Process Dynamics and Control, 4e
Process Dynamics and Control, 4e
4th Edition
ISBN: 9781119285915
Author: Seborg
Publisher: WILEY
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Chapter 6, Problem 6.21E

(vii)

Interpretation Introduction

Interpretation:

Simplified dynamic model for the given process is to be determined. Also, any additional assumptions are to be stated.

Concept introduction:

For chemical processes, dynamic models consisting ordinary differential equations are derived through unsteady-state conservation laws. These laws generally include mass and energy balances.

The process models generally include algebraic relationships which commence from thermodynamics, transport phenomena, chemical kinetics, and physical properties of the processes.

Interpretation Introduction

(a)

Interpretation:

The transfer functions which relate the primary outputs to the inputs are to be determined.

Concept introduction:

For chemical processes, dynamic models consisting of ordinary differential equations are derived through unsteady-state conservation laws. These laws generally include mass and energy balances.

The process models generally include algebraic relationships which commence from thermodynamics, transport phenomena, chemical kinetics, and physical properties of the processes.

For a function f(t), the Laplace transform is given by,

F(s)=L[f(t)]=0f(f)estdt

Here, F(s) represents the Laplace transform, s is a variable that is complex and independent, f(t) is any function of time which is being transformed, and L is the operator which is defined by an integral.

f(t) is calculated by taking inverse Laplace transform of the function F(s).

The difference in the actual variable (y) and the original variable (y¯) is known as deviation variable (y)

. It is generally used while modelling a process. Mathematically it is defined as:

y=yy¯

In steady-state process, the accumulation in the process is taken as zero.

Interpretation Introduction

(b)

Interpretation:

The physical arguments for each form of the transfer function are to be interpreted.

Concept introduction:

For chemical processes, dynamic models consisting of ordinary differential equations are derived through unsteady-state conservation laws. These laws generally include mass and energy balances.

The process models generally include algebraic relationships which commence from thermodynamics, transport phenomena, chemical kinetics, and physical properties of the processes.

For a function f(t), the Laplace transform is given by,

F(s)=L[f(t)]=0f(f)estdt

Here, F(s) represents the Laplace transform, s is a variable that is complex and independent, f(t) is any function of time which is being transformed, and L is the operator which is defined by an integral.

f(t) is calculated by taking inverse Laplace transform of the function F(s).

The difference in the actual variable (y) and the original variable (y¯) is known as the deviation variable (y)

. It is generally used while modeling a process. Mathematically it is defined as:

y=yy¯

In the steady-state process, the accumulation in the process is taken as zero.

Interpretation Introduction

(c)

Interpretation:

The qualitative form for the response of each transfer functions derived in part (a) for a step change in each input is to be discussed.

Concept introduction:

For chemical processes, dynamic models consisting ordinary differential equations are derived through unsteady-state conservation laws. These laws generally include mass and energy balances.

The process models generally include algebraic relationships which commence from thermodynamics, transport phenomena, chemical kinetics, and physical properties of the processes.

For a function f(t), the Laplace transform is given by,

F(s)=L[f(t)]=0f(f)estdt

Here, F(s) represents the Laplace transform, s is a variable which is complex and independent, f(t) is any function of time which is being transformed, and L is the operator which is defined by an integral.

f(t) is calculated by taking inverse Laplace transform of the function F(s).

The difference in the actual variable (y) and the original variable (y¯) is known as deviation variable (y)

. It is generally used while modelling a process. Mathematically it is defined as:

y=yy¯

In steady-state process, the accumulation in the process is taken as zero.

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