Andreas Lintermann
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View article: Comparative analysis of the flow in a realistic human airway
Comparative analysis of the flow in a realistic human airway Open
Accurate simulations of the flow in the human airway are essential for advancing diagnostic methods. Many existing computational studies rely on simplified geometries or turbulence models, limiting their simulation's ability to resolve flo…
View article: Resource-adaptive successive doubling for hyperparameter optimization with large datasets on high-performance computing systems
Resource-adaptive successive doubling for hyperparameter optimization with large datasets on high-performance computing systems Open
View article: Towards a widespread usage of computational fluid dynamics simulations for automated virtual nasal surgery planning
Towards a widespread usage of computational fluid dynamics simulations for automated virtual nasal surgery planning Open
View article: Parallel Reinforcement Learning and Gaussian Process Regression for Improved Physics-Based Nasal Surgery Planning
Parallel Reinforcement Learning and Gaussian Process Regression for Improved Physics-Based Nasal Surgery Planning Open
Septoplasty and turbinectomy are among the most frequent but also most debated interventions in the field of rhinology. A previously developed tool enhances surgery planning by physical aspects of respiration, i.e., for the first time a re…
View article: Surrogate Modeling of Fluid Flow Under Different Conditions Using Physicsinformed Deep Operator Networks
Surrogate Modeling of Fluid Flow Under Different Conditions Using Physicsinformed Deep Operator Networks Open
View article: Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems
Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems Open
On High-Performance Computing (HPC) systems, several hyperparameter configurations can be evaluated in parallel to speed up the Hyperparameter Optimization (HPO) process. State-of-the-art HPO methods follow a bandit-based approach and buil…
View article: Parallel and scalable AI in HPC systems for CFD applications and beyond
Parallel and scalable AI in HPC systems for CFD applications and beyond Open
This manuscript presents the library AI4HPC with its architecture and components. The library enables large-scale trainings of AI models on High-Performance Computing systems. It addresses challenges in handling non-uniform datasets throug…
View article: Prediction of Turbulent Boundary Layer Flow Dynamics with Transformers
Prediction of Turbulent Boundary Layer Flow Dynamics with Transformers Open
Time-marching of turbulent flow fields is computationally expensive using traditional Computational Fluid Dynamics (CFD) solvers. Machine Learning (ML) techniques can be used as an acceleration strategy to offload a few time-marching steps…
View article: Distributed hybrid quantum-classical performance prediction for hyperparameter optimization
Distributed hybrid quantum-classical performance prediction for hyperparameter optimization Open
Hyperparameter optimization (HPO) of neural networks is a computationally expensive procedure, which requires a large number of different model configurations to be trained. To reduce such costs, this work presents a distributed, hybrid wo…
View article: On the choice of physical constraints in artificial neural networks for predicting flow fields
On the choice of physical constraints in artificial neural networks for predicting flow fields Open
The application of Artificial Neural Networks (ANNs) has been extensively investigated for fluid dynamic problems. A specific form of ANNs are Physics-Informed Neural Networks (PINNs). They incorporate physical laws in the training and hav…
View article: Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations
Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations Open
Accurately computing the flow in the nasal cavity with computational fluid dynamics (CFD) simulations requires highly resolved computational meshes based on anatomically realistic geometries. Such geometries can only be obtained from compu…
View article: Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields
Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields Open
The robustness of an artificial neural network that performs model order reduction for flow field data is studied. The network is trained with a large-scale distributed learning approach using up to 6,259 nodes of the supercomputer Fugaku.…
View article: Distributed Hybrid Quantum-Classical Performance Prediction for Hyperparameter Optimization
Distributed Hybrid Quantum-Classical Performance Prediction for Hyperparameter Optimization Open
Hyperparameter Optimization of neural networks is a computationally expensive procedure, which requires a large number of different model configurations to be trained. To reduce such costs, this work presents a distributed, hybrid workflow…
View article: Turbulent Flow Prediction-Simulation: Strained Flow with Initial Isotropic Condition Using a GRU Model Trained by an Experimental Lagrangian Framework, with Emphasis on Hyperparameter Optimization
Turbulent Flow Prediction-Simulation: Strained Flow with Initial Isotropic Condition Using a GRU Model Trained by an Experimental Lagrangian Framework, with Emphasis on Hyperparameter Optimization Open
This study presents a novel approach to using a gated recurrent unit (GRU) model, a deep neural network, to predict turbulent flows in a Lagrangian framework. The emerging velocity field is predicted based on experimental data from a strai…
View article: Automated surgery planning for an obstructed nose by combining computational fluid dynamics with reinforcement learning
Automated surgery planning for an obstructed nose by combining computational fluid dynamics with reinforcement learning Open
Septoplasty and turbinectomy are among the most common interventions in the field of rhinology. Their constantly debated success rates and the lack of quantitative flow data of the entire nasal airway for planning the surgery necessitate m…
View article: Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems
Resource-Adaptive Successive Doubling for Hyperparameter Optimization with Large Datasets on High-Performance Computing Systems Open
View article: Impact of the injector lateral offset on the dynamics of a lean premixed flame and the thermoacoustic stability of a burner
Impact of the injector lateral offset on the dynamics of a lean premixed flame and the thermoacoustic stability of a burner Open
The response of a laminar lean premixed flame to excitations based on its position in the combustion chamber and the stability of a burner are numerically investigated. A finite-volume large-eddy simulation method is used to solve the comp…
View article: interTwin D6.1 Report on requirements and core modules definition
interTwin D6.1 Report on requirements and core modules definition Open
interTwin co-designs and implements the prototype of an interdisciplinary Digital Twin Engine (DTE). The developed DTE will be an open source platform that includes software components for modelling and simulation to integrate application-…
View article: Large scale performance analysis of distributed deep learning frameworks for convolutional neural networks
Large scale performance analysis of distributed deep learning frameworks for convolutional neural networks Open
Continuously increasing data volumes from multiple sources, such as simulation and experimental measurements, demand efficient algorithms for an analysis within a realistic timeframe. Deep learning models have proven to be capable of under…
View article: Table of Contents
Table of Contents Open
View article: Speed-Up of Machine Learning for Sound Localization via High-Performance Computing
Speed-Up of Machine Learning for Sound Localization via High-Performance Computing Open
Sound localization is the ability of humans to determine the source direction of sounds that they hear. Emulating this capability in virtual environments can have various societally relevant applications enabling more realistic virtual aco…
View article: Correction to: Machine-Learning-Based Control of Perturbed and Heated Channel Flows
Correction to: Machine-Learning-Based Control of Perturbed and Heated Channel Flows Open
Chapter “Machine-Learning-Based Control of Perturbed and Heated Channel Flows” was previously published non-open access. It has now been changed to open access under a CC BY 4.0 license and the copyright holder updated to ‘The Author(s)’.
View article: A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows
A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows Open
Many simulation workflows require to prepare the data for the simulation manually. This is time consuming and leads to a massive bottleneck when a large number of numerical simulations is requested. This bottleneck can be overcome by an au…
View article: An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology
An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology Open
View article: Effects of the Nasal Cavity Complexity on the Pharyngeal Airway Fluid Mechanics: A Computational Study
Effects of the Nasal Cavity Complexity on the Pharyngeal Airway Fluid Mechanics: A Computational Study Open
View article: Machine-Learning-Based Control of Perturbed and Heated Channel Flows
Machine-Learning-Based Control of Perturbed and Heated Channel Flows Open
A reinforcement learning algorithm is coupled to a thermal lattice-Boltzmann method to control flow through a two-dimensional heated channel narrowed by a bump. The algorithm is allowed to change the disturbance factor of the bump and rece…
View article: Numerical Analysis of Oscillatory Flows in the Human Brain by a Lattice-Boltzmann Method
Numerical Analysis of Oscillatory Flows in the Human Brain by a Lattice-Boltzmann Method Open
The cerebrospinal fluid flow in a brain ventricular system is analyzed by the numerical approach employing a lattice-Boltzmann (LB) method. The cerebrospinal fluid, which surrounds the human brain and spinal cord, fills the cerebral ventri…
View article: Hybrid datasets: Incorporating experimental data into Lattice‐Boltzmann simulations
Hybrid datasets: Incorporating experimental data into Lattice‐Boltzmann simulations Open
Summary A novel method, which combines both fluid‐mechanical experimental and numerical data from magnetic resonance velocimetry and Lattice‐Boltzmann (LB) simulations is presented. The LB method offers a unique and simple way of integrati…
View article: Lattice–Boltzmann simulations for complex geometries on high-performance computers
Lattice–Boltzmann simulations for complex geometries on high-performance computers Open
Complex geometries pose multiple challenges to the field of computational fluid dynamics. Grid generation for intricate objects is often difficult and requires accurate and scalable geometrical methods to generate meshes for large-scale co…
View article: Zonal Flow Solver (ZFS): a highly efficient multi-physics simulation framework
Zonal Flow Solver (ZFS): a highly efficient multi-physics simulation framework Open
Multi-physics simulations are at the heart of today's engineering applications. The trend is towards more realistic and detailed simulations, which demand highly resolved spatial and temporal scales of various physical mechanisms to solve …