Bridge pier scour hazards assessment using smart-spheres

Author(s):  
Alex Corrigan ◽  
Hassan Elmubarak ◽  
Yi Xu ◽  
Panagiotis Michalis ◽  
Manousos Valyrakis

<p>Under climate change, shifting  weather conditions, (both in terms of increasing frequency and intensifying magnitude) result in increasing occurrence of catastrophic failures of the constantly exposed and ageing infrastructure, across the world. Energetic flow events, advected past hydraulic infrastructure (such as bridge piers and abutments), may lead to scour [1, 2, 3], which is the primary cause of bridge collapses, resulting in high socio-economical costs, including loss of life.</p><p>This research aims to demonstrate the use of a novel monitoring device for the assessment of scour initiated by turbulent flows. This is pursued via the use of a miniaturized instrumented particle, namely “smart-sphere”, to record directly the frequency of entrainment from its downstream placement a model bridge pier at the Water Engineering lab of the University of Glasgow [4, 5, 6]. The change in entrainment frequencies is used as a metric to assess the increasing risk to scour, with increasing flow conditions, recorded acoustic Doppler velocimetry (ADV). The utility of the method as well as the potential use of the acquired data for prediction of bridge pier scour is presented and the tool as well is discussed with the potential for use to an appropriate field site [7, 8, 9].</p><p> </p><p>Acknowledgments</p><p>This research project has been supported by Transport Scotland, under the 2019/20 Innovation Fund and the Student research award.</p><p> </p><p>References</p><p>[1] Pähtz, Th., Clark, A., Duran, O., Valyrakis, M. 2019. The physics of sediment transport initiation, cessation and entrainment across aeolian and fluvial environments, Reviews of Gephysics, https://doi.org/10.1029/2019RG000679.</p><p>[2] Yagci, O., Celik, F., Kitsikoudis, V., Kirca, O., Hodoglu, C., Valyrakis, M., Duran, Z., Kaya S. 2016. Scour patterns around individual vegetation elements, Advances in Water Resources, 97, pp 251-265, doi: 10.1016/j.advwatres.2016.10.002.</p><p>[3] Michalis, P., Saafi, M. and M.D. Judd. (2012) Integrated Wireless Sensing Technology for Surveillance and Monitoring of Bridge Scour. Proceedings of the 6th International Conference on Scour and Erosion, France, Paris, pp. 395-402.</p><p>[4] Valyrakis, M. & Pavlovskis, E. 2014. "Smart pebble” design for environmental monitoring applications, In Proceedings of the 11th International Conference on Hydroinformatics, Hamburg, Germany.</p><p>[5] Valyrakis M., A. Alexakis. 2016. Development of a “smart-pebble” for tracking sediment transport. International Conference on Fluvial Hydraulics River Flow 2016, St. Liouis, MO, 8p.</p><p>[6] Valyrakis, M., Farhadi, H. 2017. Investigating coarse sediment particles transport using PTV and “smart-pebbles” instrumented with inertial sensors, EGU General Assembly 2017, Vienna, Austria, 23-28 April 2017, id. 9980.</p><p>[7] Valyrakis, M., Diplas, P., Dancey, C.L. 2011. Prediction of coarse particle movement with adaptive neuro-fuzzy inference systems, Hydrological Processes, 25 (22). pp. 3513-3524. ISSN 0885-6087, doi:10.1002/hyp.8228.</p><p>[8] Valyrakis, M., Michalis, P., Zhang, H. 2015a. A new system for bridge scour monitoring and prediction. Proceedings of the 36th IAHR World Congress, The Hague, the Netherlands, pp. 1-4.</p>

2001 ◽  
Vol 28 (3) ◽  
pp. 520-535 ◽  
Author(s):  
A Melih Yanmaz ◽  
Ozgur Cicekdag

Bridge scour is an extremely complex phenomenon because of the random characteristics of sediment laden flow in close proximity to piers and abutments. This occurrence leads to high uncertainties and unavoidable risk in bridge pier and abutment design. In this study, a composite reliability model is developed for the reliability assessment of bridge pier scour using static resistance – loading interference. Based on the physical interpretation of the phenomenon and a statistical analysis of the available information, the relative maximum scour depth (corresponding to the minimum required relative pier footing elevation) and the linear combination of the relative approach flow depth and flow Froude number are defined as the system resistance and external loading, respectively. By examining a set of laboratory and field data, a two-parameter bivariate lognormal distribution is found to represent the joint probability density function of resistance and loading. Reliability expressions are developed in terms of resistance. Use of the model is illustrated in a practical application in which a relationship is obtained between the reliability and safety factors under various return periods. This information is of importance in decision making.Key words: reliability, bridge pier, scour, resistance, loading, safety factor, return period.


Author(s):  
Yousef Hassanzadeh ◽  
Amin Jafari-Bavil-Olyaei ◽  
Mohammad Taghi-Aalami ◽  
Nazila Kardan

An accurate estimation of bridge pier scour has been considered as one of the important parameters in designing of bridges. However, due to the numerous involved parameters and convolution of this phenomenon, many existing approaches cannot predict scour depth with an acceptable accuracy. Obtained results from the empirical relationships show that these relationships have low accuracy in determining the maximum scour depth and they need a high safety factor for many cases, which leads to uneconomic designs of bridges. To cover these disadvantages, three new models are provided to estimate the bridge pier scour using an adaptive network-based fuzzy inference system. The parameters of the system are optimized by using the colliding bodies optimization, enhanced colliding bodies optimization and vibrating particles system methods. To evaluate the efficiency of the proposed methods, their results were compared with those of simple adaptive network-based fuzzy inference system and its improved versions by using the particle swarm optimization and genetic algorithm as well as the empirical equations. Comparison of results showed that the new vibrating particles system based algorithm could find better results than other two ones. In addition, comparison of the results obtained by the proposed methods with those of the empirical relations confirmed the high performance of the new methods.


2020 ◽  
Author(s):  
Gaston Latessa ◽  
Dong Xu ◽  
Chunning Ji ◽  
Manousos Valyrakis

<p>Numerical simulations for the transport of coarse sediment particles in turbulent flows are performed, with particular emphasis on the energy and momentum exchange [1, 2, 3] between the two phases at the particle scale.  The solid particles positions and velocities are solved through the Discrete Element Method (DEM), coupled with a Computational Fluid Dynamics (CFD) model which updates the dynamically evolving flow field through the numerical solution of the Reynolds Averaged of Navier-Stokes equations (RANS).</p><p>At the core of this work, the coupling of these two models (DEM-CFD) based on the Fictitious Boundary Method, is analysed. The models have a high mesh resolution, by adopting a meshing strategy which aims at sufficiently discretising the flow field surrounding each particle. Smooth and rough bed cases are simulated, under a wide range of Reynolds numbers covering applications from particle entrainment, up to bulk bedload transport through rolling and saltation. The numerical results are benchmarked against experimental data obtained from controlled laboratory experiments [4, 5, 6].</p><p>The implementation of coupled CFD-DEM models provides a very powerful tool for improving the understanding of fluid and particle physics in sediment transport. Particularly, the potential to perform a large number of validated numerical that robustly predict geomorphological changes in aquatic environments and fluvial systems.</p><p><strong>References</strong></p><p>[1] Valyrakis M., P. Diplas, C.L. Dancey, and A.O. Celik. 2008. Investigation of evolution of gravel river bed microforms using a simplified Discrete Particle Model, International Conference on Fluvial Hydraulics River Flow 2008, Ismir, Turkey, 03-05 September 2008, 10p.</p><p>[2] Valyrakis M., Diplas P. and Dancey C.L. 2013. Entrainment of coarse particles in turbulent flows: An energy approach. J. Geophys. Res. Earth Surf., Vol. 118, No. 1., pp 42- 53, doi:340210.1029/2012JF002354.</p><p>[3] Pähtz, Th., Clark, A., Duran, O., Valyrakis, M. 2019. The physics of sediment transport initiation, cessation and entrainment across aeolian and fluvial environments, Reviews of Gephysics, https://doi.org/10.1029/2019RG000679.</p><p>[4] Valyrakis, M. & Pavlovskis, E. 2014. "Smart pebble” design for environmental monitoring applications, In Proceedings of the 11th International Conference on Hydroinformatics, Hamburg, Germany.</p><p>[5] Valyrakis M., A. Alexakis. 2016. Development of a “smart-pebble” for tracking sediment transport. International Conference on Fluvial Hydraulics River Flow 2016, St. Liouis, MO, 8p.</p><p>[6] Valyrakis, M., Farhadi, H. 2017. Investigating coarse sediment particles transport using PTV and “smart-pebbles” instrumented with inertial sensors, EGU General Assembly 2017, Vienna, Austria, 23-28 April 2017, id. 9980.</p>


2011 ◽  
Vol 14 (3) ◽  
pp. 628-645 ◽  
Author(s):  
Mujahid Khan ◽  
H. Md. Azamathulla ◽  
M. Tufail

Prediction of bridge pier scour depth is essential for safe and economical bridge design. Keeping in mind the complex nature of bridge scour phenomenon, there is a need to properly address the methods and techniques used to predict bridge pier scour. Up to the present, extensive research has been carried out for pier scour depth prediction. Different modeling techniques have been applied to achieve better prediction. This paper presents a new soft computing technique called gene-expression programming (GEP) for pier scour depth prediction using laboratory data. A functional relationship has been established using GEP and its performance is compared with other artificial intelligence (AI)-based techniques such as artificial neural networks (ANNs) and conventional regression-based techniques. Laboratory data containing 529 datasets was divided into calibration and validation sets. The performance of GEP was found to be highly satisfactory and encouraging when compared to regression equations but was slightly inferior to ANN. This slightly inferior performance of GEP compared to ANN is offset by its capability to provide compact and explicit mathematical expression for bridge scour. This advantage of GEP over ANN is the main motivation for this work. The resulting GEP models will add to the existing literature of AI-based inductive models for bridge scour modeling.


2016 ◽  
Vol 2016 ◽  
pp. 1-19 ◽  
Author(s):  
Youssef I. Hafez

Most existing equations for predicting local scour at bridge piers suffer from overprediction of the scour depths which results in higher foundation costs. To tackle this problem, a mathematical model for predicting bridge pier scour is developed herein based on an energy balance theory. The present study equation was compared to commonly used bridge scour equations using scour field data in USA. The developed equation has several advantages among which we have the following: it adds to the understanding of the physics of bridge pier scour, is valid for slender and wide piers, does not suffer from overprediction of scour depths, addresses clear water and live bed scour, and includes the effects of various characteristics of the bed material such as specific gravity (or density), porosity, size, and angle of repose. In addition, the developed equation accounts for the debris effect and aids in the design of scour mitigation methods such as collars, side bars, slots, and pier protective piles.


2012 ◽  
Vol 11 (5) ◽  
pp. 975-989 ◽  
Author(s):  
Luigia Brandimarte ◽  
Paolo Paron ◽  
Giuliano Di Baldassarre

Author(s):  
C.D. Anglin ◽  
R.B. Nairn ◽  
A.M. Cornett ◽  
L. Dunaszegi ◽  
J. Turnham ◽  
...  

Author(s):  
Peggy Johnson ◽  
Paul Clopper ◽  
Lyle Zevenbergen

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