Chemical process systems

The graphics capabiUties of the CAD/CAM environment offer a number of opportunities for data manipulation, pattern recognition, and image creation. The direct appHcation of computer graphics to the automation of graphic solution techniques, such as a McCabe-Thiele binary distillation method, or to the preparation of data plots are obvious examples. Graphic simulation has been appHed to the optimisation of chemical process systems as a technique for energy analysis (84). 

For moderately tight, small chemical processing systems (say 500cu.ft.), an ejector air capacity of lOlbs/hr is adequate. For large systems, use 201bs/hour. For very tight, small systems, an air capacity of 2-51bs/hr is reasonable. 

The Boolean equation for the probability of a chemical process system failure is R = A (B-i-C (D-rE (B-l-F G+C). Using Table 2.1-1, factor (he equation into a sum of products to get the mincut representation with each of the products representing an accident sequence. 

Table 7.3-2 lists some objectives for performing PSA on chemical process systems. Objective 1 is to determine if a process or plant has sufficient risk to justify a detailed analysis. This scoping analysis may be performed with a HAZOP (Section 3.3.4) or an FMEA (3.3. S) with either... 

This chapter shows that chemical process systems may fail and have serious consequences to the workers, public and the environment. Comparing with Chapter 6, chemical processes are similar to the processes in a nuclear power plant, hence, they may be analyzed similarly because both consist of tanks, pipes heat exchangers, and sources of heat. As an example of analysis, we analyze a storage tank rupture. 

Bhat, N. V., and McAvoy, T. J., Use of neural nets for dynamic modeling and control of chemical process systems. Comput. Chem. Eng. 14, 573 (1990). 

Wang, L.K., Yoo, S.H., and Hong, Y.N., Development of Two-Stage Physical-Chemical Process System for Treatment of Pulp Mill Wastewater, Lenox Institute of Water Technology, Lenox, M A, Technical Report LIR/05-84/2, 1984, 64 p. 

Riinsdorp, J.E. Chemical Process Systems and Automatic Control, Chemical Engineering Progress,... 

Grossmann, I. E. J. A. Caballero and H. Yeomans. Mathematical Programming Approaches to the Synthesis of Chemical Process Systems. Korean J Chem Eng 16(4) 407-426 (1999). 

Floudas, C. A. Global Optimization in Design and Control of Chemical Process Systems J Process Cont 10 125-134 (2000a). 

Greeff, D. J. and C. Aldrich. Empirical Modelling of Chemical Process Systems with Evolutionary Programming Comput Chem Eng 22 995-1005 (1998). 

Each chemical industrial facility is unique with respect to age, operation, and complexity. Another aspect to be considered relates to the chemical processing system. This... 

An alarm system is a type of electronic monitoring system that is used to detect and respond to specific types of events—such as unauthorized access to an asset, or a possible fire. In chemical processing systems, alarms are also used to alert operators when process operating or monitoring conditions go out of preset parameters (i.e., process alarms). These types of alarms are primarily integrated with process monitoring and reporting systems (i.e., SCADA systems). Note that this discussion does not focus on alarm systems that are not related to a facility s processes. 

As described above, a lockout device can be used as a security measure to prevent unauthorized access to aboveground valves located within chemical processing systems. Valve lockout devices are locks that are specially designed to fit over valves and valve handles to control their ability to be turned or seated. These devices can be used to lock the valve into the desired position. Once the valve is locked, it cannot be turned unless the locking device is unlocked or removed by an authorized individual. 

Wireless data communications devices are used to enable transmission of data between computer systems and/or between a SCADA server and its sensing devices, without individual components being physically linked together via wires or cables. In industrial chemical processing systems, these devices are often used to link remote monitoring stations (i.e., SCADA components) or portable computers (i.e., laptops) to computer networks without using physical wiring connections. 

Chemical process systems are subject to uncertainties due to many random events such as raw material variations, demand fluctuations, equipment failures, and so on. In this chapter we will utilize stochastic programming (SP) methods to deal with these uncertainties that are typically employed in computational finance applications. These methods have been very useful in screening alternatives on the basis of the expected value of economic criteria as well as the economic and operational risks involved. Several approaches have been reported in the literature addressing the problem of production planning under uncertainty. Extensive reviews surveying various issues in this area can be found in Applequist et al. (1997), Shah (1998), Cheng, Subrahmanian, and Westerberg (2005) and Mendez et al. (2006). 

Remark 1 The nonlinear equalities h(x) = 0 and the set of linear equalities which are included in h(x) = 0, correspond to mass and energy balances and design equations for chemical process systems, and they can be large. Since the nonlinear equality constraints cannot be treated explicitly by the OA algorithm, some of the possible alternatives would be to perform ... 

This chapter provides an introduction to Process Synthesis. Sections 7.1 and 7.2 discuss the components of a chemical process system and define the process synthesis problem. Section 7.3 presents the different approaches in the area of process synthesis. Section 7.4 focuses on the optimization approach and discusses modeling issues. Finally, Section 7.5 outlines application areas which are the subject of discussion in chapters 8, 9 and 10. 

Powers, G.J., and Tompkins, F.C., Synthesis Strategy for Fault Trees in Chemical Processing Systems, Chemical Engineering Progress Loss Prevention, 8, pp. 91-98... 

In order to make design or operation decisions a process engineer uses a process model. A process model is a set of mathematical equations that allows one to predict the behavior of a chemical process system. Mathematical models can be fundamental, empirical, or (more often) a combination of the two. Fundamental models are based on known physical-chemical relationships, such as the conservation of mass and energy, as well as thermodynamic (phase equilibria, etc.) and transport phenomena and reaction kinetics. An empirical model is often a simple regression of dependent variables as a function of independent variables. In this section, we focus on the development of process models, while Section III focuses on their numerical solution. 

Some chemical process systems may have a single steady state (single solution to a process model) under some design or operation conditions and multiple solutions under other design conditions. There are automatic techniques to vary a parameter of a system model to determine when these solutions branch from a single solution to multiple solutions. The FORTRAN code AUTO is perhaps the most widely used code for this. 

Chemical process systems can be described by a number of physical parameters. In the majority of cases, however, these systems are very complex and the number of parameters needed to describe them very... 

Hartmann, K., "Experience in the Synthesis of Optimum Chemical Process Systems," CACE 79, Montreux, Switzerland, April 8-11, 1979. 

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