Simlab

In the Simulation Laboratory we develop and use numerical simulations to address industrial scale engineering problems. We are problem solvers and enablers at heart and see a numerical simulation as a tool to address a specific technical challenge. This is why our expertise ranges from fluid flow, thermodynamics and structural dynamics  to fully coupled multiphysical systems. We provide simulation know-how in a wide range of industries  like chemical, food and pharma, automotive and aerospace, buildings and tunnelling as well as turbo-machinery. And our presence does not end with the delivery of the results. We stop when you feel you have got what you need.

You need to solve a complex technical problem and there are no resources for a time-consuming trial and error approach? Or you wish to introduce a simulation environment in your business unit but do not know where to start? Here we are. Whether it is a specific technical challenge or a general strategic consulting, we place your company at the forefront of computational technology. Get it right the first time and let us close the gap for you!

Simulation Portfolio

CFD

CFD stands for Computational Fluid Dynamics and means the analysis of fluid flow through the use of numerical methods. Typical fields of applications are laminar or turbulent Aero- and Hydrodynamics.

FEA

FEA stands for Finite Element Analysis and means the analysis of physical systems through the use of the Finite Element Method. Typical fields of applications are linear or non-linear structural analysis.

Multiphysics

Multiphysics Simulations are used when a number of different physical processes are involved. The governing equations of the single processes are typically coupled in time and space and describe a system as whole.

Simulation Tools

OpenFOAM

OpenFOAM (Open Source Field Operation and Manipulation) is a C++ toolbox predominantly used in the field of CFD.

Ansys Workbench

A commercial multiphysics software toolbox including CFD, FEM, Electromagenitism and more.

MixIT

A software tool based on OpenFOAM specifically developed for reactor flow modelling in the chemical industry.

Case Studies

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Prevent Sedimentation

Determine suitable vessel equipment and operating conditions based on CFD

Many processes like crystallization, vial filling or emulsification require a homogeneous dispersion of the particles. There are a number of parameters involved that determine the homogeneity, like reactor characteristics, solids loading, particle properties and more. Sedimentation needs to be avoided to maximize the yield and to obtain constant quality throuout the entire bulk. This case study shows how this can be addresses using CFD.

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Powder Dissolution

Derive powder dissolution conditions to prevent lump formation based on CFD

For some powder dissolution processes where matching the specific dissolution kinetics of the powder is critical to the drug product quality, it is essential to derive suitable process conditions. The dissolution conditions at lab scale can differ significantly from those at industrial scale. With CFD these conditions can be modelled with sufficiently high resolution in space and time, to ensure sufficient dissolution also at industrial scale.

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Robust Crystallization

Determine the ideal antisolvent addition position based on CFD

The antisolvent addition position is often not considered as one of the crucial parameters for a robust crystallization. However, at lab scale, mixing times are tyically several orders of magnitude shorter than at pilot or industrial scale. Hence, when scaling up the process, adverse scale effects can be observed. This is very costly and can also lead to a delay of the launch. See how the risk of adverse scale effects due to an unfvourable antisolvent addition strategy can be decreased.

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FAQ Toggle Section

This depends on the simulation problem and on the preferences of the customer. E.g. a research question can be addressed with a commercial tool like Ansys but also with the open scource tool like OpenFOAM. Sometimes customers prefer one or the other tool, e.g. due to better comparability with former calculations or to be able to further process the calculations internally. We can address this since we have the same level of proficiency for both tools.

We are experienced in handling computationally intensive cases through parallel computing on several hundert cores on high performance computer (HPC) clusters. With the available cloud services the number of cores is not what determines the computational time anymore but rather the computational case itself. 

We follow a white-box approach and provide the entire model for further use at the end of the project including the raw data to ensure replicability.