3D bioprinting with cell containing bioinks show great promise in the biofabrication of patient specific tissue constructs. To fulfil the multiple requirements of a bioink, a wide range of materials and bioink composition are being developed and evaluated with regard to cell viability, mechanical performance and printability. It is essential that the printability and printing fidelity is not neglected since failure in printing the targeted architecture may be catastrophic for the survival of the cells and consequently the function of the printed tissue. However, experimental evaluation of bioinks printability is time-consuming and must be kept at a minimum, especially when 3D bioprinting with cells that are valuable and costly. This paper demonstrates how experimental evaluation could be complemented with computer based simulations to evaluate newly developed bioinks. Here, a computational fluid dynamics simulation tool was used to study the influence of different printing parameters and evaluate the predictability of the printing process. Based on data from oscillation frequency measurements of the evaluated bioinks, a full stress rheology model was used, where the viscoelastic behaviour of the material was captured. Simulation of the 3D bioprinting process is a powerful tool and will help in reducing the time and cost in the development and evaluation of bioinks. Moreover, it gives the opportunity to isolate parameters such as printing speed, nozzle height, flow rate and printing path to study their influence on the printing fidelity and the viscoelastic stresses within the bioink. The ability to study these features more extensively by simulating the printing process will result in a better understanding of what influences the viability of cells in 3D bioprinted tissue constructs.

A new framework for simulation of electrostatic spray painting is proposed based on novel algorithms for coupled simulations of air flow, electromagnetic fields, and paint droplets. Particularly important for the computational efficiency is the Navier-Stokes solver. The incompressible solver is based on a finite volume discretization on a dynamic Cartesian octree grid and unique immersed boundary methods are used to model the presence of objects in the fluid. This enables modeling of moving objects at virtually no additional computational cost and greatly simplifies preprocessing by avoiding the cumbersome generation of a body-conforming mesh. To validate the simulation framework an extensive measurement campaign has been performed. Several test plates and car fenders were painted with different process conditions and robot paths. The same cases were then simulated and overall the agreement between simulations and experiments are remarkably good. The very efficient implementation gives a major improvement of computational speed compared to other approaches and makes it possible to simulate spray painting of a full car in just a few hours on a standard computer.

In this paper a numerical multiscale method for discrete networks is presented. The method gives an accurate coarse scale representation of the full network by solving sub-network problems. The method is used to solve problems with highly varying connectivity or random network structure, showing optimal order convergence rates with respect to the mesh size of the coarse representation. Moreover, a network model for paper-based materials is presented. The numerical multiscale method is applied to solve problems governed by the presented network model.