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- 저자 : Shojaee Saeed (검색결과 6 건)
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Behnam Daraei,Saeed Shojaee,Saleh Hamzehei-Javaran 국제구조공학회 2020 Steel and Composite Structures, An International J Vol.37 No.1
In this paper, free vibration finite element analysis of axially moving laminated composite beams subjected to axial tension is studied. It is assumed that the beam has a constant axial velocity and is subject to uniform axial tension. The analysis is based on higher-order theories that have been presented by Carrera Unified Formulation (CUF). In the CUF technique, the three dimensional (3D) displacement fields are expressed as the approximation of the arbitrary order of the displacement unknowns over the cross-section. This higher-order expansion is considered in equivalent single layer (ESL) model. The governing equations of motion are obtained via Hamilton’s principle. Finally, several numerical examples are presented and the effect of the ply-angle, travelling speed and axial tension on the natural frequencies and beam stability are demonstrated.
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Structural design with dynamic constraints using weighted chaos game optimization
Goodarzimehr Vahid,Talatahari Siamak,Shojaee Saeed,Hamzehei-Javaran Saleh,Sareh Pooya 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.6
The chaos game optimization (CGO) algorithm is a recently developed metaheuristic inspired by chaos theory and fractal configurations. In CGO, possible optimal solutions are defined as seeds and the searching process is performed using some simple equations. In this paper, weighted chaos game optimization (WCGO) is proposed and implemented to optimize engineering structures with dynamic constraints. In this method, an inertia weight coefficient based on the minimum and maximum values of the objective function is introduced to create a better balance between exploration and exploitation during the searching process. By applying the inertia weight coefficient to the seeds, their positions can be controlled accurately. To evaluate the performance of WCGO, a wide range of mathematical benchmark functions, as well as several structural design optimization problems under dynamic constraints, are computationally investigated using the new algorithm. In order to demonstrate the efficiency and robustness of WCGO, its results have been compared with those obtained by some conventional methods from the literature. Additionally, a Friedman rank test is conducted to perform a statistical study on the performance of the considered algorithms. The findings indicate that WCGO performs better than its rivals in solving these structural optimization problems with dynamic constraints.
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Fateme Manzouri,Mohammad Zare,Saeed Shojae 대한공간정보학회 2022 Spatial Information Research Vol.30 No.4
Soil salinity is one of the most important environmental issues, especially in arid and semi-arid regions, due to the influence of various parameters such as climate variables. Nowadays, the use of computational intelligence systems has expanded as a new strategy for soil studies based on satellite imagery. The purpose of this study is comparison of performance and efficiency of two multivariate regression methods as linear methods, and artificial neural network as a nonlinear method, to model and estimate salinity on topsoil in Jarghouyeh_e_Sofla plain. For this purpose, 61 soil samples were collected from 0 to 10 cm depth in study area and electrical conductivity values were extracted in laboratory. Two types of data were used: electrical conductivity of sampling points as independent variables and satellite data including salinity indices and Landsat Operational Land Imager sensor bands of Landsat8 as associated variables. The combination of input parameters was carried out in regression and neural network by using backward regression and principal component analysis, respectively. Therefore, data were divided into two series: train series (60 to 70%) and test series (20 to 30%). The results of assessment based on correlation coefficient and root mean square error in the neural network and regression was equal to 0.65, 27.74 and 29.9 and 31.85, respectively. It showed that the neural network has the highest precision in forecasting soil salinity.
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Moosaie Iman,Mostofinejad Davood,Shojaee Saeed 한국물리학회 2022 Current Applied Physics Vol.36 No.-
Although the classical continuum theory is advantageous in finding solutions to a wide range of engineering problems, it cannot describe some phenomena such as dispersion of acoustic waves, effects of surfaces and interfaces on the mechanical behavior of small-scale structures, and microstructure contribution in special materials. Owing to this fact, several enhanced continuum theories have evolved in the literature. However, the difficulty in determination of the length scale parameters that appear in the governing equations of such theories hampers their widespread use in practice. To date, except for a very limited number of materials, there is no known experimental procedure for the identification of these parameters. In this research, the internal length scales for an augmented continuum theory, i.e., Mindlin’s strain gradient theory, have been theoretically determined for some crystalline materials with cubic structure that are of engineering interest, using ab initio DFT. According to the values obtained for these parameters, it can be perceived that the strain gradient theory is a valuable tool for capturing the size effects at even the smallest scales comparable to the dimensions of a unit cell of a crystal lattice.
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Computational fluid dynamics studies of dry and wet pressure drops in structured packings
Seyyed Hossein Hosseini,Saeed Shojaee,Goodarz Ahmadi,Mortaza Zivdar 한국공업화학회 2012 Journal of Industrial and Engineering Chemistry Vol.18 No.4
Computational fluid dynamics was used to study the hydrodynamic of structured packings. The results showed that the k–v was a suitable turbulence model for analyzing the flows in structured packings. A simple method was proposed for evaluating the liquid holdup based on the Iliuta and Larachi (2001)model [25], the calculated liquid film thickness in 2D framework, and the empirical correlation of Brito et al. (1994) [26]. The presented method can be used for estimating the wet pressure drop in 3D structured packings for loading region with good accuracy as well as computational economy. The process of liquid film formation was also discussed.
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Analysis of flow through dam foundation by FEM and ANN models Case study: Shahid Abbaspour Dam
Shahrbanouzadeh, Mehrdad,Barani, Gholam Abbas,Shojaee, Saeed Techno-Press 2015 Geomechanics & engineering Vol.9 No.4
Three-dimensional simulation of flow through dam foundation is performed using finite element (Seep3D model) and artificial neural network (ANN) models. The governing and discretized equation for seepage is obtained using the Galerkin method in heterogeneous and anisotropic porous media. The ANN is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning, using the water level elevations of the upstream and downstream of the dam, as input variables and the piezometric heads as the target outputs. The obtained results are compared with the piezometric data of Shahid Abbaspour's Dam. Both calculated data show a good agreement with available measurements that demonstrate the effectiveness and accuracy of purposed methods.
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