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Showing 14 results for Shojaee

S. Shojaee, M. Mohammadian,
Volume 1, Issue 1 (3-2011)
Abstract

This paper proposes an effective algorithm based on the level set method (LSM) to solve shape and topology optimization problems. Since the conventional LSM has several limitations, a binary level set method (BLSM) is used instead. In the BLSM, the level set function can only take 1 and -1 values at convergence. Thus, it is related to phase-field methods. We don’t need to solve the Hamilton-Jacobi equation, so it is free of the CFL condition and the reinitialization scheme. This favorable properties lead to a great time advantage in this method. In this paper, the BLSM is implemented with the additive operator splitting (AOS) scheme and several numerical issues of the implementation are discussed. The proposed scheme is much more efficient than the conventional level set method. Several 2D examples are presented which demonstrate the effectiveness and robustness of the proposed method.
S. Shojaee, S. Hasheminasab,
Volume 1, Issue 2 (6-2011)
Abstract

Although Genetic algorithm (GA), Ant colony (AC) and Particle swarm optimization algorithm (PSO) have already been extended to various types of engineering problems, the effects of initial sampling beside constraints in the efficiency of algorithms, is still an interesting field. In this paper we show that, initial sampling with a special series of constraints play an important role in the convergence and robustness of a metaheuristic algorithm. Random initial sampling, Latin Hypercube Design, Sobol sequence, Hammersley and Halton sequences are employed for approximating initial design. Comparative studies demonstrate that well distributed initial sampling speeds up the convergence to near optimal design and reduce the required computational cost of purely random sampling methodologies. In addition different penalty functions that define the Augmented Lagrangian methods considered in this paper to improve the algorithms. Some examples presented to show these applications.
S. Shojaee, N. Valizadeh , M. Arjomand,
Volume 1, Issue 4 (12-2011)
Abstract

One primary problem in shape optimization of structures is making a robust link between design model (geometric description) and analysis model. This paper investigates the potential of Isogeometric Analysis (IGA) for solving this problem. The generic framework of shape optimization of structures is presented based on Isogeometric analysis. By discretization of domain via NURBS functions, the analysis model will precisely demonstrate the geometry of structure. In this study Particle Swarm Optimization (PSO) is used for Isogeometric shape optimization. The option of selecting the position and weight of control points as design variables, needless to sensitivity analysis relationships, is the superiority of the proposed method over gradient-based methods. The other advantages of this method are its straightforward implementation
S. Shojaee, M. Mohamadianb , N. Valizadeh,
Volume 2, Issue 1 (3-2012)
Abstract

In the present paper, an approach is proposed for structural topology optimization based on combination of Radial Basis Function (RBF) Level Set Method (LSM) with Isogeometric Analysis (IGA). The corresponding combined algorithm is detailed. First, in this approach, the discrete problem is formulated in Isogeometric Analysis framework. The objective function based on compliance of particular locations of materials in the structure is used and find the optimal distribution of material in the domain to minimize the compliance of the system under a volume constraint. The refinement is employed for construction of the physical mesh to be consistent with the mesh is used for level set function. Then a parameterized level set method with radial basis functions (RBFs) is used for structural topology optimization. Finally, several numerical examples are provided to confirm the validity of the method.
S. Shojaee, E. Izadpenah, A. Haeri,
Volume 2, Issue 2 (6-2012)
Abstract

NURBS-based isogeometric analysis (IGA) has currently been applied as a new numerical method in a considerable range of engineering problems. Due to non-interpolatory characteristic of NURBS basis functions, the properties of Kronecker Delta are not satisfied in IGA, and as a consequence, the imposition of essential boundary condition needs special treatment. The main contribution of this study is to use the well-known Lagrange multiplier method to impose essential boundary conditions for improving the accuracy of the isogeometric solution. Unlike the direct and transformation methods which are based on separation of control points, this method is capable of modeling incomplete Dirichlet boundaries. The solution accuracy and convergence rates of proposed method are compared with direct and transformation methods through various numerical examples.
S. Shojaee, M. Arjomand, M. Khatibinia,
Volume 3, Issue 1 (3-2013)
Abstract

An efficient method for size and layout optimization of the truss structures is presented in this paper. In order to this, an efficient method by combining an improved discrete particle swarm optimization (IDPSO) and method of moving asymptotes (MMA) is proposed. In the hybrid of IDPSO and MMA, the nodal coordinates defining the layout of the structure are optimized with MMA, and afterwards the results of MMA are used in IDPSO to optimize the cross-section areas. The results show that the hybrid of IDPSO and MMA can effectively accelerate the convergence rate and can quickly reach the optimum design.
H. Fattahi, M. A. Ebrahimi Farsangi, S. Shojaee, K. Nekooei , H. Mansouri,
Volume 3, Issue 2 (6-2013)
Abstract

An excavation damage zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. This paper presents an approach to build a model for the identification and classification of the EDZ. The Support vector machine (SVM) is a new machine learning method based on statistical learning theory, which can solve the classification problem with small sampling, non-linearity and high dimension. However, the practicability of the SVM is influenced by the difficulty of selecting appropriate SVM parameters. In this study, the proposed hybrid Harmony search (HS) with the SVM was applied for identification and classification of damaged zone, in which HS was used to determine the optimized free parameters of the SVM. For identification and classification of the EDZ, based upon the modulus of the deformation modulus and using the hybrid of HS with the SVM a model for the identification and classification of the EDZ was built. To illustrate the capability of the HS-SVM model defined, field data from a test gallery of the Gotvand dam, Iran were used. The results obtained indicate that the HS-SVM model can be used successfully for identification and classification of damaged zone around underground spaces.
H. Fattahi, S. Shojaee, M A. Ebrahimi Farsangi, H. Mansouri,
Volume 3, Issue 3 (9-2013)
Abstract

The excavation damaged zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. In this paper, a methodology was examined for computing the creation probability of damaged zone by Latin hypercube sampling based on a feed-forward artificial neural network (ANN) optimized by hybrid particle swarm optimization and genetic algorithm (HPSOGA). The HPSOGA was carried out to decide the initial weights of the neural network. A case study in a test gallery of the Gotvand dam, Iran was carried out and creation probabilities of 0.191 for highly damaged zone (HDZ) and 0.502 for EDZ were obtained.
H. Fattahi, S. Shojaee , M. A Ebrahimi Farsangi,
Volume 3, Issue 4 (10-2013)
Abstract

The development of an excavation damaged zone (EDZ) around an underground excavation can change the physical, mechanical and hydraulic behaviors of the rock mass near an underground space. This might result in endangering safety, achievement of costs and excavation planed. This paper presents an approach to build a prediction model for the assessment of EDZ, based upon rock mass characteristics changed. Rock engineering systems (RES) was used as an appropriate method for choosing the best parameter that expresses the occurrence of EDZ. Modulus of deformation with the highest weight in the system was selected as the most effective changed parameter. The adaptive network-based fuzzy inference system (ANFIS) with modulus of deformation as input was used to build a prediction model for the assessment of EDZ. Three ANFIS models were implemented, grid partitioning (GP), subtractive clustering method (SCM) and fuzzy c-means clustering method (FCM). A comparison was made between these three models and the results show the superiority of the ANFIS-SCM model. Furthermore, a case study in a test gallery of the Gotvand dam, Iran was carried out to illustrate the capability of the ANFIS model defined.
F. Sarvi , S. Shojaee , P. Torkzadeh,
Volume 4, Issue 2 (6-2014)
Abstract

This paper presents an efficient method for updating the structural finite element model. Model updating is performed through minimizing the difference of recorded acceleration of real damaged structure and hypothetical damaged structure, by updating physical parameters in each phase using iterative process of Levenberg-Marquardt algorithm. This algorithm is based on sensitivity analysis and provides a linear solution for nonlinear damage detection problem. The presented method is capable of detecting the exact location and ratio of structural damage in the presence of noise or incomplete data.
S. Shojaee, A. Mohaghegh, A. Haeri,
Volume 5, Issue 4 (7-2015)
Abstract

In this paper the piecewise level set method is combined with phase field method to solve the shape and topology optimization problem. First, the optimization problem is formed based on piecewise constant level set method then is updated using the energy term of phase field equations. The resulting diffusion equation which updates the level set function and optimization problem is solved through finite element method. The proposed method enhances the convergence rate and solution efficiency. Various two-dimensional examples are solved to verify the performance of proposed method.
S. Alimollaie, S. Shojaee,
Volume 7, Issue 4 (10-2017)
Abstract

Optimization techniques can be efficiently utilized to achieve an optimal shape for arch dams. This optimal design can consider the conditions of the economy and safety simultaneously. The main aim is to present an applicable and practical model and suggest an algorithm for optimization of concrete arch dams to enhance their seismic performance. To achieve this purpose, a preliminary optimization is accomplished using PSO procedure in the first stage. Capabilities of Ansys Parametric Design Language (APDL) are applied for modeling the Dam-Foundation-Reservoir system. In the second stage with training the neural network, Group Method of Data Handling (GMDH) and replacement of Ansys analyst, optimal results have been achieved with the lowest error and less number of iteration respectively. Then a real world double-arch dam is presented to demonstrate the effectiveness and practicality of the PSO-GMDH. The numerical results reveal that the proposed method called PSO-GMDH provides faster rate and high searching accuracy to achieve the optimal shape of arch concrete dams and the modification and optimization of shape have a quite important role in increasing the safety against dynamic design loads.


I. Manafi, S. Shojaee,
Volume 8, Issue 2 (8-2018)
Abstract

Due to the favorable performance of structural topology optimization to create a proper understanding in the early stages of design, this issue is taken into consideration from the standpoint of research or industrial application in recent decades. Over the last three decades, several methods have been proposed for topology optimization. One of the methods that has been effectively used in structural topology optimization is level set method. Since in the level set method, the boundary of design domain is displayed implicitly, this method can easily modify the shape and topology of structure. Topological design with multiple constraints is of great importance in practical engineering design problems. Most recent topology optimization methods have used only the volume constraint; so in this paper, in addition to current volume constraint, the level set method combines with other constraints such as displacement and frequency. To demonstrate the effectiveness of the proposed level set approach, several examples are presented.
P. Darvishi , S. Shojaee,
Volume 8, Issue 4 (10-2018)
Abstract

In recent years, the optimization of truss structures has been considered due to their several applications and their simple structure and rapid analysis. DNA computing algorithm is a non-gradient-based method derived from numerical modeling of DNA-based computing performance by new computers with DNA memory known as molecular computers. DNA computing algorithm works based on collective intelligence. It works with doing random search in the search space and creating the initial random population by modeling DNA-based computing operators and applies the operators derived from genetic algorithm to achieve the optimum solution of the objective function. Generalized Convex Approximation (GCA) method is a gradient-based method that with approximation of the main function and starting from a point, finds the optimum solution using information about functions and their gradient. In this research, in order to minimize the weight of truss, the cross-section areas of the elements as discrete variables are optimized by DNA computing algorithm, and the coordinates of truss nodes as continuous variables are optimized by Generalized Convex Approximation (GCA) method. Therefore, to simultaneously optimize the size and geometry of truss structures, these two methods are used in combination. The results of numerical examples show the proper functioning of this process.

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