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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
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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