissipation in relativistic plasmas with particle-in-cell (PIC) simulations and fluid simulations. The theoretical model, fluid and particle-in-cell simulations are cross-checked for agreement and convergence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Design principles for lifelong learning AI accelerators

Lifelong learning-an agent's ability to learn throughout its lifetime-is a hallmark of biological learning systems and a central challenge for artificial intelligence (AI). The development of lifelong learning algorithms could lead to a range of novel AI applications, but this will also require the development of appropriate hardware accelerators, particularly if the models are to be deployed on edge platforms, which have strict size, weight and power constraints. Here we explore the design of lifelong learning AI accelerators that are intended for deployment in untethered environments. We identify key desirable capabilities for lifelong learning accelerators and highlight metrics to evaluate such accelerators. We then discuss current edge AI accelerators and explore the future design of lifelong learning accelerators, considering the role that different emerging technologies could play. The Perspective explores the future design of lifelong learning artificial intelligence (AI) accelerators that are intended for deployment in untethered environments, identifying key desirable capabilities for such edge AI accelerators and guidance on metrics to evaluate them.

42 ENGINEERING↗
DOE OSTI2024

Robust and optimal alignment of high-dimensional data using maximum likelihood estimation through a random sample consensus framework

Abstract Correcting spatial orientations of groups of high-dimensional data sets such that they are all in a consistent coordinate system is often a time-consuming and error-prone process. Automation of this process can be accomplished by using Generalized Procrustes Analysis to estimate the relative orientations among a population of high-dimensional data sets. A least squares Procrustes solution is applied through a maximum likelihood estimation and random sample consensus framework for robustness. The likelihood model is comprised of a mixture distribution where inliers are modeled using t -distribution and outliers from a uniform distribution. Applications will focus on a synthetic data set that emulates triaxial acceleration data and also real shock data from a population of triaxial accelerometers. Outliers represent either non-rigid body responses, environmental noise, and/or sensor and data acquisition issues. The intended application for the methodology is to robustly automate the rotation of populations of experimentally collected triaxial accelerometer data sets to a single global coordinate system.

LOSAC↗
DOE OSTI2021

Ir-192 radioisotope replacement with a hand-portable 1 MeV Ku-band electron linear accelerator

Although linear accelerators are used in many security, industrial and medical applications, the existing technologies are too large and expensive for several critical applications such as radioactive source replacement, field radiography and mobile cargo scanners. Here, one of the main requirements for these sources is to be highly portable to allow field operation. In response to this problem, RadiaBeam has designed a hand-portable 1 MeV X-ray source, scalable to higher energies, based on Ku-band split electron linac, that can be used for Ir-192 radioisotope replacement. In this paper, we present its multiphysics and engineering design studies, as well as an accelerating structure prototype along with RF measurements.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

ECP SOLLVE: Validation and Verification Testsuite Status Update and Compiler Insight for OpenMP

The OpenMP language continues to evolve with every new specification release, as does the need to validate and verify the new features that have been implemented by the different vendors. With the release of OpenMP 5.0 and OpenMP 5.1, new target offload and host-based features have been introduced to the programming model. While OpenMP continues to grow in maturity, there is an observable growth in the number of compiler and hardware vendors that support OpenMP. In this manuscript, the main focus is on evaluating the conformity and OpenMP implementation progress of various compiler vendors such as Cray, IBM, GNU, Clang/LLVM, NVIDIA, and Intel. More specifically, the 4.5, 5.0, and 5.1 versions of the OpenMP specification are analyzed. For our experimental setup, the Crusher and Summit computing systems hosted by Oak Ridge National Lab’s Computing Facilities are utilized. The effort of vendor agnostic analysis of these implementations is especially valuable for application developers who are using new OpenMP features to accelerate their scientific codes. Insights are presented into the current implementation status of various vendors, the progression of specific compiler’s support for OpenMP overtime, the subset of OpenMP 4.5, 5.0, and 5.1 that is supported by all compilers, and examples of how our test suite has influenced discussion regarding the correct interpretation of the OpenMP specification. By evaluating OpenMP conformity of pre-Exascale computing systems, the aim is to detail progress and status of AMD + Cray ecosystem before the system and their OpenMP implementation is used for mission critical applications when the first Exascale Computer Frontier is made available to applications.

Huber, Thomas↗
DOE OSTI2022

Metall: A persistent memory allocator for data-centric analytics

Data analytics applications transform raw input data into analytics-specific data structures before performing analytics. Unfortunately, such data ingestion steps are often more expensive than analytics. In addition, various types of NVRAM devices are already used in many HPC systems today. Such devices will be useful for storing and reusing data structures beyond a single process life cycle. We developed Metall, a persistent memory allocator built on top of the memory-mapped file mechanism. Metall enables applications to transparently allocate custom C++ data structures into various types of persistent memories. Metall incorporates a concise and high-performance memory management algorithm inspired by Supermalloc and the rich C++ interface developed by Boost.Interprocess library. On a dynamic graph construction workload, Metall achieved up to 11.7x and 48.3x performance improvements over Boost.Interprocess and memkind (PMEM kind), respectively. We also demonstrate Metall’s high adaptability by integrating Metall into a graph processing framework, GraphBLAS Template Library. Here this study’s outcomes indicate that Metall will be a strong tool for accelerating future large-scale data analytics by allowing applications to leverage persistent memory efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Experimental demonstration of externally driven millimeter-wave particle accelerator structure

We report the experimental demonstration of a mm-wave electron accelerating structure powered by a high-power rf source. We demonstrate reliable coupling of an unprecedented rf power—up to 575kW into the mm-wave accelerator structure using a quasi-optical setup. This standing wave accelerating structure consists of a single-cell copper cavity and a Gaussian to TM 01 mode converter. The accelerator structure is powered by 110 GHz, 10-ns long rf pulses. These pulses are chopped from 3 microsecond pulses from a gyrotron oscillator using a laser-driven silicon switch. We show an unprecedented high gradient up to 230MV/m that corresponds to a peak surface electric field of more than 520 MV/m. We have achieved these results after conditioning the cavity with more than 100,000 pulses. We also report preliminary measurements of rf breakdown rates, which are important for understanding rf breakdown physics in the millimeter-wave regime. Furthermore, these results open up many frontiers for applications not only limited to the next generation particle accelerators but also x-ray generation, probing material dynamics, and nonlinear light-matter interactions at mm-wave frequency.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

TeraChem protocol buffers ( TCPB ): Accelerating QM and QM/MM simulations with a client–server model

The routine use of electronic structures in many chemical simulation applications calls for efficient and easy ways to access electronic structure programs. Here, we describe how the graphics processing unit (GPU) accelerated electronic structure program TeraChem can be set up as an electronic structure server, to be easily accessed by third-party client programs. We exploit Google’s protocol buffer framework for data serialization and communication. The client interface, called TeraChem protocol buffers (TCPB), has been designed for ease of use and compatibility with multiple programming languages, such as C++, Fortran, and Python. To demonstrate the ease of coupling third-party programs with electronic structures using TCPB, we have incorporated the TCPB client into Amber for quantum mechanics/molecular mechanics (QM/MM) simulations. The TCPB interface saves time with GPU initialization and I/O operations, achieving a speedup of more than 2× compared to a prior file-based implementation for a QM region with ~250 basis functions. We demonstrate the practical application of TCPB by computing the free energy profile of p-hydroxybenzylidene-2,3-dimethylimidazolinone (p-HBDI - )—a model chromophore in green fluorescent proteins—on the first excited singlet state using Hamiltonian replica exchange for enhanced sampling. All calculations in this work have been performed with the non-commercial freely-available version of TeraChem, which is sufficient for many QM region sizes in common use.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception: Preprint

This paper puts forth a system architecture for an infrastructure-based cooperative perception (CP) fusion engine, to provide a complete state-space digital representation, with measurable accuracy, to support a wide-range of applications. The architecture includes the inputs, functional flow, data standardization recommendations, outputs and supported applications. The CP engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure (IRI), that complements and accelerates connected and automated vehicle (CAV) technology. that the CP acquires and fuses information from sensors (radar, LiDAR, and cameras), and CAVs to intelligently perceive roadway traffic states of all moving objects, create a complete three-dimensional digital representation of that state-space, and communicate it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications for CAVs as examples. The IRI approach, as opposed to a vehicle centric approach, is found to be more scalable in that it can deployed to the roughly 300,000 signalized intersections more readily than the over 300 million vehicles in the US, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and GHG reduction.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Ion Channel Laser Based on Direct Laser Acceleration of a Shaped Beam Driver (Final Technical Report)

The main focus of our research was to understand the synergies between an electron bunch and a laser pulse when the two co-propagate through the plasma. We have clearly demonstrated using theoretical and computational modeling that the propagation distance of both the bunch and the laser pulse could be extended. The ability of the combined bunch/pulse system to extend the propagation distance and the size of the plasma bubble enables highly-efficient sources of relativistic electrons. As pointed out by the Plasma Decadal Study, such electron sources can be used for generating extremely bright x-rays for a variety of applications can serve as probes and diagnostics for other plasma experiments: high energy density (HED) sciences, inertial confinement fusion (ICF), and potentially Fusion Materials and Technology (FM&T). Development of advanced diagnostics of plasma-based accelerators is yet another key area identified by recent reports. Even broader security and medical applications of compact accelerator-based radiation sources, such as very high energy electron (VHEE) sources for FLASH radiobiology, have been identified by a recent multi-agency panel. A number of key technical issues were considered and successfully resolved during the course of the grant. Those include: beam loading effect of both the driver and witness bunches on the wake, laser channeling by the bunch, and the direct laser acceleration (DLA) of the driver bunch by the laser pulse. To demonstrate clear synergy, we were able to ascertain that the total energy gain of a witness bunch in the wake of the combined bunch/laser complex is large than the sum of the energy gains in the wake of the laser pulse alone, and the driver bunch alone. We have also demonstrated that not only the energy gain is improved, but the energy spread is not sacrificed. To carry out these simulations, we have to develop a range of in-house computational tools, including a fully-3D code WAND-PIC.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Particle-in-cell simulation of laser wakefield accelerators with oblique lasers in quasicylindrical geometry

In the studies of optical injections in laser or beam-driven wakefield accelerators, there is a frequent demand for using obliquely propagating assistant lasers in particle-in-cell simulations. In conventional methods, this is only possible in either two- or three-dimensional Cartesian geometries, which have the drawbacks of either lack of fidelity for the actual situation or requiring a huge amount of computational resources. In this work, we develop a new method that uses an expression-defined oblique laser field to simulate such situations in quasicylindrical geometry particle-in-cell simulations, having the advantages of both maintaining good fidelity and saving computational resources. As an example, we use this method in the scissor-cross ionization injection scheme for the optimization of the injected beam quality. This method is widely applicable to particle injections with assistant lasers in wakefield accelerators, as long as the assistant lasers only influence the injected particles during the injection process. Published by the American Physical Society 2025

Ma, Minghao (ORCID:0009000602317775)↗
DOE OSTI2021

Upgrade of the ILC Cryomodule

Results of testing modified components for the cryomodule of the International Linear Collider (ILC) are summarized. To reduce the ILC project cost, it is proposed to replace titanium cryomodule components with stainless steel (SS) ones. New bimetallic transitions (Ti/SS, Nb/SS) have been produced by a unique method based on explosion welding. Successive upgrading of these components to the latest version of the Nb/Ti/SS transition element has led to improvement of the ILC cryomodule. This new component resolves problems of residual stress, and its specific design prevents the possibility of a shift due to the difference in the linear expansion coefficients of the constituent metals. Furthermore, leak tests with the He gas revealed no leaks at the background rate of ≈0.2 × 10$^{–10}$ atm cc/s. The test results are very encouraging. The up-to-date design of trimetallic Nb/Ti/SS element promises technologically simpler and less expensive manufacture. Investigations have shown that explosion welding allows unique trimetallic components to be made not only for cryogenic units of accelerators but also for laboratory equipment and for general engineering applications.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Complex Parsing for In-Network Acceleration of High-Energy Physics Experiments

This paper describes a novel application and evaluation of programmable networking in High-Energy Physics (HEP): a complete parser for the custom packet format used by Fermilab’s DUNE experiment. Notably, this parser is implemented on a Tofino programmable network switch and evaluated on the FABRIC testbed by using network traffic generated by the ICEBERG DUNE prototype. The parsed network traffic consists of Jumbo Ethernet frames that contain digitizations of sensor readings from ICEBERG’s detector.This work is an early investigation into providing in-network processing support for HEP experiments. The paper describes DUNE’s custom packet format, the challenges encountered when implementing a parser for that format, and an exploration of the techniques that are needed to overcome those challenges. We identify performance bottlenecks and discuss directions for future research.

Sagstad, Bjoern [IIT, Chicago] (ORCID:000900033610↗
DOE OSTI2025

Modernizing Accelerator Responsiveness and Controls in Operations

Accelerators increasingly use artificial intelligence (AI) and machine learning (ML) software and workflows for a variety of tasks, from optimization to fault detection and recovery. Efficient and sustainable application of these technologies necessitates specialized and facility-specific infrastructure commitments. Accelerator facilities also introduce unique radiation and security hazards, placing additional demands on operational infrastructure. These needs further escalate the prioritization of effective collaboration models and associated funding mechanisms and legal frameworks.

43 PARTICLE ACCELERATORS↗