Introduction to Engineering: A Project-Based Method
Edition: 1
Copyright: 2018
Pages: 228
Edition: 1
Copyright: 2019
Pages: 230
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Project 1: Importance of an Engineering Field/A Day at Work/How to Become an Engineer in that Field/Information of Interest/Delivery/Specific Engineering Project
1.1 Project 1 –Engineering Fields
1.1.1 What to Do?
1.1.2 What to Write in the Reports?
1.2 Brainstorming
1.3 Presentation Skills, Report Writing, References Formatting
1.4 Logbook
1.5 Team Web Page
1.6 What is Engineering?
1.6.1 Continuing Education
1.6.2 Management & Technical/ Engineering Ethics
1.6.3 What is the Difference between Science and Engineering?
1.6.4 Engineering Design Process
1.6.5 Input (independent variable)/Output (dependent variable) System Diagram
1.6.6 Data Modeling
1.6.7 Prediction
Project 2: Design for Predictability & Data Modeling
2.1 Project 2 –Engineering Design: Data Modeling and System Predictability
2.2 Data Collection: Systematic and Random Error Reduction
2.3 Human Factor
2.4 Excel: Built-in Functions, Elementary Math Functions, Coefficients vs. Independent Variable, XY Scatter Plot (Scatter with only Markers and Scatter with Smooth Lines), Chart Layouts (Chart Title and Axis Titles), Solver Add-in, Copy Columns of Data into Excel, Text-toColumn, Swapping Two Columns of Data, Sorting Data
2.4.1 Excel Built-in Functions and Elementary Math Functions
2.4.2 Data Modeling with Excel –Cubic Polynomial
2.4.3 Data Modeling with Excel –Other Polynomial Models
2.5 Full Polynomial Model & Engineering vs. Highest Order Polynomial & Science
2.6 Calculation of the Constant Acceleration of Gravity g From a pendulum data
2.7 Non-linear Exponential Models & NIST Ultrasonic Response vs. Metal Distance
2.8 Notations, Formulas and Dimensional Analysis, Units, Accuracy and Significant Figures, Scientific Notation
2.8.1 Notations
2.8.2 Physics Formulas and Dimensional Analysis
2.8.3 Units
2.8.5 Scientific Notation
2.8.6 Accuracy and Significant Figures
2.9 Estimation: Adopting a Simple Model and Establishing a Method of Calculation
2.10 Problem Solving: Diagrams, Equations, Math Calculations and Check
Project 3 Virtual Instrument vs. Physical Instrument
3.1 Project 3A –Developing Virtual Instruments
3.2 Introduction to LabVIEW
3.2.1 How to Locate Different Elements within the Front Panel and the Block Diagram
3.3 Circuit Analysis: Series and Parallel, Ohm’s Law
3.3.1 Circuit Analysis with LabVIEW I
3.3.2 Implementation
3.3.3 Saving a VI into a LabVIEW Library
3.3.4 Circuit Analysis with LabVIEW II
3.3.5 Implementation
3.3.6 Circuit Analysis with LabVIEW III
3.3.7 Implementation
3.4 LabVIEW Sub Virtual Instruments: Terminal Patterns, Edit Icon, Select a VI Programming Function
3.4.1 Circuit Analysis with LabVIEW IV
3.4.2 Implementation
3.5 Scaling up Applications: Sub VI/Subroutine/Super-operator: Advantages and Disadvantages
3.6 Project 3B -VI for Solving Complex Circuits using Matrices
3.6.1 Loop Analysis
3.6.2 Solution using Matrices
3.6.3 Implementation
3.6.4 How do these Three Equations from Loop Analysis Lead to the Equations we got from Doing Series and Parallel Combinations
Project 4 Virtual Instrument for Specific Application
4.1 Project 4 -Developing Virtual Instruments for a Client
4.1.1 Suggested LabVIEW Elements for each Project
4.1.2 Part II Assigned Modifications for each Project
4.2 Plotting a Function with LabVIEW: For Loop (Functions/Programming/Structures), Evaluation of a Single Variable Array (Functions/Mathematics/Scripts & Formulas/1D & 2D Evaluations), Bundle (Functions/ Programming/Cluster Class & Variant)
4.2.1 Introduction to Function Plotting
4.2.2 Generating the Time Series
4.2.3 Plotting a Function with LabVIEW
4.2.4 Smoother Plot and Time Series Resolution: N and ∆
4.2.5 How to Change the Plotting Interval
4.3 Time of Flight with LabVIEW: Less? or Greater? (Functions/Programming/Comparisons), Case Structure (Functions/Programming/Structures), Formula Node (Functions/Programming/Structures), Numeric Constant (Functions/Programming/Numeric), String Constant (Functions/Programming/String)
4.3.1 Physics of the Time of Flight
4.3.2 LabVIEW Implementation
4.3.3 Testing the Time-of-flight Virtual Instrument
4.3.4 Using the Virtual Instrument to Find the Maximum Initial Velocity up to a Given Number of Digits of Precision
4.4 Sound Wave Superposition: Formula Waveform (Functions/Signal Processing/Waveform Generation), Shift Register and For Loop (Functions/Programming/Structures), Play Waveform (Functions/Programming/Graphics & Sound/Sound/Play Waveform), FFT (Functions/Signal Processing/ Transforms), Absolute Value (Functions/Programming/ Numeric)
4.4.1 Introduction to Sinusoids
4.4.2 Superposition of Two Sinusoids
4.4.3 Spectrum of a Sum of Sinusoids
4.5 Binary Numbers and A/D and D/A Conversions
4.5.1 Analog to Digital Conversion (A/D)
4.5.2 Digital to Analog Conversion (D/A)
4.5.3 The Binary Dot
4.5.4 Power and Limitation of a Digital Computer
4.6 Data Modeling and Random Noise: Array (Controls/ Array, Matrix & Clusters), XY Graph (Controls/ Graph), Random Number (0-1) (Functions/Programming/Numeric), Build Array (Functions/Programming/ Array), Eval Single–Variable Array (Functions/Mathematics/Scripts & Formula/1D & 2D Evalution), Gaussian Peak Fit (Functions/Mathematics/Fitting)
Project 5 Data Modeling with Matlab
5.1 Project 5
5.2 Matlab: importdata, sort, polyfit, polyval, struct2cell, cell2mat, for, if, input, figure, plot, subplot, axis, xlabel, ylabel, title, strcat, num2str
5.2.1 Introduction to MatLab
5.2.2 Introduction to MatLab -Transition from Analog to Digital Waves
5.2.3 Introduction to MatLab –Matrices
5.2.4 Introduction to MatLab –Matrices & For Loop
5.2.5 Data Modeling with Matlab –Project 5
5.2.6 Data Modeling with Matlab –Project 5 (II)
Project 6 Visualizing Motion in 2D & 3D with Matlab
6.1 Project 6 –Moving Objects in 2D & 3D with Matlab
6.2 Matlab: polar, plot3, surf, ezmesh, ezmeshc, ezsurf, ezsurfc, ezcontour, ezcontourf, ezplot3, ezpolar, sosurface
6.2.1 Visualization with Matlab: Representing Sinusoids of Different Frequencies with ezplot and plot
6.2.2 Visualization with Matlab: Moving 2D and 3D Gaussian Pulses
Appendix A – Project Report Template
Appendix B – Logbook Questions
Appendix C – Classwork
Appendix D – Homework
Appendix E – What is Engineering?
Appendix F – Instructions for the Team Webmaster
Appendix G – Report-Related Web Pages
Dr. Materdey is an award-winning faculty at the University of Massachusetts Boston. He has taught project-based introduction to engineering for over 20 years. In the classroom, he promotes active learning by guiding students through design projects, asking questions and applying problem solving skills. He combines expertise in electrical engineering, physics, mathematics, and industry consulting to deliver self-sufficient, interconnected, concise and flexible lessons for students to learn and discover the subject matter quickly while remembering fundamental concepts for life. The Committee’s Chair for the Academic Quality Assessment and Development Review, Prof Ronald Roedel, Associate Dean of the Ira A. Fulton School of Engineering, Arizona State University, wrote ‘this Introduction to Engineering is an exemplary course that could be a model for any program in the country’. Dr. Materdey received a Ph.D. in computational electromagnetics from the University of Granada, Spain, and a Ph.D. in theoretical physics from Cornell University. He is a founding member of the University of Massachusetts Boston's Engineering Department, and currently serves as its Undergraduate Program Director.
Project 1: Importance of an Engineering Field/A Day at Work/How to Become an Engineer in that Field/Information of Interest/Delivery/Specific Engineering Project
1.1 Project 1 –Engineering Fields
1.1.1 What to Do?
1.1.2 What to Write in the Reports?
1.2 Brainstorming
1.3 Presentation Skills, Report Writing, References Formatting
1.4 Logbook
1.5 Team Web Page
1.6 What is Engineering?
1.6.1 Continuing Education
1.6.2 Management & Technical/ Engineering Ethics
1.6.3 What is the Difference between Science and Engineering?
1.6.4 Engineering Design Process
1.6.5 Input (independent variable)/Output (dependent variable) System Diagram
1.6.6 Data Modeling
1.6.7 Prediction
Project 2: Design for Predictability & Data Modeling
2.1 Project 2 –Engineering Design: Data Modeling and System Predictability
2.2 Data Collection: Systematic and Random Error Reduction
2.3 Human Factor
2.4 Excel: Built-in Functions, Elementary Math Functions, Coefficients vs. Independent Variable, XY Scatter Plot (Scatter with only Markers and Scatter with Smooth Lines), Chart Layouts (Chart Title and Axis Titles), Solver Add-in, Copy Columns of Data into Excel, Text-toColumn, Swapping Two Columns of Data, Sorting Data
2.4.1 Excel Built-in Functions and Elementary Math Functions
2.4.2 Data Modeling with Excel –Cubic Polynomial
2.4.3 Data Modeling with Excel –Other Polynomial Models
2.5 Full Polynomial Model & Engineering vs. Highest Order Polynomial & Science
2.6 Calculation of the Constant Acceleration of Gravity g From a pendulum data
2.7 Non-linear Exponential Models & NIST Ultrasonic Response vs. Metal Distance
2.8 Notations, Formulas and Dimensional Analysis, Units, Accuracy and Significant Figures, Scientific Notation
2.8.1 Notations
2.8.2 Physics Formulas and Dimensional Analysis
2.8.3 Units
2.8.5 Scientific Notation
2.8.6 Accuracy and Significant Figures
2.9 Estimation: Adopting a Simple Model and Establishing a Method of Calculation
2.10 Problem Solving: Diagrams, Equations, Math Calculations and Check
Project 3 Virtual Instrument vs. Physical Instrument
3.1 Project 3A –Developing Virtual Instruments
3.2 Introduction to LabVIEW
3.2.1 How to Locate Different Elements within the Front Panel and the Block Diagram
3.3 Circuit Analysis: Series and Parallel, Ohm’s Law
3.3.1 Circuit Analysis with LabVIEW I
3.3.2 Implementation
3.3.3 Saving a VI into a LabVIEW Library
3.3.4 Circuit Analysis with LabVIEW II
3.3.5 Implementation
3.3.6 Circuit Analysis with LabVIEW III
3.3.7 Implementation
3.4 LabVIEW Sub Virtual Instruments: Terminal Patterns, Edit Icon, Select a VI Programming Function
3.4.1 Circuit Analysis with LabVIEW IV
3.4.2 Implementation
3.5 Scaling up Applications: Sub VI/Subroutine/Super-operator: Advantages and Disadvantages
3.6 Project 3B -VI for Solving Complex Circuits using Matrices
3.6.1 Loop Analysis
3.6.2 Solution using Matrices
3.6.3 Implementation
3.6.4 How do these Three Equations from Loop Analysis Lead to the Equations we got from Doing Series and Parallel Combinations
Project 4 Virtual Instrument for Specific Application
4.1 Project 4 -Developing Virtual Instruments for a Client
4.1.1 Suggested LabVIEW Elements for each Project
4.1.2 Part II Assigned Modifications for each Project
4.2 Plotting a Function with LabVIEW: For Loop (Functions/Programming/Structures), Evaluation of a Single Variable Array (Functions/Mathematics/Scripts & Formulas/1D & 2D Evaluations), Bundle (Functions/ Programming/Cluster Class & Variant)
4.2.1 Introduction to Function Plotting
4.2.2 Generating the Time Series
4.2.3 Plotting a Function with LabVIEW
4.2.4 Smoother Plot and Time Series Resolution: N and ∆
4.2.5 How to Change the Plotting Interval
4.3 Time of Flight with LabVIEW: Less? or Greater? (Functions/Programming/Comparisons), Case Structure (Functions/Programming/Structures), Formula Node (Functions/Programming/Structures), Numeric Constant (Functions/Programming/Numeric), String Constant (Functions/Programming/String)
4.3.1 Physics of the Time of Flight
4.3.2 LabVIEW Implementation
4.3.3 Testing the Time-of-flight Virtual Instrument
4.3.4 Using the Virtual Instrument to Find the Maximum Initial Velocity up to a Given Number of Digits of Precision
4.4 Sound Wave Superposition: Formula Waveform (Functions/Signal Processing/Waveform Generation), Shift Register and For Loop (Functions/Programming/Structures), Play Waveform (Functions/Programming/Graphics & Sound/Sound/Play Waveform), FFT (Functions/Signal Processing/ Transforms), Absolute Value (Functions/Programming/ Numeric)
4.4.1 Introduction to Sinusoids
4.4.2 Superposition of Two Sinusoids
4.4.3 Spectrum of a Sum of Sinusoids
4.5 Binary Numbers and A/D and D/A Conversions
4.5.1 Analog to Digital Conversion (A/D)
4.5.2 Digital to Analog Conversion (D/A)
4.5.3 The Binary Dot
4.5.4 Power and Limitation of a Digital Computer
4.6 Data Modeling and Random Noise: Array (Controls/ Array, Matrix & Clusters), XY Graph (Controls/ Graph), Random Number (0-1) (Functions/Programming/Numeric), Build Array (Functions/Programming/ Array), Eval Single–Variable Array (Functions/Mathematics/Scripts & Formula/1D & 2D Evalution), Gaussian Peak Fit (Functions/Mathematics/Fitting)
Project 5 Data Modeling with Matlab
5.1 Project 5
5.2 Matlab: importdata, sort, polyfit, polyval, struct2cell, cell2mat, for, if, input, figure, plot, subplot, axis, xlabel, ylabel, title, strcat, num2str
5.2.1 Introduction to MatLab
5.2.2 Introduction to MatLab -Transition from Analog to Digital Waves
5.2.3 Introduction to MatLab –Matrices
5.2.4 Introduction to MatLab –Matrices & For Loop
5.2.5 Data Modeling with Matlab –Project 5
5.2.6 Data Modeling with Matlab –Project 5 (II)
Project 6 Visualizing Motion in 2D & 3D with Matlab
6.1 Project 6 –Moving Objects in 2D & 3D with Matlab
6.2 Matlab: polar, plot3, surf, ezmesh, ezmeshc, ezsurf, ezsurfc, ezcontour, ezcontourf, ezplot3, ezpolar, sosurface
6.2.1 Visualization with Matlab: Representing Sinusoids of Different Frequencies with ezplot and plot
6.2.2 Visualization with Matlab: Moving 2D and 3D Gaussian Pulses
Appendix A – Project Report Template
Appendix B – Logbook Questions
Appendix C – Classwork
Appendix D – Homework
Appendix E – What is Engineering?
Appendix F – Instructions for the Team Webmaster
Appendix G – Report-Related Web Pages
Dr. Materdey is an award-winning faculty at the University of Massachusetts Boston. He has taught project-based introduction to engineering for over 20 years. In the classroom, he promotes active learning by guiding students through design projects, asking questions and applying problem solving skills. He combines expertise in electrical engineering, physics, mathematics, and industry consulting to deliver self-sufficient, interconnected, concise and flexible lessons for students to learn and discover the subject matter quickly while remembering fundamental concepts for life. The Committee’s Chair for the Academic Quality Assessment and Development Review, Prof Ronald Roedel, Associate Dean of the Ira A. Fulton School of Engineering, Arizona State University, wrote ‘this Introduction to Engineering is an exemplary course that could be a model for any program in the country’. Dr. Materdey received a Ph.D. in computational electromagnetics from the University of Granada, Spain, and a Ph.D. in theoretical physics from Cornell University. He is a founding member of the University of Massachusetts Boston's Engineering Department, and currently serves as its Undergraduate Program Director.