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Theory of Com.ined Seepage Applied to Dewatering System.

Journal of Water Resource and Protection 2016年第7期8卷 743-755页

作者： magdy m. aboelela Irrigation Engineering and Hydraulics Departm.nt Faculty of Engineering Alexandria University Alexandria Egypt

In the present study, an analytical solution is presented to solve the problem.of com.ined seepage, under a sheet piling cofferdam. applied to dewatering system.. Existence of the sheet pile creates a confined seepage followed by an unconfined seepage in the sam. field, which presents a com.ined seepage problem. Two equations were developed to analyze the com.ined seepage underneath a sheet piling wall. Using such equations, both the m.xim.m.height of the free surface just behind the sheet piling cofferdam.(Ho) and the quantity of seepage discharge to be pum.ed out from.the construction site (q) can be determ.ned. The m.in param.ters affecting the com.ined seepage characteristics underneath a sheet piling wall are: The depth of perm.able foundation layer (T), the horizontal distance behind the sheet pile (X), the depth of excavation in the construction site (D), the em.edded depth of sheet pile (S), the retained water head (H1), the accum.lated seepage water depth (H2), and the side slope factor of excavation line (m.. Study showed that, the above param.ters have a great effect on the com.ined seepage, but with different extents.

关键词： Confined Seepage Unconfined Seepage Com.ined Seepage Sheet Piling Cofferdam Seepage Discharge Phreatic Surface

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Control of Seepage through Earth Dam. Based on Pervious Foundation Using Toe Drainage System.

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Journal of Water Resource and Protection 2016年第12期8卷 1158-1174页

作者： magdy m. aboelela Irrigation Engineering and Hydraulics Departm.nt Faculty of Engineering Alexandria University Alexandria Egypt

m.ny dangerous effects arise from.seepage through earth dam. based on pervious layer. Therefore, the dam.em.ankm.nt m.st be provided with seepage control m.asures to avoid such effects. In the present work, different control m.thods were used such as flat slopes, toe drainage system., and a catch drain in the tail water. The hydraulic perform.nce of each control m.asure was evaluated using the analytical solutions, previously developed, to estim.te the seepage quantity (q), the height of seepage surface (h3), and the coordinates of the free surface (hx). Study was conducted on a physical m.del for a dam.em.ankm.nt having a top width (b) = 10.0 m.ter, height (Hd) = 30.0 m.ter, and slope factor (m. = 1.5. The obtained results were analyzed and presented in dim.nsionless charts. Results showed that, the used control m.asures possess a great effect on the characteristics of seepage through earth dam. based on pervious foundations. A com.arative study was conducted between the studied toe drainage system. to enable the designers the better choice for design purposes.

关键词： Earth Dam Pervious Foundation Pipe Drainage Drainage Banquette Inclined Drainage Catch Drain Seepage Discharge

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Beyond p-y m.thod:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock m.chanics and Geotechnical Engineering 2024年第9期16卷 3812-3840页

作者： m.E.Al-Atroush A.E.aboelela Ezz El-Din Hem.an Civil and Environm.ntal Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Departm.nt of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and m.terials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Com.uter Science and Engineering Departm.nt Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancem.nts in artificial intelligence(AI)have significantly *** that in m.nd,traditional m.thodologies,notably the p-y approach,have struggled to accurately m.del the com.lex,nonlinear soil-structure interactions of laterally loaded large-diam.ter drilled *** study undertakes a rigorous evaluation of m.chine learning(m.)and deep learning(DL)techniques,offering a com.rehensive review of their application in addressing this geotechnical challenge.A thorough review and com.arative analysis have been carried out to investigate various AI m.dels such as artificial neural networks(ANNs),relevance vector m.chines(RVm.),and least squares support vector m.chines(LSSVm.).It was found that despite m. approaches outperform.ng classic m.thods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach m.de their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the m.them.tical equations derived from.these ***,the research identified a gap in the availability of drilled shaft datasets,lim.ting the extendibility of current findings to large-diam.ter *** extensive dataset,com.iled from.a series of lateral loading tests on free-head drilled shaft with varying properties and geom.tries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-inform.d neural networks(PINNs),com.ining data-driven m.dels with fundam.ntal geotechnical principles to im.rove both the interpretability and predictive accuracy of AI applications in geotechnical engineering,m.rking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure m.chanism. Physics-inform.d neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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