Finite element and population balance models for food-freezing processes



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Kansas State University


Energy consumption due to dairy production constitutes 10% of all energy usage in the U.S. Food Industry. Improving energy efficiency in food refrigeration and freezing plays an important role in meeting the energy challenges of today. Freezing and hardening are important but energy-intensive steps in ice cream manufacturing. This thesis presents a series of models to address these issues. The first step taken to model energy consumption was to create a temperature-dependent ice cream material using empirical properties available in the literature. The homogeneous ice cream material is validated using finite element analysis (FEA) and previously published experimental findings. The validated model is then used to study the efficiency of various package configurations in the ice cream hardening process. The next step taken is to consider product quality by modeling the ice crystal size distribution (CSD) throughout the hardening process. This is achieved through the use of population balance equations (PBE). Crystal size and corresponding hardened ice cream coarseness can be predicted through the PBE model presented in this thesis. The crystallization results are validated through previous experimental study. After the hardening studies are presented, the topic of continuous freezing is discussed. The actual ice cream continuous freezing process is inherently complex, and therefore simplifying assumptions are utilized in this work. Simulation is achieved through combined computational fluid dynamics (CFD) and PBE modeling of a sucrose solution. By assuming constant fluid viscosity, a two-dimensional cross section is able to be employed by the model. The results from this thesis provide a practical advancement of previous ice cream simulations and lay the groundwork for future studies.



Finite element analysis, Ice cream, Constitutive modeling, Energy systems, Manufacturing, Population balance equations

Graduation Month



Master of Science


Department of Mechanical and Nuclear Engineering

Major Professor

Xiao J. Xin