In this course participants learn about the implications and reasons for scaling-up (or down) and the inherent associated difficulties. You learn to derive suitable scale-up criteria by systematic analysis of the situation and deriving relevant dimensionless numbers. The dimensional analysis (or ‘Pi-theorem’-) technique is an explicit learning goal. As scale-up might involve resolving conflicting criteria when complete process similarity can not achieved, a good problem analysis and making ‘best guess’ decisions (working with uncertainty) is important and will be practiced by case studies and in the final assignment.
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Introduction to scale-up (rationale, problems); Scale-up Problem Analysis (identification of relevant parameters); Dimensional Analysis for deriving dimensionless numbers for scale-up, Examples (analysis, deriving scale-up criteria, process similarity, pitfalls and successes), Case study (in class) and working on a new scale-up problem (in groups of 2 persons or individual)
Course structure: Lectures; individual written exam (pi-theorem), case studies (in class), group or individual assignment (small report + presentation)
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