
WB443105: 
Modeling of Process and Energy Systems 
ECTS: 
4 
Responsible Instructor: 
Dr.ir. P. Colonna 
Instructor: 
Ir. T. Mathijssen, E. Rinaldi 
Contact Hours / Week x/x/x/x: 
0/0/4/0 
Education Period: 
3 
Start Education: 
3 
Exam Period: 
3, 4 
Course Language: 
English 
Parts: 
Part 01 Introduction Part 02 Conservation Laws Part 03 Modeling Paradigms Part 04 Numerical Methods and Software / 1st Midterm Exam Part 05 Software We Use (handson) Part 06 Fluid Properties, Heat Transfer, Fluid Dynamics, Chemical Reactions Part 07 Validation and Model Analysis, Examples Part 08 Modeling Example/ 2nd Midterm Exam 
Summary: 
Physical modeling of energy systems and processes, Simulation, Steadystate, Offdesign, Dynamics, Laws of conservation, Lumped parameters models, Distributed parameters models, Causality, Energy conversion systems, Processes, Thermodynamics, Heat Transfer, Fluid Dynamics, Ordinary Differential Equations, Numerical Methods and Analysis, Modularity, Process Components, Power plant, Cogeneration, Trigeneration, Fluid Properties, Simulation Software, Model validation. 
Course Contents: 
This is a basic course on the modeling of energy conversion systems and processes based on physical equations. The focus is on lumped parameters models, but notions on distributed parameters models are included. Concepts from thermodynamics, fluid dynamics and heat transfer are merged with new aspects that are typical of system modeling, so that the student learns how to develop and implement model equations. The applicative part includes simple exercises on the development of models of unit operations (e.g. evaporator, turbine, compressor...) and on their implementation using Matlab/Simulink (steady state and dynamic). Program: Introduction: The role of models in Process Systems Engineering, Examples of processes, modeling paradigms, applications, tools, method. Process representation, definition of ondesign and offdesign steady state models, dynamic models and their applications to design, operation and control. Conservation equations: intensive, extensive, lumped parameters and distributed parameters, steady state and dynamic, examples. Constitutive equations: review of fluid properties, heat transfer, fluid dynamics, chemical reactions..., Numerical methods: review of theoretical aspects and numerical solution techniques for nonlinear algebraic systems and differentialalgebraic systems of equations. Lumped parameters modeling: Modeling approaches, Modularity and Hierarchy, Model representation, connections and intermodule variables, "open loop" modeling, Well posedness and Index problem in DAE"s, Bilateral coupling and causality, Connecting rules and example of model decomposition. Model validation: steady state validation, qualitative dynamic validation, quantitative dynamic validation. Examples: to choose from: boiler, condenser, compressor, turbine, ... 
Study Goals: 
After learning the content of the course the student will have the following capabilities: 1. Describe the role of models in Process and Energy Systems Engineering, and describe examples of systems, processes, modeling paradigms, applications, software tools, methods. 2. Represent a process with process flow diagrams, and define and use ondesign and off design steady state models, "open loop" dynamic models and their applications to design, operation and control. 3. Present various forms of conservation equations: intensive, extensive, lumped parameters and distributed parameters, steady state and dynamic, and to make examples. The student is able to apply the basic principle of accounting for conserved variables and to write conservation balances that occur in typical energy and chemical processes. 4. List the main characteristics and choose among different models of fluid properties, heat transfer correlations, fluid dynamic correlations and chemical reactions model in order to appropriately select the constitutive equations that close the lumped parameter modeling problem. 5. List the main characteristics and choose among various numerical techniques for the solution of nonlinear algebraic systems of equations, differential algebraic systems of equations, partial differential systems of equations, which are the mathematical problems that have to be solved when simulating a process. 6. List the various modeling approaches and describe the concept of modularity, hierarchy, connections and intermodule variables that are necessary to correctly setup a complex model. The student is also able to apply these concepts to develop a model. 7. Present the fundamentals of the Index of differentialalgebraic systems of equations. The student is able to detect index>1 problems for simple cases, can describe the bilateral coupling concept and is able to apply it in order to obtain index = 1 problems. 8. Apply (based on the previous concepts) connecting rules to sub models and to formulate model decompositions. 9. Describe the basics of distributed parameters modeling, their development. Te student is able to describe examples, related boundary conditions and the use of lumped parameters model to represent distributed parameters models. 10. Apply the method to develop a model to obtain the steady state and dynamic model of a process component, to implement it in a computer code and to simulate a transient and validate the results. 
Education Method: 
Lecture 
Computer Use: 
The computer is used to develop dynamic models of plant components and to run simulations for the purpose of validating and analyzing the response of the system. Due to licenses availability on campus, Mathworks Matlab/Simulink is employed. 
Course Relations: 
Follow up courses: wb443305 Conceptual Process Design and Optimization wb443205 Process Dynamics and Control 
Literature and Study Materials: 
Course material: Printouts from lecture slides  K. Hangos, I. Cameron, Process Modelling and Model Analysis, Academic Press, 2001  MMS, Modular Modeling System v.5.1, Reference Manual, and Basics, Framatome Technologies, 1998.  O.H. Bosgra, wb2311 Introduction to modeling, Lecture notes, 2002, Delft University of Technology.  (Matlab) Simulink, online help, The Mathworks inc.  A.W. Ordys, A.W. Pike, M.A. Johnson, R.M. Katebi and M.J. Grimble, Modeling and Simulation of Power Generation Plants, Springer Verlag, London, 1994.  P. Moin, Fundamentals of Engineering Numerical Analysis, Cambridge University Press, 2001. List of scientific articles is made available to students 
Prerequisites: 
O.D.E., numerical methods: wi2051wb – Differential Eqns. Principles of programming: e.g. IN2049wbmt – Programming in Visual Basic (stopped in 2006) or in2050wbmt – Programming in Delphi Thermodynamics: wb4100 – Thermodynamics 1, wb1224 – Thermodynamics 2 Heat and Mass Transfer: wb3550 – Heat and Mass Transfer Thermodynamics of Processes and Systems: wb4302 –Tmd. Eval. of Proc. and Sys. Fluid Properties: wb442903 – Tmd of Mixtures Process/System Components: wb443505 – Equipment for heat transfer, wb443605 – Equipment for mass transfer 
Assessment: 
A sufficient performance in the written test (6) covering the content of the lectures is a prerequisite for obtaining the modeling exercise. There are to routes to pass the exam: 1. Nominal route: 2 midterm exams + modeling exercise 2. Alternative route: written exam (2 times per year, in April & November) + modeling exercise The model documentation and Simulink files must be submitted via Blackboard (Projects>File Exchange). The final course grade is given 4 times per year, after a short discussion based on the modeling exercise. Efforts are made so that the exercise is graded as soon as possible, after it has been handed in. If the exercise is evaluated less than 4, the revised exercise cannot be submitted for the subsequent examination date. 
Enrolment / Application: 
Please enroll using the Blackboard. Note: enroll only once, the first time you attend lectures. Students attending lectures in successive years should not enroll multiple times. 
Design Content: 
Modeling and simulation of components typical of energy conversion systems or chemical plants, like boilers, evaporators, condensers, turbines, compressors, distillation columns, etc. 
