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13 Pages

### ICA #7

Course: ENGR 101, Spring 2011
School: USC
Rating:

Word Count: 250

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17 Q 12 25 40 50 58 Temp 1.5 2 3.25 5 6.25 7 RelationshipBetwe 7.5 7 6.5 6 5.5 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 5 f(x) = 0.12x + 0.06 TempChange( T)[K] 10 15 20 ationshipBetweenHeatAppliedandTempChange .5 7 .5 6 .5 5 .5 4 .5 3 .5 2 .5 1 .5 0 5 f(x) = 0.12x + 0.06 T)[K] 10 15 20 25 30 35 40 45 50 55 60 65 HeatApplied(Q)[J] TimeAfter Intersection#1 Intersection#2 Intersection#3 2 0.05 0.1 0.5 5 0.1 0.5 1.5...

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Coursehero >> California >> USC >> ENGR 101

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17 Q 12 25 40 50 58 Temp 1.5 2 3.25 5 6.25 7 RelationshipBetwe 7.5 7 6.5 6 5.5 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 5 f(x) = 0.12x + 0.06 TempChange( T)[K] 10 15 20 ationshipBetweenHeatAppliedandTempChange .5 7 .5 6 .5 5 .5 4 .5 3 .5 2 .5 1 .5 0 5 f(x) = 0.12x + 0.06 T)[K] 10 15 20 25 30 35 40 45 50 55 60 65 HeatApplied(Q)[J] TimeAfter Intersection#1 Intersection#2 Intersection#3 2 0.05 0.1 0.5 5 0.1 0.5 1.5 8 0.3 1 2.5 11 0.4 1.3 3.1 Traffic 3.5 3 2.5 2 1.5 1 0.5 f(x) = 0.04x - 0.06 0 0 2 4 f(x) = 0.29x - 0.01 TimeAfterInstallatoin f(x) = 0.14x - 0.16 6 ViolationTim TrafficLightViolations 0.29x - 0.01 f(x) = 0.14x - 0.16 Intersection #1 Linear Regression for Intersection #1 Intersection #2 Linear Regression for Intersection #2 Intersection #3 Linear Regression for Intersection #3 f(x) = 0.04x - 0.06 2 4 6 8 10 12 ViolationTime(V)[s] f(x) = 1.#NAN x^1.#NAN VehicleSpeed 24inches 28inches 30inches 1 55 64 69 2 28 32 35 3 18 21 23 4 14 16 17 Transm 12 10 8 TireDiameter[in] 6 4 2 0 0 2 4 Vehic x^1.#NAN TransmissionandFuelEfficiency Row 8 Power Regression for Row 8 Row 9 Power Regression for Row 9 Row 10 Power Regression for Row 10 Row 11 2 4 6 VehicleSpeed[mph] 8 10 12 SideLength labWeight S TotalWeight 10 10500 10500 16 26880 37380 22 50820 88200 28 82320 170520 34 121380 291900 40 168000 459900 46 222180 682080 52 283920 966000 58 353220 1319220 430080 64 1749300 70 514500 2263800 76 606480 2870280 82 706020 3576300 88 813120 4389420 94 927780 5317200 100 1050000 6367200 7000000 6000000 5000000 Weight(w)[lb] 4000000 3000000 2000000 1000000 0 0 f f ConstructingaPyramid 7000000 6000000 5000000 4000000 3000000 2000000 1000000 0 0 20 40 60 80 100 120 SideLength(L)[ft] f(x) = 105 x^2 Slab Weight Power Regression for Slab Weight Total Weight Power Regression for Total Weight Weight(w)[lb] f(x) = 15.99 x^2.79 Slab Weight Power Regression for Slab Weight Total Weight Power Regression for Total Weight Temperature DiodeA DiodeB DiodeC 275 852 2086 264 281 523 1506 179 294 194 779 81 309 69 390 35 315 47 301 26 Tem 2500 2000 Current(I)[mA] 1500 1000 500 f(x) = 1195875415.2 f(x) = 357076850580 f(x) = 2170937343.67 0 270 275 280 285 290 Tempera TempvsCurrent 500 000 500 000 500 f(x) = 2170937343.670.94^x 0 270 275 280 285 290 295 300 305 310 315 320 Temperature(T)[K] f(x) = 357076850580.710.93^x f(x) = 1195875415.230.95^x Diode A Exponential Regression for Diode A Diode B Exponential Regression for Diode B Diode C Exponential Regression for Diode C Altitude 0 3.4 5.2 9.9 19 30 43 60 Pressure 1 0.5 0.33 0.1 0.01 0 0 0 Altitu 1.2 1 Pressure(P)[atm] 0.8 0.6 0.4 0.2 0 0 5 10 15 f(x) = 0.730.82^x 20 Altitudevs.Pressure .2 1 .8 .6 .4 .2 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 Altitude(A)[mi] f(x) = 0.730.82^x
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