1,363,111 research outputs found

    Inverse model to determine the optimal number of drops of RDC column using fuzzy approach

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    Inverse modeling is natural in many real world application including industrial chemical engineering problems. This paper describes the process of determines optimal input and output of number of drops in various stage of rotating disc contactor column using fuzzy model. An algorithm of the fuzzy model is developed to simulate the above process

    Integration of an object formalism within a hybrid dynamic simulation environment

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    PrODHyS is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of systems engineering. Its major characteristic is its ability to simulate processes described by a hybrid model. In this framework, this paper focuses on the "Object Differential Petri Net" (ODPN) formalism integrated within PrODHyS. The use of this formalism is illustrated through a didactic example relating to the field of Chemical Process System Engineering (PSE)

    Model based fault diagnosis for hybrid systems : application on chemical processes

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    The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

    Integration of a failure monitoring within a hybrid dynamic simulation environment

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    The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

    The role of Computer Aided Process Engineering in physiology and clinical medicine

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    This paper discusses the potential role for Computer Aided Process Engineering (CAPE) in developing engineering analysis and design approaches to biological systems across multiple levels—cell signalling networks, gene, protein and metabolic networks, cellular systems, through to physiological systems. The 21st Century challenge in the Life Sciences is to bring together widely dispersed models and knowledge in order to enable a system-wide understanding of these complex systems. This systems level understanding should have broad clinical benefits. Computer Aided Process Engineering can bring systems approaches to (i) improving understanding of these complex chemical and physical (particularly molecular transport in complex flow regimes) interactions at multiple scales in living systems, (ii) analysis of these models to help to identify critical missing information and to explore the consequences on major output variables resulting from disturbances to the system, and (iii) ‘design’ potential interventions in in vivo systems which can have significant beneficial, or potentially harmful, effects which need to be understood. This paper develops these three themes drawing on recent projects at UCL. The first project has modeled the effects of blood flow on endothelial cells lining arteries, taking into account cell shape change resulting in changes in the cell skeleton which cause consequent chemical changes. A second is a project which is building an in silico model of the human liver, tieing together models from the molecular level to the liver. The composite model models glucose regulation in the liver and associated organs. Both projects involve molecular transport, chemical reactions, and complex multiscale systems, tackled by approaches from CAPE. Chemical Engineers solve multiple scale problems in manufacturing processes – from molecular scale through unit operations scale to plant-wide and enterprise wide systems – so have an appropriate skill set for tackling problems in physiology and clinical medicine, in collaboration with life and clinical scientists

    Silicon production process evaluations

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    Chemical engineering analysis of the HSC process (Hemlock Semiconductor Corporation) for producing silicon from dichlorosilane in a 1,000 MT/yr plant was continued. Progress and status for the chemical engineering analysis of the HSC process are reported for the primary process design engineering activities: base case conditions (85%), reaction chemistry (85%), process flow diagram (60%), material balance (60%), energy balance (30%), property data (30%), equipment design (20%) and major equipment list (10%). Engineering design of the initial distillation column (D-01, stripper column) in the process was initiated. The function of the distillation column is to remove volatile gases (such as hydrogen and nitrogen) which are dissolved in liquid chlorosilanes. Initial specifications and results for the distillation column design are reported including the variation of tray requirements (equilibrium stages) with reflux ratio for the distillation

    Silicon production process evaluations

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    Chemical engineering analysis was continued for the HSC process (Hemlock Semiconductor Corporation) in which solar cell silicon is produced in a 1,000 MT/yr plant. Progress and status are reported for the primary engineering activities involved in the preliminary process engineering design of the plant base case conditions (96%), reaction chemistry (96%), process flow diagram (85%), material balance (85%), energy balance (60%), property data (60%), equipment design (40%), major equipment list (30%) and labor requirements (10%). Engineering design of the second distillation column (D-02, TCS column) in the process was completed. The design is based on a 97% recovery of the light key (TCS, trichlorosilane) in the distillate and a 97% recovery of the heavy key (TET, silicon tetrachloride) in the bottoms. At a reflux ratio of 2, the specified recovery of TCS and TET is achieved with 20 trays (equilibrium stages, N=20). Respective feed tray locations are 9, 12 and 15 (NF sub 1 = 9, NF sub 2 = 12,, and NF sub 3 = 15). A total condenser is used for the distillation which is conducted at a pressure of 90 psia
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