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.
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.
process systems, modeling and simulation, optimization, process analysis and synthesis
|✔ Specialist skills||Intercultural skills||Communication skills||✔ Critical thinking skills||✔ Practical and/or problem-solving skills|
Class 2 - 11: Towards the end of class for optimization and modeling & simulation of process systems, students are given exercise problems related to what is taught on that day to solve.
Class 12 - 14: Students are given subjects 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|
|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 formulation of the objective function||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||Linear Programming and its chemical engineering applications||Students must be able to solve the optimization problems for analysis, synthesis and operation of process systems, by linear programming.|
|Class 8||Global optimization for problems with continuous and discrete variables||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||Multi-scale modeling and simulation||Understanding of holistic system thinking for complex systems is required. Students must be able to present application methods of multi-scale modeling and simulation for analysis and synthesis of process systems.|
|Class 10||Neural network modeling and machine learning||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 11||Discrete-event system modeling||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 12||Application of optimization (I): Heat transfer and energy conversation||Students must be able to solve the optimization problems for heat transfer and energy conversation.|
|Class 13||Application of optimization (II): Separation processes||Students must be able to solve the nonlinear programming problems for analysis, synthesis and operation of process systems, by using Newton's method.|
|Class 14||Application of optimization (III): Chemical reactor design and operation||Students must be able to solve the optimization problems for chemical reactor design and operation.|
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 textbooks and other course material.
Kuroda, Chiaki ed.. Systems Analysis. Tokyo: Asakura Shoten. ISBN-13:978-4254256048
Akagi, Shinsuke. Systems Engineering. Tokyo: Kyoritsu Shuppan. ISBN-13:978-4320071339
Students’ course scores are based on submitted reports to subjects and exercise problems.
Students require knowledge of chemical engineering.