Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Engineering - Particle accelerators”

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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Laser-driven electron acceleration in a plasma channel with an additional electric field

We examine the electron acceleration in a two-dimensional plasma channel under the action of a laser field and an additional static electric field. We propose to design an appropriate additional electric field (its direction and location), in order to launch the electron onto an energetic trajectory. We find that the electron acceleration strongly depends on the coupled effects of the laser polarization, the direction, and location of the additional electric field. The additional electric field affects the electron dynamics by changing the dephasing rate. Particularly, a suitably designed additional electric field leads to a considerable energy gain from the laser pulse after the interaction with the additional electric field. The electron energy gain from the laser with the additional electric field can be much higher than that without the additional electric field. This engineering provides a possible means for producing high energetic electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Modeling and simulation challenges pursued by the Consortium for Advanced Simulation of Light Water Reactors (CASL)

The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear power industry that M&S can assist in addressing. To date CASL has developed a multi-physics “core simulator” based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of zirconium alloy clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry. - Highlights: • Complexity of physics based modeling of light water reactor cores being addressed. • Capability developed to help address problems that have challenged the nuclear power industry. • Simulation capabilities that take advantage of high performance computing developed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Using collective variables to drive molecular dynamics simulations

A software framework is introduced that facilitates the application of biasing algorithms to collective variables of the type commonly employed to drive massively parallel molecular dynamics (MD) simulations. The modular framework that is presented enables one to combine existing collective variables into new ones, and combine any chosen collective variable with available biasing methods. The latter include the classic time-dependent biases referred to as steered MD and targeted MD, the temperature-accelerated MD algorithm, as well as the adaptive free-energy biases called metadynamics and adaptive biasing force. The present modular software is extensible, and portable between commonly used MD simulation engines.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Stagnation region heat transfer augmentation at very high turbulence levels

Current land-based gas turbines are growing in size producing higher approach flow Reynolds numbers at the leading edge of turbine nozzles. These vanes are subjected to high intensity large scale turbulence. This present paper reports on the research which significantly expands the parameter range for stagnation region heat transfer augmenta-tion due to high intensity turbulence. Heat transfer measurements were acquired over two constant heat flux test surfaces with large diameter leading edges (10.16 cm and 40.64 cm). The test surfaces were placed downstream from a new high intensity (17.4%) mock combustor and tested over an eight to one range in approach flow Reynolds number for each test surface. Stagnation region heat transfer augmentation for the smaller (Re D = 15,625–125,000) and larger (Re D = 62,500–500,000) leading edge regions ranged from 45% to 81% and 80% to 136%, respectively. Furthermore, these data also include heat transfer distributions over the full test surface compared with the earlier data acquired at six additional inlet turbulence conditions. These surfaces exhibit continued but more moderate acceleration downstream from the stagnation regions and these data are expected to be useful in testing bypass transition predictive approaches. This database will be useful to gas turbine heat transfer design engineers. [DOI: 10.1115/1.4032677]

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Increased Fissile Loading Flowsheet Review

A request was made by H-Canyon Process Engineering to assess the impact of blending dissolved, neutralized Spent Nuclear Fuel (SNF) with future sludge batches and their impact on downstream processing facilities. The purpose of this change is to accelerate the deinventory of SNF which is currently stored in the L-Area Disassembly Basin.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

I.3.4.1.1 Overview of Advanced Characterization Within the Powertrain Materials Program (Task 4A1) (Oak Ridge National Laboratory); (Task 4A2) (Argonne National Laboratory); and (Task 4A3) (Pacific Northwest National Laboratory)

This report describes the activities performed during the third year of Thrust 4A, “Advanced Characterization,” within the DOE-EERE VTO PMCP. The goal of the PMCP, which was launched in October 2018, has been to accelerate design, development, demonstration, and deployment of new, cost-effective advanced alloy solutions via a modern ICME approach. The properties of these new materials are targeted to enable improvements in engine efficiency, lightweighting, and durability enhancement over the full range of on-road vehicle classes (e.g., Classes 1-8), including range extenders for future electric HD freight vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Modeling Freight Traffic Demand and Highway Networks for Hydrogen Fueling Station Planning: A Case Study of U.S. Interstate 75 Corridor

The use of hydrogen as an alternative transportation fuel has gained much interest in recent years. Hydrogen can be utilized in electric vehicles equipped with hydrogen powertrains (including hydrogen internal combustion engines or fuel cells). Given that most of the freight in the U.S. is transported via diesel trucks, transition to hydrogen fuel would help achieve significant environmental benefits as well as accelerate the decarbonization of the freight transportation sector. This paper presents the methodology and results of a case study on modeling freight traffic demand and highway networks based on publicly available data for the Interstate 75 freight corridor. The purpose of this study is to prepare input traffic and network data that can support the planning of a hydrogen fueling station infrastructure. In particular, the data can be used for siting and characterizing an optimized framework of hydrogen fueling stations from candidate diesel stations along the Interstate 75 corridor. The methodologies developed and presented in this paper may be readily expanded and applied to any transport corridor given the data availability. This paper is the first in a series that will build out a comprehensive model to optimize a consolidated national hydrogen refueling infrastructure eco-system targeted at commercial vehicles.

Uddin, Majbah↗
DOE OSTI2024

Methods of controllable interstitial oxygen doping in niobium

A method for vacuum heat treating Nb, such as is used in superconducting radio frequency cavities, to engineer the interstitial oxygen profile with depth into the surface to conveniently optimize the low-temperature rf surface resistance of the material. An example application is heating of 1.3 GHz accelerating structures between 250-400° C. to achieve a very high quality factor of 5×1010 at 2.0 K. With data supplied by secondary ion mass spectrometry measurements, application of oxide decomposition and oxygen diffusion theory was applied to quantify previously unknown parameters crucial in achieving the oxygen alloy concentration profiles required to optimize the rf surface resistance. RF measurements of vacuum heat treated Nb superconducting radio frequency cavities confirmed the minimized surface resistance (higher Q0) previously expected only from 800° C. diffusive alloying with nitrogen.

Palczewski, Ari D.↗
DOE OSTI2013

High-Power Warm-White Hybrid LED Package for Illumination

In this project, an integrated warm-white hybrid light engine was developed. The hybrid approach involves combining phosphor-converted off-white InGaN LEDs and direct-emitting red AlInGaP LEDs in a single light engine to achieve high efficacy together with high color rendering index. We developed and integrated technology improvements in InGaN and AlInGaP die technology, phosphor technology, package architecture and encapsulation, to realize a hybrid warm-white LED package with an efficacy of 140 lm/W at a correlated color temperature of 3000K and a color rendering index of 90, measured under representative operating conditions. This efficacy is 26% higher than the best warm-white LEDs of similar specification that are commercially available at the end of the project. Since the InGaN- and AlInGaP-based LEDs used in the hybrid engine show different behavior as a function of current and temperature, a control system needs to be in place to ensure a stable color point over all operating conditions. In this project, we developed an electronic control circuit that is fully integrated into the light engine in such a way that the module can simply be driven by a conventional single-channel driver. The integrated control circuit uses a switch-mode boost converter topology to control the LED drive currents based on the temperature and the input current of the light engine. A color control performance of 5 SDCM was demonstrated, and improvement to 3 SDCM is considered well within reach. The combination of high efficacy and ease of integration with existing single-channel drivers is expected to facilitate the adoption of the hybrid technology and accelerate the energy savings associated with solid-state lighting. In the product commercialization plan, downlights and indirect-lit troffers have been selected as the first target applications for this product concept. Fully functional integrated prototypes have been developed for both applications, and the business case evaluation is ongoing as of the end of the project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Invited: Software defined accelerators from learning tools environment

Next generation systems, such as edge devices, will need to provide efficient processing of machine learning (ML) algorithms along several metrics, including energy, performance, area, and latency. However, the quickly evolving field of ML makes it extremely difficult to generate accelerators able to support a wide variety of algorithms. At the same time, designing accelerators in hardware description languages (HDLs) by hand is hard and time consuming, and does not allow quick exploration of the design space. In this paper we present the Software Defined Accelerators From Learning Tools Environment (SODALITE), an automated open source high-level ML framework-to-verilog compiler targeting ML Application-Specific Integrated Circuits (ASICs) chiplets. The SODALITE approach will implement optimal designs by seamlessly combining custom components generated through high-level synthesis (HLS) with templated and fully tunable Intellectural Properties (IPs) and macros, integrated in an extendable resource library. Through a closed loop design space exploration engine, developers will be able to quickly explore their hardware designs along different dimensions.

High-Level Synthesis, Accelerators, Hardware-Softw↗
DOE OSTI2023

Highly transferable atomistic machine-learning potentials from curated and compact datasets across the periodic table

Machine learning atomistic potentials trained using density functional theory (DFT) datasets allow for the modeling of complex material properties with near-DFT accuracy while imposing a fraction of its computational cost. The curation of the DFT datasets can be extensive in size and time-consuming to train and refine. In this study, we focus on addressing these barriers by developing minimalistic and flexible datasets for many elements in the periodic table regardless of their mass, electronic configuration, and ground state lattice. These DFT datasets have on average, ~4000 different structures and 27 atoms per structure, which we found sufficient to maintain the predictive accuracy of DFT properties and notably with high transferability. We envision these highly curated training sets as starting points for the community to expand, modify, or use with other machine learning atomistic potential models, whatever may suit individual needs, further accelerating the utilization of machine learning as a tool for material design and discovery.

42 ENGINEERING↗
DOE OSTI2019

Multiply accelerated ReaxFF molecular dynamics: coupling parallel replica dynamics with collective variable hyper dynamics

To address the time scales required to study complex chemical reactions, methods performing accelerated molecular dynamics are necessary even with the recent advancement in high-performance computing. A number of different acceleration techniques are available. Here we explore potential synergies between two popular acceleration methods – Parallel Replica Dynamics (PRD) and Collective Variable Hyperdynamics (CVHD), by analysing the speedup obtained for the pyrolysis of n-dodecane. We determine that PRD + CVHD provides additional speedup to CVHD by reaching the required time scales for the reaction at an earlier wall-clock time. Although some speedup is obtained with the additional replicas, we found that the effectiveness of the inclusion of PRD is depreciated for systems where there is a dramatic increase in reaction rates induced by CVHD. Similar observations were made in the simulation of ethylene-carbonate/Li system, which is inherently more reactive than pyrolysis, suggest that the speedup obtained via the combination of the two acceleration methods can be generalised to most practical chemical systems.

42 ENGINEERING↗
DOE OSTI2025

Risk Assessment of EIC Central Detector (ePIC) Solenoid Magnet (MARCO)

As part of the BNL-JLab-CEA Electron Ion Collider (EIC) collaboration, the design of a 2 T, 2.8 m bore diameter, 3.8 m long conduction cooled superconducting detector magnet design is completed. Such magnet will be employed at the interaction region of ePIC for physics experiment. The magnet is a passive shielded solenoidal magnet system consisting of 3 coils wound with specially designed conductor using NbTi Rutherford type cable in copper stabilized channel. This paper describes the risk analysis as the part of Failure Modes and Effects Analysis (FMEA) that was carried out as a team to identify their various failure modes and risks associated with the magnets system. In conclusion, this FMEA is intended to become the content of the designed document as an integral part of the engineering assessment and the statement of work for the potential vendors towards design and built.

Ghoshal, Probir K. [Thomas Jefferson National Acce↗
DOE OSTI2014

Novel Multiple-Gigahertz Electron Beams for Advanced X-Ray and Gamma-Ray Light Sources

Current and future generations of advanced light sources largely depend on high brightness electron beams. LLNL has spent the past decade developing Mono-Energetic Gamma-ray (MEGa-ray) sources by scattering laser light off an electron beam for nuclear physics applications. At the SLAC National Accelerator Laboratory, the Linac Coherent Light Source (LCLS) is generating extraordinarily high peak brightness x-ray beams useful for biological, chemical, and physics studies by passing a 13.6 GeV electron beam through a series of magnetic undulators to form a Free-Electron Laser (FEL). Los Alamos is in the process developing the “MaRIE” (Matter-Radiation Interactions in Extremes) concept, which will also rely on FELs. All these light sources would benefit from improved average brightness by increasing the repetition rate of the electron beam source. Since the undulators are based on permanent magnets, they will generate x-rays from as many electron bunches as can be delivered. Similarly, for MEGa-ray sources very little laser light is scattered from each individual electron bunch. If there are additional electron bunches to see the laser, they will also scatter photons, generating more gamma-rays. Modeling has shown that using trains of hundreds of electron bunches allows high gamma-ray fluxes to be generated using ns-long scattering laser pulses. This means that chirped pulse amplification would not be needed for the interaction laser, considerably simplifying the architecture. This would also allow for lower laser bandwidth at the interaction point, along with a larger focal spot size, eliminating the laser contribution to the scattered gamma-ray bandwidth. Additionally, lower charge per bunch allows more flexibility in the transport, simplifying efforts to mitigate noise-inducing dark current. The overarching goal of the proposed research is to develop and demonstrate the required technology to generate multi-GHz rep-rate electron beams at pC-scale bunch charges to allow 100x increases in the average beam current. To achieve this, the project consisted of two major efforts: 1. Demonstration of a photocathode drive laser capable of generating the electron beam. 2. Commissioning of an x-band accelerator to enable studies of inter-bunch electromagnetic field interactions. Excellent results were achieved in both areas.

42 ENGINEERING↗
DOE OSTI2014

Systems and methods for cylindrical hall thrusters with independently controllable ionization and acceleration stages

Systems and methods may be provided for cylindrical Hall thrusters with independently controllable ionization and acceleration stages. The systems and methods may include a cylindrical channel having a center axial direction, a gas inlet for directing ionizable gas to an ionization section of the cylindrical channel, an ionization device that ionizes at least a portion of the ionizable gas within the ionization section to generate ionized gas, and an acceleration device distinct from the ionization device. The acceleration device may provide an axial electric field for an acceleration section of the cylindrical channel to accelerate the ionized gas through the acceleration section, where the axial electric field has an axial direction in relation to the center axial direction. The ionization section and the acceleration section of the cylindrical channel may be substantially non-overlapping.

42 ENGINEERING↗
DOE OSTI2013

Optimization Using Metamodeling in the Context of Integrated Computational Materials Engineering (ICME)

Predictive Design Technologies, LLC (PDT) proposed to employ Integrated Computational Materials Engineering (ICME) tools to help the manufacturing industry in the United States regain the competitive advantage in the global economy. ICME uses computational materials science tools within a holistic system in order to accelerate materials development, improve design optimization, and unify design and manufacturing. With the advent of accurate modeling and simulation along with significant increases in high performance computing (HPC) power, virtual design and manufacturing using ICME tools provide the means to reduce product development time and cost by alleviating costly trial-and-error physical design iterations while improving overall quality and manufacturing efficiency. To reduce the computational cost necessary for the large-scale HPC simulations and to make the methodology accessible for small and medium-sized manufacturers (SMMs), metamodels are employed. Metamodels are approximate models (functional relationships between input and output variables) that can reduce the simulation times by one to two orders of magnitude. In Phase I, PDT, partnered with Mississippi State University (MSU), demonstrated the feasibility of the proposed methodology by employing MSU?s internal state variable (ISV) plasticity-damage model with the help of metamodels to optimize the microstructure-process-property-cost for tube manufacturing processes used by Plymouth Tube Company (PTC), which involves complicated temperature and mechanical loading histories. PDT quantified the microstructure-property relationships for PTC?s SAE J525 electric resistance-welded cold drawn low carbon hydraulic 1010 steel tube manufacturing processes at seven different material states and calibrated the ISV plasticity material parameters to fit experimental tensile stress-strain curves. PDT successfully performed large scale finite element (FE) simulations in an HPC environment using the ISV plasticity model in Abaqus FE analyses of the tube forming, sizing, drawing, welding, and normalizing processes. The simulation results coupled with the manufacturing cost data were used to develop prototype metamodeling (quick response) codes which could be used to predict and optimize the microstructure-process-property-cost relationships. The developed ICME metamodeling toolkits are flexible enough to be applied to other manufacturing processes (e.g. forging, forming, casting, extrusion, rolling, stamping, and welding/joining) and metamodeling codes can run on laptop computers. Based on the work completed in Phase I, in Phase II, PDT proposes to continue to refine the ISV model by correlating and incorporating the uncertainties in the microstructure, mechanical testing, and modeling. Following the model refinement, FE analyses will be simulated and will provide even more realistic predictions as they include an appropriate window of uncertainty. Using the HPC output (FE analyses) as input, the quick-response metamodel codes will more accurately predict and optimize the microstructure-process-property-cost relationships. Furthermore, PDT propose to employ the ICME metamodeling toolkits to help develop a new tube product using entirely new high strength steel. The modeling of the high strength steel manufacturing process will replace the costly and time consuming trial-and-error methods that were used in the tubing industry previously. This simulation-based process prototyping will greatly benefit our industrial partners by opening up new market spaces due to new products with greater capabilities.

36 MATERIALS SCIENCE↗