ABSTRACT

Temperature Prediction ................................................................................ 163 6.2.1 Temperature Profi le Prediction ......................................................... 163 6.2.2 Thermophysical Properties Prediction .............................................. 165

6.3 Conductive Models Solved by Applying the Finite Difference Method ............................................................................. 166 6.3.1 Temperature Distribution Prediction ................................................. 166 6.3.2 Enzyme and Microbial

Inactivation Prediction ...................................................................... 168 6.4 Convective Models Solved by Applying

Computational Fluid Dynamics .................................................................... 170 6.4.1 Prediction of Temperature Uniformity

and Velocity Distribution................................................................... 170 6.4.1.1 Infl uence of Infl ow Velocity

on Temperature Distribution ............................................... 170 6.4.1.2 Infl uence of Fluid Viscosity on Temperature

Uniformity and Flow ........................................................... 172 6.4.1.3 Flow Fields Predicted and Measured Inside a High-

Pressure Vessel .................................................................... 173 6.4.1.4 Infl uence of the Vessel Boundaries on Temperature

Uniformity ........................................................................... 173 6.4.1.5 Vessel Boundary for Turbulent Conditions: The

Logarithmic Wall Function ................................................. 175 6.4.1.6 Temperature and Flow in Vessels with Packages at

Various Scales ..................................................................... 175

6.4.1.7 Temperature Uniformity in a Pressure Vessel Containing Solid Food Materials ........................................ 178

6.4.1.8 Effect of Adding a Carrier on Temperature Uniformity and Flow ..................................... 179

6.4.2 Coupling of CFD Models with Enzyme and Microbial Inactivation Kinetic Models .............................................................. 182 6.4.2.1 Prediction and Quantifi cation

of Residual α-Amylase and E. Coli Inactivation ................ 183 6.4.2.2 Distribution of C. botulinum Inactivation

in a Pilot-Scale Vessel ......................................................... 184 6.4.2.3 Timescale Analysis: Infl uence of Pressure

Vessel Size on Temperature Distribution ............................ 188 6.5 Macroscopic Model to Represent Processing

Conditions in an Entire High-Pressure System ............................................ 193 6.6 Application of Artifi cial Neural Networks

for High-Pressure Process Temperature Prediction ..................................... 196 6.7 Comparison of Capabilities

of Existing Models ........................................................................................ 199 6.8 Concluding Remarks .....................................................................................202 Nomenclature .........................................................................................................203 References ..............................................................................................................206