Functionally graded material (FGM) illustrates a novel class of composites that consists of a graded pattern of material composition. FGM is engineered to have a continuously varying spatial composition profile. Current work focused on buckling analysis of beam made of stepwise linear and quadratic graded material in axial direction subjected to axial span-load with piecewise function and rested on shear layer based on classical beam theory. The various boundary and natural conditions including simply supported (S-S), pinned – clamped (P-C), axial hinge – pinned (AH-P), axial hinge – clamped (AH-C), pinned – shear hinge (P-SHH), pinned – shear force released (P-SHR), axial hinge – shear force released (AH-SHR) and axial hinge – shear hinge (AH-SHH) are considered. To the best of the author's knowledge, buckling behavior of this kind of Euler-Bernoulli beams has not been studied yet. The equilibrium differential equation is derived by minimizing total potential energy via variational calculus and solved analytically. The boundary conditions, natural conditions and deformation continuity at concentrated load insertion point are expressed in matrix form and nontrivial solution is employed to calculate first buckling loads and corresponding mode shapes. By increasing truncation order, the relative error reduction and convergence of solution are observed. Fast convergence and good compatibility with various conditions are advantages of the proposed method. A MATLAB code is provided in appendix to employ the numerical procedure based on proposed method.

In this paper, a cylindrical shell is immersed in a non-viscous fluid using first order shell theory of Sander. These equations are partial differential equations which are solved by approximate technique. Robust and efficient techniques are favored to get precise results. Employment of the Rayleigh-Ritz procedure gives birth to the shell frequency equation. Use of acoustic wave equation is done to incorporate the sound pressure produced in a fluid. HankelHanke's functions of second kind designate the fluid influence. Mathematically the integral form of the Lagrange energy functional is converted into a set of three partial differential equations. Throughout the computation, simply supported edge condition is used. Expressions for modal displacement functions, the three unknown functions are supposed in such way that the axial, circumferential and time variables are separated by the product method. Comparison is made for empty and fluid-filled cylindrical shell with circumferential wave number, length- and height-radius ratios, it is found that the fluid-filled frequencies are lower than that of without fluid. To generate the fundamental natural frequencies and for better accuracy and effectiveness, the computer software MATLAB is used.

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

The lightweight superstructure is beneficial for bridges in remote areas and emergency erection. In such weight-sensitive applications, the combination of fiber-reinforced polymer (FRP) as a material and box-beams as a structural system have enormous scope. This combination offers various advantages, but as a thin-walled structure, their designs are often governed by buckling criteria. FRP box-beams lose their stability either by flange or web buckling mode. In this paper, the web buckling behavior of simply supported FRP box-beam subjected to transverse load has been studied by modeling full box-beam to consider the effect of real state of stress (stress variation in length direction) and boundary conditions (rotational restraint at web-flange junction). A parametric study by varying the sectional geometry and fiber orientation is carried out by using ANSYS software. The accuracy of the FE models was ensured by verifying them against the available results provided in the literature. With the help of developed database the influential parameters (i.e., αs, βw, δw and γ) affecting the web bucklings are identified. Design trends have been developed which will be helpful to the designers in the preliminary stage. Finally, the importance of governing parameters and design trends are demonstrated through pedestrian bridge design.

The present study focuses on the application of artificial neural network (ANN) and Multiple linear Regression (MLR) analysis for developing a model to predict the unconfined compressive strength (UCS) and split tensile strength (STS) of the fiber reinforced clay stabilized with grass ash, fly ash and lime. Unconfined compressive strength and Split tensile strength are the nonlinear functions and becomes difficult for developing a predicting model. Artificial neural networks are the efficient tools for predicting models possessing non linearity and are used in the present study along with regression analysis for predicting both UCS and STS. The data required for the model was obtained by systematic experiments performed on only Kaolin clay, clay mixed with varying percentages of fly ash, grass ash, polypropylene fibers and lime as between 10-20%, 1-4%, 0-1.5% and 0-8% respectively. Further, the optimum values of the various stabilizing materials were determined from the experiments. The effect of stabilization is observed by performing compaction tests, split tensile tests and unconfined compression tests. ANN models are trained using the inputs and targets obtained from the experiments. Performance of ANN and Regression analysis is checked with statistical error of correlation coefficient (R) and both the methods predict the UCS and STS values quite well; but it is observed that ANN can predict both the values of UCS as well as STS simultaneously whereas MLR predicts the values separately. It is also observed that only STS values can be predicted efficiently by MLR.

Among the themes related to earthquake countermeasures at construction sites, those for tower cranes are particularly important. An accident involving the collapse of a crane during the construction of a skyscraper has serious consequences, such as human injury or death, enormous repair costs, and significant delays in construction. One of the causes of deadly tower crane collapses is the destruction of the site joints of the tower crane mast. This paper proposes a new design method by static elastoplastic finite element analysis using a supercomputer for the design of the end plate–type tensile bolted joints, which are generally applied to the site joints of a tower crane mast. This new design method not only enables highly accurate and reliable joint design but also allows for a design that considers construction conditions, such as the introduction of a pre-tension axial force on the bolts. By applying this new design method, the earthquake resistance of tower cranes will undoubtedly be improved.

In this paper is presented the minimum cost (optimal design) for reinforced concrete circular isolated footings based on an analytic model. This model considers a load and two moments in directions of the X and Y axes, and the pressure has a variation linear, these are the effects that act on the footing. The minimum cost (optimal design) and the Maple program are shown in Flowcharts. Two numerical experiments are shown to obtain the minimum cost design of the two materials that are used for a circular footing supporting an axial load and moments in two directions in accordance to the code of the ACI (American Concrete Institute), and it is compared against the current design (uniform pressure). Also, the same examples are developed through the normal procedure to verify the minimum cost (optimal design) presented in this document, i.e., the equations of moment, bending shear and punching shear are used to check the thickness, and after, the steel areas of the footing are obtained, and it is compared against the current design (uniform pressure). Results section show that the optimal design is more accurate and more economical than to any other model. Therefore, it is concluded that the optimized design model presented in this paper should be used to obtain the minimum cost design for the circular isolated footings.

This study aimed to investigate the effect of initial member length an imperfection in the load carrying capacity of double-layer domes space structures. First, for the member length imperfection of each member, a random number is generated from a normal distribution. Thereupon, the amount of the imperfection randomly varies from one member to another. Afterwards, based on the Push Down analysis, the collapse behavior and the ultimate capacity of the considered structure is determined using nonlinear analysis performed by the OpenSees software and this procedure is repeated numerous times by Monte Carlo simulation method. Finally, the reliability of structures is determined. The results show that the collapse behavior of double-layer domes space structures is highly sensitive to the random distribution of initial imperfections.

This paper presents a variant of the Harmony Search Algorithm (HS) and its application to discrete optimization. The main proposed modifications regarding original HS are related to stopping criterion and reinitialization of population, called Harmony Memory. In order to investigate the efficiency of the algorithm, it was applied for obtaining optimal sections of reinforced concrete columns subjected to uniaxial flexural compression. To minimize the cost of the section, the amount and diameters of the reinforcement bars and the dimensions of the columns cross sections were considered as design variables. The obtained results were compared to those generated by other optimization methods. Since, to the examples, Harmony Search reached the same results achieved by Simulated Annealing, some additional analysis are presented in order to compare these methods regarding success rate and number of iterations to reach the optimum.

This study presents algorithms for determining the fuzzy critical loads of planar steel frame structures with fixity factors of beam - column and column - base connections are modeled as triangular fuzzy numbers. The finite element method with linear elastic semi-rigid connection and Response Surface Method (RSM) in mathematical statistic are applied for problems with symmetric triangular fuzzy numbers. The <TEX>${\alpha}$</TEX> - level optimization using the Differential Evolution (DE) involving integrated finite element modeling is proposed to apply for problems with any triangular fuzzy numbers. The advantage of the proposed methodologies is demonstrated through some example problems relating to for the twenty - story, four - bay planar steel frames.