
Michael Schlottke-LakemperRWTH Aachen University · Applied and Computational Mathematics
Michael Schlottke-Lakemper
Dr.-Ing.
About
34
Publications
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289
Citations
Introduction
Additional affiliations
April 2019 - October 2021
May 2017 - February 2019
January 2012 - April 2017
Education
August 2009 - August 2010
October 2005 - December 2011
Publications
Publications (34)
TrixiParticles.jl is a Julia-based open-source package for particle-based multiphysics simulations and part of the Trixi Framework (Schlottke-Lakemper et al., 2021). It handles complex geometries and specialized applications, such as computational fluid dynamics (CFD) and structural dynamics, by providing a versatile platform for particle-based met...
HOHQMesh generates unstructured all-quadrilateral and hexahedral meshes with high order boundary information for use with spectral element solvers. Model input by the user requires only an optional outer boundary curve plus any number of inner boundary curves that are built as chains of simple geometric entities (lines and circles), user defined eq...
Data privacy is a significant concern in many environments today. This is particularly true if sensitive information, e.g., engineering, medical, or financial data, is to be processed on potentially insecure systems, as it is often the case in cloud computing. Fully homomorphic encryption (FHE) offers a potential solution to this problem, as it all...
We use the framework of upwind summation-by-parts (SBP) operators developed by Mattsson (2017, doi:10.1016/j.jcp.2017.01.042) and study different flux vector splittings in this context. To do so, we introduce discontinuous-Galerkin-like interface terms for multi-block upwind SBP methods applied to nonlinear conservation laws. We investigate the beh...
In this paper, we extend the Paired-Explicit Runge-Kutta schemes by Vermeire et. al. to fourth-order of consistency. Based on the order conditions for partitioned Runge-Kutta methods we motivate a specific form of the Butcher arrays which leads to a family of fourth-order accurate methods. The employed form of the Butcher arrays results in a specia...
Presenting the particle-based multiphysics solver TrixiParticles.jl
https://github.com/trixi-framework/TrixiParticles.jl
The full talk is available here:
https://www.youtube.com/live/V7FWl4YumcA?t=4667s
There is a pressing demand for robust, high-order baseline schemes for conservation laws that minimize reliance on supplementary stabilization. In this work, we respond to this demand by developing new baseline schemes within a nodal discontinuous Galerkin (DG) framework, utilizing upwind summation-by-parts (USBP) operators and flux vector splittin...
TrixiParticles.jl is a numerical simulation framework for particle-based multi-physics simulations implemented in Julia. Our primary goal is to provide a user-friendly open-source package, accessible also to those unfamiliar with particle-based methods. Therefore, TrixiParticles.jl is designed with easy extensibility in mind, allowing researchers t...
Many modern discontinuous Galerkin (DG) methods for conservation laws make use of summation by parts operators and flux differencing to achieve kinetic energy preservation or entropy stability. While these techniques increase the robustness of DG methods significantly, they are also computationally more demanding than standard weak form nodal DG me...
We study a temporal step size control of explicit Runge-Kutta (RK) methods for compressible computational fluid dynamics (CFD), including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler equations. We demonstrate that error-based approaches are convenient in a wide range of applications and compare them to m...
The Julia programming language has evolved into a modern alternative to fill existing gaps in scientific computing and data science applications. Julia leverages a unified and coordinated single-language and ecosystem paradigm and has a proven track record of achieving high performance without sacrificing user productivity. These aspects make Julia...
We study temporal step size control of explicit Runge-Kutta methods for compressible computational fluid dynamics (CFD), including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler equations. We demonstrate that error-based approaches are convenient in a wide range of applications and compare them to more cla...
We present Trixi.jl, a Julia package for adaptive high-order numerical simulations of hyperbolic partial differential equations. Utilizing Julia’s strengths, Trixi.jl is extensible, easy to use, and fast. We describe the main design choices that enable these features and compare Trixi.jl with a mature open source Fortran code that uses the same num...
Many modern discontinuous Galerkin (DG) methods for conservation laws make use of summation by parts operators and flux differencing to achieve kinetic energy preservation or entropy stability. While these techniques increase the robustness of DG methods significantly, they are also computationally more demanding than standard weak form nodal DG me...
We present Trixi.jl, a Julia package for adaptive high-order numerical simulations of hyperbolic partial differential equations. Utilizing Julia's strengths, Trixi.jl is extensible, easy to use, and fast. We describe the main design choices that enable these features and compare Trixi.jl with a mature open source Fortran code that uses the same num...
One of the challenges when simulating astrophysical flows with self-gravity is to compute the gravitational forces. In contrast to the hyperbolic hydrodynamic equations, the gravity field is described by an elliptic Poisson equation. We present a purely hyperbolic approach by reformulating the elliptic problem into a hyperbolic diffusion problem, w...
One of the challenges when simulating astrophysical flows with self-gravity is to compute the gravitational forces. In contrast to the hyperbolic hydrodynamic equations, the gravity field is described by an elliptic Poisson equation. We present a purely hyperbolic approach by reformulating the elliptic problem into a hyperbolic diffusion problem, w...
High parallel efficiency for large-scale coupled multiphysics simulations requires the computational load to be evenly distributed among all compute cores. For complex applications and massively parallel computations, even minor load imbalances can have a severe impact on the overall performance and resource usage. Exemplarily for a volume-coupled...
One of the main challenges for multiphysics simulations of volume-coupled problems is data exchange, which becomes a serious bottleneck for large-scale applications executed on distributed memory computer architectures. Unlike surface coupling, the transfer of volumetric information via network communication can be too inefficient. To circumvent th...
The complexity of parallel computer architectures continuously increases with the pursuit of exaflop computing, which makes accurate development effort estimation and modelling more important than ever. While sophisticated cost models are widely used in traditional software engineering, they have rarely been investigated for the performance-oriente...
Classic hybrid computational fluid dynamics - computational aeroacoustics simulations rely on disk I/O to exchange large volumes of data between the flow solver and the aeroacoustics solver, which considerably limits the scalability of the overall scheme. A direct-hybrid method is presented that eliminates this restriction by executing both solvers...
Classic hybrid methods for computational aeroacoustics use different solvers and methods to predict the flow field and the acoustic pressure field in two separate steps, which involves data exchange via disk I/O between the solvers. This limits the efficiency of the approach, as parallel I/O usually does not scale well to large numbers of cores. In...
Hybrid computational fluid dynamics (CFD) - computational aeroacoustics (CAA) schemes are the standard method for aeroacoustics simulations. This approach requires the exchange of information between the CFD and the CAA step, which is usually accomplished by storing acoustic source data. This data exchange procedure, however, poses two problems whe...
In this paper, a highly scalable numerical method is presented that allows to compute the aerodynamic sound from a turbulent flow field on HPC systems. A hybrid CFD-CAA method is used to compute the flow and the acoustic field, in which the two solvers are running in parallel to avoid expensive I/O operations for the acoustic source terms. Herein,...
Aeroacoustics simulations leverage the tremendous computational power of today’s supercomputers, e.g., to predict the noise emissions of airplanes. The emergence of GPUs that are usable through directive-based programming models like OpenACC promises a cost-efficient solution for flow-induced noise simulations with respect to hardware expenditure a...
A hybrid method for a fully coupled determination of aerodynamic sound is introduced. From the instantaneous velocity and vorticity, determined by approximate solutions of the Navier-Stokes equations, acoustic source terms are obtained, which are plugged into the acoustic perturbation equations being solved with a high-order discontinuous Galerkin...
In this work, a highly scalable numerical method is presented that allows to compute
the aerodynamic sound from the flow field for large-scale problems. The acoustic perturbation equations are solved by a high-order discontinuous Galerkin method and by using the acoustic source terms obtained from an approximate solution of the Navier-Stokes equati...
A hybrid method for a fully coupled determination of aero- dynamic sound is introduced. From the instantaneous velocity and vorticity, determined by approximate solutions of the Navier-Stokes equations, acoustic source terms are obtained, which are plugged into the acoustic perturbation equations being solved with a high-order discontinuous Galerki...
Todays HPC systems are increasingly utilizing accelerators to lower time to solution for their users and reduce power consumption. To utilize the higher performance and energy efficiency of these accelerators, application developers need to rewrite at least parts of their codes. Taking the C++ flow solver ZFS as an example, we show that the directi...
The efficient and accurate simulation of turbulent flows is one of the most challenging problems in the field of computational fluid dynamics. Due to the large number of scales present in the flow, very fine grids are required to fully capture all physical effects, which drives up computational times. In this thesis, a Kinetic Energy Simulation (KE...