LAMP Conceptual Design Review -Radio-Frequency Quadrupole (RFQ)
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The goal of this internship is to develop a fluid dynamics characterization of the high-pressure flow used for cleaning the internal surface of the SRF cavities. Initially, the High Pressure Rinsing (HPR) process is introduced, focusing on the problems of the SRF cavities and how this method can be used to increase their acceleration efficiency and performance. The characterization of the problem is then presented, including an introduction to the multiphase flow modeling and the analysis of the Fermilab facility for the HPR. To accomplish the goal, a preliminary estimation of the variables was performed using MATLAB. Then, multiple 2D simulations were developed with Ansys Fluent, and the influence of the main parameter was investigated. The simulation results are then presented and analysed, with a focus on the possible future developments of the HPR process fluid dynamic characterization.
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IEEE APS & USNC-URSI 2022, Denver, CO, July 10-15, 2022
Superconducting radiofrequency (SRF) technology is being used not only in discovery science programs and basic research but also for several applications that benefit society more directly. The advantage of superconducting resonators over those made of normal-conducting metal is their ability to store electromagnetic energy with much lower dissipation. The high-quality factor and longer dissipation time provided by these superconducting resonators can deliver superior performance. Currently, the quantum processing architecture uses resonators and interconnecting circuits operating in the microwave regime with superconducting strip-line technology and low noise electronic devices for switching and communication. The performance of these devices can be enhanced by embedding them in 3D SRF cavity resonators to prolong the coherence time, which improves the utility of the device by reducing error rates and allowing more manipulations (calculations) before the quantum state decays. Here, we present a short review of current microwave technology used in quantum computers and progress towards the 3D resonators to enhance thecoherence time.
A dependable and consistent electron source is a crucial requirement for the achievement of high-power free electron lasers (FELs). Over the past two decades, it has been demonstrated that photoinjectors based on SRF technology (SRF guns) are suitable for continuous wave (CW) beam generation. SRF guns possess both the high accelerating field gradients of normal conducting RF photoinjectors and the low power dissipation thanks to mature SRF cavity technology, and therefore have the potential to provide the high-brightness, high-current beams required for CW-XFELs. After the demonstration of the first SRF gun in Dresden-Rossendorf, several SRF gun programs based on different approaches have achieved promising progress and even succeeded in routine operation. SRF guns are expected to play an important role in XFEL facilities in the near future. In this paper, we give an overview of design concepts, important parameters and development status of the worldwide SRF gun projects.
The manufacturing of active RF devices like klystrons is dominated by expensive and time-consuming cycles of machining and brazing. In this article, we characterize the RF properties of X-band klystron cavities and an integrated circuit manufactured with a novel additive manufacturing process. Parts are 3D printed in 316 L stainless steel with direct metal laser sintering, electroplated in copper, and brazed in one simple braze cycle. Stand-alone test cavities and integrated circuit cavities were measured throughout the manufacturing process. The un-tuned cavity frequency varies by less than 5% of the intended frequency, and Q factors reach above 1200. A tuning study was performed, and unoptimized tuning pins achieved a tuning range of 138 MHz without compromising Q. Klystron system performance was simulated with as-built cavity parameters and realistic tuning. Together, these results show promise that this process can be used to cheaply and quickly manufacture a new generation of highly integrated high power vacuum devices.
This work presents a detailed case study on using Generative AI (GenAI) to develop AI surrogates for simulation models in fusion energy research. The scope includes the methodology, implementation, and results of using GenAI to assist in model development and optimization, comparing these results with previous manually developed models.
Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. The machine learning models use a database of 16,000+ GENRAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods ensure that the database covers the range of 9 input parameters ($n_{e0}$, $T_{e0}$, $I_p$, $B_t$, $R_0$, $n_{||}$, $Z_{eff}$, $V_{loop}$, $P_{LHCD}$) with sufficient density in all regions of parameter space. The surrogate models reduce the inference time from minutes to ~ms with high accuracy across the input parameter space.
Abstract not provided.
An apparatus for generating a highly energetic plasma employs a low-energy neutral beam injected into a magnetically contained mirror plasma to produce plasma ions boosted in energy to fusion levels by a coordinated radiofrequency field.
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