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Process simulation—steady state stream variables

Many process simulators come with optimizers that vary any arbitrary set of stream variables and operating conditions and optimize an objective function. Such optimizers start with an initial set of values of those variables, carry out the simulation for the entire flow sheet, determine the steady-state values of all the other variables, compute the value of the objective function, and develop a new guess for the variables for the optimization so as to produce an improvement in the objective function. [Pg.78]

Mathematically speaking, a process simulation model consists of a set of variables (stream flows, stream conditions and compositions, conditions of process equipment, etc) that can be equalities and inequalities. Simulation of steady-state processes assume that the values of all the variables are independent of time a mathematical model results in a set of algebraic equations. If, on the other hand, many of the variables were to be time dependent (m the case of simulation of batch processes, shutdowns and startups of plants, dynamic response to disturbances in a plant, etc), then the mathematical model would consist of a set of differential equations or a mixed set of differential and algebraic equations. [Pg.80]

Pure component physical property data for the five species in our simulation of the HDA process were obtained from Chemical Engineering (1975) (liquid densities, heat capacities, vapor pressures, etc.). Vapor-liquid equilibrium behavior was assumed to be ideal. Much of the flowsheet and equipment design information was extracted from Douglas (1988). We have also determined certain design and control variables (e.g., column feed locations, temperature control trays, overhead receiver and column base liquid holdups.) that are not specified by Douglas. Tables 10.1 to 10.4 contain data for selected process streams. These data come from our TMODS dynamic simulation and not from a commercial steady-state simulation package. The corresponding stream numbers are shown in Fig. 10.1. In our simulation, the stabilizer column is modeled as a component splitter and tank. A heater is used to raise the temperature of the liquid feed stream to the product column. Table 10.5 presents equipment data and Table 10.6 compiles the heat transfer rates within process equipment. [Pg.297]

The dynamic simulation study of the system with control structure 2 indicatesThat a reactor shutdown occurs when the disturbance in Fqa drives the reactor compositions into a region where Za becomes greater than To understand the fundamental reason for this observed phenomenon, we develop a linearized model of a simplified process. The separation section is assumed to be at steady state, and the only dynamics are in the reactor compositions. Perfect reactor level control is assumed. The disturbance is the fresh feed flow rate Fqa Reactor effluent flow rate F is fixed. State variables are Za nd zb- Algebraic dependent variables at any point in time are the flow rates B, Dj, and Foe- To simplify the analysis we assume that the losses of components A and B (Aj ss and fi os.s) the product Bj stream are constant. [Pg.217]

Analysis, or simulation, is the tool chemical engineers use to interpret process flowsheets, to locate malfunctions, and to predict the performance of processes. The heart of analysis is the mathematical model, a collection of equations that relate the process variables, such as stream temperature, pressure, flow rate, and composition, to surface area, valve settings, geometrical configuration, and so on. The steady-state simulators solve for the unknown variables, given the values of certain known quantities. [Pg.108]

The standard state-of-the-art steady-state process simulation is based on stream flows, which do not change with time. Therefore, flash calculations with other variables like constant specific volume or entropy are not provided. For the design of vessels and safety valves, the so-called isochoric flash is important. It uses the specific volume as the second fixed variable and determines the pressure which... [Pg.591]


See other pages where Process simulation—steady state stream variables is mentioned: [Pg.1907]    [Pg.100]    [Pg.58]    [Pg.1666]    [Pg.2389]    [Pg.2372]    [Pg.1911]    [Pg.147]   
See also in sourсe #XX -- [ Pg.109 , Pg.112 ]




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Process simulators steady-state simulations

Process state

Process stream

Process variability

Process variables

Processing variables

State variable states

State variables

Steady Streaming

Steady processes

Steady simulation

Steady-state simulation

Stream variables

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