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Assessment of an alternative to deep foundations in compressible clays: the structural cell foundation

Sergio A. MARTÍNEZ-GALVÁN, Miguel P. ROMO

《结构与土木工程前沿（英文）》 2018年 第12卷 第1期   页码 67-80 doi: 10.1007/s11709-017-0399-5

摘要： The new type of deep foundation for buildings on saturated, compressible-low strength clayey soil deposits, branded structural cell essentially consists of a rigid concrete top slab, structurally connected to reinforced concrete peripheral walls (diaphragms) that enclose the natural soil. Accordingly, as the initial volume of the confined soft clays within the lateral stiff diaphragms will remain constant upon loading, the hollowed structural cell will be “transformed” into a very large cross-section pillar of unit weight slightly higher than that of the natural soft clayey soil. This type of foundation seems to be a highly competitive alternative to the friction pile-box foundations (widely used in Mexico City clays), due to its economic and environmental advantages. Economies result, for example, from the absence of huge excavations hence sparing the need of earth retaining structures. Further savings result from appreciably smaller concrete volumes required for building the structural cell than the friction pile-box foundation; moreover, the construction time of the former is much shorter than that of the latter. Regarding the impact to the environment, less air contamination follows from the fact that both traffic jams and soil excavation lessen appreciably. Considering these facts and others regarding scheduling, it was decided to replace 48-friction pile-box foundations specified in the master plan project by this new type of foundation. The overall behavior of these cell foundations over a five-year period is fared from close visual observations and their leveling during the first three years after their construction.

关键词： deep foundations     bearing capacity     resistant moment     structural cell     3D numerical modeling    

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Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

《结构与土木工程前沿（英文）》 2021年 第15卷 第2期   页码 318-332 doi: 10.1007/s11709-021-0715-y

摘要： The aim of this study is to propose a new detection method for determining the damage locations in pile foundations based on deep learning using acoustic emission data. First, the damage location is simulated using a back propagation neural network deep learning model with an acoustic emission data set acquired from pile hit experiments. In particular, the damage location is identified using two parameters: the pile location ( ) and the distance from the pile cap ( ). This study investigates the influences of various acoustic emission parameters, numbers of sensors, sensor installation locations, and the time difference on the prediction accuracy of and . In addition, correlations between the damage location and acoustic emission parameters are investigated. Second, the damage step condition is determined using a classification model with an acoustic emission data set acquired from uniaxial compressive strength experiments. Finally, a new damage detection and evaluation method for pile foundations is proposed. This new method is capable of continuously detecting and evaluating the damage of pile foundations in service.

关键词： pile foundations     damage location     acoustic emission     deep learning     damage step    

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Influence of site conditions on seismic design parameters for foundations as determined via nonlinear

Muhammad Tariq A. CHAUDHARY

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 275-303 doi: 10.1007/s11709-021-0685-0

摘要： Site conditions, including geotechnical properties and the geological setting, influence the near-surface response of strata subjected to seismic excitation. The geotechnical parameters required for the design of foundations include mass density ( ), damping ratio ( ), shear wave velocity ( ), and soil shear modulus ( ). The values of the last three parameters are sensitive to the level of nonlinear strain induced in the strata due to seismic ground motion. In this study, the effect of variations in soil properties, such as plasticity index ( ), effective stress ( ), over consolidation ratio (OCR), impedance contrast ratio ( ) between the bedrock and the overlying strata, and depth of soil strata over bedrock ( ), on seismic design parameters ( , , and ) was investigated for National Earthquake Hazards Reduction Program (NEHRP) site classes C and D, through 1D nonlinear seismic site response analysis. The Morris one-at-a-time (OAT) sensitivity analysis indicated that , , and were significantly influenced by variations in , while affected more than it affected and . However, the influence of on these parameters was less significant. It was also found that variations in soil properties influenced seismic design parameters in soil type D more significantly than in soil type C. Predictive relationships for , , and were derived based on the 1D seismic site response analysis and sensitivity analysis results. The , , and values obtained from the analysis were compared with the corresponding values in NEHRP to determine the similarities and differences between the two sets of values. The need to incorporate and in the metrics for determining , , and for the seismic design of foundations was highlighted.

关键词： site effects     1D seismic site response analysis     sensitivity analysis     foundations     shear wave velocity     soil shear modulus    

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Model testing of tripod caisson foundations in silty clay subjected to eccentric lateral loads

《结构与土木工程前沿（英文）》 2023年 第17卷 第3期   页码 467-476 doi: 10.1007/s11709-023-0933-6

摘要： In this study, model tests were conducted to investigate the bearing capacities of tripod caisson foundations subjected to eccentric lateral loads in silty clay. Lateral load–rotation curves of five eccentric-shaped tripod suction foundations were plotted to analyze the bearing capacities at different loading angles. It was observed that the loading angle significantly influenced the bearing capacity of the foundations, particularly for eccentric tripod caisson foundations. Compared with eccentric tripod caisson foundations, the traditional tripod foundation has a relatively high ultimate lateral capacity at the omnidirectional loading angle. By analyzing the displacement of the caissons, a formula for the rotational center of the tripod caisson foundation subjected to an eccentric lateral load was derived. The depth of the rotation center was 0.68–0.92 times the height of the caisson when the bearing capacity reached the limit. Under the undrained condition, suction was generated under the lid of the “up-lift” caisson, which helps resist lateral forces from the wind and waves.

关键词： tripod caisson foundation     silty clay     eccentric lateral capacity     model tests    

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Investigation of the seismic behavior of grouted sandy gravel foundations using shaking table tests

Tiancheng WANG; Yu LIANG; Xiaoyong ZHANG; Zhihuan RUAN; Guoxiong MEI

《结构与土木工程前沿（英文）》 2022年 第16卷 第9期   页码 1196-1211 doi: 10.1007/s11709-022-0865-6

摘要： Sandy gravel foundations exhibit non-linear dynamic behavior when subjected to strong ground motions, which can have amplification effects on superstructures and can reveal insufficient lateral resistance of foundations. Grouting methods can be used to improve the seismic performance of natural sandy gravel foundations. The strength and stiffness of grouted sandy gravel foundations are different from those of natural foundations, which have unknown earthquake resistance. Few studies have investigated the seismic behavior of sandy gravel foundations before and after grouting. In this study, two shaking table tests were performed to evaluate the effect of grouting reinforcement on seismic performance. The natural frequency, acceleration amplification effect, lateral displacement, and vertical settlement of the non-grouted and grouted sandy gravel foundations were measured and compared. Additionally, the dynamic stress-strain relationships of the two foundations were obtained by a linear inversion method to evaluate the seismic energy dissipation. The test results indicated that the acceleration amplification, lateral displacement amplitude, and vertical settlement of the grouted sandy gravel foundation were lower than that of the non-grouted foundation under low-intensity earthquakes. However, a contrasting result was observed under high-intensity earthquakes. This demonstrated that different grouting reinforcement strategies are required for different sandy gravel foundations. In addition, the dynamic stress-strain relationship of the two foundations exhibited two different energy dissipation mechanisms. The results provide insights relating to the development of foundations for relevant engineering sites and to the dynamic behavior of grouted foundations prior to investigating soil-structure interaction problems.

关键词： sandy gravel foundation     grouting-treated reinforcement     shaking table test     seismic behavior    

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Innovative piled raft foundations design using artificial neural network

Meisam RABIEI, Asskar Janalizadeh CHOOBBASTI

《结构与土木工程前沿（英文）》 2020年 第14卷 第1期   页码 138-146 doi: 10.1007/s11709-019-0585-8

摘要： Studying the piled raft behavior has been the subject of many types of research in the field of geotechnical engineering. Several studies have been conducted to understand the behavior of these types of foundations, which are often used for uniform loading on the raft and piles with the same length, while generally the transition load from the upper structure to the foundation is non-uniform and the choice of uniform length for piles in the above model will not be optimally economic and practical. The most common method in identifying the behavior of piled rafts is the use of theoretical relationships and software analyses. More precise identification of this type of foundation behavior can be very difficult due to several influential parameters and interaction of set behavior, and it will be done by doing time-consuming computer analyses or costly full-scale physical modeling. In the meantime, the technique of artificial neural networks can be used to achieve this goal with minimum time consumption, in which data from physical and numerical modeling can be used for network learning. One of the advantages of this method is the speed and simplicity of using it. In this paper, a model is presented based on multi-layer perceptron artificial neural network. In this model pile diameter, pile length, and pile spacing is considered as an input parameter that can be used to estimate maximum settlement, maximum differential settlement, and maximum raft moment. By this model, we can create an extensive domain of results for optimum system selection in the desired piled raft foundation. Results of neural network indicate its proper ability in identifying the piled raft behavior. The presented procedure provides an interesting solution and economically enhancing the design of the piled raft foundation system. This innovative design method reduces the time spent on software analyses.

关键词： innovative design     piled raft foundation     neural network     optimization    

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苏通大桥主塔深水基础的设计与施工

任回兴,欧阳效勇,贺茂生,杨红,孙克强

《中国工程科学》 2009年 第11卷 第3期   页码 38-43

摘要：

从建设条件、基础设计和施工等方面，介绍了苏通大桥主塔深水基础建设过程中在设计方面的部分考虑及施工过程中攻克深水、潮流、软基和通航等不利因素影响的一些方法，可供类似工程借鉴参考。

关键词： 苏通大桥     群桩基础     钢吊箱     冲刷防护    

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Linear and nonlinear elastic analysis of closely spaced strip foundations using Pasternak model

Priyanka GHOSH, S. RAJESH, J. SAI CHAND

《结构与土木工程前沿（英文）》 2017年 第11卷 第2期   页码 228-243 doi: 10.1007/s11709-016-0370-x

摘要： In this study, an attempt is made to determine the interaction effect of two closely spaced strip footings using Pasternak model. The study considers small strain problem and has been performed using linear as well as nonlinear elastic analysis to determine the interaction effect of two nearby strip footings. The hyperbolic stress-strain relationship has been considered for the nonlinear elastic analysis. The linear elastic analysis has been carried out by deriving the equations for the interference effect of the footings in the framework of Pasternak model equation; whereas, the nonlinear elastic analysis has been performed using the finite difference method to solve the second order nonlinear differential equation evolved from Pasternak model with proper boundary conditions. Results obtained from the linear and the nonlinear elastic analysis are presented in terms of non-dimensional interaction factors by varying different parameters like width of the foundation, load on the foundation and the depth of the rigid base. Results are suitably compared with the existing values in the literature.

关键词： bearing capacity     linear and non-linear elasticity     foundation     interaction effect     numerical modeling     Pasternak model    

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Foundations bearing capacity subjected to seepage by the kinematic approach of the limit analysis

Mehdi VEISKARAMI, Ghasem HABIBAGAHI

《结构与土木工程前沿（英文）》 2013年 第7卷 第4期   页码 446-455 doi: 10.1007/s11709-013-0227-5

摘要： An estimate of the ultimate load on foundations on soil layers subject to groundwater flow has been presented. The kinematic approach of the limit analysis was employed to find the upper-bound limit of the bearing capacity. Both smooth and rough base strip foundations were considered associated with different collapse patterns. Presence of the groundwater flow leads to a non-symmetric collapse pattern, i.e., a weak side and a strong side in two-sided collapse patterns, depending on the direction of the flow. It was found that the bearing capacity has a decreasing trend with increase in the groundwater flow gradient and hence, a reduction factor has been introduced to the third term in the bearing capacity equation as a function of the flow gradient.

关键词： foundation     bearing capacity     limit analysis     numerical computation     plasticity     seepage    

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Analysis of foundation sliding of an arch dam considering the hydromechanical behavior

Maria Luísa Braga FARINHA, José Vieira de LEMOS, Emanuel MARANHA DAS NEVES

《结构与土木工程前沿（英文）》 2012年 第6卷 第1期   页码 35-43 doi: 10.1007/s11709-012-0142-1

摘要： This paper presents the application of a methodology which can be used to assess arch dam foundation stability, using the discrete element method (DEM) and the code 3DEC. A global three-dimensional model of a dam foundation was developed, in which some discontinuities were simulated and both the grout and drainage curtains were represented. The model, calibrated taking into account recorded data, was used to carry out nonlinear mechanical analysis. The same model was employed to perform a hydraulic analysis, based on equivalent continuum concepts, which allowed the water pressure pattern within the foundation to be obtained. These water pressures were applied on discontinuities involved in the possible sliding mechanism along the dam/foundation interface, and the safety of the dam/foundation system was evaluated using a process of reduction of strength characteristics, with the aim of calculating the minimum safety factors that ensure stability. Results were compared with those obtained with the usual bi-linear uplift pressure distribution at the base of the dam, commonly used in concrete dam design. The relevance of carrying out hydraulic analysis in arch dam foundation failure studies is highlighted.

关键词： concrete dams     rock foundations     hydromechanical behavior     failure analysis    

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Digital image correlation-based structural state detection through deep learning

《结构与土木工程前沿（英文）》 2022年 第16卷 第1期   页码 45-56 doi: 10.1007/s11709-021-0777-x

摘要： This paper presents a new approach for automatical classification of structural state through deep learning. In this work, a Convolutional Neural Network (CNN) was designed to fuse both the feature extraction and classification blocks into an intelligent and compact learning system and detect the structural state of a steel frame; the input was a series of vibration signals, and the output was a structural state. The digital image correlation (DIC) technology was utilized to collect vibration information of an actual steel frame, and subsequently, the raw signals, without further pre-processing, were directly utilized as the CNN samples. The results show that CNN can achieve 99% classification accuracy for the research model. Besides, compared with the backpropagation neural network (BPNN), the CNN had an accuracy similar to that of the BPNN, but it only consumes 19% of the training time. The outputs of the convolution and pooling layers were visually displayed and discussed as well. It is demonstrated that: 1) the CNN can extract the structural state information from the vibration signals and classify them; 2) the detection and computational performance of the CNN for the incomplete data are better than that of the BPNN; 3) the CNN has better anti-noise ability.

关键词： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

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Development and deep-sea exploration of the Haidou-1

《工程管理前沿（英文）》   页码 546-549 doi: 10.1007/s42524-023-0260-6

摘要： Development and deep-sea exploration of the Haidou-1

关键词： hadal zone     autonomous and remotely-operated vehicle     integrated exploration operation     deep dive exceeding 10000 meters    

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Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

《结构与土木工程前沿（英文）》   页码 994-1010 doi: 10.1007/s11709-023-0942-5

摘要： The moving trajectory of the pipe-jacking machine (PJM), which primarily determines the end quality of jacked tunnels, must be controlled strictly during the entire jacking process. Developing prediction models to support drivers in performing rectifications in advance can effectively avoid considerable trajectory deviations from the designed jacking axis. Hence, a gated recurrent unit (GRU)-based deep learning framework is proposed herein to dynamically predict the moving trajectory of the PJM. In this framework, operational data are first extracted from a data acquisition system; subsequently, they are preprocessed and used to establish GRU-based multivariate multistep-ahead direct prediction models. To verify the performance of the proposed framework, a case study of a large pipe-jacking project in Shanghai and comparisons with other conventional models (i.e., long short-term memory (LSTM) network and recurrent neural network (RNN)) are conducted. In addition, the effects of the activation function and input time-step length on the prediction performance of the proposed framework are investigated and discussed. The results show that the proposed framework can dynamically and precisely predict the PJM moving trajectory during the pipe-jacking process, with a minimum mean absolute error and root mean squared error (RMSE) of 0.1904 and 0.5011 mm, respectively. The RMSE of the GRU-based models is lower than those of the LSTM- and RNN-based models by 21.46% and 46.40% at the maximum, respectively. The proposed framework is expected to provide an effective decision support for moving trajectory control and serve as a foundation for the application of deep learning in the automatic control of pipe jacking.

关键词： dynamic prediction     moving trajectory     pipe jacking     GRU     deep learning    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

《机械工程前沿（英文）》 2022年 第17卷 第2期 doi: 10.1007/s11465-022-0673-7

摘要： Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis. However, the tuning aiming at obtaining the well-trained CNN model is mainly manual search. Tuning requires considerable experiences on the knowledge on CNN training and fault diagnosis, and is always time consuming and labor intensive, making the automatic hyper parameter optimization (HPO) of CNN models essential. To solve this problem, this paper proposes a novel automatic CNN (ACNN) for fault diagnosis, which can automatically tune its three key hyper parameters, namely, learning rate, batch size, and L2-regulation. First, a new deep reinforcement learning (DRL) is developed, and it constructs an agent aiming at controlling these three hyper parameters along with the training of CNN models online. Second, a new structure of DRL is designed by combining deep deterministic policy gradient and long short-term memory, which takes the training loss of CNN models as its input and can output the adjustment on these three hyper parameters. Third, a new training method for ACNN is designed to enhance its stability. Two famous bearing datasets are selected to evaluate the performance of ACNN. It is compared with four commonly used HPO methods, namely, random search, Bayesian optimization, tree Parzen estimator, and sequential model-based algorithm configuration. ACNN is also compared with other published machine learning (ML) and deep learning (DL) methods. The results show that ACNN outperforms these HPO and ML/DL methods, validating its potential in fault diagnosis.

关键词： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

《信息与电子工程前沿（英文）》 2015年 第16卷 第11期   页码 930-939 doi: 10.1631/FITEE.1500125

摘要： Head pose estimation has been considered an important and challenging task in computer vision. In this paper we propose a novel method to estimate head pose based on a deep convolutional neural network (DCNN) for 2D face images. We design an effective and simple method to roughly crop the face from the input image, maintaining the individual-relative facial features ratio. The method can be used in various poses. Then two convolutional neural networks are set up to train the head pose classifier and then compared with each other. The simpler one has six layers. It performs well on seven yaw poses but is somewhat unsatisfactory when mixed in two pitch poses. The other has eight layers and more pixels in input layers. It has better performance on more poses and more training samples. Before training the network, two reasonable strategies including shift and zoom are executed to prepare training samples. Finally, feature extraction filters are optimized together with the weight of the classification component through training, to minimize the classification error. Our method has been evaluated on the CAS-PEAL-R1, CMU PIE, and CUBIC FacePix databases. It has better performance than state-of-the-art methods for head pose estimation.

关键词： Head pose estimation     Deep convolutional neural network     Multiclass classification    

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标题 作者 时间 类型 操作

Assessment of an alternative to deep foundations in compressible clays: the structural cell foundation

Sergio A. MARTÍNEZ-GALVÁN, Miguel P. ROMO

期刊论文

Detection of damage locations and damage steps in pile foundations using acoustic emissions with deep

Alipujiang JIERULA, Tae-Min OH, Shuhong WANG, Joon-Hyun LEE, Hyunwoo KIM, Jong-Won LEE

期刊论文

Influence of site conditions on seismic design parameters for foundations as determined via nonlinear

Muhammad Tariq A. CHAUDHARY

期刊论文

Model testing of tripod caisson foundations in silty clay subjected to eccentric lateral loads

期刊论文

Investigation of the seismic behavior of grouted sandy gravel foundations using shaking table tests

Tiancheng WANG; Yu LIANG; Xiaoyong ZHANG; Zhihuan RUAN; Guoxiong MEI

期刊论文

Innovative piled raft foundations design using artificial neural network

Meisam RABIEI, Asskar Janalizadeh CHOOBBASTI

期刊论文

苏通大桥主塔深水基础的设计与施工

任回兴,欧阳效勇,贺茂生,杨红,孙克强

期刊论文

Linear and nonlinear elastic analysis of closely spaced strip foundations using Pasternak model

Priyanka GHOSH, S. RAJESH, J. SAI CHAND

期刊论文

Foundations bearing capacity subjected to seepage by the kinematic approach of the limit analysis

Mehdi VEISKARAMI, Ghasem HABIBAGAHI

期刊论文

Analysis of foundation sliding of an arch dam considering the hydromechanical behavior

Maria Luísa Braga FARINHA, José Vieira de LEMOS, Emanuel MARANHA DAS NEVES

期刊论文

Digital image correlation-based structural state detection through deep learning

期刊论文

Development and deep-sea exploration of the Haidou-1

期刊论文

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

期刊论文

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

期刊论文

Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

期刊论文