Introduction This module about Process Optimization was produced under the Program for North American Mobility in Higher Education as part of the Process.

Slides:

Advertisements

Similar presentations

Tier III: Optimization Design Problems Derek McCormack Section 1: Sample Problems.

Advertisements

Lingo Optimization Software

CHEN 4460 – Process Synthesis, Simulation and Optimization

Convex Optimization Chapter 1 Introduction. What, Why and How  What is convex optimization  Why study convex optimization  How to study convex optimization.

Mohamed Hefeeda 1 School of Computing Science Simon Fraser University, Canada Multimedia Streaming in Dynamic Peer-to-Peer Systems and Mobile Wireless.

ECIV 301 Programming & Graphics Numerical Methods for Engineers.

EMGT 501 HW # (b) (c) 6.1-4, Due Day: Sep. 21.

Supply Chain Design Problem Tuukka Puranen Postgraduate Seminar in Information Technology Wednesday, March 26, 2009.

__________________ Engineering Education Systems for Environmental Project Management - Example of the Amise Simulation Program François Baillon School.

The Islamic University of Gaza Faculty of Engineering Numerical Analysis ECIV 3306 Introduction.

Lecture outline Support vector machines. Support Vector Machines Find a linear hyperplane (decision boundary) that will separate the data.

Introduction to Management Science

Introduction to Management Science

Optimization of Linear Problems: Linear Programming (LP) © 2011 Daniel Kirschen and University of Washington 1.

Water Resources Planning and Management Daene C. McKinney Introduction.

Wind Power Scheduling With External Battery. Pinhus Dashevsky Anuj Bansal.

Goals and aims To introduce Linear Programming To find a knowledge on graphical solution for LP problems To solve linear programming problems using excel.

Engineering & the Environment. Lei Wang October 20, 2004 ECE 290.

CHAPTER 7 NON-LINEAR CONDUCTION PROBLEMS

One Place for all profitable web solutions Getontheweb.in Himansshu H Singh P E -

Some aspects of energy efficiency and energy conservation in buildings Dorota Chwieduk Department of Eco-Building Engineering Institute of Fundamental.

M ATHEMATICAL F RAMEWORK FOR O PTIMIZATION OF V ACATION P ACKAGE S YNTHESIS P ROCESS Group-CI-G1.

Introduction from NetDimensions Andrew Lupton.

Introduction to Management Science

Web Service Development Within Different Study Years Maja Pušnik, Boštjan Šumak Institute of Informatics, FERI Maribor.

Ilkka Kiema Future Internet and Economics (FIEN) Workshop May 6, 2009 Some Economic Aspects of Future Internet.

Bachelor’s Program in CIVIL ENGINEERING Duration of Studies: 8 terms Academic Degree to be Awarded Bachelor of Civil Engineering.

© 2015 McGraw-Hill Education. All rights reserved. Chapter 1 Introduction.

The Balance Between Theoretical and Practical Work Within Electrical and Computer Engineering Courses Dr. Bahawodin Baha March Development Partnerships.

Bettina Muster-Slawitsch AEE – Institut für Nachhaltige Technologien (AEE INTEC) A-8200 Gleisdorf, Feldgasse 19 AUSTRIA Integration of Solar Heat in Industry.

MEASURE THE QUALITY OF SERVICES WITH INTELLIGENT CHECKLISTS MODERN QUALITY CONTROLS EASY. FAST. INTELLIGENT.

Professor: Chu, Ta Chung Student: Nguyen Quang Tung Student’s ID: M977Z235 Fuzzy multiobjective linear model for supplier selection in a supply chain.

Mathematical Models & Optimization?

OR Chapter 1. Introduction  Ex : Diet Problem Daily requirements : energy(2000kcal), protein(55g), calcium(800mg) Food Serving size Energy (kcal)

Most of contents are provided by the website Introduction TJTSD66: Advanced Topics in Social Media Dr.

CSE 102 Introduction to Computer Engineering What is Computer Engineering?

Finite Element Methods and Crack Growth Simulations Materials Simulations Physics 681, Spring 1999 David (Chuin-Shan) Chen Postdoc, Cornell Fracture Group.

Operations Research The OR Process. What is OR? It is a Process It assists Decision Makers It has a set of Tools It is applicable in many Situations.

CSE4334/5334 DATA MINING CSE4334/5334 Data Mining, Fall 2014 Department of Computer Science and Engineering, University of Texas at Arlington Chengkai.

Implementation of Innovations at FSMN by Miroslav Ćirić & Predrag Krtolica.

1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle.

Linear Programming and Applications

Introduction of Outcomes-based Curricula Ministry of Education Fall 2008.

Tier 2Modulo 15NAMP Process Control and Process Integration 1 Created at Universidad de Guanajuato & École Polytechnique de Montréal Module 15: Process.

Process design and integration Timo Laukkanen. The main objectives of this course To learn how to use tools that can be used to design heat recovery systems.

The fundamental problem in education What the Teacher would like to teach.

Online Knowledge Product SAP SCM 7.0 online training Online | classroom| Corporate Training | certifications | placements| support CONTACT US: MAGNIFIC.

S5.40. Module Structure 30% practical tests / 70% written exam 3h lectures / week (except reading week) 3 x 2h of computer labs (solving problems practicing.

Advanced Energy Solutions

Transportation Networks CIVE 744

Ardavan Asef-Vaziri Systems and Operations Management

Introduction to Linear Programs

We teach ATM Networks to Think

Xiaohong (Dorothy) Yuan North Carolina A&T State University 11/16/2017

Lecture Objectives: Discuss accuracy of energy simulation and Introduce advance simulation tools Review the course topics Do the Course and Instructor.

Process design, process integration and energy system optimization

H. Dennis Spriggs, Benjamin J. Brant, Daniel L. Rudnick

Introduction This module about Process Optimization was produced under the Program for North American Mobility in Higher Education as part of the Process.

Support Vector Machines Introduction to Data Mining, 2nd Edition by

Teaching to the Rigor of the CCSS in Mathematics Grades 6-HS

Technical Graphics Design Appreciation and Awareness

Module 40 Planning Our Energy Future

I. Floorplanning with Fixed Modules

A Mathematical Programming Language

Tier III: Optimization Design Problems

Basics of Energy Management

Solving Equations 3x+7 –7 13 –7 =.

Requirements Engineering

Survey on Coverage Problems in Wireless Sensor Networks - 2

Enterprise Systems Optimization Spring, 2012

Presentation transcript:

Introduction This module about Process Optimization was produced under the Program for North American Mobility in Higher Education as part of the Process Integration for Environmental Control in Engineering curricula. It was produced by students at Texas A&M University (Daniel Grooms) and the University of Ottawa (Derek McCormak).Texas A&M University University of Ottawa

Purpose The purpose of this module is to teach fundamental aspects of process optimization. Process optimization is a very important subject. If a process is not optimized, it will not use energy or raw materials efficiently, and ultimately not be as profitable. With increasingly stringent environmental regulations, and an ever increasing demand on natural resources, process optimization is necessary to operate responsibly and profitably. The goal of this module is to teach the student the basics of mathematical optimization and to introduce some more complex material to attempt to develop a solution formulation process.

Module Structure This module is structured as three tiers, each with a specific goal. Each tier has several subsections. Tier I: Mathematical Methods of Optimization Tier II: Case Studies Tier III: Optimization Design Problems

Tier I Tier I contains some of the most common mathematical methods used for optimization. Solved examples have been given with each method for the student to follow along with. The goal of this tier is to provide the student with a basic understanding of methods that are used to optimize functions.

Tier I Contents Tier I contains the following subsections : 1.1: Introduction 1.2: Linear Programming 1.3: Nonlinear Programming 1.4: Multi-Objective Optimization

Tier II Tier II contains some more specific cases. The first subsection introduces the student to Lingo optimization software, a program that is very user friendly and available online as a free trial version. The second subsection details a specific case, the optimization of a heat exchange network. The purpose of this tier is to introduce the student to broader optimization material.

Tier II Contents Tier II contains the following subsections: 2.1: Lingo Optimization Software 2.2: Heat Exchange Network Optimization by Thermal Pinch Analysis

Tier III Tier III contains some examples for the student to work on. Solutions have been given. The purpose of this tier is to provide the student with some practice at solving optimization problems, with the emphasis being more on the formulation of a solution than on the actual mathematics involved.

Tier III Contents Tier III contains the following subsections: 3.1: Sample Problems