Predicting the compaction parameters of solidified dredged fine sediments with statistical approach

2022 ◽  
pp. 1-16
Author(s):  
Hongwei Wang ◽  
Rachid Zentar ◽  
Dongxing Wang
Keyword(s):  
Statistical Approach ◽  
Fine Sediments

scholarly journals Modelling the mechanical strength development of treated fine sediments: a statistical approach

2018 ◽  
Vol 40 (14) ◽  
pp. 1890-1909
Author(s):  
Ishak Moghrabi ◽  
Harifidy Ranaivomanana ◽  
Fateh Bendahmane ◽  
Ouali Amiri ◽  
Daniel Levacher
Keyword(s):  
Mechanical Strength ◽  
Statistical Approach ◽  
Strength Development ◽  
Fine Sediments

Delivering Sustainable Water Systems Using Kalman Filter and Statistical Approach

2017 ◽  
Vol 4 (1) ◽  
pp. 41-52
Author(s):  
Dedy Loebis
Keyword(s):  
Kalman Filtering ◽  
Statistical Approach ◽  
Water Systems ◽  
Data Sets ◽  
Pressure Data ◽  
Burst Event ◽  
Sample Data ◽  
Other Information ◽  
Supply Systems ◽  
Frequency Features

This paper presents the results of work undertaken to develop and test contrasting data analysis approaches for the detection of bursts/leaks and other anomalies within wate r supply systems at district meter area (DMA)level. This was conducted for Yorkshire Water (YW) sample data sets from the Harrogate and Dales (H&D), Yorkshire, United Kingdom water supply network as part of Project NEPTUNE EP/E003192/1 ). A data analysissystem based on Kalman filtering and statistical approach has been developed. The system has been applied to the analysis of flow and pressure data. The system was proved for one dataset case and have shown the ability to detect anomalies in flow and pres sure patterns, by correlating with other information. It will be shown that the Kalman/statistical approach is a promising approach at detecting subtle changes and higher frequency features, it has the potential to identify precursor features and smaller l eaks and hence could be useful for monitoring the development of leaks, prior to a large volume burst event.

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