11. As part of a project, you have been asked to determine the adjusted height of a client's office building. To obtain sufficient redundancy in the number of observations required to perform the necessary least-squares solution, you have measured 2 distances (d. and d.) and 2 angles (0, and 0.) as depicted in the following figure. The subsequent observations and their associated uncertainties are summarized in the table below. Assume that all observations were obtained independently and that 0, is exactly 69° 18' 33".
11. As part of a project, you have been asked to determine the adjusted height of a client's office building. To obtain sufficient redundancy in the number of observations required to perform the necessary least-squares solution, you have measured 2 distances (d. and d.) and 2 angles (0, and 0.) as depicted in the following figure. The subsequent observations and their associated uncertainties are summarized in the table below. Assume that all observations were obtained independently and that 0, is exactly 69° 18' 33".
Chapter2: Loads On Structures
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:11. As part of a project, you have been asked to determine the adjusted height of a
client's office building. To obtain sufficient redundancy in the number of
observations required to perform the necessary least-squares solution, you have
measured 2 distances (d. and d.) and 2 angles (0, and 0.) as depicted in the following
figure. The subsequent observations and their associated uncertainties are
summarized in the table below. Assume that all observations were obtained
independently and that 0, is exactly 69° 18' 33".
Transcribed Image Text:В
0,
1.
A-
Observation
Value
Precis ion
dAB
150.293 m
0.005 m
dac
159.982 m
0.005 m
15°29'58"
15"
95°11'03"
15"
In preparation for performing a weighted, non-linear conditional least-squares
adjustment of the given data, give:
(a) The degrees of freedom
(b) All necessary observation equations
(c) The weight matrix and a priori variance factor
(d) The design matrix.
31
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