Engineering topics

Neveu, Nicole

Publications and source records attributed to Neveu, Nicole.

3 records

DOE OSTI2023

Microphonics in the LCLS-II Superconducting Linac

The LCLS-II project has installed a new superconducting linac at SLAC that consists of 35 1.3 GHz cryomodules and 2 3.9 GHz cryomodules. The linac will provide a 4 GeV electron beam for generating soft and hard X-ray pulses. Cavity detuning induced by microphonics was a significant design challenge for the LCLS-II cryomodules. Cryomodules were produced that were within the detuning specification (10 Hz for 1.3 GHz cryomodules) on test stands. Here we present first measurements of the microphonics in the installed LCLS-II superconducting linac. Overall, the microphonics in the linac are manageable with 94% of cavities coming within the detune specification. Only two cavities are gradient limited due to microphonics. We identify a leaking cool down valve as the source of microphonics limiting those two cavities.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Comparison of multiobjective optimization methods for the $\mathrm{LCLS-II}$ photoinjector

Particle accelerators are among some of the largest science experiments in the world and can consist of thousands of components with a wide variety of input ranges. These systems can easily become unwieldy optimization problems during design and operations studies. Starting in the early 2000s, searching for better beam dynamics configurations became synonymous with heuristic optimization methods in the accelerator physics community. Genetic algorithms and particle swarm optimization are currently the most widely used. These algorithms can take thousands of simulation evaluations to find optimal solutions for one machine prototype. For large facilities such as the Linac Coherent Light Source (LCLS) and others, this equates to a limited exploration of many possible design configurations. In this paper, the LCLS-II photoinjector is optimized with three optimization algorithms. All optimizations were started from both a uniform random and Latin hypercube sample. In all cases, the optimizations started from Latin hypercube samples outperformed optimizations started from uniform samples. All three algorithms were able to optimize the photoinjector, with the model-based methods approximating the Pareto front in fewer simulation evaluations. This work, in combination with previous optimization observations, indicates objective penalties have a strong impact on the efficiency of such methods. In general, we recommend heuristic methods for initial optimizations and model-based methods when information about the objective space is available.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Algorithm 1028: VTMOP: Solver for Blackbox Multiobjective Optimization Problems

VTMOP is a Fortran 2008 software package containing two Fortran modules for solving computationally expensive bound-constrained blackbox multiobjective optimization problems. VTMOP implements the algorithm of [32], which handles two or more objectives, does not require any derivatives, and produces well-distributed points over the Pareto front. The first module contains a general framework for solving multiobjective optimization problems by combining response surface methodology, trust region methodology, and an adaptive weighting scheme. The second module features a driver subroutine that implements this framework when the objective functions can be wrapped as a Fortran subroutine. Lastly, support is provided for both serial and parallel execution paradigms, and VTMOP is demonstrated on several test problems as well as one real-world problem in the area of particle accelerator optimization.

97 MATHEMATICS AND COMPUTING↗