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{\rtf1\ansi\ansicpg1252\cocoartf1347\cocoasubrtf570 {\fonttbl\f0\fswiss\fcharset0 Helvetica;} {\colortbl;\red255\green255\blue255;} \margl1440\margr1440\vieww10800\viewh8400\viewkind0 \pard\tx720\tx1440\tx2160\tx2880\tx3600\tx4320\tx5040\tx5760\tx6480\tx7200\tx7920\tx8640\pardirnatural \f0\fs24 \cf0 # Material Flow Analysis\ \ This program allows the user predict the flow of available waste materials given\ (1) demand peak\ (2) composition\ (3) lifetime (mean and standard deviation)\ \ ## Demand\ \ Demand curve is assumed to follow S-shaped distribution of time. This means slow initial demand, \ rapid intermediate demand which peaks and slows down again\ \ ## Future Modifications\ \ In order to capture the uncertainty of our waste prediction there are several \ ways uncertainty can be injected into the model \ (1) use mean and standard deviation for composition\ (2) use Monte Carlo analysis to generate statistics across two variables\ (3) generate multiple demand curves with probability for each }
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What are the emerging data trends in the field of clean energy?
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