SE-5101: Foundations of Physical Systems Modeling

Transcription

1 SE-5101/5201 Foundations of Physical Systems Modeling Spring 2017 University of Connecticut Institute for Advanced Systems Engineering SE-5101: Foundations of Physical Systems Modeling Course Instructor: George M. Bollas Course Objectives: This course is designed to provide students with the foundations of physical systems modeling and computational methods for performance analysis. Students will develop skills in the areas of fundamental physical and mathematical representations of heat transfer, fluid transport, separations, and their incorporation in large-scale systems. This course will also introduce concepts on how systems can be architected and designed with the aid of models and the basic principles of model-based systems engineering. Topics include system and component requirements specification, creation of system models for design and control analysis of physical systems. Emphasis is placed on the modeling of such systems in the equation oriented programming environment of the Modelica language, and the utilization of these system models within the Functional Mockup Interface for co-simulation and Model Exchange. Examples of Aircraft Environmental Control, Chiller Plants, Engines, Power Generation, and Manufacturing Systems are used for the demonstration of the theoretical and modeling aspects of physical System modeling. The course is addressed to all graduate students in engineering and students who are pursuing the System Modeling and Robust Design track or the Controlled Systems curriculum tracks of the UTC-IASE. Anticipated Student Outcomes: By the end of SE-5101/5201, students will be able to: 1) Exhibit proficiency in simulating systems with heat and mass transfer, separation, and mixing, at different levels of complexity 2) Become comfortable with concepts of acuasal, equation oriented modeling 3) Become knowledgeable of the role of modeling abstraction, reduction, and metamodeling in the field of model-based systems engineering 4) Develop skills in the fundamental physical and mathematical representations of fluid dynamics, thermodynamics, heat transfer 5) Understand how cyber-physical systems can be architected and designed with the aid of models 6) Demonstrate an ability to work in teams and to communicate effectively, via interim and final progress reports. 7) Integrate acquired knowledge in the analysis of a physical system of their field. 1

2 Course Organization The course is organized into five learning modules: (1) Industry product development processes and Model-Based Systems Engineering principles (2) Modeling preliminaries (3) Thermal fluid system models and applications (4) Large-scale system modeling (5) Model abstraction and exchange Background information is provided and required on the following subjects: (1) Thermodynamic Laws (2) Conservation of Mass, Momentum and Energy (3) Steady state and dynamic form of transport equations. (4) Thermodynamic properties, gas mixtures and equilibrium (5) Control-volume analysis. (6) Viscous and inviscid flows (7) Mechanics and Thermodynamics of Compressible Flow (8) Turbulent flow (9) Conservation of energy and Bernoulli s equation (10) Pressure drop in pipes, valves etc. (11) Mathematical Approximations in Physical Systems Modeling a. Ordinary Differential Equations and their solvers b. Geometric and related classifications of Partial Differential Equations c. Solution methods for PDE systems d. Introduction to finite differences, finite volumes, finite elements e. Differential Algebraic Equations and their solvers (12) Maxwell s equations and basic electromagnetics The structuring of these learning modules into 13 lectures of a one semester course, along with the topics and references, is described in the following. 2

3 SE-5101: Foundations of Physical Systems Modeling Fundamental Methods & Engineering Science System Control Thermal Fluid Systems Modeling Uncertainty Analysis & Robust Design Formal Methods Embedded / Networked Systems Modeling Abstractions Design Flows System Design Controlled Systems Embedded Systems Common Examples & Capstone Projects Course Outline Module 1: Model-Based Systems Engineering Principles Lecture 1: Model-Based Systems Engineering Fundamentals Where does this course fit in: Requirements, Simulation, Optimization, Control & Performance o Translation of requirements into objective functions o Systems modeling o Component modeling, model libraries and large-scale systems o Mathematical implications o Cross-platform modeling o Controlled systems o Modeling abstraction and reduction in MBSE Model-Based Systems Engineering and INCOSE definitions Systems design principles o V-design principles o Phase Gate Design o Platform-based design Modeling approaches o Causal and acuasal modeling o Concepts and approaches to modeling abstraction Course housekeeping o Software availability o Procedures 3

4 Module 2: Modeling Preliminaries Lecture 2: Introduction to Acausal Modeling and the Modelica Language Concepts of modeling and the impact of causality o Object oriented programing o Equation oriented modeling o Model structures, classes and notation o Inheritance Introduction to Modelica o Classes and variables Equations Arrays Algorithms and Functions Examples Lecture 3: Introduction to Dymola and Model Libraries Modeling and Simulation Environments using the Modelica language Dymola libraries o Modelica Libraries o Modelica Media o Dymola Libraries o Other Examples Lecture 4: General Principles of Modeling Flow and Effort Fundamental analogies between mechanical, electrical, hydraulic and thermal system modeling Electrical, Mechanical, Electromechanical, Hydraulic and Thermal Systems Examples Lecture 5: Mathematical Approximations Ordinary Differential Equations and their solvers Geometric and related classifications of Partial Differential Equations Solution methods for PDE systems o Introduction to finite differences, finite volumes, finite elements Differential Algebraic Equations and their solvers Module 3: Thermal Fluid Systems Lecture 6: Heat Transfer and Applications 4

5 Heat transfer fundamentals Heat Exchangers and types Heat transfer modeling applications & examples Lecture 7: Fluid Transport and Pressure Change Applications Fluid Transport Fundamentals Pipes Valves, Compressors & Turbines Fluid Transport modeling applications & examples Lecture 8: Separations and Applications Phase change separations Membrane separations Separations modeling applications & examples Module 4: Large-Scale System Modeling Lecture 9: System Control and Cyber-Physical Systems Cyber-physical Systems: definitions and implications Actuators Sensors Controllers o Basic Concepts of P, PI and PID controller modeling o Model-based controller tuning fundamentals Lecture 10: Composing Acausal Models for Large-Scale Systems Composing system level models in Dymola Component couplings (pressure, temperature, enthalpy, mass flow) System flowsheets in Dymola Different time scales, stiff systems and pseudo-steady-state models Lecture 11: Large-Scale System Models Examples Chiller Plants Aircraft Environmental Control Systems Vapor and gas cycles: (Rankine, Vapor refrigeration, Brayton) Power Systems Manufacturing Module 5: Model Extensions: Abstraction & Exchange Lecture 12: Modeling Abstractions 5

6 Definitions: Model Abstraction, Reduction, Approximation, etc. Introduction to Model Reduction Methods Meta-modeling and surrogate models Model Abstraction Grey-box (hybrid) modeling Lecture 13: Bring it all together: The Functional Mockup Interface (FMI) Introduction to the functionality and use of the FMI FMI for Model Exchange FMI for Co-Simulation Advanced FMI manipulation in Matlab Examples 6

7 USEFUL READING References for Thermodynamics, Fluid Mechanics and Heat and Mass Transfer 1. Fundamentals of Engineering Thermodynamics (6 th edition), M. J. Moran and H.N. Shapiro, Wiley. ISBN: Fundamentals of Fluid Mechanics (6 th edition), M.R. Munson, D.F. Young, T. H. Okiishi and W.W. Huebsch, Wiley. ISBN: Fundamentals of Heat and Mass Transfer (6 th edition), F. P. Incropera, D. P. Dewitt, T. L. Bergman and A. S. Lavine, Wiley. ISBN: References for Thermo-Fluid Examples 1. J. F. Blackburn, J. L. Shearer by, G. Reethof Fluid Power Control. MIT Press. 2. Ma, Y., F. Borrelli, B. Hencey, B. Coffey, S. Bengea and P. Haves Model Predictive Control for the Operation of Building Cooling Systems. Control Systems Technology. 3. Watton, J Fundamentals of Fluid Power Control. Cambridge. 4. Wetter, M Modeling of Thermofluid Networks near Zero Mass Flow Rate with Feedback Control using an Equation-Based Language. LBNLWorking Paper. References for Modelica modeling 1. Introduction to Modeling and Simulation of Technical and Physical Systems with Modelica, P. Fritzson, 2011, Wiley-IEEE Press ISBN: Introduction to Physical Modeling with Modelica, M. Tiller, Springer, 2001 ISBN: Principles of Object-Oriented Modeling and Simulation with Modelica 2.1, P. Fritzson, 2004, Wiley-IEEE Press ISBN:

8 Course Delivery & Grading The course will be offered online in small recorded modules according to the course syllabus. Direct communication with the instructor will be available once a week for discussion, questions and quizzes. Grading of the course will be exclusively based on the Course Project described below. Optional homework and quizzes will be assigned to students during the semester for bonus grade. Project, Presentations and Project Report A project is to be developed by each student, which is expected to evolve during the entirety of the semester. The project refers mainly to design project identification, challenge quantification, significance and relevance to the MBD philosophy, plan of attack, system modeling, system optimization using cross-platform programming. The final deliverable (presentation) should identify all the aforementioned elements in a quantifiable manner and suggest a strategy for solution. A separate rubric with the details of the project will be provided to the students on HuskyCT. A mid-term and final report are the main deliverables of this project, on the basis of which student will be graded. 8

9 Other Policies Student Conduct: Students are responsible for adherence to the University of Connecticut student code of conduct. Perhaps the most important policy to pay attention to is the section on Student Academic Misconduct. Academic misconduct is dishonest or unethical academic behavior that includes, but is not limited, to misrepresenting mastery in an academic area (e.g., cheating), intentionally or knowingly failing to properly credit information, research or ideas to their rightful originators or representing such information, research or ideas as your own (e.g., plagiarism). Examples of academic misconduct in this class include, but are not limited to: copying solutions from the solutions manual, using solutions from students who have taken this course in previous years, copying your friends homework, looking at another student s paper during an exam, lying to the professor or TA and incorrectly filling out the student workbook. Attendance: Attendance will not be taken; however, it is practically impossible to follow the class if classes are missed. Absences: Make-up of missed exams requires permission from the Dean of Students, see Academic Regulations. Midterm-exams are treated the same as Final Examinations. Students involved in official University activities that conflict with class time must inform the instructor in writing prior to the anticipated absence and take the initiative to make up missed work in a timely fashion. In addition, students who will miss class for a religious observance must inform their instructor in writing within the first three weeks of the semester, and prior to the anticipated absence, and should take the initiative to work out with the instructor a schedule for making up missed work. 9

10 Course Schedule * Date 1 Topic Module No Jan 23 Lecture 1: Model-Based Systems Engineering Fundamentals 1 Project Dates Jan 30 Lecture 2: Introduction to Acausal Modeling and the 2 Modelica Language Feb 6 Lecture 3: Introduction to Dymola and Model Libraries 2 Feb 13 Lecture 4: General Principles of Modeling 2 Project Proposal Report Feb 20 Lecture 5: Mathematical Approximations 2 Feb 27 Lecture 6: Heat Transfer and Applications 3 Mar 6 Lecture 7: Fluid Transport and Pressure Change 3 Applications Mar 20 Lecture 8: Separations and Applications 3 Mar 27 Lecture 9: System Control and Cyber-Physical Systems 4 Project Mid-Term Report Apr 3 Lecture 10: Composing Acausal Models for Large-Scale 4 Systems Apr 10 Lecture 11: Large-Scale System Models Examples 4 Apr 17 Lecture 12: Modeling Abstractions 5 Apr 24 Lecture 13: Bring it all together: The Functional Mockup Interface 5 May 1 End of class, final project due Project Final Report * Schedule is tentative and may change 1 Date indicates release of lecture modules Instructors Contact Information: George Bollas: george.bollas@uconn.edu Helpful links: Virtual Computer Lab at UConn: Course Material: Institute for Advanced Systems Engineering: 10