Abstract

Spiral blast freezing is a common unit operation used in food processing facilities for rapidly freezing a variety of foodstuffs. The purpose of a blast freezer is to generate high velocity, low temperature air flow over food products being conveyed within refrigerated enclosures to accomplish the freezing process. However, air flow patterns observed within field operating blast freezers are often suboptimal, resulting in diminished system performance. This paper applies a Monte Carlo simulation technique to a food product freezing simulation in order to identify velocity profiles that optimize the freezing process. A one-dimensional food product model is used to evaluate the interplay between the time variation in the magnitude of the air velocity over food products conveyed through the freezing system and the resulting dwell time needed to achieve a target product core temperature at the blast freezer exit. Temporal heat transfer coefficients derived from field measurements made in a newly installed spiral blast freezer serve as a basis to calibrate the one-dimensional product model.The results of the Monte Carlo analysis show freezing system performance is improved when high and stable air velocities over the product are achieved early in the freezing process dwell time. Air flow patterns within a freezing system that result in high air velocity later in the freezing process dwell time are suboptimal. Field-measured data on a newly installed spiral blast freezer showed this suboptimal air flow pattern and the use of baffling within the spiral enables improved airflow leading to an estimated 10% increase in production throughput.

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