Scale-down process physical measurements

In all of the above cases, a strong non-linear coupling exists between reaction and transport at micro- and mesoscales, and the reactor performance at the macroscale. As a result, the physics at small scales influences the reactor and hence the process performance significantly. As stated in the introduction, such small-scale effects could be quantified by numerically solving the full CDR equation from the macro down to the microscale. However, the solution of the CDR equation from the reactor (macro) scale down to the local diffusional (micro) scale using CFD is prohibitive in terms of numerical effort, and impractical for the purpose of reactor control and optimization. Our focus here is how to obtain accurate low-dimensional models of these multi-scale systems in terms of average (and measurable) variables. 

There is enough published microscopy of foods (Aguilera and Stanley, 1999) to indicate that their structures are enormously variable and complex. The physical property of appearance is derived from the structure itself, and texture, flavour, taste, and subsequent bioavailability of nutrients are derived from the manner in which the structure collapses or breaks down. Simple theories of composite solids tell us that the spatial organisation of components and materials, their own physical properties and the interfacial interactions between them will determine overall properties. The components and materials themselves consist of molecular assemblies. This hierarchy of structure suggests we will need measurement at all length scales from molecular to macro structure and over timescales relevant to processing (milliseconds to hours) and product stability (minutes to months). 

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