Virtual milk for modelling and simulation of dairy processes

Area of Science:

• Chemical Engineering
• Food Science
• Process Simulation

Background:

• Generic process simulators lack specific milk components, limiting dairy process modeling accuracy.
• Previous work introduced pseudo-milk components for commercial simulators, but further validation and expansion were needed.

Purpose of the Study:

• To extend the pseudo-milk concept by investigating the impact of total solids and temperature on milk's physical properties.
• To develop predictive models for milk viscosity and heat capacity.
• To validate the enhanced pseudo-milk model against actual milk properties.

Main Methods:

• Studied the effect of total milk solids and temperature on thermal conductivity, density, viscosity, and heat capacity.
• Employed expanded fluid and power law models for viscosity prediction (4-75°C).
• Developed a regressed model for heat capacity based on temperature and fat content.

Main Results:

• Validated pseudo-milk components against actual milk properties, showing differences <2% (thermal conductivity), <4% (density), <3% (viscosity), and <1.5% (heat capacity).
• Successfully modeled viscosity and heat capacity across a wide temperature range and for different milk compositions.
• Demonstrated the capability to simulate diverse dairy processes with accurate material and energy balances.

Conclusions:

• The enhanced pseudo-milk model significantly improves the accuracy of dairy process simulations.
• This approach enables precise modeling of various milk types (whole, skim, concentrated) and their processing.
• Accurate prediction of physical properties is crucial for optimizing dairy manufacturing and energy efficiency.