Ziccum AB and project partner Zurich institute of Applied Sciences Updates LaminarPace Simulation Project Progress and Findings

Ziccum AB and project partner Zurich institute of Applied Sciences (ZHAW) have made a milestone review of the LaminarPace simulation (LaPaSim) project progress and findings. The complex, dynamic model digitally replicating the LaminarPace operation has been created and validated against comprehensive data sets created in physical trial runs and is now reaching a stage close to full completion. Ziccum can now perform trial runs in the 3D simulation environment, enabling the generation of vast amounts of data and in-depth understanding of optimal parameters and scale-out.

The LaPaSim project is developing a 3D multi-physical model of Ziccum?s unique drying technology LaminarPace to evaluate and predict key-performance-attributes, such as flow rates, temperatures, pressures and substance output, for a full range of LaminarPace applications. The project is a collaboration between Ziccum and the Institute of Computational Physics (ICP) at the School of Engineering at Zurich?s ZHAW University of applied sciences. The ICP Multiphysics Modeling and Imaging team, led by Professor Gernot Kurt Boiger, specialize in developing multi-physical models of complex industrial processes using mathematical models.

A 2-day workshop on 22 ? 23 February with Ziccum and the ICP team marked the completion of the latest stage of the project. Several milestones have been achieved: a 3D numerical simulation OpenFOAM model which accurately reflects LaminarPace's geometry and multi-dimensional parameter space is now close to completion.

The model can be adapted to a range of process-design-concepts and has cloud-computing compatibility for all scripts and software, meaning that it can be seamlessly integrated into chosen cloud platforms capable of Massive Simultaneous Cloud Computing. With the 3D model now set up, the LaminarPace development can proceed with trial runs in the 3D simulation environment, enabling the generation of vast amounts of data to gain in-depth understanding of optimal process parameters and how to best scale-out the technology to commercial scale.