Abstract
Freezing processes are highly energy demanding and increased efficiency are both economically and
environmentally beneficial. However, industrial freezing plants are often not optimized regarding energy
efficiency. Operating conditions, such as the heat flow from the products, change during the process and air
flow and temperature distribution throughout the tunnel is uneven, resulting in different freezing times for
products at different locations. Measurements at plants are hard and expensive to conduct, so in order to be
able to predict fish temperatures and freezing times at any location within the tunnel, a discretized dynamic
model of an air blast freezing tunnel for fish, allowing different air velocities at different heights, has been
developed. The simulation results have been compared to measurements of air and product temperatures at
an industrial freezing plant and CFD simulation of the air velocity from a previous study. The results show
that the product temperatures can be well predicted with the simulation program.
environmentally beneficial. However, industrial freezing plants are often not optimized regarding energy
efficiency. Operating conditions, such as the heat flow from the products, change during the process and air
flow and temperature distribution throughout the tunnel is uneven, resulting in different freezing times for
products at different locations. Measurements at plants are hard and expensive to conduct, so in order to be
able to predict fish temperatures and freezing times at any location within the tunnel, a discretized dynamic
model of an air blast freezing tunnel for fish, allowing different air velocities at different heights, has been
developed. The simulation results have been compared to measurements of air and product temperatures at
an industrial freezing plant and CFD simulation of the air velocity from a previous study. The results show
that the product temperatures can be well predicted with the simulation program.
