engs103p coursework no 4

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  • 7/26/2019 ENGS103P Coursework No 4

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    Abel NyamapfeneModule Coordinator ENGS103P Mathematical Modelling & AnalysisUniversity College London, Gower Street, London WC1E 6BTTel: +44 (0)20 7679 [email protected]

    Mathematical Modelling & Analysis I ENGS103P

    Coursework No 4

    Topic Coverage: Topic 9: Engineering Uncertainty

    Topic 10: Analysing Data

    Date When Coursework Set 07 December 2015

    Coursework Submission Deadline 11 January 2016

    Date of Coursework Return 05 February 2016

    Student Name:

    Student UCL ID number:

    Workgroup Number:

    Workgroup Lead:

    Department:

    LONDONS GLOBAL UNIVERSITY

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    Show all your workings

    Engineering Unc ertainty

    1. The water supply for a City C comes from two sources A and B through thewater supply network shown in the figure below.

    F1 , F2 and F3 denote the failure of branch 1, 2, and 3 respectively. It is knownthat P(F1 ) = 0.1, P(F2 ) = 0.15, and P(F3) = 0.05.

    Assuming the failures of the branches are independent. Determine the probabilityof failure of this water supply system to City C. [10%]

    2. Consider two river streams flowing past an industrial plant. Let A denote the

    event that stream a is polluted, and B denote that stream b is polluted. It is

    determined from historical observations that

    5

    2)( AP ,

    4

    3)( BP ,

    5

    4)OR( BAP

    a. Determine )( BAP and )A(BP . [10%]

    b. Interpret the results. [5%]

    c. Determine whether A and B are independent. [5%]

    3. The bearing capacityX of the soil under a column-footing foundation is known tovary between 6-15 kips/sq ft. Its probability density function is given as

    15

    17.2

    1)(

    xxfX if 156 x

    0)( xfX otherwise

    If the column is designed to carry a load of 7.5 kips/sq ft, what is the probability

    of failure of the foundation? [20%]

    Source B

    Source A

    City CBranch 3

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    Analysing Data

    4. Table 1 shows measurements of current (mA) flowing in a sample of labelled

    100 Ohms resistors at 1 V.

    From Table 1 what is the systematic error from the sample to the nominalresistance value and what is the random error on the measurement. [10%]

    Table 1: Measured current (mA) across sample of labelled 100 Ohms resistors at 1 V

    10.10 9.85 9.93 10.01 9.82 9.99 10.16 10.03 9.89 9.97

    5. Table 2 shows a range of voltage values applied across a given resistance

    together with measurements of the corresponding value of current flowing

    through the resistance.

    a. By carrying out a linear regression in Matlab or Excel find the best fit straight line

    for the given data. [10%]

    b. Use linear interpolation to estimate the value of the current at 0.45 V. [10%]

    Table 2: For a given resistance in the sample current as a function of voltage

    Voltage(V)

    0 0.1 0.2 0.3 0.4 0,.5 0.6 0.7 0.8 0.9 1

    Current(mA)

    0 0.99 2.00 3.01 4.1 4.85 5.99 7.02 7.98 9.00 10.03

    6. Table 3 shows a range of voltage values applied across a diode together with

    measurements of the corresponding value of current flowing through the diode.

    Use regression techniques to find the ideality factor of the diode and calculatethe maximum error of a linear interpolation in the 0.9-1 V range compared tothe fitted value. [20%]

    Table 3: Current as a function of voltage in a diode

    Voltage

    (V)

    0 0.1 0.2 0.3 0.4 0,.5 0.6 0.7 0.8 0.9 1

    Current(mA)

    0 0 0 0 0 0 0 0.07 0.92 12.02 158.29

    NB:Equation of a diode:

    = exp( ) 1 Where I is in milli-amperes, V is in Volts, =ideality factor

    = 38.68

    =1.00 109