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EUSC Spring 2014

This course teaches students how to systematically solve engineering problems by decomposing them and using tools such as advanced spreadsheet features and MATLAB. Topics covered include problem decomposition, data representation, curve fitting, mathematical modeling, and team-based engineering projects.

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EUSC Spring 2014

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  1. EUSCSpring 2014 EGR 102 Update

  2. Course Description • Application of systematic approaches to engineering problems. Problem decomposition and identification of a solution approach. Solution using tools such as advanced spreadsheet features and MATLAB. Data representation, curve fitting and analysis. Mathematical modeling of engineering systems. Application of principles through team-based engineering projects. • Prerequisite • (EGR 100 or concurrently*) and ((MTH 132 or concurrently) or (MTH 152H or concurrently) or (LB 118 or concurrently)) *math ready students are taking EGR 102 1st due to enrollment issues 100 is in the process of being removed as a pre-erq

  3. EGR 102 Course Learning Objectives Students will be able to: • systematically solve engineering problems by decomposition to determine solution approaches • solve problems using appropriate computational tools • graphically portray data in meaningful manner using spreadsheet programs & advanced computational environments • write programs to solve problems & model systems • interpret & communicate results

  4. Instructional Model • Lecture once a week • Hard copy of homework • Quiz over prior week topic • 2 80 minute labs/week • 1 TA • 2-3 mentors per lab (goal is ~10 to 1) • Electronic submission for each lab

  5. Enrollment • Fall 2013 • 351 students • 1 lecture section • 10 Lab sections • Spring 2014 • 780 students • 2 lecture sections • 18 Lab sections

  6. Topics Covered in Lecture and Lab • Conservation Law • Cost Engineering • Matrix Math • Gaussian Elimination • Curve Fitting • Linear Regression • Polynomial Regression • Structured Programing • Flow Charting • Root Finding • Optimization • Numerical Integration • ODEs • Introduction to Excel (4 labs) • Basics • If functions and nested If functions • Solver • Matrix Multiplication (MMULT) • Trend lines and error bars • Introduction to MATLAB (14 labs) • Basics • Scripts • Functions • Vectors • Plotting • Iterative Programming • Nested Programming • Project (6 Labs) • Writing • Exams, Final wrap up (5 labs) Lecture Lab General subject selection is process driven for skill set development

  7. Matching Weeks • Cost Engineering • Homework requires both hand calculation and Excel work using intrinsic functions • Matrix Review and Gaussian elimination • Homework emphasizes systematic approach • Bisection and Newton-Raphson Root finding • Excel Basics and Functions • MATLAB Introduction lab homework focuses on matrix manipulation • Iterative programming application of Newton-Raphson • Nested Programming and functions application is Bisection method Lecture Lab

  8. Cost Engineering • Time value of money • Cost, including incremental, average, sunk, and estimating • Economic analyses • Depreciation

  9. Cash Flow Diagram • All options need to be evaluated at the same ‘time’ • Present worth analysis Present Worth Option 1 $1,000,000.00 Option 2 $641,057.64 Option 3 $1,227,826.51 Lecture 02

  10. Bisection Method • Root finding • Good mathematical formulation • Specific criteria to follow • Algebraic equations • Comparison criteria easily understood

  11. Start Flow Chart xl, xu, Lmin Calculate estimated root: xr= [xl+xu)/2] <0 (xu – xl) ‐ Lmin >0 >0 F(xl)*F(xr) <0 =0 F(xl)* F(xr)] xu=xr xl=xr Stop

  12. MATLAB function [ root,iterations ] = bisection2( xU,xL,Lmin) % Inputs: xU, upper limit of interval % xL, lower limit of interval % Lmin, tolerance % Outputs: root, final root after iterating % iterations, number of iterations performed %------------------------------------------------------------------------- %Evaluate f(xu) and f(xl) by calling function f_5A fU=f_5A(xU); fL=f_5A(xL); %Display an error message if the interval supplied is not valid if (fU*fL)>0 error(':( The equation does not cross the x-axis in the interval supplied') end %Initialize counter by setting it equal to zero. Initialize interval length L=xU-xL; counter=0; %Create the While loop to perform the bisection method while L>=Lmin %Calculate xR and xR=(xU+xL)/2; %Calculate f(xr) and f(xL) fR=f_5A(xR); fL=f_5A(xL); %If fR*fL is greater than zero, xL becomes xR, if it is less than zero, %xU becomes xR. if (fR*fL)>0; xL=xR; else (fR*fL)<0; xU=xR; end %Update counter counter=counter+1; L=xU-xL; end %Define the outputs root=xR; iterations=counter;

  13. Current Project • Wastewater Treatment Plant: Lift station Pump design • Develop system curves from data • Manipulate given data in Excel, produce file that is imported to MATLAB • Requires use of Excel help for Table look up • Create distinct vectors from imported data • Write code for calculation of head loss • Requires use of MATLAB help for intrinsic 2nd order polynomial fit • Create plots of system curves to select pump • Annual Cost analysis of pump options

  14. EGR 102 Prior Project • Bumper crash analysis • Data from local design house • Objective: • Maximize energy absorption • Optimize key radii & material thickness • Tasks: • Evaluate design at key points • Generate & filter force-deflection curves • Calculate energy by numerical integration • Surface curve fit energy, stroke & stress data • Optimize design CoRe Experience

  15. Overriding Theme • Problem Solving • Thought process • Engineering Approach • Select the best tool for solution • Calculator • Excel • MATLAB

  16. Challenges • 2 credit course • Instructional Model • Number of students • Moving away from text • Requiring purchase of MATLAB and Calculator • Computer skills from HS • Range from none to extensive • Transference? • RAM of calculator (TI-83) • 25 by 25 matrix inversion • But I can just right click… • YouTube said… • Wolfram alpha • Academic Dishonesty Course perspective Students perspective

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