• Advances in nano research
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• v.13 no.2
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• pp.147-164
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• 2022

This article investigates the longitudinal vibration of a nanorod embedded in viscoelastic medium according to the nonlocal strain gradient theory. Viscoelastic medium is considered based on Kelvin-Voigt model. Governing partial differential equation is derived based on longitudinal equilibrium and analytical solution is obtained by adopting harmonic motion solution for the nanorod. Modal frequencies and corresponding damping ratios are presented to demonstrate the influences of nonlocal parameter, material length scale, elastic and damping parameters of the viscoelastic medium. It is observed that material length scale parameter is very influential on modal frequencies especially at lower values of nonlocal parameter whereas increase in length scale parameter has less effect at higher values of nonlocal parameter when the medium is purely elastic. Elastic stiffness and damping coefficient of the medium have considerable impacts on modal frequencies and damping ratios, and the highest impact of these parameters on frequency and damping ratio is seen in the first mode. Results calculated based on strain gradient theory are quite different from those calculated based on classical elasticity theory. Hence, nonlocal strain gradient theory including length scale parameter can be used to get more accurate estimations of frequency response of nanorods embedded in viscoelastic medium.

• Computers and Concrete
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• v.20 no.5
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• pp.605-616
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• 2017

Concrete filled steel tubular (CFST) composite girder is a new type of structures for bridge constructions. The existing design codes cannot be used to predict the thermal stress in the CFST truss girder structures under solar radiation. This study is to develop the temperature gradient curves for predicting thermal stress of the structure based on field and laboratory monitoring data. An in-field testing had been carried out on Ganhaizi Bridge for over two months. Thermal couples were installed at the cross section of the CFST truss girder and the continuous data was collected every 30 minutes. A typical temperature gradient mode was then extracted by comparing temperature distributions at different times. To further verify the temperature gradient mode and investigate the evolution of temperature fields, an outdoor experiment was conducted on a 1:8 scale bridge model, which was installed with both thermal couples and strain gauges. The main factors including solar radiation and ambient temperature on the different positions were studied. Laboratory results were consistent with that from the in-field data and temperature gradient curves were obtained from the in-field and laboratory data. The relationship between the strain difference at top and bottom surfaces of the concrete deck and its corresponding temperature change was also obtained and a method based on curve fitting was proposed to predict the thermal strain under elevated temperature. The thermal stress model for CFST composite girder was derived. By the proposed model, the thermal stress was obtained from the temperature gradient curves. The results using the proposed model were agreed well with that by finite element modelling.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.422-428
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• 2008

In this paper, we propose the robust object detection algorithm with spatial gradient information. To do this, first, we eliminate error values that appear due to complex environment and various illumination change by using prior methods based on hue and intensity from the input video and background. Visible shadows are eliminated from the foreground by using an RGB color model and a qualified RGB color model. And unnecessary values are eliminated by using the HSI color model. The background is removed completely from the foreground leaving a silhouette to be restored using spatial gradient and HSI color model. Finally, we validate the applicability of the proposed method using various indoor and outdoor conditions in a complex environments.

• Steel and Composite Structures
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• v.45 no.3
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• pp.331-348
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• 2022

The main goal of this article is to develop the finite element formulation based on the nonlocal strain gradient and the refined higher-order deformation theory employing a new function f(z) to investigate the static bending and free vibration of functionally graded porous (FGP) nanobeams. The proposed model considers the simultaneous effects of two parameters: nonlocal and strain gradient coefficients. The nanobeam is made by FGP material that exists in un-even and logarithmic-uneven distribution. The governing equation of the nanobeam is established based on Hamilton's principle. The authors use a 2-node beam element, each node with 8 degrees of freedom (DOFs) approximated by the C¹ and C² continuous Hermit functions to obtain the elemental stiffness matrix and mass matrix. The accuracy of the proposed model is tested by comparison with the results of reputable published works. From here, the influences of the parameters: nonlocal elasticity, strain gradient, porosity, and boundary conditions are studied.

• Computers and Concrete
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• v.12 no.2
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• pp.229-241
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• 2013

The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.448-448
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• 2018

In this study, the regression models (Load ESTimator and eight-parameter model) were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST commonly used in interpolating pollutant loads could not necessarily provide the best results with the automatic selected regression model. It is inferred that the various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds applied. The recently developed eight-parameter model integrated with Genetic Algorithm (GA) and Gradient Descent Method (GDM) were also compared with LOADEST indicating that the eight-parameter model performed better than LOADEST, but it showed different behaviors in calibration and validation. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside of calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., $R^2$ and gradient and constant of linear regression line). The results showed higher precisions with the $R^2$ values closed to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) closed to 0.0 in the eight-parameter model with GDM. In hence, based on these finding we recommend that users need to evaluate the regression models under various criteria and calibration methods to provide the more accurate and precise results for pollutant load estimations.

• Advances in Energy Research
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• v.6 no.2
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• pp.91-101
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• 2019

This paper proposes an efficient data-driven approach to build models for predicting energy consumption in buildings. Data used in this research is collected by installing humidity and temperature sensors at different locations in a building. In addition to this, weather data from nearby weather station is also included in the dataset to study the impact of weather conditions on energy consumption. One of the main emphasize of this research is to make feature selection independent of domain knowledge. Therefore, to extract useful features from data, two different approaches are tested: one is feature selection through principal component analysis and second is relative importance-based feature selection in original domain. The regression model used in this research is gradient boosting regression and its optimal parameters are chosen through a two staged coarse-fine search approach. In order to evaluate the performance of model, different performance evaluation metrics like r2-score and root mean squared error are used. Results have shown that best performance is achieved, when relative importance-based feature selection is used with gradient boosting regressor. Results of proposed technique has also outperformed the results of support vector machines and neural network-based approaches tested on the same dataset.

• Structural Engineering and Mechanics
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• v.51 no.4
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• pp.627-641
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• 2014

Functionally graded steels (FGSs) are a family of functionally graded materials (FGMs) consisting of ferrite (${\alpha}$), austenite (${\gamma}$), bainite (${\beta}$) and martensite (M) phases placed on each other in different configurations and produced via electroslag remelting (ESR). In this research, the flow stress of dual layer austenitic-martensitic functionally graded steels under hot deformation loading has been modeled considering the constitutive equations which describe the continuous effect of temperature and strain rate on the flow stress. The mechanism-based strain gradient plasticity theory is used here to determine the position of each layer considering the relationship between the hardness of the layer and the composite dislocation density profile. Then, the released energy of each layer under a specified loading condition (temperature and strain rate) is related to the dislocation density utilizing the mechanism-based strain gradient plasticity theory. The flow stress of the considered FGS is obtained by using the appropriate coefficients in the constitutive equations of each layer. Finally, the theoretical model is compared with the experimental results measured in the temperature range $1000-1200^{\circ}C$ and strain rate 0.01-1 s-1 and a sound agreement is found.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.477-490
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• 2018

Effects of inflow Reynolds number (Re), turbulence intensity (I) and pressure gradient on the transition flow over a blade section were studied using the ${\gamma}-Re{\theta}$ transition model (STAR-CCM+). Results show that the $Re_T$ (transition Re) at the transition location ($P_T$) varies strongly with Re, I and the magnitude of pressure gradient. The $Re_T$ increases significantly with the increase of the magnitude of favorable pressure gradient. It demonstrates that the $Re_T$ on different blade sections of a rotating propeller are different. More importantly, when there is strong adverse pressure gradient, the $P_T$ is always close to the minimum pressure point. Based on these conclusions, the $P_T$ on model propeller blade surface can be estimated. Numerical investigations of pressure distribution and transition flow on a propeller blade section prove these findings. Last, a simple method was proposed to estimate the $P_T$ only based on the propeller geometry and the advance coefficient.

• Structural Engineering and Mechanics
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• v.69 no.2
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• pp.205-219
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• 2019

This paper analyzes nonlinear free vibration of the circular nano-tubes made of functionally graded materials in the framework of nonlocal strain gradient theory in conjunction with a refined higher order shear deformation beam model. The effective material properties of the tube related to the change of temperature are assumed to vary along the radius of tube based on the power law. The refined beam model is introduced which not only contains transverse shear deformation but also satisfies the stress boundary conditions where shear stress cancels each other out on the inner and outer surfaces. Moreover, it can degenerate the Euler beam model, the Timoshenko beam model and the Reddy beam model. By incorporating this model with Hamilton's principle, the nonlinear vibration equations are established. The equations, including a material length scale parameter as well as a nonlocal parameter, can describe the size-dependent in linear and nonlinear vibration of FGM nanotubes. Analytical solution is obtained by using a two-steps perturbation method. Several comparisons are performed to validate the present analysis. Eventually, the effects of various physical parameters on nonlinear and linear natural frequencies of FGM nanotubes are analyzed, such as inner radius, temperature, nonlocal parameter, strain gradient parameter, scale parameter ratio, slenderness ratio, volume indexes, different beam models.