arXiv subjects

Ursula van Rienen

Publications and source records attributed to Ursula van Rienen.

10 recordsLinked to original sources

arXiv2025

Beam-cavity interactions in the rapid cycling synchrotron chain of the future muon collider

The International Muon Collider Collaboration (IMCC) is engaged in a design study for a future facility intended to collide muons. Subsequent to the initial linear acceleration, the counter-rotating muons and anti-muons are accelerated in a chain of rapid cycling synchrotrons (RCS) up to the multi-TeV collision energy. To maximise the number of muons available in the collider, it is essential to exploit the time dilation of the muon lifetime by employing a large accelerating gradient. The 1.3 GHz TESLA cavity serves as the baseline for the RCS chain. Considering the high bunch population and the small aperture of the cavity, the resulting beam-induced voltage per bunch passage is considerable, resulting in a substantial perturbation of the cavity voltage for subsequent bunch passages. In this contribution, the effects of beam loading during the acceleration cycle on the muons are calculated with the objective of determining the optimum parameters for minimising the cavity voltage transients. The interaction of the induced voltages, considering the counter-rotating beams, is studied.

physics.acc-ph↗

arXiv2022

Muon Collider Physics Summary

The perspective of designing muon colliders with high energy and luminosity, which is being investigated by the International Muon Collider Collaboration, has triggered a growing interest in their physics reach. We present a concise summary of the muon colliders potential to explore new physics, leveraging on the unique possibility of combining high available energy with very precise measurements.

hep-ph↗

arXiv2020

rf measurements and tuning of the 1-meter-long 750 MHz radio-frequency quadrupole for artwork analysis

The 750 MHz PIXE-RFQ (radio-frequency quadrupole), developed and built at CERN, provides 2 MeV protons over a length of one meter for proton-induced X-ray emission analysis (PIXE) of cultural heritage artwork. In this paper, we report low-power rf measurements and tuning of the PIXE-RFQ, which have been completed mid-2020. Using a novel algorithm based on direct measurements of the response matrix, field and frequency could tuned at the same time in only two steps to satisfying accuracy. Additionally, we report measurements of single modules, quality factors, and coupling strength. In all cases, very good agreement between rf measurement and design values was observed.

physics.acc-ph↗

arXiv2020

An Artifact-based Workflow for Finite-Element Simulation Studies

Workflow support typically focuses on single simulation experiments. This is also the case for simulation based on finite element methods. If entire simulation studies shall be supported, flexible means for intertwining revising the model, collecting data, executing and analyzing experiments are required. Artifact-based workflows present one means to support entire simulation studies, as has been shown for stochastic discrete-event simulation. To adapt the approach to finite element methods, the set of artifacts, i.e., conceptual model, requirement, simulation model, and simulation experiment, and the constraints that apply are extended by new artifacts, such as geometrical model, input data, and simulation data. Artifacts, their life cycles, and constraints are revisited revealing features both types of simulation studies share and those they vary in. Also, the potential benefits of exploiting an artifact-based workflow approach are shown based on a concrete simulation study. To those benefits belong guidance to systematically conduct simulation studies, reduction of effort by automatically executing specific steps, e.g., generating and executing convergence tests, and support for the automatic reporting of provenance.

cs.CE↗

arXiv2020

Multi-objective design optimization of a Quadrupole Resonator under uncertainties

For a precise determination of the radio frequency (RF) properties of superconducting materials, a calorimetric measurement is carried out with the aid of a so-called Quadrupole Resonator (QPR). This procedure is affected by certain systematic measurement errors with various sources of uncertainties. In this paper, to reduce the impact of geometrical uncertainties on the measurement bias, the modified steepest descent method is used for the multi-objective shape optimization of a QPR {in terms of an expectation measure}. Thereby, variations of geometrical parameters are modeled by the Polynomial Chaos (PC) expansion technique. Then, the resulting Maxwell's eigenvalue problem with random input data is solved using the PC-based stochastic collocation method (PC-SCM). Furthermore, to assess the contribution of the particular geometrical parameters, the variance-based sensitivity analysis is proposed. This allows for modifying the steepest descent algorithm, which results in reducing the computational load needed to find optimal solutions. Finally, optimization results in the form of an efficient approximation of the Pareto front for a three dimensional (3D) model of the QPR are shown.

physics.acc-ph↗

arXiv2019

Uncertainty Modeling and Analysis of the European X-ray Free Electron Laser Cavities Manufacturing Process

This paper reports on comprehensive efforts on uncertainty quantification and global sensitivity analysis for accelerator cavity design. As a case study object the TESLA shaped superconducting cavities, as produced for the European X-ray Free Electron Laser (EXFEL), are selected. The choice for these cavities is explained by the available measurement data that can be leveraged to substantiate the simulation model. Each step of the manufacturing chain is documented together with the involved uncertainties. Several of these steps are mimicked on the simulation side, e.g. by introducing a random eigenvalue problem. The uncertainties are then quantified numerically and in particular the sensitivities give valuable insight into the systems behavior. We also compare these findings to purely statistical studies carried out for the manufactured cavities. More advanced, adaptive, surrogate modeling techniques are adopted, which are crucial to incorporate a large number of uncertain parameters. The main contribution is the detailed comparison and fusion of measurement results for the EXFEL cavities on the one hand and simulation based uncertainty studies on the other hand. After introducing the quantities of physical interest for accelerator cavities and the Maxwell eigenvalue problem, the details on the manufacturing of the EXFEL cavities and measurements are reported. This is followed by uncertainty modeling with quantification studies.

cs.CE↗

arXiv2019

Constrained multi-objective shape optimization of superconducting RF cavities considering robustness against geometric perturbations

High current storage rings, such as the Z-pole operating mode of the FCC-ee, require accelerating cavities that are optimized with respect to both the fundamental mode and the higher order modes. Furthermore, the cavity shape needs to be robust against geometric perturbations which could, for example, arise from manufacturing inaccuracies or harsh operating conditions at cryogenic temperatures. This leads to a constrained multi-objective shape optimization problem which is computationally expensive even for axisymmetric cavity shapes. In order to decrease the computation cost, a global sensitivity analysis is performed and its results are used to reduce the search space and redefine the objective functions. A massively parallel implementation of an evolutionary algorithm, combined with a fast axisymmetric Maxwell eigensolver and a frequency-tuning method is used to find an approximation of the Pareto front. The computed Pareto front approximation and a cavity shape with desired properties are shown. Further, the approach is generalized and applied to another type of cavity.

physics.acc-ph↗

arXiv2017

Low-Dimensional Stochastic Modeling of the Electrical Properties of Biological Tissues

Uncertainty quantification plays an important role in biomedical engineering as measurement data is often unavailable and literature data shows a wide variability. Using state-of-the-art methods one encounters difficulties when the number of random inputs is large. This is the case, e.g., when using composite Cole-Cole equations to model random electrical properties. It is shown how the number of parameters can be significantly reduced by the Karhunen-Loeve expansion. The low-dimensional random model is used to quantify uncertainties in the axon activation during deep brain stimulation. Numerical results for a Medtronic 3387 electrode design are given.

cs.CE↗

arXiv2017

Adaptive Estimation of the Neural Activation Extent in Computational Volume Conductor Models of Deep Brain Stimulation

Objective: The aim of this study is to propose an adaptive scheme embedded into an open-source environment for the estimation of the neural activation extent during deep brain stimulation and to investigate the feasibility of approximating the neural activation extent by thresholds of the field solution. Methods: Open-source solutions for solving the field equation in volume conductor models of deep brain stimulation and computing the neural activation are embedded into a Python package to estimate the neural activation dependent on the dielectric tissue properties and axon parameters by employing a spatially adaptive scheme. Feasibility of the approximation of the neural activation extent by field thresholds is investigated to further reduce the computational expense. Results: The varying extents of neural activation for different patient-specific dielectric properties were estimated with the adaptive scheme. The results revealed the strong influence of the dielectric properties of the encapsulation layer in the acute and chronic phase after surgery. The computational time required to determine the neural activation extent in each studied model case was substantially reduced. Conclusion: The neural activation extent is altered by patient-specific parameters. Threshold values of the electric potential and electric field norm facilitate a computationally efficient method to estimate the neural activation extent. Significance: The presented adaptive scheme is able to robustly determine neural activation extents and field threshold estimates for varying dielectric tissue properties and axon diameters while reducing substantially the computational expense.

q-bio.NC↗

arXiv2017

Uncertainty Quantification of Oscillation Suppression during DBS in a Coupled Finite Element and Network Model

Models of the cortico-basal ganglia network and volume conductor models of the brain can provide insight into the mechanisms of action of deep brain stimulation (DBS). In this study, the coupling of a network model, under parkinsonian conditions, to the extracellular field distribution obtained from a three dimensional finite element model of a rodent's brain during DBS is presented. This coupled model is used to investigate the influence of uncertainty in the electrical properties of brain tissue and encapsulation tissue, formed around the electrode after implantation, on the suppression of oscillatory neural activity during DBS. The resulting uncertainty in this effect of DBS on the network activity is quantified using a computationally efficient and non-intrusive stochastic approach based on the generalized Polynomial Chaos. The results suggest that variations in the electrical properties of brain tissue may have a substantial influence on the level of suppression of oscillatory activity during DBS. Applying a global sensitivity analysis on the suppression of the simulated oscillatory activity showed that the influence of uncertainty in the electrical properties of the encapsulation tissue had only a minor influence, in agreement with previous experimental and computational studies investigating the mechanisms of current-controlled DBS in the literature.

q-bio.NC↗