The phrase "agglomeration model" is correct and usable in written English.
It can be used in discussions related to urban planning, economics, or geography, particularly when referring to theories or frameworks that explain the clustering of industries or populations.
Example: "The agglomeration model suggests that businesses benefit from being close to one another, leading to increased efficiency and innovation."
Alternatives: "clustering model" or "concentration model".
A combined imbibition drying model is developed and included into a comprehensive stochastic agglomeration model that allows the simulation of agglomerate formation in a batch process.
The consistency between the agglomeration model and new experimental data is concluded to be satisfactory.
Accordingly, we developed an agglomeration model that accounts for the influence of particle size on the threshold voltage.
The agglomeration model suggests in accordance with previous studies that increasing the nozzle pressure as well as coating-solution-dry-matter-concentration decreases the tendency of agglomeration.
The present study introduces a stochastic Lagrangian agglomeration model to be applied within the framework of the classical Euler/Lagrange approach.
There has long been a need for a mathematical gibbsite agglomeration model that is both capable of describing the process and is easy to implement.
Penn State has developed an agglomeration modeling methodology that considers non-uniform temperature, gaseous atmosphere and heterogeneity in ash chemical composition to predict slag-liquid formation and agglomerate growth rate.
Turbulent shear and inertial particle agglomeration models (Allen and Smith 2001; Saffmann and Turner 1988) define the agglomeration rate of aerosol particles based on their sticking efficiency, particle radius, fluid properties and turbulent energy dissipation rate.
Thus, taking the above described agglomeration models into account, 0.1% up to 5.8% and 0.3% up to 0.9% of the delivered 25 nm and 85 nm NPs entered the cells, respectively.
Large observed SIR are smoothed towards 1 in all three approaches, i.e. for those agglomerations model predicted SIRs are closer to 1 and the agglomeration is represented in Figure 4 with a point below the line of equality.
The agglomeration efficiency model was validated by incorporating it into a population balance model of a laboratory precipitator and demonstrating good agreement between the simulated dynamic particle size distributions and the experimental values.
