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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Evaluation of Temporal Diagnostic Techniques for Two-Bunch Facet Beam

Three temporal diagnostic techniques are considered for use in the FACET facility at SLAC, which will incorporate a unique two-bunch beam for plasma wakefield acceleration experiments. The results of these experiments will depend strongly on the the inter-bunch spacing as well as the longitudinal profiles of the two bunches. A reliable, singleshot, high resolution measurement of the beam's temporal profile is necessary to fully quantify the physical mechanisms underlying the beam driven plasma wakefield acceleration. In this study we show that a transverse deflecting cavity is the diagnostic which best meets our criteria. Based on our laboratory testing, numerical calculations, and simulations of the three single-shot temporal diagnostic devices, the X-band TCAV system is the best candidate for resolving FACET's two-bunch beam, with an estimated resolution of 7 {micro}m. Both the S-band TCAV system and the EO system could resolve the peak-to-peak separation of the two bunches in the FACET beam with estimated resolutions of 25 {micro}m and 30 {micro}m, respectively, but would be unable to resolve the temporal profiles of the individual bunches themselves. Because the TCAV signal is more easily interpreted and because the reliability of the EO system is less well known, however, the S-band TCAV system would be the next preferred option after the X-band TCAV system. The Fesca-200 streak camera, though simple, compact, and reliable, is unable to achieve a resolution that would be of use to FACET.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Modern gyrokinetic particle-in-cell simulation of fusion plasmas on top supercomputers

The Gyrokinetic Toroidal Code at Princeton (GTC-P) is a highly scalable and portable particle-in-cell (PIC) code. It solves the 5D Vlasov-Poisson equation featuring efficient utilization of modern parallel computer architectures at the petascale and beyond. Motivated by the goal of developing a modern code capable of dealing with the physics challenge of increasing problem size with sufficient resolution, new thread-level optimizations have been introduced as well as a key additional domain decomposition. GTC-P's multiple levels of parallelism, including inter-node 2D domain decomposition and particle decomposition, as well as intra-node shared memory partition and vectorization have enabled pushing the scalability of the PIC method to extreme computational scales. In this paper, we describe the methods developed to build a highly parallelized PIC code across a broad range of supercomputer designs. This particularly includes implementations on heterogeneous systems using NVIDIA GPU accelerators and Intel Xeon Phi (MIC) co-processors and performance comparisons with state-of-the-art homogeneous HPC systems such as Blue Gene/Q. New discovery science capabilities in the magnetic fusion energy application domain are enabled, including investigations of Ion-Temperature-Gradient (ITG) driven turbulence simulations with unprecedented spatial resolution and long temporal duration. Performance studies with realistic fusion experimental parameters are carried out on multiple supercomputing systems spanning a wide range of cache capacities, cache-sharing configurations, memory bandwidth, interconnects and network topologies. Furthermore, these performance comparisons using a realistic discovery-science-capable domain application code provide valuable insights on optimization techniques across one of the broadest sets of current high-end computing platforms worldwide.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

1972713

Energy-frontier particle accelerators are among the most exciting, complex, challenging, and expensive research instruments performing high precision measurements confirming the fundamentals of the physics and broadening new research horizons. Currently the highest energy machines (under design or commissioned), from multi-GeV to several TeV, (ILC, FCC, CLIC) capable of searching for the most basic building blocks of matter are either driven by circular or linear accelerators [1-6]. Here (see also [7,8]) we suggest a novel design of circular-linear accelerator based on the merging of the weakly emitting, low-energy storage rings and energy recovery linear accelerators. To enable the operation of such a system and in particular the energy recovery from spent, high-intensity beams the use of the dual-axis asymmetric cavities is suggested. Merging circular and linear systems, and applications of dual axes cavities, aims to resolve both scientific and societal challenges. The merge of the systems will allow: 1) maintain high beam quality, high luminosity, and high energy efficiency; 2) offer a ?flexible? energy management via ?separation? of the collider and storage rings operations; 3) attract private partners via use of the storage rings to drive the next generation of the photon factories. The concept presented can be potentially used to reach ultimate energy frontiers in high-energy physics as well as to drive next generation light sources. We note that the numbers which will be presented are for illustration purpose and can be improved further.

Konoplev, I.↗
DOE OSTI2016

First results of the plasma wakefield acceleration experiment at PITZ

The self-modulation instability of long particle beams was proposed as a new mechanism to produce driver beams for proton driven plasma wakefield acceleration (PWFA). The PWFA experiment at the Photo Injector Test facility at DESY, Zeuthen site (PITZ) was launched to experimentally demonstrate and study the self-modulation of long electron beams in plasma. Key aspects for the experiment are the very flexible photocathode laser system, a plasma cell and well-developed beam diagnostics. In this contribution we report about the plasma cell design, preparatory experiments and the results of the first PWFA experiment at PITZ.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys

Refractory alloys (RAs) are promising materials due to their exceptional physicochemical properties, but most research remains at the laboratory scale. For broader adoption, advancements in manufacturing are essential. Because their high stability makes conventional methods like machining and casting difficult, additive manufacturing (AM) is emerging as an effective approach for fabricating refractory alloy components. However, AM's repeated non-equilibrium thermal cycles introduce undesired features (e.g. defects, anisotropic microstructures, and residual stresses), which are magnified due to RAs’ unique properties. This paper comprehensively reviews the state-of-the-art methods of AM for refractory alloys. It explores data analytics techniques to establish design rules based on multi-fidelity experimental and computational methods. Furthermore, it investigates integrated, collaborative efforts to harmonise standalone databases, information, knowledge, and predictive models at multi-physics, multi-stage, and multi-scale. Unlike the existing literature that focuses primarily on material systems or process fundamentals, this work provides an integrated perspective on AM of refractory alloys from a data analytics standpoint, highlighting the roles of integrated computational materials engineering (ICME), verification, validation, and uncertainty quantification (VV&UQ), and digital twin-driven qualification in overcoming data scarcity and accelerating rapid qualification.

Additive manufacturing↗
DOE OSTI2018

Development of Fleet Energy Savings Evaluation Tools for Smart Mobility: Smart Vehicle Energy Technology (SVET) Model for Passenger Fleets and Freight Fleet Level Energy Estimation Tool (FFLEET) for Freight Fleets

As part of the U.S. Department of Energy’s (DOE) Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative, the Oak Ridge National Laboratory (ORNL) led a study to develop web-based tools intended to enable vehicle fleet operators, including both passenger and freight fleets, to quantify the energy savings achievable by implementing advanced transportation technologies. By developing a profile of a fleet’s existing vehicle inventory and providing data about how and where the vehicles are driven, fuel consumption can be calculated for the entire fleet and users can perform “what if” scenarios to evaluate the energy savings that can be realized when replacing existing vehicles and implementing new technologies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

From natural language to control signals: a conceptual framework for semantic channel finding in complex experimental infrastructure

Modern experimental platforms such as particle accelerators, fusion devices, telescopes, and industrial process control systems expose tens to hundreds of thousands of control and diagnostic channels, accumulated over decades of hardware evolution. Operators and AI systems alike depend on informal expert knowledge, inconsistent naming conventions, and scattered documentation to locate the signals required for monitoring, troubleshooting, and automated control, creating a persistent bottleneck for reliability, scalability, and emerging language-model-driven interfaces. We formalize semantic channel finding, the task of mapping natural-language intent to concrete control-system signals, as a general problem in complex experimental infrastructure, and introduce a four-paradigm conceptual framework to guide architecture selection based on facility-specific data regimes. The paradigms span (i) direct in-context lookup over small, curated channel dictionaries, (ii) constrained hierarchical navigation through structured trees, (iii) interactive agent exploration using iterative reasoning and tool-based database queries, and (iv) ontology-grounded semantic search that decouples channel meaning from facility-specific naming conventions. We demonstrate the practical feasibility of each paradigm through proof-of-concept implementations at four operational facilities spanning two orders of magnitude in scale: from compact free-electron lasers to large synchrotron light sources, operating under diverse control-system architectures ranging from clean hierarchical naming schemes to legacy environments with decades of heterogeneous conventions. Where evaluated against expert-curated operational queries, these instantiations achieve 90%–97% accuracy, validating the framework’s applicability across real-world deployment scenarios. To accelerate adoption across the broader scientific and industrial control-system community, we release open-source, plug-and-play implementations of all three interactive paradigms-direct lookup, hierarchical navigation, and middle-layer exploration-within the Osprey framework, together with tools for channel database generation, interactive testing, and minimal-configuration deployment. This work establishes semantic channel finding as a foundational capability for human-centric and agentic AI interfaces at large-scale facilities, providing both a systematic framework for architecture design and practical resources to enable adoption without building custom infrastructure from scratch.

channel finding↗
DOE OSTI2023

Energy-Efficient Driving in Connected Corridors via Minimum Principle Control: Vehicle-in-the-Loop Experimental Verification in Mixed Fleets

Connected and automated vehicles (CAVs) can plan and actuate control that explicitly considers performance, system safety, and actuation constraints in a manner more efficient than their human-driven counterparts. In particular, eco-driving is enabled through connected exchange of information from signalized corridors that share their upcoming signal phase and timing (SPaT). This is accomplished in the proposed control approach, which follows first principles to plan a free-flow acceleration-optimal trajectory through green traffic light intervals by Pontryagin's Minimum Principle in a feedback manner. Urban conditions are then imposed from exogeneous traffic comprised of a mixture of human-driven vehicles (HVs) - as well as other CAVs. As such, safe disturbance compensation is achieved by implementing a model predictive controller (MPC) to anticipate and avoid collisions by issuing braking commands as necessary. The control strategy is experimentally vetted through vehicle-in-the-loop (VIL) of a prototype CAV that is embedded into a virtual traffic corridor realized through microsimulation. Up to 36% fuel savings are measured with the proposed control approach over a human-modelled driver, and it was found connectivity in the automation approach improved fuel economy by up to 26% over automation without. Additionally, the passive energy benefits realizable for human drivers when driving behind downstream CAVs are measured, showing up to 22% fuel savings in a HV when driving behind a small penetration of connectivity-enabled automated vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1993

Concept definition study for an extremely large aerophysics range facility

A conceptual design of a very large aeroballistic range is presented, as are its operational characteristics and procedures. The proposed model launcher is a two-stage light-gas gun, having a launch tube diameter of 254 mm, and the capability of accelerating a 14 kg launch mass to 6.1 km/sec. The gun's 91.4 cm diameter piston is driven by pressurized helium. High pressures in the central breech are contained by a multiple disk arrangement. The blast tank and sabot separation tank are described, as are methods for arresting sabot segments. The conceptual design of the range itself includes a 3.3 m diameter test or flight chamber some 330 m in length. Provisions are made for testing of free flight models and tests in which the model is confined by a track system. Methods for model deceleration and recovery are described. Provisions required for future addition of advanced model launchers such as an electromagnetic launcher or ram accelerator are addressed. Siting and safety issues are also addressed.

Swift, Hallock F.↗
DOE OSTI2024

Effects of Halides on Organic Compound Degradation during Plasma Treatment of Brines

Plasma has been proposed as an alternative strategy to treat organic contaminants in brines. Chemical degradation in these systems is expected to be partially driven by halogen oxidants, which have been detected in halide-containing solutions exposed to plasma. In this study, we characterized specific mechanisms involving the formation and reactions of halogen oxidants during plasma treatment. Here, we first demonstrated that addition of halides accelerated the degradation of a probe compound known to react quickly with halogen oxidants (i.e., para -hydroxybenzoate) but did not affect the degradation of a less reactive probe compound (i.e., benzoate). This effect was attributed to the degradation of para-hydroxybenzoate by hypohalous acids, which were produced via a mechanism involving halogen radicals as intermediates. We applied this mechanistic insight to investigate the impact of constituents in brines on reactions driven by halogen oxidants during plasma treatment. Bromide, which is expected to occur alongside chloride in brines, was required to enable halogen oxidant formation, consistent with the generation of halogen radicals from the oxidation of halides by hydroxyl radical. Other constituents typically present in brines (i.e., carbonates, organic matter) slowed the degradation of organic compounds, consistent with their ability to scavenge species involved during plasma treatment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Accelerating phase-field-based microstructure evolution predictions via surrogate models trained by machine learning methods

Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

42 ENGINEERING↗
NASA NTRS2017

Next Generation Agricultural System Models and Knowledge Products: Synthesis and Strategy

The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. This strategy is designed to facilitate a transition from the current, primarily supply-driven approach toward a more demand-driven approach that would address key Use Cases where better data, models and knowledge products are seen by end-users as essential to meet their needs.

Next generation↗
DOE OSTI2025

Beyond the four core effects: revisiting thermoelectrics with a high-entropy design

Low-exergy waste heat, which constitutes the majority of industrial-scale thermal losses, remains largely unrecoverable with conventional technologies. Thermoelectrics offer a solid-state solution for converting this hard-to-access energy into electricity, making them attractive for decentralized power generation and sensor applications. High-entropy materials (HEMs) have gained traction as a strategy for better-performing thermoelectrics, but the mechanisms driving their benefits require further exploration. This article highlights key insights for heat and electronic transport in HEMs. For heat transport, we argue that reduced, and often ultralow, lattice thermal conductivity in HEMs—with respect to ordered counterparts—can be taken for granted, emerging naturally as a fifth core effect of high-entropy systems. While band convergence is often considered beneficial for electronic transport, its impact depends strongly on the electronic structure. We summarize the scenarios where it can be detrimental to thermoelectric performance. These insights motivate strategies that align seamlessly with advancements in artificial intelligence and data-driven approaches, helping accelerate the discovery of next-generation thermoelectric materials.

Oses, Corey [Johns Hopkins Univ., Baltimore, MD (U↗
DOE OSTI2013

Pulsed pyroelectric crystal-powered gamma source

A compact pulsed gamma generator is being developed to replace radiological sources used in commercial, industrial and medical applications. Mono-energetic gammas are produced in the 0.4 - 1.0 MeV energy range using nuclear reactions such as {sup 9}Be(d,n{gamma}){sup 10}B. The gamma generator employs an RF-driven inductively coupled plasma ion source to produce deuterium ion current densities up to 2 mA/mm{sup 2} and ampere-level current pulses can be attained by utilizing an array extraction grid. The extracted deuterium ions are accelerated to approximately 300 keV via a compact stacked pyroelectric crystal system and then bombard the beryllium target to generate gammas. The resulting microsecond pulse of gammas is equivalent to a radiological source with curie-level activity.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems, etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Equipment

A discussion is presented on the problems encountered in designing and constructing a simulator to determine human vestibular response to a range of linear accelerations from 0 to 0.3 g's. Starting with a set of initial performance specifications, the designers combined an array of commercially available components into a system which, altough requiring further refinement before completion, shows considerable promise of fulfilling the initial requirements. The resulting system consists of a wheeled vehicle driven by a cable and drum arrangement, powered by a hydraulic-electric servo-valve. Technical design considerations are presented along with a discussion of the trade-offs between various component options. A description of the system characteristics as well as an analysis of preliminary test results and recommendations for future system improvements are included.

Source record↗
NASA NTRS1980

Scientific management and implementation of the geophysical fluid flow cell for Spacelab missions

Scientific support for the spherical convection experiment to be flown on Spacelab 3 was developed. This experiment takes advantage of the zero gravity environment of the orbiting space laboratory to conduct fundamental fluid flow studies concerned with thermally driven motions inside a rotating spherical shell with radial gravity. Such a system is a laboratory analog of large scale atmospheric and solar circulations. The radial body force necessary to model gravity correctly is obtained by using dielectric polarization forces in a radially varying electric field to produce radial accelerations proportional to temperature. This experiment will answer fundamental questions concerned with establishing the preferred modes of large scale motion in planetary and stellar atmospheres.

Hart, J.↗