Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2251263
Maria A. Meza-Abalo, Carlos A. Vega Posada, David G. Zapata-Medina
ABSTRACTNon-prismatic piles are typically used in cases where large lateral loads must be resisted. In many applications, piles are partially or fully embedded in multi-layered non-homogeneous soil, with each layer having its own set of properties. Analytical, simple solutions to study this problem are more limited and complex than that of prismatic ones. The analysis becomes even more complicated when both the variation of the cross-sectional area of the element and the soil inhomogeneity are included in the formulation. This work presents the derivation of the stiffness matrix and load vector of a non-uniform section of pile partially or fully embedded in non-homogeneous soil. The analysis of non-uniform piles in multi-layered soil is carried out by dividing the pile into multiple sub-elements and then assembling them using conventional matrix methods. Four examples, encompassing partially and fully embedded piles, are presented to validate the simplicity and accuracy of the proposed solution.KEYWORDS: Non-prismatic pilemulti-layered soilnon-homogeneous soilpartially embedded piledifferential transformation method Disclosure statementNo potential conflict of interest was reported by the author(s).List of Symbols A(x)=Area of the element at a depth xB(x)=Diameter of the element at a depth xE=Young’s modulus of the elementGp=Shear modulus of the pileI(x)=Second moment of inertia of the element at a depth xKL=First-parameter of the Pasternak foundationKo=Modulus of subgrade reactionLe=Embedded length of the pileLp=Total length of the pileLu=Unembedded length of the pileM=Bending momentm=Taper ratiomh=Variation of the modulus of subgrade reaction with depthPo=Axial loadq(x)=Applied transverse loadrb=Radius at the bottom of the elementreq=Equivalent radius at half of the length of the elementrt=Radius at the top of the elementSa, Sb=Shear stiffness of the linear transverse springs at ends A and B, respectively.V=Shear forcex=Coordinate along the longitudinal axisy=Transverse deflectionY=Non-dimensional term for the transverse deflectionkg=Second-parameter of elastic foundationκa, κb=Flexural stiffness of the flexural springs at ends A and B, respectively.ξ=Non-dimensional term for the length
{"title":"Analytical solution for laterally loaded non-uniform circular piles in multi-layered inhomogeneous soil","authors":"Maria A. Meza-Abalo, Carlos A. Vega Posada, David G. Zapata-Medina","doi":"10.1080/19386362.2023.2251263","DOIUrl":"https://doi.org/10.1080/19386362.2023.2251263","url":null,"abstract":"ABSTRACTNon-prismatic piles are typically used in cases where large lateral loads must be resisted. In many applications, piles are partially or fully embedded in multi-layered non-homogeneous soil, with each layer having its own set of properties. Analytical, simple solutions to study this problem are more limited and complex than that of prismatic ones. The analysis becomes even more complicated when both the variation of the cross-sectional area of the element and the soil inhomogeneity are included in the formulation. This work presents the derivation of the stiffness matrix and load vector of a non-uniform section of pile partially or fully embedded in non-homogeneous soil. The analysis of non-uniform piles in multi-layered soil is carried out by dividing the pile into multiple sub-elements and then assembling them using conventional matrix methods. Four examples, encompassing partially and fully embedded piles, are presented to validate the simplicity and accuracy of the proposed solution.KEYWORDS: Non-prismatic pilemulti-layered soilnon-homogeneous soilpartially embedded piledifferential transformation method Disclosure statementNo potential conflict of interest was reported by the author(s).List of Symbols A(x)=Area of the element at a depth xB(x)=Diameter of the element at a depth xE=Young’s modulus of the elementGp=Shear modulus of the pileI(x)=Second moment of inertia of the element at a depth xKL=First-parameter of the Pasternak foundationKo=Modulus of subgrade reactionLe=Embedded length of the pileLp=Total length of the pileLu=Unembedded length of the pileM=Bending momentm=Taper ratiomh=Variation of the modulus of subgrade reaction with depthPo=Axial loadq(x)=Applied transverse loadrb=Radius at the bottom of the elementreq=Equivalent radius at half of the length of the elementrt=Radius at the top of the elementSa, Sb=Shear stiffness of the linear transverse springs at ends A and B, respectively.V=Shear forcex=Coordinate along the longitudinal axisy=Transverse deflectionY=Non-dimensional term for the transverse deflectionkg=Second-parameter of elastic foundationκa, κb=Flexural stiffness of the flexural springs at ends A and B, respectively.ξ=Non-dimensional term for the length","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135518875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2238471
Zhuoyuan Cheng
{"title":"Design of Shallow and Deep Foundations, 1st Edition","authors":"Zhuoyuan Cheng","doi":"10.1080/19386362.2023.2238471","DOIUrl":"https://doi.org/10.1080/19386362.2023.2238471","url":null,"abstract":"","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43199707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2246254
D. Silva, A. Moura
ABSTRACT Load–transfer methods are important tools to analyse and predict pile settlements. Several studies on single piles and pile groups used experimental data from instrumentation, in order to evaluate the load–transfer mechanism to the foundation soil, by obtaining skin friction and toe resistance. For single piles, the load–transfer curves can be approximated by hyperbolic models, and for pile groups, by models in which the interaction between nearby piles is added to the hyperbolic curve of each individual pile through analytical formulations. By collecting experimental data from 68 piles executed in granular soils that were instrumented and subjected to static load tests, this study evaluated the fitting of load–transfer curves to hyperbolic functions for single piles and pile groups. Remarkable fitting to hyperbolic functions was found for single piles, and very good agreement was also obtained for pile groups (adjusted R 2 around 0.96). The deformation parameters (M s and M b) by Bohn et al. for single piles were reassessed, and new reference values that led to more convergent predictions were proposed. Lastly, the use of the parameters M s and M b was also extended to pile groups and new preliminary reference values were suggested.
{"title":"Evaluation of fitting to hyperbolic functions of load transfer curves for piles in granular soil profiles","authors":"D. Silva, A. Moura","doi":"10.1080/19386362.2023.2246254","DOIUrl":"https://doi.org/10.1080/19386362.2023.2246254","url":null,"abstract":"ABSTRACT Load–transfer methods are important tools to analyse and predict pile settlements. Several studies on single piles and pile groups used experimental data from instrumentation, in order to evaluate the load–transfer mechanism to the foundation soil, by obtaining skin friction and toe resistance. For single piles, the load–transfer curves can be approximated by hyperbolic models, and for pile groups, by models in which the interaction between nearby piles is added to the hyperbolic curve of each individual pile through analytical formulations. By collecting experimental data from 68 piles executed in granular soils that were instrumented and subjected to static load tests, this study evaluated the fitting of load–transfer curves to hyperbolic functions for single piles and pile groups. Remarkable fitting to hyperbolic functions was found for single piles, and very good agreement was also obtained for pile groups (adjusted R 2 around 0.96). The deformation parameters (M s and M b) by Bohn et al. for single piles were reassessed, and new reference values that led to more convergent predictions were proposed. Lastly, the use of the parameters M s and M b was also extended to pile groups and new preliminary reference values were suggested.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43165758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2251239
André Querelli, Tiago de Jesus Souza
ABSTRACT This paper application of a method developed in Brazil for predicting driving transferred energy. The method was recently developed in Brazil and was used in short piles in 2019. In this more recent paper, it was sought to extend the application of the method to long piles (Pile length > 30 m) in soils of different characteristics. It is based on the pile measurements of permanent and elastic displacements during driving and calibration of the site-specific λ coefficient. The article validates the methodology in a case study of two sites with 159 dynamic tests of steel-driven piles in the cities of Santos (SP) and Itaguaí (RJ). Through calibration of λ, the energy predictions showed a good correlation to those obtained from the dynamic tests. There is an additional contribution to the original author’s analysis – increasing the previous testing database – about the correlation between λ and the pile length, as the study includes piles from 36 to 60 m in length – a range that was not included during the author’s first method evaluation. Its major advantage is allowing effective energy estimations in non‑instrumented piles as it is not practical to monitor every single pile of a construction driving site to assess the transferred energy. The presented method is useful in the practice of driven foundation and its quality control.
{"title":"Predicting driving transferred energy: case studies of steel piles","authors":"André Querelli, Tiago de Jesus Souza","doi":"10.1080/19386362.2023.2251239","DOIUrl":"https://doi.org/10.1080/19386362.2023.2251239","url":null,"abstract":"ABSTRACT This paper application of a method developed in Brazil for predicting driving transferred energy. The method was recently developed in Brazil and was used in short piles in 2019. In this more recent paper, it was sought to extend the application of the method to long piles (Pile length > 30 m) in soils of different characteristics. It is based on the pile measurements of permanent and elastic displacements during driving and calibration of the site-specific λ coefficient. The article validates the methodology in a case study of two sites with 159 dynamic tests of steel-driven piles in the cities of Santos (SP) and Itaguaí (RJ). Through calibration of λ, the energy predictions showed a good correlation to those obtained from the dynamic tests. There is an additional contribution to the original author’s analysis – increasing the previous testing database – about the correlation between λ and the pile length, as the study includes piles from 36 to 60 m in length – a range that was not included during the author’s first method evaluation. Its major advantage is allowing effective energy estimations in non‑instrumented piles as it is not practical to monitor every single pile of a construction driving site to assess the transferred energy. The presented method is useful in the practice of driven foundation and its quality control.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49076507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2251795
M.B.C. Ülker, E. Altınok, G. Taşkın
Field pile load tests are fairly expensive experiments that can be applied to certain pile types required to be installed in full scale. Hence, it is neither practical nor efficient to perform a load test for every installed pile. While there exist many empirical relations for predicting pile capacities, such methods typically suffer from accuracy and generality. Therefore, current geotechnical practice still looks for methods to accommodate full-scale pile load testing to serve as accurate and practical tools. In this study, load bearing capacities of closed- and open-ended piles in cohesive and cohesionless soils are predicted using machine learning. Nine such methods are utilized in the analyses where Cone Penetration Test (CPT) and pile data are considered as the learning features necessary to teach those methods the database gathered via a comprehensive search. Then, machine learning models are developed, and the databases are separated into five-folds according to the cross-validation-principle, which are used for both training and testing of the machine learning methods. Model predictions are validated with classical CPT-based equations. Results indicate that Relevance Vector Regression and the Random Forest methods typically generate considerably better predictions than the other methods and empirical equations. Thus, machine learning methods are found as reliable tools to predict the pile load capacities of both open-ended and closed-ended pile provided that there is a large enough database and that an appropriate method is used.
{"title":"Data-driven modeling of ultimate load capacity of closed- and open-ended piles using machine learning","authors":"M.B.C. Ülker, E. Altınok, G. Taşkın","doi":"10.1080/19386362.2023.2251795","DOIUrl":"https://doi.org/10.1080/19386362.2023.2251795","url":null,"abstract":"Field pile load tests are fairly expensive experiments that can be applied to certain pile types required to be installed in full scale. Hence, it is neither practical nor efficient to perform a load test for every installed pile. While there exist many empirical relations for predicting pile capacities, such methods typically suffer from accuracy and generality. Therefore, current geotechnical practice still looks for methods to accommodate full-scale pile load testing to serve as accurate and practical tools. In this study, load bearing capacities of closed- and open-ended piles in cohesive and cohesionless soils are predicted using machine learning. Nine such methods are utilized in the analyses where Cone Penetration Test (CPT) and pile data are considered as the learning features necessary to teach those methods the database gathered via a comprehensive search. Then, machine learning models are developed, and the databases are separated into five-folds according to the cross-validation-principle, which are used for both training and testing of the machine learning methods. Model predictions are validated with classical CPT-based equations. Results indicate that Relevance Vector Regression and the Random Forest methods typically generate considerably better predictions than the other methods and empirical equations. Thus, machine learning methods are found as reliable tools to predict the pile load capacities of both open-ended and closed-ended pile provided that there is a large enough database and that an appropriate method is used.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135518184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2241285
Apurva Ak, S. Chandrakaran, N. Sankar
ABSTRACT Rattan fibre as a reinforcement material can be a promising candidate for fabricating mattresses that improves the bearing capacity and settlement reduction of sand. Apart from observing the potential of rattan mats in reinforcing the sand beds, an attempt is made to understand the role of apertures with varying dimensions in enhancing the load bearing performance of sand. A series of plate load tests were performed to study the effect of the depth of top layer reinforcement, width, aperture size of rattan mats and number of reinforcement layers. After comparing the test results of various aperture sized mats, openly woven rattan mats performed superior to closely woven mats. The incorporation of rattan mats under the most effective reinforcement configuration has enhanced the bearing strength improvement factor and settlement reduction factor to 7.1 and 0.85, respectively, for closely woven rattan mats and about 8.16 and 0.94 for openly woven rattan mats with optimum aperture sizes.
{"title":"Influence of aperture size on the performance of square footing resting on rattan reinforced sand","authors":"Apurva Ak, S. Chandrakaran, N. Sankar","doi":"10.1080/19386362.2023.2241285","DOIUrl":"https://doi.org/10.1080/19386362.2023.2241285","url":null,"abstract":"ABSTRACT Rattan fibre as a reinforcement material can be a promising candidate for fabricating mattresses that improves the bearing capacity and settlement reduction of sand. Apart from observing the potential of rattan mats in reinforcing the sand beds, an attempt is made to understand the role of apertures with varying dimensions in enhancing the load bearing performance of sand. A series of plate load tests were performed to study the effect of the depth of top layer reinforcement, width, aperture size of rattan mats and number of reinforcement layers. After comparing the test results of various aperture sized mats, openly woven rattan mats performed superior to closely woven mats. The incorporation of rattan mats under the most effective reinforcement configuration has enhanced the bearing strength improvement factor and settlement reduction factor to 7.1 and 0.85, respectively, for closely woven rattan mats and about 8.16 and 0.94 for openly woven rattan mats with optimum aperture sizes.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46300519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-21DOI: 10.1080/19386362.2023.2251809
Zhe Luo
ABSTRACT This study aimed to develop an integrated approach to analyse the interaction between soils and beams. The research methods involved placing a statically indeterminate beam on spatially random soils, where soil springs acted as supports for the beam. The soil spring stiffness values were simulated using random field theory. This integrated approach was embedded in the Monte Carlo simulation framework to facilitate probabilistic assessment. This study concluded that the force method solution accurately determined the bending moment and shear diagrams for a beam supported by soil springs. Additionally, soil spatial variability had a significant impact on the beam responses, including the variations in footing settlements, support reactions, bending moment, and shear force. This study also identified a critical scale of soil fluctuation that coincides with the beam span, which resulted in the highest probability of structural bending failure. Overall, this study highlights the importance of accounting for soil spatial variability in an integrated geotechnical and structural design approach.
{"title":"Integrated analysis of soil-structure interaction for statically indeterminate beams on spatially random soils","authors":"Zhe Luo","doi":"10.1080/19386362.2023.2251809","DOIUrl":"https://doi.org/10.1080/19386362.2023.2251809","url":null,"abstract":"ABSTRACT This study aimed to develop an integrated approach to analyse the interaction between soils and beams. The research methods involved placing a statically indeterminate beam on spatially random soils, where soil springs acted as supports for the beam. The soil spring stiffness values were simulated using random field theory. This integrated approach was embedded in the Monte Carlo simulation framework to facilitate probabilistic assessment. This study concluded that the force method solution accurately determined the bending moment and shear diagrams for a beam supported by soil springs. Additionally, soil spatial variability had a significant impact on the beam responses, including the variations in footing settlements, support reactions, bending moment, and shear force. This study also identified a critical scale of soil fluctuation that coincides with the beam span, which resulted in the highest probability of structural bending failure. Overall, this study highlights the importance of accounting for soil spatial variability in an integrated geotechnical and structural design approach.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49535002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-16DOI: 10.1080/19386362.2023.2212996
Ningthoujam Jibanchand, K. Devi
ABSTRACT Due to significant uncertainties associated with soil, it is challenging to anticipate settlement accurately for shallow footings on cohesionless soil. To produce more precise predictive settlement models, four ensemble learning models have been created in this study: Bagging, Random Forest (RF), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost). The models are created utilizing a sizable database based on standard penetration tests (SPT). A variety of evaluation criteria, including R 2, RMSE, and MAE, were employed to rate the performance of the models. The analysis results showed that Bagging and XGBoost models demonstrate excellent performance with R 2 values of 0.901 and 0.915, respectively, surpassing other models studied here as well as other models from the literature. Consequently, Bagging and XGBoost can be effective methods for predicting settlement in shallow foundations on cohesionless soil.
{"title":"Application of ensemble learning in predicting shallow foundation settlement in cohesionless soil","authors":"Ningthoujam Jibanchand, K. Devi","doi":"10.1080/19386362.2023.2212996","DOIUrl":"https://doi.org/10.1080/19386362.2023.2212996","url":null,"abstract":"ABSTRACT Due to significant uncertainties associated with soil, it is challenging to anticipate settlement accurately for shallow footings on cohesionless soil. To produce more precise predictive settlement models, four ensemble learning models have been created in this study: Bagging, Random Forest (RF), Adaptive Boosting (AdaBoost), and Extreme Gradient Boosting (XGBoost). The models are created utilizing a sizable database based on standard penetration tests (SPT). A variety of evaluation criteria, including R 2, RMSE, and MAE, were employed to rate the performance of the models. The analysis results showed that Bagging and XGBoost models demonstrate excellent performance with R 2 values of 0.901 and 0.915, respectively, surpassing other models studied here as well as other models from the literature. Consequently, Bagging and XGBoost can be effective methods for predicting settlement in shallow foundations on cohesionless soil.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45033612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-16DOI: 10.1080/19386362.2023.2227505
T. D. Toan, S. Lam, Y. Wong, M. Meng
ABSTRACT In this research, a fuzzy rule–based decision support (FRBDS) tool is developed to assist selection of ground treatment techniques for road embankments. Using input variables such as embankment height, geological condition and soft soil thickness, the FRBDS evaluates the ground treatment level, based upon which the highway engineer determines a suitable treatment method taking into account project constraints. In the case study, the FRBDS is applied for a 10-km package of HaNoi–HaiPhong expressway construction project and is evaluated in comparison to expert judgements. The results show that the treatment methods provided by the two approaches are similar for 36 out of 52 sections of the package, but the FRBDS provides more consistent and rational solutions. In particular, the FRBDS significantly reduces technological fragmentation. It can be concluded that the FRBDS is a useful tool that establishes structured innovative solutions to improve the quality of decision-making for large transportation projects.
{"title":"Conceptual fuzzy-based decision support tool for soil improvement under highway embankment - a case study of HaNoi–HaiPhong expressway","authors":"T. D. Toan, S. Lam, Y. Wong, M. Meng","doi":"10.1080/19386362.2023.2227505","DOIUrl":"https://doi.org/10.1080/19386362.2023.2227505","url":null,"abstract":"ABSTRACT In this research, a fuzzy rule–based decision support (FRBDS) tool is developed to assist selection of ground treatment techniques for road embankments. Using input variables such as embankment height, geological condition and soft soil thickness, the FRBDS evaluates the ground treatment level, based upon which the highway engineer determines a suitable treatment method taking into account project constraints. In the case study, the FRBDS is applied for a 10-km package of HaNoi–HaiPhong expressway construction project and is evaluated in comparison to expert judgements. The results show that the treatment methods provided by the two approaches are similar for 36 out of 52 sections of the package, but the FRBDS provides more consistent and rational solutions. In particular, the FRBDS significantly reduces technological fragmentation. It can be concluded that the FRBDS is a useful tool that establishes structured innovative solutions to improve the quality of decision-making for large transportation projects.","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48324663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-16DOI: 10.1080/19386362.2023.2227036
S. Mehra, A. Trivedi
ABSTRACT The progressive twist and displacement in the sand are investigated for a set of pile groups (1,2; 1,3; 2,2) corresponding to the application of the torsional loads. A novel numerical model supported by a set of experimental observations has been considered to capture pile-soil interaction for the pile groups subjected to torsional load. The torque mobilization, progressive twist, and displacement have been computed for a range of the initial shear modulus ratio for the entire set of pile groups. As a result of twisting, the torsional energy zones are set into the soil, and there is the formation of a heave and cavity around the pile group. The torsional energy and twist rigidity parameters were evaluated for a range of shear modulus ratios of the soil. It has been observed that the torsional energy of the pile group (1,2) is significantly higher than pile groups (1,3; 2,2). A classification for torsional energy zones associated with twist rigidity and displacement rigidity factor has been suggested to set the limits for twist and displacement of the pile groups relative to a single pile. A relationship of the torsional energy with progressive twist and displacement is obtained. The components of torsional energy associated with progressive twist and displacement were obtained in the range of 0.43–0.50 and 0.50–0.57 respectively Graphical abstract
{"title":"Progressive twist, displacement and torsional energy around pile groups","authors":"S. Mehra, A. Trivedi","doi":"10.1080/19386362.2023.2227036","DOIUrl":"https://doi.org/10.1080/19386362.2023.2227036","url":null,"abstract":"ABSTRACT The progressive twist and displacement in the sand are investigated for a set of pile groups (1,2; 1,3; 2,2) corresponding to the application of the torsional loads. A novel numerical model supported by a set of experimental observations has been considered to capture pile-soil interaction for the pile groups subjected to torsional load. The torque mobilization, progressive twist, and displacement have been computed for a range of the initial shear modulus ratio for the entire set of pile groups. As a result of twisting, the torsional energy zones are set into the soil, and there is the formation of a heave and cavity around the pile group. The torsional energy and twist rigidity parameters were evaluated for a range of shear modulus ratios of the soil. It has been observed that the torsional energy of the pile group (1,2) is significantly higher than pile groups (1,3; 2,2). A classification for torsional energy zones associated with twist rigidity and displacement rigidity factor has been suggested to set the limits for twist and displacement of the pile groups relative to a single pile. A relationship of the torsional energy with progressive twist and displacement is obtained. The components of torsional energy associated with progressive twist and displacement were obtained in the range of 0.43–0.50 and 0.50–0.57 respectively Graphical abstract","PeriodicalId":47238,"journal":{"name":"International Journal of Geotechnical Engineering","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41934998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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