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Handbook for Water Distribution System Model Calibration
Paperback
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ISBN10: 1647171156
ISBN13: 9781647171155
Publisher: American Water Works Association
Published: Nov 28 2023
Pages: 134
Weight: 0.72
Height: 0.29 Width: 8.50 Depth: 11.00
Language: English
ISBN13: 9781647171155
Publisher: American Water Works Association
Published: Nov 28 2023
Pages: 134
Weight: 0.72
Height: 0.29 Width: 8.50 Depth: 11.00
Language: English
Since the advent of digital computers, numerical solvers have become progressively more powerful and reliable. However, the accuracy of the model depends on the extent to which it reflects the real system. To ensure that the model is an accurate representation of the real system (essentially a digital twin of the real system), it is necessary to compare model results with real-world data and adjust model parameters to reduce the level of uncertainties in the model results, and then identify and correct as many discrepancies as is feasible. _x000d_
According to the Calibration Subcommittee of the AWWA Engineering Modeling Applications Committee (2013a), water distribution model calibration consists of comparing model results with accurate field measurements and making adjustments to model and reviewing field data to improve agreement over a range of conditions that correspond to how the model is intended to be used. Calibration should result in a more accurate model, a better understanding of the strengths and weaknesses of the model, and greater confidence in model results. _x000d_
Hydraulic models of water distribution systems are widely used to help solve engineering and operational problems in water systems. To ensure that a model accurately represents a real system, model results are compared with physical measurements over a range of conditions. If the model predictions agree with the data, the model can be used with confidence for the conditions it was calibrated.
Hydraulic models of water distribution systems are widely used to help solve engineering and operational problems in water systems. To ensure that a model accurately represents a real system, model results are compared with physical measurements over a range of conditions. If the model predictions agree with the data, the model can be used with confidence for the conditions it was calibrated.
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