• Wind and Structures
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• v.34 no.2
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• pp.199-213
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• 2022

The current study investigates the dynamic effects in the tornado-structure response of an aeroelastic self-supported lattice transmission tower model tested under laboratory simulated tornado-like vortices. The aeroelastic model is designed for a geometric scale of 1:65 and tested under scaled down tornadoes in the Wind Engineering, Energy and Environment (WindEEE) Research Institute. The simulated tornadoes have a similar length scale of 1:65 compared to the full-scale. An extensive experimental parametric study is conducted by offsetting the stationary tornado center with respect to the aeroelastic model. Such aeroelastic testing of a transmission tower under laboratory tornadoes is not reported in the literature. A multiaxial load cell is mounted underneath the base plate to measure the base shear forces and overturning moments applied to the model in three perpendicular directions. A three-axis accelerometer is mounted at the level of the second cross-arm to measure response accelerations to evaluate the natural frequencies through a free-vibration test. Radial, tangential, and axial velocity components of the tornado wind field are measured using cobra probes. Sensitivity analyses are conducted to assess the variation of the structural dynamic response associated with the location of the tornado relative to the lattice transmission tower. Three different layouts representing the change in the orientation of the tower model relative to the components of the tornado-induced loads are considered. The structural responses of the aeroelastic model in terms of base shear forces, overturning moments, and lateral accelerations are measured. The results are utilized to understand the dynamic response of self-supported transmission towers to the tornado-induced loads.

• Advances in nano research
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• v.5 no.1
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• pp.35-47
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• 2017

This paper deals with free vibration analysis of nanosize rings and arches with consideration of surface effects. The Gurtin-Murdach model is employed for incorporating the surface effect parameters including surface density, while the small scale effect is taken into consideration based on nonlocal elasticity theory of Eringen. An analytical Navier solution is presented to solve the governing equations of motions. Comparison between results of the present work and those available in the literature shows the accuracy of this method. It is explicitly shown that the vibration characteristics of the curved nanosize beams are significantly influenced by the surface density effects. Moreover, it is shown that by increasing the nonlocal parameter, the influence of surface density reduce to zero, and the natural frequency reaches its classical value. Numerical results are presented to serve as benchmarks for future analyses of nanosize rings and arches.

• Steel and Composite Structures
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• v.26 no.5
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• pp.607-620
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• 2018

Vibration analysis of deep curved FG nano-beam has been carried out based on modified couple stress theory. Material properties of curved Timoshenko beam are assumed to be functionally graded in radial direction. Governing equations of motion and related boundary conditions have been obtained via Hamilton's principle. In a parametric study, influence of length scale parameter, aspect ratio, gradient index, opening angle, mode number and interactive influences of these parameters on natural frequency of the beam, have been investigated. It was found that, considering geometrical deepness term leads to an increase in sensitivity of natural frequency about variation of aforementioned parameters.

• Steel and Composite Structures
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• v.49 no.3
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• pp.293-306
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• 2023

This article focuses on the study of the buckling behavior of two-dimensional functionally graded (2D-FG) nanosize tubes, including porosity, based on the first shear deformation and higher-order theory of the tube. The nano-scale tube is simulated using the nonlocal gradient strain theory, and the general equations and boundary conditions are derived using Hamilton's principle for the Zhang-Fu's tube model (as a higher-order theory) and Timoshenko beam theory. Finally, the derived equations are solved using a numerical method for both simply-supported and clamped boundary conditions. A parametric study is performed to investigate the effects of different parameters, such as axial and radial FG power indices, porosity parameter, and nonlocal gradient strain parameters, on the buckling behavior of the bi-dimensional functionally graded porous tube. Keywords: Nonlocal strain gradient theory; buckling; Zhang-Fu's tube model; Timoshenko theory; Two-dimensional functionally graded materials; Nanotubes; Higher-order theory.

• Steel and Composite Structures
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• v.27 no.2
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• pp.201-216
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• 2018

In this paper, three-dimensional (3D) elasticity theory in conjunction with nonlocal strain gradient theory (NSGT) is developed for mechanical analysis of anisotropic nanoparticles. The present model incorporates two scale coefficients to examine the mechanical characteristics much accurately. All the elastic constants are considered and assumed to be the functions of (r, ${\theta}$, ${\varphi}$), so all kind of anisotropic structures can be modeled. Moreover, all types of functionally graded spherical structures can be investigated. To justify our model, our results for the radial vibration of spherical nanoparticles are compared with experimental results available in the literature and great agreement is achieved. Next, several examples of the radial vibration and wave propagation in spherical nanoparticles including nonlocal strain gradient parameters are presented for more than 10 different anisotropic nanoparticles. From the best knowledge of authors, it is the first time that 3D elasticity theory and NSGT are used together with no approximation to derive the governing equations in the spherical coordinate. Moreover, up to now, the NSGT has not been used for spherical anisotropic nanoparticles. It is also the first time that all the 36 elastic constants as functions of (r, ${\theta}$, ${\varphi}$) are considered for anisotropic and functionally graded nanostructures including size effects. According to the lack of any common approximations in the displacement field or in elastic constant, present theory can be assumed as a benchmark for future works.

• Journal of Power System Engineering
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• v.16 no.4
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• pp.51-59
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• 2012

The computational flow analysis using LES technique was carried out to investigate the flow characteristics of a sirocco fan under the maximum flowrate condition. The commercial SC/Tetra software was used for this unsteady and three-dimensional numerical analysis. In consequence, because a flow is unstable within the range of about 50% of a housing depth from a bellmouth around the cutoff region, the passing flow through the blade cascade occurred on the X-Y plane is a slow or a reverse with approaching to the housing inlet. Also, the secondary flow shows on the radial plane of a housing, and its vortex center exists within about 33% of a housing depth from a bellmouth except the cutoff region. Moreover, the flow occurring on the exit plane of a sirocco fan shows a complex secondary flow.

• Journal of Korea Port Economic Association
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• v.31 no.1
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• pp.37-49
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• 2015

According to outstanding maritime economists from domestic and overseas, shipping lines or ships' enlargement reduce fixed costs, and assist realization of scale of economy of shipping. On the contrary, recent Korean liquidity crisis on the shipping lines (SL) has been focused on the leading companies such as Hanjin Shipping (HJS), Korealines, and STX Pan Ocean. In this respect, this study aims to review Korean SLs' strategies and suggest the optimal solution between the specialization and enlargement. For these purposes, this research adopts slack based measure data envelopment analysis (SBM-DEA) model as a research methodology. As for decision making units (DMUs), SLs which have increased the vessel numbers and belonged to top tier group in year 2013, are selected. The results are comprised with two aspects. Firstly, HJS, KMTC, Korea LNG Trading (KLT), EUKOR, and Sinokor Tanker show the most efficient in regard to constant return to scale (CRS) model. Secondly, HJS, KMTC, KLT, Daerim, Chungang, Sinnokor Tanker, and EUKOR are the most efficient companies in terms of variable return to scale (VRS) model. Lastly, these results could be affected to the management philosophy and can answer the following question. Which is the most optimized SL?s management decision making, enlargement or specialization?

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4274-4281
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• 2023

Blanket is of vital importance for engineering application of the fusion reactor. Nuclear heat deposition in materials is the main heat source in blanket structure. In this paper, the three-dimensional method for thermal-hydraulics/neutronics coupling analysis is developed and applied for the full-scale module of the helium-cooled ceramic breeder tritium breeding blanket (HCCB TBB) designed for China Fusion Engineering Test Reactor (CFETR). The explicit coupling scheme is used to support data transfer for coupling analysis based on cell-to-cell mapping method. The coupling algorithm is realized by the user-defined function compiled in Fluent. The three-dimensional model is established, and then the coupling analysis is performed using the paralleled Coupling Analysis of Thermal-hydraulics and Neutronics Interface Code (CATNIC). The results reveal the relatively small influence of the coupling analysis compared to the traditional method using the radial fitting function of internal heat source. However, the coupling analysis method is quite important considering the nonuniform distribution of the neutron wall loading (NWL) along the poloidal direction. Finally, the structure optimization of the blanket is carried out using the coupling method to satisfy the thermal requirement of all materials. The nonlinear effect between thermal-hydraulics and neutronics is found during the blanket structure optimization, and the tritium production performance is slightly reduced after optimization. Such an adverse effect should be thoroughly evaluated in the future work.

• Geomechanics and Engineering
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• v.7 no.1
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• pp.105-131
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• 2014

In this paper, the effects of variability of smear zone characteristics induced by installation of prefabricated vertical drains on the preloading design are investigated employing analytical and numerical approaches. Conventional radial consolidation theory has been adopted to conduct analytical parametric studies considering variations of smear zone permeability and extent. FLAC 2D finite difference software has been employed to conduct the numerical simulations. The finite difference analyses have been verified using three case studies including two embankments and a large-scale laboratory consolidometer with a central geosynthetic vertical drain. A comprehensive numerical parametric study is conducted to investigate the influence of smear zone permeability and extent on the model predictions. Furthermore, the construction of the trial embankment is recommended as a reliable solution to estimate accurate smear zone properties and minimise the post construction settlement. A back-calculation procedure is employed to determine the minimum required waiting time after construction of the trial embankment to predict the smear zone characteristics precisely. Results of this study indicate that the accurate smear zone permeability and extent can be back-calculated when 30% degree of consolidation is obtained after construction of the trial embankment.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.