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The reuse of treated wastewater is attractive as a communal source of excess water source in water-scarce counties and nations. The expansion of the urban population and the increase in the coverage of water supply networks and sewage networks will raise the amount of municipal sewage. This can turn into a new-fangled water resource. In the current research, the new campus city was selected as the first case study to design a wastewater reuse and recycling system. Accordingly, one of the mostdoi:10.3390/su132413553 fatcat:cggzn4kmo5gy7ocsakecp7p32y
more »... portant innovations in the proposed research is the unique applied dimensions, in addition to its first-time performance, and the application of the Geo-land method in wastewater recycling as the theoretical dimension of the design. Clustering the decentralized reuse of wastewater for urban areas showed that significant parts of residential areas are located in the first high priority group. Urban planners can consider the results in establishing a comprehensive plan to prioritize the decentralized use of wastewater in the urban area.
Social and economical damages are the most important damages of the bridge failure. Stability problems of such structures against failure and the depth of the abutments are directly related to the amount of the adjusted scour. Economy, reliability and stability have been the main concerns on enhancing the designing of abutment bridges to prevent or reduce embankement scour. In this study a detailed comparison of the researches on scour at abutment bridge are presented including all possibledoi:10.19026/rjaset.8.973 fatcat:5fz7bbriorhidkdemfjcf2vapi
more »... cts and scour depth estimation formulae. The experimental data for prediction the abutment local scour depth were investigated. Statistical and graphical analysis allow to recommend the most accurate formula in prediction scour depth at the abutment bridges. Availability of additional data and further analysis would allow promoting the bridge abutment design and decreasing the bridges' construction and maintenance cost by increasing the accuracy of the footing depth design.
ORCID Ata Amini http://orcid.org/0000-0001-9358-185X Pezhman Taherei Ghazvinei http://orcid.org/0000-0001-9186-7109 Figure 1 . 1 Laboratory flume and its streambed: (a) the porous brick, (b) the streambed ...doi:10.1080/15715124.2016.1274321 fatcat:oxsikstw7jan3plcfryxj623ze
ORCID Pezhman Taherei Ghazvinei http://orcid.org/0000-0001- 9186-7109 Shahaboddin Shamshirband http://orcid.org/0000-0002- 6605-498X ... in the irrigation method for sugarcane production, the water is provided for farm irrigating by buried pipes, where water is distributed by furrow in the farm using flexible polyethylene gated pipe (Taherei ...doi:10.1080/19942060.2018.1526119 fatcat:bmgwdohp3vcnfeolmrnokooqfa
Local scour depth at complex piers (LSCP) cause expensive costs when constructing bridges. In this study, a hybrid artificial intelligence approach of random subspace (RS) meta classifier, based on the reduced error pruning tree (REPTree) base classifier, namely RS-REPTree, was proposed to predict the LSCP. A total of 122 laboratory datasets were used and portioned into training (70%: 85 cases) and validation (30%: 37 cases) datasets for modeling and validation processes, respectively. Thedoi:10.3390/su12031063 fatcat:vtnncyvklja5xnorpo4h2bwug4
more »... stical metrics such as mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (R), and Taylor diagram were used to check the goodness-of-fit and performance of the proposed model. The capability of this model was assessed and compared with four state-of-the-art soft-computing benchmark algorithms, including artificial neural network (ANN), support vector machine (SVM), M5P, and REPTree, along with two empirical models, including the Florida Department of Transportation (FDOT) and Hydraulic Engineering Circular No. 18 (HEC-18). The findings showed that machine learning algorithms had the highest goodness-of-fit and prediction accuracy (0.885 < R < 0.945) in comparison to the other models. The results of sensitivity analysis by the proposed model indicated that pile cap location (Y) was a more sensitive factor for LSCP among other factors. The result also depicted that the RS-REPTree ensemble model (R = 0.945) could well enhance the prediction power of the REPTree base classifier (R = 0.885). Therefore, the proposed model can be useful as a promising technique to predict the LSCP.
"How to mitigate the effects of scour on bridge piers through the use of combined countermeasures." (2015).  Amini, Seyed Ata, Pezhman Taherei Ghazvinei, Shervin Motamedi, and Roslan Bin Hashim. ...doi:10.28991/cej-2019-03091381 fatcat:yt5gjz7zy5esjj2dihej5hgt7e