In spring 2021 I joined forces with three classmates, and as part of the ETH lecture “Advanced Systems Lab” we revisited the FLIP Fluids Solver project from two years prior. The goal this time was to optimise the code using the skills acquired in this lecture and improve the time required to run a simulation.
In the academic year 2019-2020 I joined ARIS Space, the student association for space in german Switzerland. There I joined team EULER, whose mission statement was to build a sounding rocket for the 2020 Spaceport America Cup competition which would reach the target apogee of 30,000 feet (9.144 km) with as much precision as possible.
My Batchelor’s Thesis was titled “Comparative study of density-based versus pressure-based solvers for supersonic flow”. The idea of the thesis stemmed from my work at ARIS, where one of the natural questions that arose was which solver would be best for my use case: simulating the aerodynamics of a supersonic sounding rocket. Under the supervision
Before running any CFD simulations we need to generate a mesh around our geometry to perform calculations on. This page is meant to document the standard process we use to generate this mesh for ARIS rockets. Inputs: Geometry exported from some CAD software in named STL format. The sample OpenFOAM case folder (ofcase_heidi_fullbody_meshing) Outputs: 3D
This page is meant as a brief overview and reference of the principal components of rocket aerodynamics, such as aerodynamic forces and design of nose cone, fins and boat-tail.
This page is meant as a reference of the principal components and other useful information about the OpenFOAM CFD toolkit.
Below is a simple implementation of the producer-consumer parallel strategy with MPI. It’s just a dummy example, and could probably be improved greatly, but it is a nice illustration of the producer-consumer model, as well as uses for MPI_ANY_SOURCE, MPI_ANY_TAG, and MPI_Status. #include <stdio.h> #include <mpi.h> #include <time.h> #include <stdlib.h> #include <math.h> // Producer-consumer scheme
CUDA is a very powerful API which allows us to run highly parallel software on Nvidia GPUs. It is typically used to accelerate specific operations, called kernels, such as matrix multiplication, matrix decomposition, training neural networks et cetera. One such common operation is a reduction: adding up a long array of numbers. One simple implementation
This is a summary of the introductory lecture to the coure Image Analysis and Computer Vision which I took at ETH in the autumn semester 2018. Interaction of light and matter Interactions of light and matter be divided into three main types (plus diffraction). Phenomenon Example Absorption Blue water Scattering Blue sky, red sunset Reflection
In the autumn semester of 2018 I took the course Robot Dynamics. The summary I took with me to the exam is available here in PDF format as well as in LaTeX format. Here’s an overview of the topics the course covered: Kinematics Rotation and angular velocity Rigid Body Formulation Homogeneous transformations Kinematics of systems