Benefits:

• Insights into processes with limited measurability
• Visualization of mixing processes
• Determination of component characteristics (pressure drop, flow coefficient, etc.)
• Cost-efficient execution of virtual test series

Applications:

• Design and development of fittings, nozzles, and valves
• Food & beverage industry and pharmaceutical sector
• Plant engineering and process engineering
• Container construction and cleaning technology

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For a realistic representation, it is essential to choose a turbulence model that is suitable for mixing processes. In addition, wall friction losses must be represented. This allows the calculation of the momentum exchange in fittings and in the outflow area, as well as the mixing in the container.

Benefits:

• Plant optimization
• Product validation
• CFD as a cost-effective decision aid
• Insights into processes with limited measurability

Applications:

• Convection dryer/drying process
• Autoclave
• Infrared heating
• Laminating
• Afterheat effects in the engine

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In drying processes, components are heated to application-specific target temperatures, e.g., in convection dryers, to cure process materials. Co-simulation models both oven movement and heat conduction, enabling precise evaluation and economic optimization of product and system regarding temperature control and energy efficiency. Component temperatures can then be mapped onto finite element meshes for thermomechanical distortion analysis.

Benefits:

• Plant optimization
• Air entrapment and liquid drag out
• Insights into processes with limited measurability

Applications:

• Tank flow
• Coating
• Coating thickness
• Immersion processes and tank flow

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In immersion processes, CFD and FE simulations are used to analyze pressures, forces, and component deformations that may lead to plastic distortion or adhesive failure, allowing these risks to be minimized. VOF simulations identify residual liquids in components, which can then be removed through suitable openings or movements of the conveyor system. In addition, insights into the flow conditions support targeted optimization of the flow around components, making the overall process more efficient and reliable.

Benefits:

• Plant optimization
• Virtual validation and optimization of the product line
• Plant- and paint-specific calibration
• Insights into processes with limited measurability

Applications:

• Tank flow
• Air bubbles
• Liquid drag out
• Cathodic dip painting

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To ensure optimum corrosion protection, cathodic dip coating (CDC) processes are simulated. With multiphase (VOF) and e-coating models, the layer thicknesses, air inclusions, and their interaction can be determined, while overset meshes capture the dipping movement. Calibration cycles secure accuracy, and efficient meshing enables fast, automated calculation of complex geometries.

Lubrication of gears in gearboxes as well as splash lubrication in the field of machining are typical applications for complex multiphase simulations with moving parts. Here, wetted surfaces, drag losses, heat dissipation and other parameters can be determined in order to avoid wear problems or to understand existing damage patterns.

Continuous quantities of oil from the oil sump or oil jet are finely atomized and distributed by rotating parts. Precise numerical discretization and modelling of adhesion properties enable the recording of even the smallest quantities of oil and their interaction.

In addition, VOF simulations can be used to model filling processes, such as those that take place in cooling circuits or batteries, for example to localize and eliminate air pockets.

Benefits:

• Volumetric flow distribution across different flow regions
• Pressure losses
• Resistance torques due to shear and pressure forces
• Degree of wetting
• Heat dissipation

Applications:

• Oil-cooling E-motor
• Lubrication of gears in gearboxes
• Splash lubrication in the field of machining

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In the course of e-mobility, calculation methods are needed to calculate the cooling performance on the windings of electric motors. Due to the different state variables of the oil, these are highly complex calculations. Rotating oil jets break down into smaller and smaller droplets that form oil clouds because of the speed of rotation and the impact on the windings. An oil film forms on the windings and the walls, which ultimately collects at various points. Simultaneously, heat transfer and electromagnetism take place.

Thanks to hybrid multiphase models, such calculations can now be carried out with very good accuracy and at an affordable cost. The rotating oil jets are modeled with Mixture Multiphase in combination with Large Scale Interfaces (MMP-LSI). The decay into droplets is modeled by a Lagrangian phase and the droplet distribution by S-Gamma. A fluid film forms on the outer wall and the windings, into which the droplets can enter and merge. The possibility of combining these different models in a single simulation enables an efficient calculation.

Benefits:

• Volumetric flow rate as a function of rotational speed (characteristic curves)
• Visualization of flow paths and distribution enables the identification of areas with low cooling performance
• Derivation of optimization measures for improved flow around components
• Locating areas prone to high dirt accumulation

Applications:

• Air cooling power electronics
• Air cooling E-motor
• Air cooling battery pack
• Air cooling combustion engines

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The key to a long service life of power electronics lies in their effective cooling in order to maintain the maximum permissible temperatures. For the development and optimization of cooling systems, calculation methods are required that can model all heat transfer mechanisms (heat conduction, free/forced convection, heat radiation) as well as active cooling air flows, often generated by fan wheels. Rotating components can be modeled using a simplified, stationary and very efficient moving reference frame (MRF) approach.

Transient methods are physically more accurate and offer advantages in terms of the quality of results, but require more computing time. Transient effects can also be resolved using the actually rotating volume mesh.

Cooling calculations enable statements to be made about cooling air volumes, component temperatures and relevant heat paths. This allows the complete understanding of the system and the identification of optimization potential.

The video shows the free-form optimization of a geometry in which the mass flows at the two outlet openings should be identical and the pressure loss should be minimized. Instead of examining many geometries with a parameterized CFD optimization (e.g. HEEDS), the adjoint solver is used. This is a numerical algorithm that uses a target function to calculate which geometry provides the best result within a defined space.

The following four steps are performed:

1. First, a CFD simulation of the current design is carried out to determine the flow conditions and the output performance.

2. Then it is determined which specific variable is to be optimized, in this case the pressure loss and the mass flows.

3) The Adjoint Solver is used to determine how changes in geometry or boundary conditions affect the target function.

4. Based on the obtained data, the design is adjusted to improve the target function.

This process is repeated iteratively until the desired result is achieved.

In an example of massive forming wire winding, the wire wrapping process of a winding machine is simulated. Such simulations are used for CAD modeling of the wires, which prevents errors during manual winding creation in CAD from occurring. In addition, the simulation enables the actual process of the automatic production machine to be modeled digitally. This saves costs on the one hand by shortening the design time, and on the other hand digitally depicts how an electric motor coil winding machine works.

Interactions between fluids and freely moving solids are modeled using Dynamic Fluid Body Interaction simulations. Objects can be moved by nascent disturbance variables such as gravity, flow forces, static friction, etc. Examples of possible applications include immersion movements of ships, marine propellers and turbines of hydroelectric power plants or pneumatic valves.

In addition, the deformability of the body can be taken into account using fluid structure interaction simulations. This modeling method enables complex calculations, for example in the field of medical technology for heart valves, but also for the deformation of solar modules that are influenced by the wind.

Multiphase forming processes are forming processes that are carried out in several consecutive process steps in order to gradually shape a workpiece into the desired form. Different forming methods (bending, embossing, etc.) can be combined or a single process can be used in multiple stages.

Forming simulation provides information on material flow, process forces and occurring stresses and supports the design and optimization of processes.

During a drying process, high temperature gradients between the components lead to different expansion movements in the material mix of an assembly. These movements can be »frozen« by hardening adhesives, resulting in permanent deformations.

Based on the simulation, the joining technology and the components are optimized in critical areas. A detailed evaluation of the joining technology is also possible. The required temperature boundary conditions are determined by a previously performed CFD simulation or measurements and projected onto the FE mesh.

We have developed a universal process as part of a ZIM project due to the demands for high flexibility and great adaptability of our automation. Our employees are supported in the application of this process by our in-house simulation assistant. The wide range of included tools is supplemented by the following functions:

• Automatic geometry import and naming according to nomenclature
• Automatic setup (specification of boundary conditions in Excel or JSON format)
• Automatic Power Point evaluation for subsequent calculations

Calculation methods that are in high demand and whose development has been completed can be almost completely automated on the basis of the functions used in the simulation assistant.