alexlib
/ hardy_cross_example.ipynb
Created
November 25, 2012 19:51
Hardy Cross method of solution of the pipe network
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alexlib
/ gessler_method_pipeline_network.ipynb
Created
November 25, 2012 20:00
Gessler method to solve the pipeline netwroks
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alexlib
/ gessler.py
Created
November 29, 2012 13:13
Gessler method of solution of the pipe network problem
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| from numpy import matrix, multiply, power, abs, transpose, sign, sum | |
| from numpy.linalg import inv | |
| L_pipe=matrix([3,2,3,2,3,2,3]) #[km] | |
| D_pipe=matrix([30,20,20,20,20,20,20]) #[cm] | |
| CHW_pipe=matrix([100,100,100,100,100,100,100]) # Friction coefficient of Hazen Williams | |
| _=multiply(power(D_pipe,4.87),power(CHW_pipe,1.852)) | |
| r_pipe =1.526e7*L_pipe/_ | |
| # for each pipe the initial guess |
alexlib
/ gessler_pipe_network.ipynb
Created
November 29, 2012 13:16
Gessler method of solution for the pipe network problem
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alexlib
/ hardy_cross_pipe_network.ipynb
Created
November 29, 2012 13:23
Hardy cross method of solution for the pipeline network problem
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alexlib
/ integrate_ode_two_reservours.ipynb
Created
December 31, 2012 09:04
Numerical solution of the unsteady flow problem between two reservours Course: Engineering Hydraulics, Mech. Eng. @ TAU The problem is to find the rate at which the total head difference between two reservours vary with time, and to find out how long does it take to the large reservour (e.g. Tiberias See) to reduce its level by 1 meter.
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alexlib
/ trajAcc_to_hdf5.ipynb
Created
January 10, 2013 00:40
Reading trajAcc.#### files created by OpenPTV software (3D particle tracking velocimetry) into Pandas (www.pydata.org) DataFrame format and stores it in HDF5 (PyTables) format.
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alexlib
/ water_hammer.ipynb
Last active
December 10, 2015 22:28
Hydraulic impact or "water hammer" problem numerical solution
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| \documentclass{article} | |
| \begin{document} | |
| Hello World | |
| \end{document} |
alexlib
/ calibration_error_analysis.ipynb
Last active
June 30, 2022 22:47
Engineering measurements course
Example of the hysteresis and sensitivity error analysis of the calibration curve
Use iPython notebook viewer to see it online http://nbviewer.ipython.org/5317510
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