SEARCH · Engineering Papers
Results for “accelerator physics”
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.
RFQ Beam Loss and Shielding Consideration
The proposed novel RFQ-based injector for LANSCE operation includes two independent low energy transports merging beams at the entrance of a single RFQ, which accelerates simultaneously both protons and H- ions with multiple flavors of the beams. One of the design issues of the project is the estimation of shielding requirements for the injector. Continuous access to the injector components reduces the number of times required to open the linac tunnel and saves time for the operation. Estimation involves the evaluation of radiation generated by beam losses in the injector. In this paper, we present an overview of the shielding in existing RFQ injectors and discuss the aspects of shielding configuration for the LANSCE RFQ-based injector.
Action Sheet 66: Neutron Induced Nuclear Data Cross Section Measurements at JRC-Geel [Slides]
Experiments for 142 Ce have been performed in 2019. The data are reduced to cross section and transmission, respectively. Report for 142 Ce experiments is in preparation. Data analysis is underway, and the evaluation should be finalized by the end of 2020. 90 Zr sample is produced, but experiments planned for 2020 are delayed due to COVID-19.
FY20 Thermal Neutron Scattering Measurements at the ORNL Spallation Neutron Source [Slides]
This presentation discusses the Spallation Neutron Source (SNS), including the facility layout and the instruments used such as ARCS, SEQUOIA, VISION, and (Q,E) Grid of Direct and Indirect Spectrometers. It also discusses overviews of measured materials including yttrium hydride (YH x ) and polystyrene.
Second Target Station High-Fidelity Target Activation Comparison
The development of the Second Target Station (STS) target system at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is well underway. The target system at STS consists of a rotating target disk that contains 21 segments of tungsten clad in tantalum clad in steel. A key aspect of the design of the target system is to account for the delayed heating and material damage caused by the delayed dose from decaying radionuclides. These radionuclides are a product of either spallation reactions or transmutation of the nuclei in the target system. These radionuclides build up in the target system components over the lifetime of the facility, and the radiation that is emitted can deposit energy in the components causing significant component heating and material damage. Monte Carlo N-Particle (MCNP) Version 6.2 transports the various particle species and calculates the spallation products and neutron fluxes throughout the target system. These spallation products and neutron fluxes along with the material definition of each component are relayed to the CINDER2008 transmutation code to calculate the radionuclide inventories and the corresponding decay gamma emission spectra. MCNP6.2 coupled with CINDER2008 is the computational method-of-choice for the analysis discussed in the following sections of this report. The analysis focuses on validating major assumptions in calculating the radionuclide inventory in the STS target system: all of the target segments are fresh, unirradiated material when the protons are incident on the segment, the average of the 21 segments of the target is sufficient to represent a single segment, and that averaging the proton pulse structure over time does not significantly affect the radionuclide inventory. The position-averaged, high-fidelity, and single-tally computational methods are used to validate the assumptions and provide a point of comparison to evaluate how the assumptions impact the radionuclide inventories. A more detailed explanation of the three computational methods is provided in Section 2. The position-averaged and single-tally methods are less computationally expensive when compared with the high-fidelity method where 54,000 individual calculations are needed to calculate 1 hr of STS operation. Section 3 details the comparison of the three methods to show that the assumptions made in the position-averaged method do not significantly impact the radionuclide inventory after 1 hr of operation. The discussions and results in this report are for 1 hr of operation. Due to the computational cost associated with calculating the transmutation and activation using the high-fidelity method, only 1 hr of operation has been calculated. The discrepancies observed after 1 hr of operation are not extrapolated out to longer operational times, and this report does not address how the discrepancies between the computational methods may manifest for longer operational periods.
Development of Low-Power H - Proton Beam Capability in Area-A
A low-power proton beam capability in Area-A will support NNSA, LANL, Global Security, DoD, and Office of Science missions. It will also provide a stepping-stone towards other future uses of Area-A. We propose a cost-effective technical approach to achieve this goal. The main focus of this project will be to provide beam for a radiation effect beamline and a second pRad beamline.
LANSCE CCL Performance Limits
This report summarizes the performance limits of the LANSCE Coupled-Cavity Linac (CCL). These results are captured or summarized directly from the references cited. This report was written in support of the LANSCE Modernization Project (LAMP). Many factors contribute to the performance limits of the CCL accelerator system. One performance limit is set by the CCL mechanical structure and available cooling. Heating of the structure is ultimately linked to the operating RF duty factor of the CCL. Another performance limit is set by the maximum RF and beam duty factors that can be supported by the 805-MHz klystrons and associated HVDC power supplies. The RF and HVDC systems also set limits for the maximum peak beam current that can be accelerated in the CCL. And finally, a maximum beam current limit is set by the beam dynamics determined by the details of the CCL physics design (number of cells per CCL tank, accelerating gradients, magnetic focusing lattice, beam losses, etc.). This limit can be informed by both simulation results and beam measurement data, if available. A detailed explanation of each performance limit is given in the sections below. The results are summarized in the table below. In all cases, it is assumed that the CCL and the RF system are operating in their nominal beam production configuration – nominal magnet set points and nominal cavity fields, unless otherwise specified.
Status of the muon neutrino charged-current zero mesons cross section measurement in the NOvA near detector
NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement will be made with respect to the kinematics of the final state particles. Our chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and will provide a handle for constraining the cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.
What is Needed for Bisco to Work in A Dipole Insert for 20 Tesla Hybrid Accelerator Magnets
Explore the source record for details and available documents.
Action Sheet 66: Neutron Induced Nuclear Data Cross Section Measurements at JRC-Geel [Slides]
This presentation is on the action sheet 66: neutron induced nuclear data cross section measurements at JRC-Geel. This presentation highlights safeguards objectives to prevent theft or diversion of nuclear material through the nuclear fuel cycle. This presentation includes a detailed look at 90 Zr experiments.
Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling under uncertainty, and its application to accelerating the discovery of new materials
In this report we summarize the work conducted by PI Perdikaris and his group under this Early Career project DE–SC0019116 during the period of 09/01/2018 – 08/31/2023. The central aim of the work was to introduce a new paradigm for scientific data analysis that can seamlessly synthesize rigorous mathematical modeling with data of variable fidelity (e.g., measurements at multiple scales/resolutions or predictions of variable fidelity models) and multiple modalities (e.g., images, time–series, or scattered measurements). The setting we are interested in involves complex systems that are partially observed and whose dynamical behavior could be hard to model or totally unknown. The inherent uncertainty associated with this setting necessitates a departure from the classical deterministic realm of modeling and scientific computation, and, consequently, our main building blocks can no longer be crisp deterministic numbers and governing laws, but instead we must operate with probabilistic models.
Status of the Muon Neutrino Charged-Current Mesonless Cross Section Measurement in the NOvA Near Detector
NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of a muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is being made with respect to the kinematics of the final state muon. The chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and aims to provide experimental constraints for the development of models of neutrino interactions. It will also provide a handle for constraining cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.
Status of the Muon Neutrino Charged-Current Zero Mesons Cross Section at the NOvA Near Detector
NOvA is a long-baseline accelerator neutrino experiment at Fermilab whose physics goals include precision neutrino oscillation as well as cross-section measurements. We present the status of the measurement of a muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is being made with respect to the kinematics of the final state muon. The chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and aims to provide experimental constraints for the development of models of neutrino interactions. It will also provide a handle for constraining cross section systematic uncertainties in oscillation analyses in current and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA near detector that allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. Charged pion background constraining is further improved via Michel electron tagging.
Calibration and Implementation of A Broadband Cross Dispersed, Medium Resolution Spectrometer
Explore the source record for details and available documents.
LaserNetUS: A Proposal to Advance North America’s First High Intensity Laser Research Network Final Report
LaserNetUS Collaborative Network established in 2018 is a network of high-power laser facilities supported by the Department of Energy (DOE) Office of Fusion Energy Sciences (FES) and operating effectively as a user facility. Its mission is to advance and promote intense laser science and applications by providing scientists and students with broad access to unique facilities and enabling technologies, advancing the frontiers of laser-science research, and fostering collaboration among researchers and networks from around the world. Users who submit proposals through an annual call are selected by an external and independent proposal review panel (PRP) not involving personnel from any of the facilities.
MEMS RF accelerators for nuclear energy and advanced manufacturing
Energetic ions are widely used to develop radiation hard structural materials and fuels for advanced nuclear energy. Ion beams are also used to generate neutrons for nuclear materials testing, as well as in a series of high impact, high value adding manufacturing processes (ranging from doping of semiconductors to hardening of materials against wear and to increase bio-compatibility of materials). But to date, high power beams of high energy ions are simply too expensive because they are delivered from large single beam accelerators. We have recently demonstrated that MEMS technology enables massively parallel, low cost batch fabrication of ion beams. We propose to scale intense ion accelerators based on MEMS (micro-electro mechanical systems) to high beam power (>10 kW). With our approach, hundreds to thousands of ion beamlets will be densely packed on silicon wafers. Ions are injected and accelerated across gaps formed in stacks of wafers, leading to uniquely high current densities for intense ion accelerators with variable kinetic energy (0.1 to 10 MeV) and variable ion species. Our team brings together experts in high power ion accelerators from Lawrence Berkeley National Laboratory and leading experts in MEMS technology from Cornell University. We will deliver a disruptive technology of low cost, flexible and massively scalable ion accelerators that will enable the rapid development of radiation hard nuclear materials for advanced nuclear energy and enable new applications in manufacturing.
Fast Adaptive Neural Control of Resonant Extraction at Fermilab
We present the development of a machine learning (ML) based regulation system for third-order resonant beam extraction in the Mu2e experiment at Fermilab. Classical and ML-based controllers have been optimized using semi-analytic simulations and evaluated in terms of regulation performance and training efficiency. We compare several controller architectures and discuss the integration of neural control into an adaptive framework. We also present progress on surrogate models that predict the controller response given a spill intensity and controller action history. To enable real-time deployment, we report progress on implementing low-latency, edge-based inference suitable for hardware-constrained environments. Our results demonstrate the feasibility and advantages of ML-based control in managing complex, time-varying physical systems, with broader implications for accelerator operations and other domains requiring fast, adaptive regulation.
Testing the Common Platform LLRF with a 197 MHz NCRF Cavity
The Common Platform is the hardware that will support the new LLRF platform to be used for the Electron-Ion Collider. The Common Platform features a carrier board that is used to interface with a variety of daughter for different applications. This paper details the testing that was done using the Common Platform and an RF Digitizer Daugther Board. Firstly, the firmware and software development is discussed followed by a description of the controls algorithms used in the testing. Then, testing and verification of the platform with a 197 MHz NCRF cavity is discussed. The paper concludes with results from the testing and the path forward.