(534b) The Process Simulation Course - the Culmination of Core Undergraduate Coursework in Chemcial Engineering

            The status of the incorporation of
computational tools in the undergraduate Chemical Engineering curriculum has
been recently reviewed by Shacham et al. (2009). This review, as well as some
additional references (Dahm et al., 2002, Rockstraw, 2005, Dias et al., 2010),
reveal that process simulation is being used to some extent in various courses.
Most often commercial simulators (such as HYSIS, AspenPlus and PRO II) are used
to model the steady state or dynamic operations of processes. The benefit of
such use of a process simulator (as stated by Dahm et al., 2002) is that it
"provides a time-efficient and effective way for students to examine
cause-effect relationships" among various parameters of the process. A
pedagogical drawback to the use of such packages is that "it is possible for
students to successfully construct and use models without really understanding
the physical phenomena within each unit operation" (Dahm et al., 2002).
Furthermore, Streicher et al. (2005) have found that "the majority of students
see simulations merely as sophisticated calculators that save time.?

       In order to promote and emphasize the
full educational benefits of process simulation, we have developed a process
simulation course where the students need to prepare process models, in most
cases, that are ultimately simulated with MATLAB. The course content begins with
the steady state operation of simple recycle processes that contain mixers,
simple splitters and conversion type reactors. Material balances on such systems
can be represented by linear models. For such systems, a direct solution (of a
system of linear equations) can be obtained and the performance of various
iterative algorithms can be examined. The students learn to establish the
computational sequence in the flow-sheet using various partitioning and tearing
algorithms. Then, students solve the problems directly and iteratively using the
successive substitution, dominant eigenvalue, Wegstein's and Broyden's methods.
After understanding the basic principles of the operation of the steady state
simulators, models of unit operations with increasing level of complexity (such
as isothermal, adiabatic and three-phase flash) are prepared. The models are
implemented as MATLAB functions where the input parameters are the vectors of
flow-rates and enthalpy of the inlet streams and the design parameters of the
process unit. The output parameters are the vectors of flow-rates and enthalpies
of the outlet streams. Physical property data and correlations that required for
the modeling the unit operation are taken from the DIPPR thermophysical database
(http://dippr.byu.edu/).
Binary equilibrium data, needed for calculations of activity coefficients, are
retrieved from the Dorthmund Data Bank (http://www.ddbst.com/en/ddbst/index.php)
and regressed with the Polymath program. The systems of nonlinear algebraic
equations that represent typically the steady state models of the various units
operations are solved using the constrained version of the Newton-Raphson method
(Shacham, 1988).

       In dynamic simulation, the emphasis is
on the solution of Multiple-Model, Multiple-Algorithm (MMMA, see Cutlip et al.,
2009) problems. An example is a process unit that can operate in different modes
(such as a reactor with heating and cooling periods) and requires different
integration algorithms (stiff and non-stiff) in each period. For example, the
students can model the operation of a runaway chemical reactor which is
described in detail by Eisenberg et al., 2006.

       The process simulation course has been
given as an elective course for fourth year undergraduate students and new
graduate students. Success in this course requires that students must review,
enhance, update and make practical use of their knowledge of programming,
material and energy balances, thermodynamics, numerical methods and reaction
engineering. With the integration of such content, the course can be considered
as a culmination of core chemical engineering coursework.

       In the extended abstract and in the
presentation, the syllabus of the "Process Simulation" course will be described
in detail.  In addition, some example problems will be presented and the student
evaluation of the course will be discussed.

References

1.      

Cutlip, M. B., N. Brauner, and M. Shacham, "Biokinetic Modeling of Imperfect
Mixing in a Chemostat ? an Example of Multiscale Modeling", Chem.
Eng.  Ed., 43, 243
(2009)                                                 

2.      
Dahm,
K. D., R. P. Hesketh, and M. J. Savelski, "Is process simulation used
effectively in ChE courses?"  Chem.
Eng.  Ed.,
36, 192 (2002)

3.      

Dias, R. S., Silva, L. C., and A. J. De Assis, Plant wide simulation using the
free chemical process simulator Sim42: Natural gas separation and reforming,
Published online in Wiley InterScience; DOI 10.1002/cae.20200

4.      

Eisenberg, S., M. Shacham and
N. Brauner, "Combining HAZOP
with Dynamic Simulation - Applications for Safety Education", Journal of Loss
Prevention in the Process Industries 19, 754?761 (2006)

5.      

Rockstraw, D. A., "ASPEN Plus in the ChE curriculum. Suitable course content and
teaching methodology," Chem.
Eng.  Ed., 
39, 68 (2005)

6.      

Shacham, M., "Numerical Solution of Constrained Non-Linear Algebraic Equations",
International Journal of Numerical Methods in Engineering, 23, 1455-1481
(1986).

7.      

Shacham, M., Cutlip, M. B. and
N. Brauner, "From Numerical
Problem Solving to Model Based Experimentation ? Incorporating Computer Based
Tools of Various Scales into the ChE Curriculum", Chem.
Eng.  Ed., 
43,  299 (2009)

8.      

Streicher, S. J., K. West, D. M. Fraser, J. M. Case, and C. Linder, "Learning
through simulation, student engagement," Chem.
Eng.  Ed., 
39,  288 (2005)