Tutorial 2

Tutorial 2

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Tutorial 2Modelling of Dynamic Systems2.1 Mixer: Dynamic model of a CSTR is derived in textbook Example 3.1. From themodel, we know that the outlet concentration of A, C , can be affected by manipulatingAthe feed concentration, C , because there is a causal relationship between theseA0variables.a. The feed concentration, C , results from mixing a stream of pure A with solvent,A0as shown in the diagram. The desired value of C can be achieved by adding aA0right amount of A in the solvent stream. Determine the model that relates theflow rate of reactant A, F , and the feed concentration, C , at constant solventA A0fle.b. Relate the gain and time constant(s) to parameters in the process.c. Describe a control valve that could be used to affect the flow of component A.Describe the a) valve body and b) method for changing its percent opening(actuator).Fs FoC CAOA,solventSolventF1CAReactantFACA,reactantFigure 2.12.2 Stirred tank mixera. Determine the dynamic response of the tank temperature, T, to a step change inthe inlet temperature, T for the continuous stirred tank shown in the Figure 2.20, below.b. Sketch the dynamic behavior of T(t).c. Relate the gain and time constants to the process parameters.d. Select a temperature sensor that gives an accuracy better than ± 1 K at atemperature of 200 K.Based on a close analysis of the physical equipment, FTOwe find that the following assumptions are valid.1. there is no heat accumulated in the tank ...

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Tutorial 2 Modelling of Dynamic Systems 2.1 Mixer: Dynamic model of a CSTR is derived in textbook Example 3.1. From the model, we know that the outlet concentration of A, C , can be affected by manipulatingA the feed concentration, C , because there is a causal relationship between theseA0 variables. a. The feed concentration, C , results from mixing a stream of pure A with solvent,A0 as shown in the diagram. The desired value of C can be achieved by adding aA0 right amount of A in the solvent stream. Determine the model that relates the flow rate of reactant A, F , and the feed concentration, C , at constant solventA A0 fle. b. Relate the gain and time constant(s) to parameters in the process. c. Describe a control valve that could be used to affect the flow of component A. Describe the a) valve body and b) method for changing its percent opening (actuator). Fs Fo C CAOA,solventSolvent F1 C A Reactant F A CA,reactant Figure 2.1 2.2 Stirred tank mixer a. Determine the dynamic response of the tank temperature, T, to a step change in the inlet temperature, T for the continuous stirred tank shown in the Figure 2.20, below. b. Sketch the dynamic behavior of T(t). c. Relate the gain and time constants to the process parameters. d. Select a temperature sensor that gives an accuracy better than ± 1 K at a temperature of 200 K. Based on a close analysis of the physical equipment, F TOwe find that the following assumptions are valid. 1. there is no heat accumulated in the tank walls, 2. the tank is insulated, 3. the tank is well-mixed, F 4. F and V are constant, T 5. physical properties are constant, and 6. the system is initially at steady state. V F Figure 2.2 2.3 Isothermal CSTR: The model used to predict the concentration of the product, C , in an isothermal CSTR will be formulated in this exercise. The reaction occurring inB the reactor is A → Br = -kCA A Concentration of component A in the feed is C , and there is no component B in theA0 feed. The assumptions for this problem are F01. the tank is well mixed, 2. negligible heat transfer, CA0 F13. constant flow rate, 4. constant physical properties, 5. constant volume, 6. no heat of reaction, and 7. the system is initially at steady state. VC A Figure 2.3 a. Develop the differential equations that can be used to determine the dynamic response of the concentration of component B in the reactor, C (t), for a givenB C (t).A0 b. Relate the gain and time constant(s) to the process parameters. c. After covering Chapter 4, solve for C (t) in response to a step change in C (t),B A0 ∆CA0. d. Sketch the shape of the dynamic behavior of C (t).B e. Could this system behave in an underdamped manner for different (physically possible) values for the parameters and assumptions? 2.4 Inventory Level: Process plants have many tanks that store material. Generally, the goal is to smooth differences in flows among units, and no reaction occurs in these tanks. We will model a typical tank shown in Figure 2.4. a. Liquid to a tank is being determined by another part of the plant; therefore, we have no influence over the flow rate. The flow from the tank is pumped using a centrifugal pump. The outlet flow rate depends upon the pump outlet pressure and the resistance to flow; it does not depend on the liquid level. We will use the valve to change the resistance to flow and achieve the desired flow rate. The tank is cylindrical, so that the liquid volume is the product of the level times the cross sectional area, which is constant. Assume that the flows into and out of the tank are initially equal. Then, we decrease Fthe flow out in a step by adjusting the in valve. Fout Li. Determine the behavior of the level as a function of time. V = A L ii. Compare this result to the textbook Example 3.6, the draining tank. Figure 2.4 Tank with pump at the outlet. iii. Describe a sensor that could be used to measure the level in this vessel. 2.5 Designing tank volume: In this question you will determine the size of a storage vessel. Feed liquid is delivered to the plant site periodically, and the plant equipment is operated continuously. A tank is provided to store the feed liquid. The situation is sketched in Figure 2.5. Assume that the storage tank is initially empty and the feed delivery is given in Figure 2.5. Determine the minimum height of the tank that will prevent overflow between the times 0 to 100 hours. Fin 3F = 12.0 m/houtL = ? 2A = 50 m 30.0 Fin 3(m /h) 0 End of problem at 100 h 40 50 70 80020 Time (h) Figure 2.5 Tank between the feed delivery and the processing units. 2.6 Modelling procedure: Sketch a flowchart of the modelling method that we are using to formulate dynamic models. Tutorial 2. Modelling of Dynamic Systems Learning Inventory Confidence 1 5 10 (low) (O.K.) (high) 1. I can formulate balances on a well- mixed system and relate key factors (gain, time constant(s)) to process parameters. 2. I can incorporate constitutive relationships to enable me to complete 1 5 10 dynamic models. 3. I can sketch step responses for first and second order dynamic systems. 4. I am continuing to build my understanding of instrumentation 1 5 10 principles, because every change I make to an experiment or plant will be through a valve or other instrument.