Codes

Neural network for data fitting. CUDA code for a neural network that fits a set of three‑dimensional data points (x,y,z). The neural network finds an approximating function f(x,y) that best fits the data. The implementation is written in CUDA and is designed to run on GPUs.
SPH magnetic particles Oldroyd-B in CUDA. Code for suspensions of magnetic particles in viscoelastic fluids written in CUDA to run on GPUs. The Oldroyd-B model is used for the solvent.
SPH magnetic particles in CUDA. Code for suspensions of magnetic particles written in CUDA to run on GPUs.
SPH Giesekus in CUDA. Code for viscoelastic suspensions written in CUDA to run on GPUs. The Giesekus model is used for the solvent.
SPH Oldroyd-B in CUDA. Code for viscoelastic suspensions written in CUDA to run on GPUs. The Oldroyd-B model is used for the solvent.
SPH in CUDA. Code for suspensions written in CUDA to run on GPUs.
Lubrication Dynamics biviscous. Code for suspensions in Newtonian and biviscous matrices with a lubrication dynamics model.
Lubrication Dynamics functionalised biviscous. Code for suspensions in functionalised biviscous matrices with a lubrication dynamics model.

Lubrication Dynamics with friction. Code for simulating suspensions of spherical particles in a fluid. The hydrodynamic interactions are modeled using lubrication. Variable Stribeck-curve dependent frictional forces are also introduced. Contact friction depend on load, sliding velocity and interstitail liquid viscosity. Particle spins are also considered.
SPH Brownian viscoelastic suspension. Code to simulate Brownian and non-Brownian suspensions with Newtonian and viscoelastic matrices using the SPH model.
SPH magnetic particles. Code for simulating suspensions with magnetic particles using the SPH method.
SPH fractional. Code for simulating fluids using the SPH integral viscoelastic method. A fractional model for the constitutive equation has been implemented.
SPH thixotropic. Code for simulating thixo-viscoplastic fluids using the SPH method.