Computational Engineering Science (B.Sc.), RWTH Aachen.
I build physics simulations and check the results against something I can trust: an analytical solution, a published benchmark, or real measured data. Mostly Python (NumPy and SciPy), with interactive demos in plain JavaScript. I am currently looking for a HiWi (student research assistant) position at a computational chair.
Portfolio: https://bypire.github.io · Email: muhammetemirfil@gmail.com
Bridge Weigh-in-Motion. Recovering a truck's axle weights from the bending response of a bridge, as a regularised Bayesian inverse problem. Tikhonov regularisation with an L-curve for the ill-posed tandem-axle case, and a credible interval calibrated from the model error. Verified against the Frýba closed-form solution and validated against sixteen months of real KW51 measurements. Live demo · Report · Code
Optimal Racing Line. The minimum-lap-time racing line computed as an optimal-control problem: arc-length direct collocation with hand-derived analytic Jacobians, solved as a nonlinear program. Verified against the closed-form skidpad lap time; 8.1 percent faster than the geometric centreline. Live demo · Report · Code
2D Navier-Stokes solver. A 2D incompressible Navier-Stokes solver written from scratch (staggered grid, projection method, immersed cylinder), verified against the Ghia lid-driven-cavity benchmark, then inverted into a vortex flow-meter that reads flow speed from the wake frequency. Live demo · Report · Code
Multiphysics Hub. A car driven in real time in the browser, coupling a four-wheel vehicle model, a 2D fluid, and a deflecting bridge. Each model is verified in Python and cross-checked against its JavaScript port. Live demo · Report · Code
Python (NumPy, SciPy, Matplotlib), JavaScript, Git, LaTeX. Methods: finite-element methods, time integration, optimal control and direct collocation, inverse problems and regularisation, Bayesian uncertainty, CFD.