• Title/Summary/Keyword: construction mechanics

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Real-time modeling prediction for excavation behavior

  • Ni, Li-Feng;Li, Ai-Qun;Liu, Fu-Yi;Yin, Honore;Wu, J.R.
    • Structural Engineering and Mechanics
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    • v.16 no.6
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    • pp.643-654
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    • 2003
  • Two real-time modeling prediction (RMP) schemes are presented in this paper for analyzing the behavior of deep excavations during construction. The first RMP scheme is developed from the traditional AR(p) model. The second is based on the simplified Elman-style recurrent neural networks. An on-line learning algorithm is introduced to describe the dynamic behavior of deep excavations. As a case study, in-situ measurements of an excavation were recorded and the measured data were used to verify the reliability of the two schemes. They proved to be both effective and convenient for predicting the behavior of deep excavations during construction. It is shown through the case study that the RMP scheme based on the neural network is more accurate than that based on the traditional AR(p) model.

Concrete arch bridges built by lattice cantilevers

  • Granata, Michele Fabio;Margiotta, Piercarlo;Recupero, Antonino;Arici, Marcello
    • Structural Engineering and Mechanics
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    • v.45 no.5
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    • pp.703-722
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    • 2013
  • In this paper a study about concrete arch bridges built by lattice cantilevers is presented. Lattice cantilevers are partial structures composed of deck, arch, piers and provisional steel diagonals, organized as reticular cantilever girders, in order to build arch bridges without the use of centrings, supports or temporary towers. Characteristics of this construction methodology with its variants are explained together with their implications in the erection sequence. Partial elastic scheme method is implemented in order to find initial forces of temporary cables and a forward analysis is carried out to follow the actual sequence of construction, by extending a procedure already applied to concrete cable-stayed bridges and to arches built by the classical suspended cantilever method. A numerical application on a case-study of a concrete arch bridge is performed together with a comparison between different methodologies followed for its construction sequence. Differences between erection by lattice cantilevers and cable-stayed cantilevers, are discussed. Results can be useful for designers in conceptual design of concrete arch bridges.

A parametric study of optimum tall piers for railway bridge viaducts

  • Martinez-Martin, Francisco J.;Gonzalez-Vidosa, Fernando;Hospitaler, Antonio;Yepes, Victor
    • Structural Engineering and Mechanics
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    • v.45 no.6
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    • pp.723-740
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    • 2013
  • This paper presents a parametric study of reinforced concrete bridge tall piers with hollow, rectangular sections. Such piers are typically used in railway construction of prestressed concrete viaducts. Twenty one different piers have been studied with seven column heights of 40, 50, 60, 70, 80, 90 and 100 m and three types of 10-span continuous viaducts, whose main span lengths are 40, 50 and 60 m. The piers studied are intermediate columns placed in the middle of the viaducts. The total number of optimization design variables varies from 139 for piers with column height of 40 m to 307 for piers with column height of 100 m. Further, the results presented are of much value for the preliminary design of the piers of prestressed concrete viaducts of high speed railway lines.

Nonlinear time-varying analysis algorithms for modeling the behavior of complex rigid long-span steel structures during construction processes

  • Tian, Li-Min;Hao, Ji-Ping
    • Steel and Composite Structures
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    • v.18 no.5
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    • pp.1197-1214
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    • 2015
  • There is a great difference in mechanical behavior between design model one-time loading and step-by-step construction process. This paper presents practical computational methods for simulating the structural behavior of long-span rigid steel structures during construction processes. It introduces the positioning principle of node rectification for installation which is especially suitable for rigid long-span steel structures. Novel improved nonlinear analytical methods, known as element birth and death of node rectification, are introduced based on several calculating methods, as well as a forward iteration of node rectification method. These methods proposed in this paper can solve the problem of element's 'floating' and can be easily incorporated in commercial finite element software. These proposed methods were eventually implemented in the computer simulation and analysis of the main stadium for the Universiade Sports Center during the construction process. The optimum construction scheme of the structure is determined by the improved algorithm and the computational results matched well with the measured values in the project, thus indicating that the novel nonlinear time-varying analysis approach is effective construction simulation of complex rigid long-span steel structures and provides useful reference for future design and construction.

Application of Artificial Neural Network method for deformation analysis of shallow NATM tunnel due to excavation

  • Lee, Jae-Ho;Akutagawa, Shnichi;Moon, Hong-Duk;Han, Heui-Soo;Yoo, Ji-Hyeung;Kim, Kwang-Yeun
    • Proceedings of the Korean Society for Rock Mechanics Conference
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    • 2008.10a
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    • pp.43-51
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    • 2008
  • Currently an increasing number of urban tunnels with small overburden are excavated according to the principle of the New Austrian Tunneling Method (NATM). For rational management of tunnels from planning to construction and maintenance stages, prediction, control and monitoring of displacements of and around the tunnel have to be performed with high accuracy. Computational method tools, such as finite element method, have been and are indispensable tool for tunnel engineers for many years. It is, however, a commonly acknowledged fact that determination of input parameters, especially material properties exhibiting nonlinear stress-strain relationship, is not an easy task even for an experienced engineer. Use and application of the acquired tunnel information is important for prediction accuracy and improvement of tunnel behavior on construction. Artificial Neural Network (ANN) model is a form of artificial intelligence that attempts to mimic behavior of human brain and nervous system. The main objective of this paper is to perform the deformation analysis in NATM tunnel by means of numerical simulation and artificial neural network (ANN) with field database. Developed ANN model can achieve a high level of prediction accuracy.

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Use of design optimization techniques in solving typical structural engineering related design optimization problems

  • Fedorik, Filip;Kala, Jiri;Haapala, Antti;Malaska, Mikko
    • Structural Engineering and Mechanics
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    • v.55 no.6
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    • pp.1121-1137
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    • 2015
  • High powered computers and engineering computer systems allow designers to routinely simulate complex physical phenomena. The presented work deals with the analysis of two finite element method optimization techniques (First Order Method-FOM and Subproblem Approximation Method-SAM) implemented in the individual Design Optimization module in the Ansys software to analyze the behavior of real problems. A design optimization is a difficult mathematical process, intended to find the minimum or maximum of an objective function, which is mostly based on iterative procedure. Using optimization techniques in engineering designs requires detailed knowledge of the analyzed problem but also an ability to select the appropriate optimization method. The methods embedded in advanced computer software are based on different optimization techniques and their efficiency is significantly influenced by the specific character of a problem. The efficiency, robustness and accuracy of the methods are studied through strictly convex two-dimensional optimization problem, which is represented by volume minimization of two bars' plane frame structure subjected to maximal vertical displacement limit. Advantages and disadvantages of the methods are described and some practical tips provided which could be beneficial in any efficient engineering design by using an optimization method.

Bending analysis of a micro sandwich skew plate using extended Kantorovich method based on Eshelby-Mori-Tanaka approach

  • Rajabi, Javad;Mohammadimehr, Mehdi
    • Computers and Concrete
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    • v.23 no.5
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    • pp.361-376
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    • 2019
  • In this research, bending analysis of a micro sandwich skew plate with isotropic core and piezoelectric composite face sheets reinforced by carbon nanotube on the elastic foundations are studied. The classical plate theory (CPT) are used to model micro sandwich skew plate and to apply size dependent effects based on modified strain gradient theory. Eshelby-Mori-Tanaka approach is considered for the effective mechanical properties of the nanocomposite face sheets. The governing equations of equilibrium are derived using minimum principle of total potential energy and then solved by extended Kantorovich method (EKM). The effects of width to thickness ratio and length to width of the sandwich plate, core-to-face sheet thickness ratio, the material length scale parameters, volume fraction of CNT, the angle of skew plate, different boundary conditions and types of cores on the deflection of micro sandwich skew plate are investigated. One of the most important results is the reduction of the deflection by increasing the angle of the micro sandwich skew plate and decreasing the deflection by decreasing the thickness of the structural core. The results of this research can be used in modern construction in the form of reinforced slabs or stiffened plates and also used in construction of bridges, the wing of airplane.

Assessment of wall convergence for tunnels using machine learning techniques

  • Mahmoodzadeh, Arsalan;Nejati, Hamid Reza;Mohammadi, Mokhtar;Ibrahim, Hawkar Hashim;Mohammed, Adil Hussein;Rashidi, Shima
    • Geomechanics and Engineering
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    • v.31 no.3
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    • pp.265-279
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    • 2022
  • Tunnel convergence prediction is essential for the safe construction and design of tunnels. This study proposes five machine learning models of deep neural network (DNN), K-nearest neighbors (KNN), Gaussian process regression (GPR), support vector regression (SVR), and decision trees (DT) to predict the convergence phenomenon during or shortly after the excavation of tunnels. In this respect, a database including 650 datasets (440 for training, 110 for validation, and 100 for test) was gathered from the previously constructed tunnels. In the database, 12 effective parameters on the tunnel convergence and a target of tunnel wall convergence were considered. Both 5-fold and hold-out cross validation methods were used to analyze the predicted outcomes in the ML models. Finally, the DNN method was proposed as the most robust model. Also, to assess each parameter's contribution to the prediction problem, the backward selection method was used. The results showed that the highest and lowest impact parameters for tunnel convergence are tunnel depth and tunnel width, respectively.

Fracture Mechanics Analysis of a Crack in the Weld using the J-integral (J-적분을 이용한 용접접합부 균열의 파괴 역학적 해석)

  • Chang, Kyong Ho;Lee, Chin Hyung
    • Journal of Korean Society of Steel Construction
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    • v.17 no.2 s.75
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    • pp.243-251
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    • 2005
  • The fracture mechanics analysis of a crack in a weld must consider residual stress generated during welding. The standard definition of the J-integral requires a path dependent value in the presence of a residual stress field. Therefore, it is necessary to develop a path independent J-integral definition for a crack in a residual stress field. This paper addresses the modification of the Rice-J-integral to produce a path- independent J-integral when residual stresses and external forces are present. The residual stress problem is treated as an initial strain problem and the J-integral proposed for this type of problems is used. A program which can evaluate the J-integral for a crack in a weld is developed using the proposed J-integral definition. The situation when only residual stress is present is examined as is the case when mechanical stresses are applied in conjunction with a residual stress.

A Copula method for modeling the intensity characteristic of geotechnical strata of roof based on small sample test data

  • Jiazeng Cao;Tao Wang;Mao Sheng;Yingying Huang;Guoqing Zhou
    • Geomechanics and Engineering
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    • v.36 no.6
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    • pp.601-618
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    • 2024
  • The joint probability distribution of uncertain geomechanical parameters of geotechnical strata is a crucial aspect in constructing the reliability functional function for roof structures. However, due to the limited number of on-site exploration and test data samples, it is challenging to conduct a scientifically reliable analysis of roof geotechnical strata. This study proposes a Copula method based on small sample exploration and test data to construct the intensity characteristics of roof geotechnical strata. Firstly, the theory of multidimensional copula is systematically introduced, especially the construction of four-dimensional Gaussian copula. Secondly, data from measurements of 176 groups of geomechanical parameters of roof geotechnical strata in 31 coal mines in China are collected. The goodness of fit and simulation error of the four-dimensional Gaussian Copula constructed using the Pearson method, Kendall method, and Spearman methods are analyzed. Finally, the fitting effects of positive and negative correlation coefficients under different copula functions are discussed respectively. The results demonstrate that the established multidimensional Gaussian Copula joint distribution model can scientifically represent the uncertainty of geomechanical parameters in roof geotechnical strata. It provides an important theoretical basis for the study of reliability functional functions for roof structures. Different construction methods for multidimensional Gaussian Copula yield varying simulation effects. The Kendall method exhibits the best fit in constructing correlations of geotechnical parameters. For the bivariate Copula fitting ability of uncertain parameters in roof geotechnical strata, when the correlation is strong, Gaussian Copula demonstrates the best fit, and other Copula functions also show remarkable fitting ability in the region of fixed correlation parameters. The research results can offer valuable reference for the stability analysis of roof geotechnical engineering.