Complex systems with internal structure

Saraiva, P.. and Stephanopoulos, G Data-Driven Learning Architectures for Proce.ss Improvement in Complex Systems with Internal Structure, Working paper. Massachusetts Institute of Technology, Dept. Chem. Eng., Cambridge, MA, 1992d. 

Flowing systems are also typical examples in which this Unear behavior is broken. This is the case of rheology, the study of viscosity of complex fluids, that is, of fluids with internal structure that exhibit a combination of viscous and elastic behavior under strain (Beris Edwards, 1994 Doi Edwards, 1998). Examples of such fluids are polymer solutions and melts, oil and toothpaste, among many others. 

GASFLOW models geometrically complex containments, buildings, and ventilation systems with multiple compartments and internal structures. It calculates gas and aerosol behavior of low-speed buoyancy driven flows, diffusion-dominated flows, and turbulent flows dunng deflagrations. It models condensation in the bulk fluid regions heat transfer to wall and internal stmetures by convection, radiation, and condensation chemical kinetics of combustion of hydrogen or hydrocarbon.s fluid turbulence and the transport, deposition, and entrainment of discrete particles. 

The use of computer simulations to study internal motions and thermodynamic properties is receiving increased attention. One important use of the method is to provide a more fundamental understanding of the molecular information contained in various kinds of experiments on these complex systems. In the first part of this paper we review recent work in our laboratory concerned with the use of computer simulations for the interpretation of experimental probes of molecular structure and dynamics of proteins and nucleic acids. The interplay between computer simulations and three experimental techniques is emphasized (1) nuclear magnetic resonance relaxation spectroscopy, (2) refinement of macro-molecular x-ray structures, and (3) vibrational spectroscopy. The treatment of solvent effects in biopolymer simulations is a difficult problem. It is not possible to study systematically the effect of solvent conditions, e.g. added salt concentration, on biopolymer properties by means of simulations alone. In the last part of the paper we review a more analytical approach we have developed to study polyelectrolyte properties of solvated biopolymers. The results are compared with computer simulations. 

Complex manufacturing systems, such as an unbleached Kraft pulp plant (Fig. 9), are almost always characterized by some type of internal structure, composed of a number of interconnected subsystems with their own data collection and decisionmaking responsibilities. This raises a number of additional issues, not addressed in previous sections. For instance, if the learning methodology described in Section VI is applied to the digester module of a pulp plant (Fig. 9), it is possible for the final selected solution, to include ranges of desired values of sulfidity... 

We presented extensions and variations of the basic learning methodologies aimed at enlarging their flexibility and cover a number of different situations, including systems where performance is evaluated by categorical or continuous variables, with single or multiple objectives, simple or complex plants containing some type of internal structure and composed of a number of interconnected subsystems. 

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