A-polynomial-regression-machine-learning-approach-for-reliability-based-optimization:This is a compact code for reliability analysis under uncertainty using a Polynomial Regression Machine Learning approach. The code implements a stochastic response surface method (SRSM) which quantifies the uncertainty in a performance function for the purpose of reliability-based design optimization (RBDO).
laranuxt-starter-kit:Minimal Web Starter Kit based on Nuxt as Frontend and Laravel as Backend API.
SuperMirror:If a Swift type conforms to CustomReflectable, it's hard to reverse engineer it. This single-file library makes it super easy.
StokesFlowAxisymmetricBoundaryIntegralMethod:Compute the motion of droplets and particles in Stokes flows in axisymmetric domains using the Boundary Element Method (BEM) or the Spectral Boundary Integral Method (SBIM). The code is written in MATLAB with some possibility to use pre-compiled c-fuctions. The code includes: direct numerical simulations (DNS) with time stepping, Newton method, Continuation Method, Linear Stability Analysis and Edge Tracking Method.
