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Intro. To Env. Eng. Lecture 5

Intro. To Env. Eng. Lecture 5. Chapter 2 1/27/00 2.2-2.3. Homework #2. Chapter 2 Problems: 1, 4, 7, 11, 14, 18, 22 Due February 3, 2000. Approximations in Engineering Calculations. Often engineers are called upon to answer questions quickly

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Intro. To Env. Eng. Lecture 5

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  1. Intro. To Env. Eng. Lecture 5 Chapter 2 1/27/00 2.2-2.3

  2. Homework #2 • Chapter 2 • Problems: 1, 4, 7, 11, 14, 18, 22 • Due February 3, 2000

  3. Approximations in Engineering Calculations • Often engineers are called upon to answer questions quickly • A value may have to be determined without the amount of time to make an exact calculation • Others are not as detail oriented

  4. Approximations in Engineering Calculations • Procedure for Calculations with Approximations • Carefully defining the problem • Introducing simplifying assumptions • Calculating an answer • Checking the answer, both systematically and realistically

  5. Approximations in Engineering Calculations • Example • How much would it cost to build an incinerator on Howard’s Campus? • Define the problem • Simplification – burning MSW on campus, number of people on campus, amount of trash per student and cost of burning an amount of trash • Calculation • Systematic and Realistic

  6. Approximations in Engineering Calculations • Significant Figures • Numbers that transfer information that has some value • Zero’s have little value • Understand the numbers that you are dealing with • Don’t deal in inches when you are talking about miles • 15,216.23 miles • 15,000 miles • Don’t deal in milligrams when interested in kilograms • 76.586 kilograms • 77 kilograms

  7. Information Analysis • Probability and Statistics • A central theme in risk assessment and analysis • How sure are you that something is going to happen? • How do you take a lot of information and make a conclusion about it or interpret it?

  8. Gaussian Distribution or Normal Distribution m = mean, estimated x x = observed sample mean  = standard deviation s = observed standard deviation n = sample size Information Analysis

  9. Information Analysis

  10. Information Analysis • Standard Deviation is a measure of the curves spread • The value of x where 68.3% of all values of x fall plus or minus m • Another useful statistic is the Coefficient of Variation

  11. Information Analysis • Cumulative Fraction (Histogram) • Often used method of plotting data Dependent Variable – Experimental result Independent variable – value chosen

  12. Information Analysis • A straight line on probability paper represents a normal distribution • With probability paper the standard deviation can be approximated by reading off

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