READ ME File For 'Data supporting a publication "Physics informed neural networks for solving flow problems modelled by the Shallow Water Equations" by Xin Qi'

Dataset DOI: 10.5258/SOTON/D2645

Date that the file was created: April, 2024

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GENERAL INFORMATION
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ReadMe Author: Xin Qi, University of Southampton 

Related projects: PhD project: "Machine learning models for solving free-surface flow problems"

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SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data, or limitations of reuse: CC BY

This dataset supports the publication:
"Physics informed neural networks for solving flow problems modelled by the Shallow Water Equations" by Xin Qi'
Journal of Hydrology


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DATA & FILE OVERVIEW
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This dataset contains:

The data are stored in CSV or txt.file, which can be proceed though Python or Matlab. 
The information for each folder:
1.	“database_wave”: The result for the test case “Flood wave propagation over a horizontal plane” . 
2.	“database_mac”: The result for the test case “Subcritical steady flow over an undulating bed”. 
3.	“database_Tiber”: The result for the test case “Simulation of real-world river flooding” . 
4.	“Appendix_spatial_analysis”: The result for the Appendix “Further Spatial Analysis For Test 3”.
5.	“Appendix_model_design_experiment”: The result for the Appendix “PINN Design Ecxperiments”.



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METHODOLOGICAL INFORMATION
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All data are generated from Python or Matlab programming


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DATA-SPECIFIC INFORMATION
This dataset contains:
1.“database_wave”: The result for the test case “Flood wave propagation over a horizontal plane” . 
2.“database_mac”: The result for the test case “Subcritical steady flow over an undulating bed”. 
3.“database_Tiber”: The result for the test case “Simulation of real-world river flooding” . 
4.“Appendix_spatial_analysis”: The result for the Appendix “Further Spatial Analysis For Test 3”.
5.“Appendix_model_design_experiment”: The result for the Appendix “PINN Design Ecxperiments”.
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Number of variables: water depth, water discharge, computation time

Number of cases: 3

Specialized formats or other abbreviations used: txt or csv

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