Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

The formal representation of process system modelling assumptions and their implications

In order to analyse the effect of modelling assumptions in a formal, rigorous way, a syntax of modelling assumptions has been defined. The syntax of modelling assumptions enables us to represent modelling assumptions as transformations acting on the set of model equations. The notion of syntactical correctness and semantical consistency of sets of modelling assumptions is defined and methods for checking them are described. It is shown on a simple example how different modelling assumptions act on the model equations and their effect on the differential index of the resulted model is also indicated.

Design analysis for refolding monomeric protein

Renaturation of protein expressed as inclusion bodies within Escherichia coli is a key step in many bioprocesses. Operating conditions for the refolding step dramatically affect the amount of protein product recovered, and hence profoundly influence the process economics. The first systematic comparison of refolding conducted in batch, fed-batch and continuous stirred-tank reactors is provided Refolding is modeled as kinetic competition between first-order refolding (equilibrium reaction) and irreversible aggregation (second-order). Simulations presented allow direct comparison between different flowsheets and refolding schemes using a dimensionless economic objective. As expected from examination of the reaction kinetics, batch operation is the most inefficient merle. For the base process considered, the overall cost of fed-batch and continuous refolding is virtually identical (less than half that of the batch process). Reactor selection and optimization of refolding using overall economics are demonstrated to be vitally important.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Effects of process modification and heat pump drying on physical and sensory properties of Chinese style shredded beef

Chinese-style dried, shredded meat is traditionally prepared by sequential cooking, shredding, pre-drying, and final drying (roasting) of lean meat. In this study, shredded dried beef (a(w)<0.6) was prepared by omitting roasting but prolonging pre-drying. Sensory scores of the modified product were lower than those for the traditional product. When heat pump drying replaced traditional oven drying, drying time was shortened without significant difference in quality attributes. Desorption curves were established for shredded beef at several drying temperatures.

Genetic algorithms for continuous optimization problems - a concept of parameter-space size adjustment

The concept of parameter-space size adjustment is pn,posed in order to enable successful application of genetic algorithms to continuous optimization problems. Performance of genetic algorithms with six different combinations of selection and reproduction mechanisms, with and without parameter-space size adjustment, were severely tested on eleven multiminima test functions. An algorithm with the best performance was employed for the determination of the model parameters of the optical constants of Pt, Ni and Cr.