How-To Guides¶

Modeling Chemical Reactions: Model a chemical reaction in M-Star CFD.
Modeling Inlet and Outlet Boundary Conditions: Discover how inlet and outlet boundary conditions are defined, created, and applied in M-Star CFD; and get guidance on configuration options, best practices, and common pitfalls.
Cooling and Dilution: Predict thermal blending in the tank, and look for temperature differences; predict the minimum residence time of the scalar field, and look for bypassing.
Choosing a Simulation Resolution: Agitated Tanks: Predict the effects of resolution on power number across a range of Reynolds numbers for multiple impellers. From this output, we will provide guidance on recommended simulation resolutions.
Loading Initial State: Use a previously run simulation result as an initial condition.
Predicting Mass Transfer (kLa) in Gasified Bioreactors: Model a sparged, benchtop bioreactor with bubble breakup and carbon dioxide production. Bioreactor performance and yield is typically informed by the overall transport rate of oxygen from gas bubbles to an agitated fluid.
Mixing Bioreactors with Bottom Mounted Impellers: Predict single- and multi-fluid blending in tall tanks.
Computing Blend Time on any Model: Perform a blend-time calculation. We will use a scalar impulse injection in combination with a global variable reduction.

Advanced Modeling¶

Implementing Custom Rheology in T-Junction Pipe: Mix a custom non-Newtonian liquid with water. Examine both a simple linear combination of the viscosities and an enhanced mixing with a static mixing element.
Using Custom Particle Variables to Track Particle Exposure: Configure custom particle variables to capture hydrodynamic conditions and gain valuable insight into the particles’ exposure to local fluid conditions.
Implementing a Simple Feedback Controller: Establish a feedback-loop–controlled CFD setup.
JKR Adhesion and Capillary Bridging Interaction Model for DEM: Explore a Discrete Element Method (DEM) interaction model designed for simulating cohesive granular materials.
Predicting Residence Time Distribution: Predict residence time distribution and minimum time of flight.

Optimizing Impeller Position: Simple: Optimize the position of the middle one of three impellers mounted on the same axis to achieve maximum energy input.
Optimizing Bubble Models: Complex: Optimize the kLa model to reproduce three experimental measurements through breakup and coalescence adjustments.

Using DOE in M-Star CFD: Use an external design of experiments (DOE) software with M-Star CFD.