A regression-based approach for estimating preliminary dimensioning of reinforced concrete cantilever retaining walls

Dağdeviren, Uğur; Kaymak, Burak

doi:10.1007/s00158-019-02470-w

Cited by 11 publications

(9 citation statements)

References 25 publications

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“…The supported criterion hyperparameter for regression is also by default considered mean squared error (MSE), which is equal to variance reduction. Table 2 illustrates different metrics for both classification and regression, which can be acquired from the formulas [80,81].…”

Section: Evaluation Metrics For ML Algorithmsmentioning

confidence: 99%

Using machine learning algorithms to predict failure on the PCB surface under corrosive conditions

2022

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Section: Evaluation Metrics For ML Algorithmsmentioning

confidence: 99%

Using machine learning algorithms to predict failure on the PCB surface under corrosive conditions

2022

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“…Optimization can be applied through multiple programming software; however, due to their complexities civil engineers often choose simpler programming languages such as MATLAB (Schmied and Karlsson [24], Pei and Xia [28], Al Sebai et al [31], Srivastavaa et al [32], Babu and Basha [36], Khajehzadeh et al [38], Khajehzadeh and Eslami [43], Sable and Patil [44], Sable and Patil [45], Kaveh and Behnam [46], Kaveh et al [47], Khajehzadeh et al [49], Gandomi et al [52], Kaveh and Mahdavi [53], Gandomi et al [61], Öztürk and Türkeli [70], Uray et al [71], Kalemci et al [78], Kayabekir [79], Kashani et al [82], Mevada et al [88], Uray et al [92], Tutus ¸et al [95], Khajehzadeh et al [101], and Khajehzadeh et al [103]), Fortran (Villalba et al [27] and Ukritchon et al [65]), C#.NET (Linh et al [93]), Python (Dodigović et al [94]), and C++ (Dagdeviren and Kaymak [72]). Studies have also tried to combine analysis software such as ABAQUS, ANSYS, PLAXIS 2D, and GeoSlope (Rahbari [23], Papazafeiropoulos et al [29], Uray and Tan [30], Rahbari et al [64], and Ravichandran et al [84]) with optimization.…”

Section: Optimization Tools and Parametric Equationsmentioning

confidence: 99%

“…Studies have also tried to combine analysis software such as ABAQUS, ANSYS, PLAXIS 2D, and GeoSlope (Rahbari [23], Papazafeiropoulos et al [29], Uray and Tan [30], Rahbari et al [64], and Ravichandran et al [84]) with optimization. Research studies of Singla and Gupta [54], Dagdeviren and Kaymak [72], and Konstandakopoulou et al [76] have tried to tackle the optimization problem by developing regression equations and eliminating the need of programming but with certain limitations. Research of Sarıbas ¸and Erbatur [19] developed RETOPT and Ceranic et al [34] developed GENOD, which are computer programs to apply optimization to the design of RC retaining walls but none of the above programs are commercially available.…”

Section: Optimization Tools and Parametric Equationsmentioning

confidence: 99%

Design Optimization of Reinforced Concrete Cantilever Retaining Walls: A State‐of‐the‐Art Review

Shakeel

Azam

Riaz

et al. 2022

Advances in Civil Engineering

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The booming growth of computational abilities in the 21st century has led to its assimilation and benefit in all horizons of engineering. For civil engineers, these advancements have led to groundbreaking technologies such as BIM, automation, and optimization. Unfortunately, even in an era of dwindling resources and dire need for sustainability, optimization has failed to attract implementation in practice. Despite an exponential growth as an area of research interest, the optimization of engineering structures such as reinforced concrete (RC) is still a complex task that requires multidisciplinary knowledge, hindering its practicability. Although past review papers have delved into this topic, they have only been able to cover the breadth of information available by covering broader aspects of optimization of structures. This study on the other hand aims to cover this topic in depth to uncover problem specific trends and issues, by focusing only on optimization of RC cantilever retaining walls. Although there is an abundance of research studies on this topic, there is an absence of any critical review to tie them up, and concurrently with its broader scope, it suffers the same lack of applicability in the field. The in-depth review presents a summarization of all the online publications including research articles, conference papers, and theses to the best of authors’ knowledge on the topic of RC cantilever retaining wall optimization. Geographical trends, regional developments, and prominent journals have been identified. The design codes, problem formulation, objectives, constraints, variables, and their optimization techniques are tabulated for ease of understanding. Unique areas of development investigated by the different researchers have been highlighted. Lastly, comprehensive recommendations for future works have been detailed with a focus on improving its applicability and assimilation into the construction industry.

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“…To get an expression for the design of the reinforced concrete retaining wall, Akbay et al (2020) and to obtain a decision diagram for retaining wall selection, Choi and Lee (2010) used regression analysis. Srivastava and Malhotra (2016) used regression analysis to estimate passive horizontal earth pressures, and Dagdeviren and Kaymak (2020) used regression analysis to obtain a pre-sizing recommendation for a T-shaped retaining wall. Azzouz et al (1976) develop regression equations to predict the compression index and compression ratio from classification or index data, and statistical techniques are utilized to assess and evaluate experimental data from consolidation experiments on a wide variety of undisturbed soils.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the Maximum Bending Moment of Cantilever Sheet Pile Walls by Using Multiple Linear Regression Analysis

Akan

2022

Mühendislik Bilimleri Ve Tasarım Dergisi

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Sheet pile walls are flexible retaining structures that are used to hold the horizontal soil pressures behind them, especially in situations that cause stress changes such as excavation. They are divided into two as cantilever and externally supported. Cantilever walls are used in excavations with a maximum depth of 6 meters and are supported by anchors in excavations deeper than this. Some of the values to be calculated in the design of cantilever sheet pile walls are the embedment depth and the maximum bending moment that(Mmax) will occur in the cross-section of the wall. There are various approaches in analytical methods that have complex calculation steps such as determining earth pressures, solving second and thirdorder equations. In this study, the Mmax that will occur in the cross-section of a cantilever sheet pile wall penetrates in the sand is estimated by the expressions obtained with the help of multiple linear regression(MLR) analysis. The results showed that the Mmax may not be achieved by only MLR models but with the help of polynomial equations.

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A regression-based approach for estimating preliminary dimensioning of reinforced concrete cantilever retaining walls

Cited by 11 publications

References 25 publications

Using machine learning algorithms to predict failure on the PCB surface under corrosive conditions

Using machine learning algorithms to predict failure on the PCB surface under corrosive conditions

Design Optimization of Reinforced Concrete Cantilever Retaining Walls: A State‐of‐the‐Art Review

Estimation of the Maximum Bending Moment of Cantilever Sheet Pile Walls by Using Multiple Linear Regression Analysis

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