bolivia survey report

8/3/2019 Bolivia Survey Report

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Bolivia Bridge Assessment Surveying Report

created by Matt Ball on June 3, 2008 for EWB-Duke

Introduction

A six member team from Duke University traveled to rural Bolivia for three weeks in May of

2008 to perform a site assessment for a potential bridge in the region. Data on river crossings,local materials, and demographics were collected. Other analyses and information on this project

can be found on the EWB-Duke wiki: www.wiki.duke.edu/display/engineerswithoutborders This

report will summarize the surveying data: collection methods and visualization techniques will be

reviewed and the output plots for each site are presented.

Methodology

Five potential crossing points were surveyed in the Iruma, Jachuma, and Obrajes1 valleys. At

each location, three lines in the riverbed perpendicular to the waters flow were marked out and

surveyed with a theodolite. A cutaway view of the riverbed can be presented by assuming the

data lies in a straight line. Data was taken on the riverbeds banks and referenced to a fixedbenchmark so a plan view of the site could also be created.

Visualization

The manually-recorded data was transferred to Excel and then plotted in MATLAB. A sample

data set as well as the script used to generate the plots may be viewed in the Appendix. Cross-

section data was plotted twice; the fixed plots show a realistic cutaway of the riverbed by fixing

thexandy scales to the same increments. The second plot enabled autoscaling to show the

irregularities of the river beds floor. The plots of each site are included below.

Improvements

The MATLAB program does not verify the straightness of the contours; a simple linear

interpolation of thexandy contour data and output of the correlation coefficient could

verify this.

It would be neat to be able to input a given depth at a site and see how the water fills up

this cross section.

1pronounced e-RU-ma, ha-CHU-ma, and oh-BRA-haes
http://www.wiki.duke.edu/display/engineerswithoutbordershttp://www.wiki.duke.edu/display/engineerswithoutborders


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Iruma


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note: no bank data was taken for the Iruma crossing


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Jachuma


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Condor Chinoka


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Obrajes Crossing One


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Obrajes Crossing Two


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Appendix

Sample Data Set:

Title Obrajes One, X-Sec 1

Time 2:00pm

Surveyors Patrick Ye (theo), Thomas Grothe (rod)

Point ID Stadia Horizontal

Bot Mid Top Deg Min

BM-1 8.46 9.18 9.89 283 57

BM-2 9.18 11.54 13.85 115 26

1 0.16 1.64 3.10 216 20.5

2 8.04 9.47 10.96 217 12

3 7.82 9.24 10.66 222 43.5

4 1.70 3.13 4.56 224 15

5 2.09 3.52 4.96 226 8.5

6 6.35 7.76 9.18 227 447 8.31 9.73 11.15 227 54.5

8 8.45 9.88 11.29 229 9.5

9 12.65 14.06 15.46 230 35

10 12.71 14.13 15.55 234 28.5

11 12.96 14.38 15.81 238 27

12 9.09 10.52 11.96 240 8

13 2.95 4.39 5.84 243 15


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MATLAB plotting script

% River Plotter, v5

% created by Matt Ball (mab43-at-duke-dot-edu), 03.06.08

% Excel version also worked on by Patrick Ye (ppy3)

clear; clc; clf

loc = input('\nfilename?\n\n'); % input file name with .xls extension and single quotes (ie 'Iruma.xls')

for m=1:4 % allows plotting of all three cross sections in a given sheet

sheet = input('\nsheet name?\n\n'); % input sheet name with single quotes (ie 'X-Sec 1')

data = eval('xlsread(loc, sheet)');

% contour plotting calculations:

for k = 1:length(data)

data(k,6) = (data(k,3) - data(k,1))*100; % distance based on theodolite operation

data(k,7) = (data(3,4) + data(3,5)/60) - (data(k,4) + data(k,5)/60); % relative angle in degrees, referencing the

first data point

data(k,8) = (data(3,6)^2 + data(k,6)^2 - 2*data(3,6)*data(k,6)*cos(data(k,7)*pi/180))^.5; % point-to-point

distance using law of cosines

data(k,9) = data(1,2) - data(k,2); % relative depth, referencing the first benchmark

end

% plan view plotting calculations:

for k = 1:length(data)

data(k,10) = (data(1,4) + data(1,5)/60) - (data(k,4) + data(k,5)/60); % relative angle in degrees, referencing the

first benchmark

data(k,11) = data(k,6)*cos(data(k,10)*pi/180); % x coordinate

data(k,12) = data(k,6)*sin(data(k,10)*pi/180); % y coordinate

end

% plotting

figure(1); plot(data(3:length(data),8), data(3:length(data),9), 'k-') % plots the contour

heading1 = [loc ',' ' ' sheet ' ' ',' ' ' 'auto scale']; % combines location and sheet into one string

ylabel('relative depth (feet)'); eval('title(heading1)');

figure(2); plot(data(3:length(data),8), data(3:length(data),9), 'k:')

heading2 = [loc ',' ' ' sheet ' ' ',' ' ' 'fixed scale'];

ylabel('relative depth (feet)'); eval('title(heading2)');

axis equal % sets the tick marks to equal increments

if m==1; col='b.'; elseif m==2; col='r.'; elseif m==3; col='g.'; else col='kx'; end; % mildly ridiculous color cycling

scheme for the next plot

figure(3); eval('plot(data(3:length(data),11), data(3:length(data),12), col)'); hold on

heading3 = [loc ',' ' ' 'plan view, all units in feet']; eval('title(heading3)');

axis equal; legend('X-Sec 1', 'X-Sec 2', 'X-Sec 3', 'banks', 0)end

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