Scour around Piers under Waves: Current Status of Research and Its Future Prospect

Gazi, Ainal Hoque; Afzal, Mohammad Saud; Dey, Subhasish

doi:10.3390/w11112212

Cited by 18 publications

(7 citation statements)

References 44 publications

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“…The approach employed by the authors constitutes the first attempt to the development of predictive scour models founded more on physical than empirical grounds. A review paper treating the topic of bridge scour under waves can be found at Gazi et al [81], whereas scour at bridge foundations under supercritical flows was recently reviewed by Link et al [82].…”

Section: Physical Modelling and Controlling Scour Parametersmentioning

confidence: 99%

The Science behind Scour at Bridge Foundations: A Review

Pizarro

Manfreda

Tubaldi

2020

Water

103

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Foundation scour is among the main causes of bridge collapse worldwide, resulting in significant direct and indirect losses. A vast amount of research has been carried out during the last decades on the physics and modelling of this phenomenon. The purpose of this paper is, therefore, to provide an up-to-date, comprehensive, and holistic literature review of the problem of scour at bridge foundations, with a focus on the following topics: (i) sediment particle motion; (ii) physical modelling and controlling dimensionless scour parameters; (iii) scour estimates encompassing empirical models, numerical frameworks, data-driven methods, and non-deterministic approaches; (iv) bridge scour monitoring including successful examples of case studies; (v) current approach for assessment and design of bridges against scour; and, (vi) research needs and future avenues.

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Section: Physical Modelling and Controlling Scour Parametersmentioning

confidence: 99%

The Science behind Scour at Bridge Foundations: A Review

Pizarro

Manfreda

Tubaldi

2020

Water

103

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“…On the other hand, the highest relocation of tracers to other CGU types during Flood 2020 was observed from runs (53%). In runs, the the scour hole may also occur (Gazi et al, 2019). Pools can thus act as both a sink and source for bedload by periodically accumulating and releasing waves of sediment during flood flow (Dhont & Ancey, 2018).…”

Section: Influence Of Cgus On Bedload Transportmentioning

confidence: 99%

Influence of channel geomorphic units on bedload transport and river morphology during low‐magnitude bed‐forming floods coupled with sediment augmentation

Mörtl

Schroff

Stähly³

et al. 2023

Earth Surf Processes Landf

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In this study, we map different types of channel geomorphic units in a sediment‐starved, residual‐flow reach before and after an artificial flood. Bedload particles of a previous sediment augmentation measure are tracked with passive integrated transponder tags, and water depth and flow velocity are recorded across ten cross‐sections. The analysis focuses on the influence of channel geomorphic units on bedload transport and river morphology. Our hypotheses are that during low‐magnitude bed‐forming floods with sediment pulse migration, (i) existing channel geomorphic units influence bedload transport and, more specifically, (ii) that their type influences the retention rate of bedload particles. Furthermore, we hypothesise that (iii) the density of channel geomorphic units is linked to the hydromorphological diversity of a river section. We provide evidence that supports the first two hypotheses and contradicts the third one. We consider our results to be transferable to similarly regulated reaches based on an analysis of site‐specific conditions and alternative explanatory factors. Further research is needed to transfer the results to varying flood and sediment supply conditions in unregulated reaches.

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“…Furthermore, bow-waves can also contribute to the scouring process. A combination of these vortexes eventually lead to scour holes around piers of bridges (Laursen and Toch, 1956;Liu et al 1961;Kwan, 1988;Hosseini et al, 2016), and detailed descriptions on abutment scour depth process are widely available in the literature (e.g., Dey, 1997;Dey and Barbhuiya, 2005;Gazi et al, 2019;Kothyari et al, 1992;Melville and Raudkivi, 1977;Melville and Sutherland, 1988;Moonen and Allegrini, 2015;Namaee and Sui, 2019;Raudkivi and Ettema, 1983).…”

Section: Introductionmentioning

confidence: 99%

A comparison between advanced hybrid machine learning algorithms and empirical equations applied to abutment scour depth prediction

Khosravi

Khozani

Mao

2021

Journal of Hydrology

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Complex vortex flow patterns around bridge piers, especially during floods, cause scour process that can result in the failure of foundations. Abutment scour is a complex three-dimensional phenomenon that is difficult to predict especially with traditional formulas obtained using empirical approaches such as regressions. This paper presents a test of a standalone Kstar model with five novel hybrid algorithm of bagging (BA-Kstar), dagging (DA-Kstar), random committee (RC-Kstar), random subspace (RS-Kstar), and weighted instance handler wrapper (WIHW-Kstar) to predict scour depth (ds) for clear water condition. The dataset consists of 99 scour depth data from flume experiments (Dey and Barbhuiya, 2005) using abutment shapes such as vertical, semicircular and 45° wing. Four dimensionless parameter of relative flow depth (h/l), excess abutment Froude number (Fe), relative sediment size (d50/l) and relative submergence (d50/h) were considered for the prediction of relative scour depth (ds/l). A portion of the dataset was used for the calibration (70%), and the remaining used for model validation.Pearson correlation coefficients helped deciding relevance of the input parameters combination and finally four different combinations of input parameters were used. The performance of the models was assessed visually and with quantitative metrics. Overall, the best input combination for vertical abutment shape is the combination of Fe, d50/l and h/l, while for semicircular and 45° wing the combination of the Fe and d50/l is the most effective input parameter combination. Our results show that incorporating Fe, d50/l and h/l lead to higher performance while involving d50/h reduced the models prediction power for vertical abutment shape and for semicircular and 45° wing involving h/l and d50/h lead to more error. The WIHW-Kstar provided the highest performance in scour depth prediction around vertical abutment shape while RC-Kstar model outperform of other models for scour depth prediction around semicircular and 45° wing.

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Scour around Piers under Waves: Current Status of Research and Its Future Prospect

Cited by 18 publications

References 44 publications

The Science behind Scour at Bridge Foundations: A Review

The Science behind Scour at Bridge Foundations: A Review

Influence of channel geomorphic units on bedload transport and river morphology during low‐magnitude bed‐forming floods coupled with sediment augmentation

A comparison between advanced hybrid machine learning algorithms and empirical equations applied to abutment scour depth prediction

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