Gene-expression programming to predict the local scour depth at downstream of stilling basins

Mesbahi, M.; Talebbeydokhti, Nasser; Hosseini, Seyed Abbas; Afzali, Seied Hosein

doi:10.24200/sci.2016.2101

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…One of the important components of the weir as a complement to the spillway and intake is the stilling basin. This structure functions to dissipate the flow energy created above the spillway due to very drastic changes in slope [5]. This weir component is very susceptible to damage due to bottom scouring initiated at the end of the stilting basin floor.…”

Section: Introductionmentioning

confidence: 99%

Safety Assessment of Irrigation Weirs by Modeling Local Scour Potential Downstream of Energy Dissipator

Tunas,

Ishak,

Saparuddin

et al. 2024

IJSSE

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The phenomenon of local scour downstream of irrigation weir energy dissipators is one of the basic degradation problems in hydraulic structures on rivers. The hydraulic jump in the stilling basin, which is triggered by flow turbulence due to energy dampening, forms current vortices in horizontal and vertical directions. Eddy currents that are not fully controlled and damped in the stilling basin can cause scouring, especially in the vertical direction just downstream of the energy dissipators construction. Simultaneous accumulation of scour in the long term can endanger buildings around the weir, especially the stilling basin, both downstream wings and the main weir. This paper aims to assess weir safety by predicting scour characteristics under end sill energy dissipators using the hybrid model: HEC-RAS and Scour Empirical Equation. The simulation is carried out on three conditions, namely minimum, average and maximum discharges with input of sediment grain gradations obtained from field measurements. The three types of discharge are obtained from the transformation of daily rainfall into daily discharge using the HEC-HMS Model. The results of scour predictions in the 3 scenarios were compared with the results of scour measurements at the study location. The results of the study indicate that the greatest scour depth at the maximum discharge of almost 1.5 meters has reached the depth of the end sill of the energy dissipator. This prediction result was also verified by the observation scour depth of more than 1.5 meters. Observation results also show that the Energy Dissipator II has collapsed massively both in the center and on the left and right sides of the energy dissipator. Based on the results of the study and investigation, it can be concluded that the weir safety at the study location can be categorized as low with the potential for very large scour.

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Section: Introductionmentioning

confidence: 99%

Safety Assessment of Irrigation Weirs by Modeling Local Scour Potential Downstream of Energy Dissipator

Tunas,

Ishak,

Saparuddin

et al. 2024

IJSSE

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“…However, edge scour still continues to occur despite the foundation protective devices installed [33]. With the advancement of artificial intelligence (AI) technology, machine learning (ML) and deep learning (DL) will have a better contribution to offshore wind turbine condition monitoring [34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. Artificial intelligence (AI) is basically an algorithm for regression analysis of existing big data rules which include machine learning, deep learning, genetic algorithm, neural network, and fuzzy.…”

Section: Introductionmentioning

confidence: 99%

Visible Light Communication System for Offshore Wind Turbine Foundation Scour Early Warning Monitoring

Lin

Chang

et al. 2019

Water

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Offshore wind farms have a superior wind source to terrestrial wind farms, but they also face more severe environmental conditions such as severe storms, typhoons, and sea waves. Scour leads to the excavation of sediments around the foundations of structures, reducing the safe capacity of the structures. The phenomenon of pier scour is extremely complex because of the combined effects of the vortex system involving time-dependent flow patterns and sediment transport mechanisms. A real-time scour monitoring system can improve the safety of structures and afford cost-effective operations by preventing premature or unnecessary maintenance. This paper proposes an on-site scour monitoring system using visible light communication (VLC) modules for offshore wind turbine installations. A flume experiment revealed that the system was highly sensitive and accurate in monitoring seabed scour processes. This arrayed-VLC sensory system, proposed in this paper, has considerable potential for safety monitoring and also can contribute to improving the accuracy of empirical scour formulas for sustainable maintenance in the life cycle of offshore structures.

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“…The feasibility of gene expression programming (GEP) was also examined for the prediction of scour depth at the downstream of sills and flip-bucket spillway [19,20]. The GEP was also used to predict scour depth in stilling basins [21]. Onen [22] employed ANN and GEP to investigate the scour process in the downstream of a side weir.…”

Section: Introductionmentioning

confidence: 99%

Open Channel Sluice Gate Scouring Parameters Prediction: Different Scenarios of Dimensional and Non-Dimensional Input Parameters

Yousif

Sulaiman

Diop

et al. 2019

Water

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The determination of scour characteristics in the downstream of sluice gate is highly important for designing and protection of hydraulic structure. The applicability of modern data-intelligence technique known as extreme learning machine (ELM) to simulate scour characteristics has been examined in this study. Three major characteristics of scour hole in the downstream of a sluice gate, namely the length of scour hole (Ls), the maximum scour depth (Ds), and the position of maximum scour depth (Lsm), are modeled using different properties of the flow and bed material. The obtained results using ELM were compared with multivariate adaptive regression spline (MARS). The dimensional analysis technique was used to reduce the number of input variable to a smaller number of dimensionless groups and both the dimensional and non-dimensional variables were used to model the scour characteristics. The prediction performances of the developed models were examined using several statistical metrics. The results revealed that ELM can predict scour properties with much higher accuracy compared to MARS. The errors in prediction can be reduced in the range of 79%–81% using ELM models compared to MARS models. Better performance of the models was observed when dimensional variables were used as input. The result indicates that the use of ELM with non-dimensional data can provide high accuracy in modeling complex hydrological problems.

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Gene-expression programming to predict the local scour depth at downstream of stilling basins

Cited by 5 publications

References 27 publications

Safety Assessment of Irrigation Weirs by Modeling Local Scour Potential Downstream of Energy Dissipator

Safety Assessment of Irrigation Weirs by Modeling Local Scour Potential Downstream of Energy Dissipator

Visible Light Communication System for Offshore Wind Turbine Foundation Scour Early Warning Monitoring

Open Channel Sluice Gate Scouring Parameters Prediction: Different Scenarios of Dimensional and Non-Dimensional Input Parameters

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