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2022　Process Systems Engineering

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Academic unit or major
Graduate major in Chemical Science and Engineering
Instructor(s)
Matsumoto Hideyuki 
Class Format
Lecture    (Livestream)
Media-enhanced courses
Day/Period(Room No.)
Tue5-6()  Fri3-4()  
Group
-
Course number
CAP.C412
Credits
2
Academic year
2022
Offered quarter
1Q
Syllabus updated
2022/4/10
Lecture notes updated
-
Language used
English
Access Index

Course description and aims

Process systems engineering is concerned with investigation on decision-making methodology for creation and operation of the chemical supply chain. This course covers the fundamentals of systems approach (modeling, simulation and optimization) in the fields of analysis, synthesis and operation of process systems. This course introduces chemical engineering application of the systems approach.
In recent years, problems that should be solved by chemical engineering become diversified and complicated, which is faced for building a sustainable society that enables to maintain development of economies by considering improvement of environment, safety and health. An aim of this course is to facilitate students' understanding of a wide variety of systems method and its application to analysis, synthesis and operation of process systems. Students will have the chance to tackle practical problems by applying knowledge acquired through the lecture.

Student learning outcomes

At the end of this course, students will be able to:
1) Have an understanding of concept of systems thinking for analysis, synthesis and operation of chemical process systems, and deal with mathematical method related to modeling and simulation.
2) Deal with typical numerical solution for optimization problem that is essential to evaluation and decision-making.
3) Apply the above-mentioned mathematical methods to solve problem facing in the chemical engineering field.

Keywords

process systems, modeling and simulation, optimization, process analysis and synthesis

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills ✔ Critical thinking skills ✔ Practical and/or problem-solving skills

Class flow

In the latter part of lecture for optimization and modeling & simulation of process systems, students are given practice problems related to what is taught on that day. Students are also given three assignments related to optimization of chemical processes. Before coming to class, students should check what topics will be covered. Required learning should be completed outside of the classroom for preparation and review purposes.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Systems and process systems Students must be able to present definition of process systems and basic concept of system thinking.
Class 2 The nature of optimization problems and problem formulation Students must be able to present characteristics of optimization problems and overviews of procedures of solving the problems in analysis, synthesis and operation of process systems.
Class 3 Linear / nonlinear regression modeling and parameter estimation Understanding of application methods of linear / nonlinear model for analysis, synthesis and operation of process systems is required. Students must be able to estimate values of parameters for the regression model.
Class 4 Basis of quadratic programming Understanding of characteristics of quadratic optimization problem is required. Students must be able to analyze characteristics of the optimization problem mathematically.
Class 5 Optimization of unconstrained functions: One-dimensional search Students must be able to solve the nonlinear programming problems for analysis, synthesis and operation of process systems, by using Newton's method.
Class 6 Unconstrained multivariable optimization Students must be able to solve the nonlinear programming problems for analysis, synthesis and operation of process systems, by using gradient method.
Class 7 Practice: Optimization of chemical process (I) Students must be able to solve the optimization problems for chemical process.
Class 8 Genetic algorithms for global optimization Understanding of characteristics of heuristic search methods (e.g. genetic algorithms) is required. Students must have knowledge of chemical engineering application of the heuristic search methods.
Class 9 Linear Programming Students must be able to solve the optimization problems for analysis, synthesis and operation of process systems, by linear programming.
Class 10 Practice: Optimization of chemical process (II) Students must be able to solve the optimization problems for chemical process.
Class 11 Modeling of lumped parameter systems and distributed parameter systems Understanding of holistic system thinking for complex systems is required. Students must be able to present application methods of modeling of lumped parameter systems and distributed parameter systems.
Class 12 Neural network modeling and its chemical engineering applications Understanding of characteristics of empirical network model is required. Students must be able to present mathematical methods for expression of structure of neural network and machine learning.
Class 13 Discrete-event system modeling and its chemical engineering applications Understanding of characteristics of discrete event system is required. Students must be able to present methods for expression of Petri net model and its application.
Class 14 Practice: Optimization of chemical process (III) Students must be able to solve the optimization problems for chemical process.

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to course material or reference book.

Textbook(s)

Use the course materials to be distributed.

Reference books, course materials, etc.

Kuroda, Chiaki ed.. Systems Analysis. Tokyo: Asakura Shoten. ISBN-13:978-4254256048

Assessment criteria and methods

Students’ course scores are based on submitted reports to subjects and exercise problems.

Related courses

  • CAP.I407 ： Introduction to Chemical Engineering (Basics)
  • CAP.C424 ： Advanced Reaction Process Engineering
  • CAP.C423 ： Computational Fluid Dynamics
  • CAP.I417 ： Introduction to Chemical Engineering (Unit Operation)
  • CAP.C421 ： Advanced Energy Transfer Operation
  • CAP.C441 ： Transport Phenomena and Operation
  • CAP.C443 ： Advanced Reaction-Separation Process

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Knowledge of process models related to unit operations and chemical reaction engineering is required to take this lecture.
If you have not studied the basics of chemical engineering in your undergraduate course, we recommend that you take other lectures on chemical engineering and then take “Process Systems Engineering” next year.

Other

Students will use MATLAB to deepen understanding of methods for modeling, simulation and optimization that they will learn in this lecture. We recommend that you prepare in advance to use MATLAB.
※In Tokyo Tech, students can freely use MATLAB with the Campus-Wide license.
https://www.t3.gsic.titech.ac.jp/matlab
(We also recommend using Python.)

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