CFD Analysis for Agglomeration Tank Design

With proper validation against physical testing, our CFD models consistently demonstrate strong agreement with real-world behavior, especially for flow patterns, mixing efficiency, and spray coverage.

Absolutely. We often help clients resolve issues like poor spray coverage, material settling, or low mixing efficiency.

Projects range from 2 to 6 weeks, depending on tank complexity and scope.

In further detail, these steps include:

1. Formulate the Flow Problem.
2. Model the Geometry and Flow Domain.
3. Establish the Boundary and Initial Conditions.
4. Generate the Grid.
5. Establish the Simulation Strategy.
6. Establish the Input Parameters and Files.
7. Perform the Simulation.
8. Monitor the Simulation for Completion.

• CFD simulations give engineers clear insights that help optimize design parameters and operating conditions. They assist in:
• Optimizing Impeller/Agitator Design: CFD compares different impeller types (such as pitched blade or Rushton turbine) and sizes to achieve the desired shear rates and flow patterns.
• Improving Tank Geometry: It evaluates height-to-diameter ratios, baffle designs, and bottom shapes to improve mixing and reduce dead zones or solid buildup.
• Ensuring Uniform Particle Distribution: CFD shows how solids move inside the tank, helping prevent sedimentation and uneven particle concentration.
• Scaling Up from Lab to Plant: CFD helps predict performance during scale-up, reducing the need for costly and time-consuming experiments

CFD can model many complex processes, often combined with Population Balance Models (PBM). These include:
• Multiphase Flow: Interaction of solids, liquids, and sometimes gases inside the tank.
• Turbulence and Shear Rates: Prediction of turbulence intensity and shear levels that influence particle breakage or growth.
• Heat and Mass Transfer: Temperature and concentration gradients, important for reactions, drying, or spray agglomeration.
• Particle Kinetics: Nucleation, growth, aggregation, and breakage of particles when PBM is coupled with CFD to predict final agglomerate size and shape.

CFD analysis involves pre-processing, solving, and post-processing. Key inputs required are:
• Geometry Model: A complete 2D or 3D tank model, including impellers, baffles, shafts, and nozzles.
• Material Properties: Density, viscosity, thermal properties, and any other physical properties of the involved phases.
• Boundary Conditions: Operating data such as inlet flow rates, agitator speed, velocities, pressure, and temperature.
• Physical Models: Appropriate turbulence models (like k-epsilon or SST) and multiphase models (such as VOF or the Discrete Phase Model).

While CFD is powerful, it has some limitations:
• Model Complexity: Agglomeration involves micro-scale flow behavior and chemical processes that are difficult to simulate accurately.
• Dependence on Sub-Models: CFD accuracy depends heavily on the quality of supporting models (like PBM) and reliable experimental data.
• High Computational Demand: Detailed 3D multiphase and PBM-coupled simulations need strong computing power and longer run times.
• Need for Validation: CFD results must be checked against real experimental data to ensure they match real-world performance.