Showing papers on "Process modeling published in 1979"
01 Jan 1979
TL;DR: This chapter discusses the applications of computers in fermentation technology, which has a variety of applications in the fermentation industry ranging from data logging and on-line analysis to process modeling, control, and optimization.
Abstract: Publisher Summary This chapter discusses the applications of computers in fermentation technology. Computers have a variety of applications in the fermentation industry ranging from data logging and on-line analysis to process modeling, control, and optimization. This is mainly in the areas of data logging and online analysis. With the advent of inexpensive and reliable minicomputers, it has become economical to utilize a computer system online. With this capability, it has been possible to move rapidly to a computer applications level that involves partial process control based upon using predetermined set points for controlling primary fermentation parameters, such as temperature, pH, and dissolved oxygen. It has also been possible to utilize the information generated online to study the process and to elaborate the process kinetics. With the development of more powerful minicomputer operating system software, it is possible to operate the computer system using both foreground/background tasks, that is, simultaneously performing the online data acquisition and analysis tasks, and simultaneously doing online process simulation. Once significant operating confidence is obtained with process kinetic models, computer systems can advance to the final stage of automatic process control.
27 citations
TL;DR: In this paper, a two-stage formulation of Dantzig's analysis was applied to realistic process design models and the authors obtained, for two realistic process models, optimal designs with improved flexibility compared to designs based on fixed parameters.
27 citations
26 citations
TL;DR: The modeller should question the need for complex models of instrumentation and avoid over-elaboration whenever possible and the detail used to model the instrumentation should match the problem one is trying to solve.
Abstract: The instrument models, described in this paper, are intended for inclusion in larger models of processes and not as detailed models of instruments in their own right These larger process models can be used either directly for control studies, or for simulation exercises where an estimate of the dynamic response of the process to disturbances is required The emphasis in this paper is on models for use in digital simulations The most important message of the paper is that the detail used to model the instrumentation should match the problem one is trying to solve ?'he modeller should question the need for complex models of instrumentation and avoid over-elaboration whenever possible
3 citations
2 citations
TL;DR: In this article, an integrated approach to the continuous process modelling and control system design is presented, taking advantage of the partly explicit process model, based on pseudo-analytical linearisation technique.