Population Balance Model (PBM)

What is the Population balance model (PBM)?

The Population Balance Model (PBM) is one of the concepts in collective phenomenology. This concept is used when components or particles move through state-space or during birth and death processes, the current particles are destroyed, and new particles are produced.

The main application of this model is related to currents that include a second phase with a specific size distribution. Particle size distribution, including solid particles, bubbles, droplets, etc., can evolve due to transfer within the base fluid or due to the occurrence of chemical reactions in a multiphase system. Evolutionary processes include nucleation, growth, Aggregation, and Breakage.

Population Balance Model

Consider, for example, a precipitation process. This process is related to forming solid particles from a liquid solution and consists of several processes, including nucleation, growth, Aggregation, failure, etc. These processes increase or decrease the number of particles of a specific size. So it can be said that PBM means balance in the number of particles with a particular state (for example, particle size in the example).

 PBM Application

The particle PBM is used in various topics, including crystallization processes, precipitative reactions, bubble columns, sprays, polymerization with fluidized bed, grain Granulation, liquid-liquid emulsion, aerosol flows, leaching metallurgy, liquid-liquid extraction, gas-liquid dispersion, liquid-liquid reactions, biology, etc.

Population Balance Equation Application

A PBM equation is needed to describe population or particle density changes in multiphase flows involving a given size distribution. This balance equation is commonly known as the PBM equation. In fact, in multiphase currents with particle distribution and the equilibrium equations of momentum, mass, and energy, the population balance equation must also be solved.

Population Balance Equations are defined in several branches of modern science (mainly chemical engineering). These equations describe the gradual evolution of particles and the motion of a particle population. In other words, these equations define how individual particle populations develop over time in a series of distinct thermophysical properties. These equations include a set of integral-partial differential equations (PDE), each of which presents the field behavior of a population of particles based on the behavior of each independent particle in the local state.

Population Balance Model

MR-CFD Population Balance Services

With several years of experience simulating a wide range of problems in various CFD fields using Fluent software, the MR-CFD team is ready to offer extensive modeling, meshing, and simulation services. Simulation Services for Population balance model are categorized as follows:

  • CFD Simulation of distribution kinetics of plastics decomposition
  • Crystallization processes CFD Simulation
  • CFD Simulation of the liquid-liquid extraction column
  • CFD Simulation of foam transport in porous media
  • Multiphase CFD simulation (nucleation, coalesce …)
  • CFD Simulation of gas-liquid dispersion and liquid-liquid reaction

You may find the related products in the categories mentioned above in our CFD shop by clicking on the following link:


Our services are not limited to the mentioned subjects. The MR-CFD team is ready to undertake different and challenging projects in the Population balance model field ordered by our customers. You can consult with our experts freely and without charge at first, and then order your project by sending the problem details to us using the following address.

[email protected]

By entrusting your project to the MR-CFD team, you will not only receive the related project’s files (Geometry, Mesh, Fluent files). Also, you will be provided with an extensive tutorial video demonstrating how you can create the geometry, mesh, and define the needed settings in the Fluent software all by yourself. And these all come with post-technical support from the MR-CFD team.


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