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This paper presents a personal adventure through molecular thermodynamics that follows the footprints of John Prausnitz and leads toward the development of activity coefficient models for process modeling and process and product design of complex chemical systems.
Mathematical models for process simulation were developed.
Six Sigma models for process improvement include DMAIC and DMADV.
D-optimal method is conducted to develop mathematical models for process responses.
This chapter discusses the symbolic discretization of population models for process simulation.
In order to dynamically simulate the crushing circuit, models for process equipment need to be further developed.
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His main interests are in Network Science and in particular mathematical models for processes on dynamic networks.
It argues that the use of discrete time models for processes that are in fact evolving in continuous time produces problems that make their application in practice highly questionable.
It could also be useful in choosing appropriate models for processes in organisms, such as plants, that due to their long duplication times cannot be easily studied.
The method is derived in a linear setting, and is applied to two examples of previously published linear models for processes involved in photosynthesis.
This paper mainly focuses on the use of multi-models for process diagnosis.
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