Lec37 2010 Sustainability P2 v03

Lec37 2010 Sustainability P2 v03 - CEE 3040 Uncertainty...

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CEE 3040 Uncertainty Analysis in Sustainability Engineering Part II Francis Vanek Lecture 37 December 1, 2010
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Today’s class outline Introduction: What is Monte Carlo simulation? Motivational examples 1. Impact of telecommuting influx on cost 2. Impact of high-speed rail (HSR) in China Demonstration: simulation modeling in a spreadsheet Calculations on transparencies Finish discussion of wind (from Lec.36) Monte Carlo calculations Concluding discussion on PowerPoint (May be limited due to time)
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Readings Shafizadeh, K., D. Niemeier, P. Mokhtarian, and I Salomon, “Costs and Benefits of Home- Based Telecommuting”, J Infrastucture Systems (ASCE), March 2007, 12-25. Called “Monte Carlo Example” in Blackboard Vanek and Albright (2008), “Systems Perspective on Transportation Systems Called “Transportation Systems Chapter” in Blackboard
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Advertising for 2011: my course, CEE 4630 “Future Transport Technologies & Systems Offered both Spring 2011 & Fall 2011 Three main topics: Passenger transportation Freight transportation Transportation energy Recommended: CEE 3610 or equivalent However, you can successfully take the course without this background Numerous cutting-edge technologies Plug-in hybrid electric vehicles, HSR, telecommuting, etc.
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Introducing Monte-Carlo Analysis
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Introduction to Monte-Carlo Ideally, we want parameters in models to be known well enough that we can use them deterministically Sometimes this is not possible BUT, “getting answers” is critical, there is an imperative to model as best as possible Solution: Monte-Carlo Sample uncertain parameters from a distribution Run experiment many times See what direction the trend leads
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Motivation for studying Monte Carlo Simulation Illustrate how computer modeling can be used to better understand the impact of new technology under conditions of uncertainty Telecommuting New transportation systems Different from using computers to directly simulate or control systems “Discrete event simulation”
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