Multi-physics Simulations for Advanced Beamline Instrumentation at European XFEL

The European X-ray Free Electron Laser (European XFEL) is a research facility providing a 4th-generation light source. It generates ultra-intense, ultrashort X-ray flashes of 150 femtoseconds with MHz repetition rate. This world'™s largest X-ray laser is opening up completely new research opportunities for scientists and industrial users across disciplines, such as mapping atomic details of viruses, filming chemical reactions, and studying processes in the interior of planets. As the X-ray beam is transported through a 1.2 km-long tunnel from the undulators to the experimental hall, it interacts directly with numerous beamline components, which range from solid materials to liquid and gas media. It is a significant challenge for the engineering design of the beamline instrumentation, which is required to be able to sustain extremely high heat loads while transporting the highly coherent X-ray laser beam to the experimental hall. Consequently, numerical simulation modelling plays an important role in the system engineering process. In this contribution, a comprehensive multi-physics Finite Element simulation for a beam shutter is presented, including physical phenomena such as heat transfer, structural deformation, gas flow, and phase transitions. Since a beam shutter is a personal interlock component with the highest safety requirements in the radiation protection scheme, it is critical to determine the damage thresholds of such components. Various beam shutter materials, such as boron carbide, silicon, and CVD diamond have been studied in simulations and validated against experimental results. Furthermore, a Computational Fluid Dynamics (CFD) simulation is presented, focusing on characterization of nozzles for the liquid sheet jet sample delivery system. The nozzle geometry and fluid parameters have been studied parametrically to understand how these boundary conditions influence the flow performance of the liquid jet. High-fidelity simulations are often very time-consuming and computationally expensive. Recent advancements in numerical methods, such as Reduced Order Modelling (ROM), AI-empowered data-driven simulation algorithms, and simulation-based generative design enhanced by machine learning, have significantly reduced complexity of the simulation tasks. These advancements provide engineers with a deeper understanding of simulation data correlations, accelerate the iterative instrumentation design process, and therefore ensure safe, robust, and efficient facility operations at European XFEL.