Lie series for celestial mechanics, accelerators, satellite stabilization and optimization
Lie series applications to celestial mechanics, accelerators, satellite orbits, and optimization
Cap, F.↗
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.
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Simulation of the thermoelectric effect in a multi-metallic superconducting cavity
Superconducting radio-frequency accelerating cavities made with different material layers, such as copper, Nb or Nb₃Sn, are susceptible to thermoelectric effects due to differences in Seebeck coefficients between the metals. A temperature gradient across the surfaces can drive thermoelectric currents, which may impact the cavity performance. A layered Cu/Nb/Nb3Sn single-cell cavity was tested with cryocoolers in 2022. Three heaters were mounted on the cavity surface at different locations and three single-axis cryogenic fluxgate magnetometers were attached close to the cavity equator. A linear increase in the magnetic field was measured while increasing the heaters' power. The cavity setup was analyzed with COMSOL and the results showed a trend similar to that observed in the experiment. This contribution details the approach chosen for the simulation and some of the challenges encountered.
Accelerator Physics↗
Spin-transparent storage rings for quantum computing
Spin-transparent storage rings, where any spin direction repeats after one full turn, can be used in conjunction with ion traps as a new quantum computing platform [1]. Advantages of spin-transparent rings for quantum computing include: large numbers of stored qubits; long quantum coherence times of up to several hours; long storage lifetimes; and room temperature operation. These exceptional qualities mean rings could provide a scalable way to implement algorithms with deep complexity requiring many quantum operations while simultaneously providing a large number of qubits. This new platform where the qubit has long quantum coherence time can also be used as a quantum sensor or a part of a quantum memory.
Accelerator Physics↗
Applications of Fracture Mechanics to Quantitative Accelerated Life Testing of Plastic Encapsulated Microelectronics
Accelerated testing must address the failure mechanisms active within the devices undergoing tests in order to assess lifetimes in a meaningful way. The assumption of constant temperature, thermally activated lifetime, based upon the Arrhenius assumptions, does not always provide the necessary understanding to interpret accelerated tests in microelectronics. Plastic encapsulants, dielectric polymers, and underfill materials are subject to delamination and cracking with thermal cycling. Crack propagation during use environment exposure, drives the potential for failure of microelectronic devices and is therefore a necessary focal point in qualification and life testing. This paper reviews the available research in the application of fracture mechanics to this class of problems in microelectronics including relevant test data. In addition, useful acceleration factor models are derived for polymer crack propagation based on principles of linear elastic fracture mechanics. Further, a simple approach to estimating the minimum temperature cycling ranges, necessary to propagate a crack, is also presented. Finally, a methodology of applying acceleration factors to develop testing plans is shown, with an example in spaceflight for a cubesat in low Earth orbit. Overall, this is a paper that shows a useful and appropriate process for creating physics of failure based life testing for delamination and cracking failures in microelectronic polymers in a temperature cycling environment.
Accelerated testing↗
Energy recovery proton linear accelerator
High-power proton linear accelerators have important applications in both scientific research and industry. However, the operation of such accelerators with megawatt-level beam power is expensive and limits the broad availability of these facilities. In this Letter, we propose a novel energy recovery proton linear accelerator in which the final GeV-level proton beam is reinjected into the linear accelerator from the accelerator exit and is decelerated in the same accelerator down to about 2 MeV, close to the initial beam energy. This substantially reduces the power consumption of the proton linear accelerator and also avoids the need for a high-power beam dump. We demonstrate this concept through self-consistent simulations and show that the beam-beam effect between the forward-accelerating beam and the backward-decelerating beam would not be a limiting factor for the proposed concept. A potential application of this concept to an electron-ion collider based on energy recovery electron and ion accelerators is discussed.
Energy recovery linacs↗
Applications of the Strategic Defense Initiative's compact accelerators
The Strategic Defense Initiative's (SDI) investment in particle accelerator technology for its directed energy weapons program has produced breakthroughs in the size and power of new accelerators. These accelerators, in turn, have produced spinoffs in several areas: the radio frequency quadrupole linear accelerator (RFQ linac) was recently incorporated into the design of a cancer therapy unit at the Loma Linda University Medical Center, an SDI-sponsored compact induction linear accelerator may replace Cobalt-60 radiation and hazardous ethylene-oxide as a method for sterilizing medical products, and other SDIO-funded accelerators may be used to produce the radioactive isotopes oxygen-15, nitrogen-13, carbon-11, and fluorine-18 for positron emission tomography (PET). Other applications of these accelerators include bomb detection, non-destructive inspection, decomposing toxic substances in contaminated ground water, and eliminating nuclear waste.
Montanarelli, Nick↗
Outlook towards deployable continual learning for particle accelerators
Particle accelerators are high power complex machines. To ensure uninterrupted operation of these machines, thousands of pieces of equipment need to be synchronized, which requires addressing many challenges including design, optimization and control, anomaly detection and machine protection. With recent advancements, machine learning (ML) holds promise to assist in more advance prognostics, optimization, and control. While ML based solutions have been developed for several applications in particle accelerators, only few have reached deployment and even fewer to long term usage, due to particle accelerator data distribution drifts caused by changes in both measurable and non-measurable parameters. In this paper, we identify some of the key areas within particle accelerators where continual learning can allow maintenance of ML model performance with distribution drifts. Particularly, we first discuss existing applications of ML in particle accelerators, and their limitations due to distribution drift. Next, we review existing continual learning techniques and investigate their potential applications to address data distribution drifts in accelerators. By identifying the opportunities and challenges in applying continual learning, this paper seeks to open up the new field and inspire more research efforts towards deployable continual learning for particle accelerators.
43 PARTICLE ACCELERATORS↗
Compiler-Driven FPGA Virtualization with SYNERGY
FPGAs are increasingly common in modern applications, and cloud providers now support on-demand FPGA acceleration in datacenters. Applications in datacenters run on virtual infrastructure, where consolidation, multi-tenancy, and workload migration enable economies of scale that are fundamental to the provider's business. However, a general strategy for virtualizing FPGAs has yet to emerge. While manufacturers struggle with hardware-based approaches, we propose a compiler/runtime-based solution called Synergy. We show a compiler transformation for Verilog programs that produces code able to yield control to software atsub-clock-tickgranularity according to the semantics of the original program. Synergy uses this property to efficiently support core virtualization primitives: suspend and resume, program migration, and spatial/temporal multiplexing, on hardware which is availabletoday.We use Synergy to virtualize FPGA workloads across a cluster of Intel SoCs and Xilinx FPGAs on Amazon F1. The workloads require no modification, run within 3--4x of unvirtualized performance, and incur a modest increase in FPGA fabric usage.
Computer Science↗
Machine-Learning Assisted Identification of Battery Life Models
Predictive battery life models are commonly utilized to extrapolate degradation trends observed during accelerated aging tests for simulation of degradation in real-world applications. Thus, fitting accelerated aging data as accurately as possible and with low uncertainty is crucial for making believable projections of battery lifetime, but it is challenging to identify algebraic expressions that accurately fit multivariate degradation trends. A review of models published in literature reveal some common expressions for fitting calendar aging data, which is only dependent on temperature and state-of-charge, but no consistency across many models for fitting cycle aging data, indicating the need for a statistically rigorous data driven approach for developing empirical models. This talk will describe a machine-learning assisted method for identification of predictive battery life models utilizing bilevel optimization and symbolic regression. Bilevel optimization with cross-validation is used to statistically determine cell- and stress-dependent model parameters, while symbolic regression identifies both linear and multiplicative candidate expressions to predict stress-dependent degradation rates by selecting low-order subsets of features from a generated feature library. Because model expressions are identified empirically, it is crucial to ensure resulting models behave according to physical expectations, so the stability of models for interpolation or extrapolation is interrogated qualitatively through simulation and quantitatively through cross-validation and uncertainty quantification via bootstrap resampling. This model identification approach substantially improves upon models identified purely using expert judgement in terms of both accuracy and uncertainty. Model simulation and validation is then conducted by deriving a state-equation form of the predictive model, enabling simulation of battery aging under dynamic stresses. This enables validation of the predictive battery model on lab-based tests with varying conditions or on drive-cycle or application-cycle testing protocols. Parameter uncertainty can be carried forward into model simulation, giving lifetime estimates and confidence windows for cell- or system-level lifetime. The financial impact of battery model uncertainty can be estimated by incorporating uncertainty into a technoeconomic model.
battery↗
Parametric Failures in COTS Capacitors
Insertion of COTS components into hi-rel systems require extensive environmental testing of the parts that often results in parametric failures. Based on experience with commercial and hi-rel PME and BME ceramic capacitors and polymer and MnO2 cathode tantalum capacitors, this presentation discusses two major reasons for parametric failures. One is due to the marketing pressure that forces manufacturers to squeeze performance of COTS components thus leaving insufficient margin between the rated and actual characteristics. Another, and probably a more serious reason is degradation of characteristics caused by physico-chemical processes in materials under environmental stresses. Reliability assessment requires development of models to predict behavior of the parts during applications based on accelerated testing that might be outside the specified conditions and target applications. Examples of models developed to simulate and predict wear-out failures are presented. Risks associated with overstressing during HALT are discussed.
Teverovsky, Alexander↗
High Q SRF cavity-based searches for beyond the standard model physics
The SRF technology developed for accelerators can be successfully applied to new applications, including quantum computing, dark matter searches and beyond the standard model physics. The ultra-high quality factor of SRF cavities can enable unprecedented sensitivity in fields outside of the usual accelerator applications, for examples fundamental and beyond the standard model physics. Applications of SRF cavities for gravitational waves searches are also being investigated. The SQMS Physics and Sensing thrust is working on this effort as it strives to combine SRF cavities with QIS, with a focus on BSM and fundamental physics.
Berlin, A.↗
Nb SRF cavities applied to searches for beyond the standard model physics
The SRF technology developed for accelerators can be successfully applied to new applications, including quantum computing, dark matter searches and beyond the standard model physics. The ultra-high quality factor of SRF cavities can al-low to achieve unprecedented sensitivity in fields outside of the usual accelerator applications, for examples fundamental and beyond the standard model physics. Applications of SRF cavities for gravitational waves searches are also being investigated. The SQMS Physics and Sensing thrust is working on this effort as it strives to combine SRF cavities with QIS, with a focus on BSM and fundamental physics. Using Nb SRF cavities, we run a proof of principle search for the dark photon dark matter candidate at fixed frequency demonstrating the deepest sensitivity to wavelike dark mater [1]. The Dark SRF experiment uses two 1.3GHz SRF cavities to conduct a light shining through wall (LSW) experiment to attempt producing and detecting dark photons in the laboratory. The results of this first superconducting LSW search were recently published [2] and we are now working on the second phase of the experiment, which will be run in a dilution refrigerator using 2.6GHz SRF cavities. In addition to the limits we have achieved, we will also present the experiments we are currently developing, such as the heterodyne axion DM search [3, 4], the SERAPH series of experiments, and gravitational waves searches based on SRF cavities as proposed in [5-8].
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)
As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.
03 NATURAL GAS↗
Stimulus: Accelerate Data Management for Scientific AI applications in HPC
Explore the source record for details and available documents.
Computer science↗
U.S. HL-LHC Accelerator Upgrade Project: Q1/Q3 Cryostat Assembly and Horizontal Test (Final Design Report)
The Inner Triplet (IT) quadrupoles are the magnetic system for reaching low beta functions around the Interaction Point (IP). The triplet is made of three optical elements: Q1, Q2, and Q3. The upgrade of the Inner Triplets in the high luminosity insertions is the cornerstone of the LHC upgrade. The decision for HL-LHC heavily relies on the success of the advanced Nb 3 Sn technology that provides access to magnetic fields well beyond 9 T, allowing the maximization of the aperture of the IT quadrupoles. A 15-year-long study led by the DOE in the US under the auspices of the U.S. LARP program, and lately by other EU programs, has shown the feasibility of Nb 3 Sn accelerator magnets. The HL-LHC is expected to be the first application of accelerator-quality Nb 3 Sn magnet technology in an operating particle accelerator.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
ACCELERATING DISCOVERY FROM HIGH PERFORMANCE COMPUTING APPLICATIONS USING DESCRIPTIVE METADATA MANAGEMENT.
Abstract not provided.
Lawson, Margaret↗
Application of Dynamical System Scaling for Accelerated Fuel Qualification Efforts
There are considerable ongoing research and testing campaigns to qualify new fuel designs such as metallic fuels for advanced reactor designs and the Accident Tolerant Fuel (ATF) campaign for light water reactors (LWR). The typical research and development lifecycle needed to qualify a nuclear fuel design, under ideal conditions, can take up to 20-25 years which limits the ability for new fuels to make fast deployments into commercial, test, and research reactors. While there are several efforts to accelerate nuclear fuel qualification through advanced modeling coupled with state-of-the-art experiments, there is not yet a framework to methodically quantify and rank distortions occurring in experimental test specimens needed to validate nuclear fuel performance codes. This study uses the Dynamical System Scaling (DSS) methodology to quantify transient scaling distortions that occur over experiment and simulated transients. DSS analysis metrics provide a researcher with several tools and information embedded within test data to identify dominant phenomena, associated timescales, and quantify a transient?s overall dynamic distortion. This is demonstrated with separate analyses of the SETH-C and CHF-SERTTA thermal-hydraulic experiments in the TREAT facility at Idaho National Laboratory. The outcome of this work is a scaling and data analysis approach to account for the influence a scaled fuel test specimen?s geometric and temporal distortions have on its ability to be representative of the full-scale design.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Research and Development of Advanced Superconducting Radiofrequency (SRF) Accelerator Technology and Components for Scientific and Industrial Applications
The purpose of this CRADA is to provide for the joint conduct of research and development (R&D) investigations between Fermi Research Alliance, LLC (Contractor), as operator of the Fermi National Accelerator Laboratory (Fermilab) and Euclid TechLabs, LLC (Participant) related to Research and Development of Advanced Superconducting Radiofrequency (SRF) Accelerator Technology and Components for Scientific and Industrial Applications.
43 PARTICLE ACCELERATORS↗