Experimental Foundations of Chemical Engineering

Fundamental knowledge consists of understanding not only the models which correlate and rationalized observations but also the quantity and quality of the observations. The degree of correlation attempted should be consistent with this quantity and quality. The scientist correlates and rationalizes observations primarily to broaden his general understanding of the physical universe, and his efforts at correlation are more often than not a way of speculating on the future experiments which should be undertaken to test his concepts. For this purpose he is often satisfied with accuracy to one order of magnitude. The engineer, faced with the design and operation of expensive equipment, is almost always interested in a much higher accuracy in his correlations. Virtually all existing data in the rate processes are forced into rationalizations based upon either potential-diff erence or potential-gradient models. The application of these models to systems of even relatively simple geometry gives rise to mathematical complexity beyond present analytic ability. Even so, our ability to measure and observe seems to be far below our ability to analyze. These two models have been used effectively in chemical engineering in the past and have served to organize a great deal of information in the rate processes. Present research efforts appear to be directed primarily toward filling in gaps in available data and in refining the application of the models. We seem to suffer from a lack of models to test and a lack of data designed to test critically the existing models. There is relatively little exploratory research in chemical engineering as compared, for example, to physics. When one views chemical engineering as a chain extending from economics, markets, mechanical design, process design, and process development to process research, the uncertainties inherent in some of the links easily involve variances of 50 to 80%. Under these circumstances it would appear that the present orientation of research is distributed much too heavily toward refinement of existing ideas and not nearly enough toward exploration.