• Geomechanics and Engineering
• /
• v.39 no.4
• /
• pp.347-356
• /
• 2024

The aim of the present investigation is focused on the nonlinear forced vibration analysis of porous FGM sandwich beam with a viscoelastic core resting on nonlinear elastic foundation. The analytical formulation incorporates both normal and shear deformations in the core by utilizing the Zig-Zag theories. The harmonic balance method is integrated with a one-mode Galerkin's procedure designed for a simply supported beam. The nonlinear geometric coupling and viscoelastic effects result in a frequency amplitude equation that is nonlinear and governed by multiple complex coefficients. The damping and frequency response curves are depicted and analyzed across various geometrical and mechanical configurations of sandwich beams. The results indicate that the porosity effects and elastic coefficients of the foundation exert a significant influence on the damping and nonlinear vibration response of these beams.

• Korean Journal of Agricultural Science
• /
• v.10 no.2
• /
• pp.324-333
• /
• 1983

Modeling of longterm runoff is theoritically based on waterbalance analysis. Simplified equation of water balance with rainfall, evapotranspiration and soil moisture storage could be formulated into regression model with variables of rainfall, pan evaporation and previous-month streamflow. The hydrologic response of water shed could be represented lumpedly, qualitatively and deductively by regression coefficients of water-balance regression model. Characteristics of regression modeling of water-balance were summarized as follows; 1. Regression coefficient $b_1$ represents the rate of direct runoff component of precipitation. The bigger the drainage area, the less $b_1$ value. This means that there are more losses of interception, surface detension and transmission in the downstream watershed. 2. Regression coefficient $b_2$ represents the rate of baseflow due to changes of soil moisture storage. The bigger the drainage area and the milder the watershed slope, the bigger b, value. This means that there are more storage capacity of watershed in mild downstream watershed. 3. Regression coefficient $b_3$ represents the rate of watershed evaporation. This depends on the s oil type, soil coverage and soil moisture status. The bigger the drainage area, the bigger $b_3$ value. This means that there are more watershed evaporation loss since more storage of surface and subsurface water would be in down stream watershed. 4. It was possible to explain the seasonal variation of streamflow reasonably through regress ion coefficients. 5. Percentages of beta coefficients what is a relative measure of the importance of rainfall, evaporation and soil moisture storage to month streamflow are approximately 89%, 9% and 11% respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.7
• /
• pp.3066-3079
• /
• 2016

Recent years have witnessed a dramatic increase in topology research of wireless sensor networks (WSNs) where both energy consumption and survivability need careful consideration. To balance energy consumption and ensure survivability against both random failures and deliberate attacks, we resort to complex network theory and propose an energy-aware preferential attachment (EPA) model to generate a robust topology for WSNs. In the proposed model, by taking the transmission range and energy consumption of the sensor nodes into account, we combine the characters of Erdős -Rényi (ER) model and Barabasi-Albert (BA) model in this new model and introduce tunable coefficients for balancing connectivity, energy consumption, and survivability. The correctness of our theoretic analysis is verified by simulation results. We find that the topology of WSNs built by EPA model is asymptotically power-law and can have different characters in connectivity, energy consumption, and survivability by using different coefficients. This model can significantly improve energy efficiency as well as enhance network survivability by changing coefficients according to the requirement of the real environment where WSNs deployed and therefore lead to a crucial improvement of network performance.

• Current Optics and Photonics
• /
• v.5 no.3
• /
• pp.270-277
• /
• 2021

The adaptive sparse representation (ASR) can effectively combine the structure information of a sample dictionary and the sparsity of coding coefficients. This algorithm can effectively consider the correlation between training samples and convert between sparse representation-based classifier (SRC) and collaborative representation classification (CRC) under different training samples. Unlike SRC and CRC which use fixed norm constraints, ASR can adaptively adjust the constraints based on the correlation between different training samples, seeking a balance between l₁ and l₂ norm, greatly strengthening the robustness and adaptability of the classification algorithm. The correlation coefficients (CC) can better identify the pixels with strong correlation. Therefore, this article proposes a hyperspectral image classification method called correlation coefficients and adaptive sparse representation (CCASR), based on ASR and CC. This method is divided into three steps. In the first step, we determine the pixel to be measured and calculate the CC value between the pixel to be tested and various training samples. Then we represent the pixel using ASR and calculate the reconstruction error corresponding to each category. Finally, the target pixels are classified according to the reconstruction error and the CC value. In this article, a new hyperspectral image classification method is proposed by fusing CC and ASR. The method in this paper is verified through two sets of experimental data. In the hyperspectral image (Indian Pines), the overall accuracy of CCASR has reached 0.9596. In the hyperspectral images taken by HIS-300, the classification results show that the classification accuracy of the proposed method achieves 0.9354, which is better than other commonly used methods.

• Journal of Soil and Groundwater Environment
• /
• v.11 no.1
• /
• pp.65-76
• /
• 2006

This paper outlines the methodology of grid-based water balance for estimating the spatial distribution of recharge, which is applied to Woedo catchment in the northern area of the Jeju Island. The catchment is divided into grids and a daily water balance in each grid is computed for the period of 5 years. Daily rainfall data in each grid is interpolated from the data of 10 rainfall gauging stations. The spatial distributions of parameters such as SCS curve number, soil water retention capacity and crop coefficients are derived from GIS analyses of soil and land use characteristics. The SCS curve number is obtained by calibrating simulated runoffs with respect to the observed runoffs. The results show that the average annual rainfall increases from 1,665 mm/year to 3,382 mm/year in accordance with the topographic elevation, and the average annual recharge varies from 372 mm/year to 2,576 mm/year according to the average annual rainfall increases. Spatial variability of recharge is the highest among the water balance components such as rainfall, direct runoff, evaprotranspiration and recharge because the rate of runoff and evapotranspiration in the area with relatively low rainfall is higher than the other area.

• Journal of Bio-Environment Control
• /
• v.29 no.1
• /
• pp.9-19
• /
• 2020

Convective heat transfer is the main component of greenhouse energy loss because the energy loss by this mechanism is greater than those of the other two components (radiative and conductive). Previous studies have examined the convective heat transfer coefficients under natural conditions, but they are not applicable to symmetric thermal screens with zero porosity, and such screens are largely produced and used in Korea. However, the properties of these materials have not been reported in the literature, which causes selectivity issues for users. Therefore, in this study, three screens having similar color and zero porosity were selected, and a mathematical procedure based on radiation balance equations was developed to determine their convective heat transfer coefficients. To conduct the experiment, a hollow wooden structure was built and the thermal screen was tacked over this frame; the theoretical model was applied underneath and over the screen. Input parameters included three components: 1) solar and thermal fluxes; 2) temperature of the screen, black cloth, and ambient air; and 3) wind velocity. The convective heat transfer coefficients were determined as functions of the air-screen temperature difference under open-air environmental conditions. It was observed from the outcomes that the heat transfer coefficients decreased with the increase of the air-screen temperature difference provided that the wind velocity was nearly zero.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2004.11a
• /
• pp.143-148
• /
• 2004

The numerical analysis of the hard disk drive slider is presented. The pressure distribution was calculated using the finite element method. The generalized Reynolds equation was applied in order to include the gas rarefaction effect. The balance of the air bearing force and preload force was considered. The characteristics of the small vibrations near the equilibrium were studied using the perturbation method. Triangular mesh with variable element size was employed to model the two-rail slider. The flying height, pitching angle, rolling angle, stiffness and damping of the two-rail slider were calculated for radial position changing from the inner radius to the outer radius and for a wide range of the slider crown values. It was found that the flying height, pitching angle and rolling angle were increased with radial position while the stiffness and damping coefficients were decreased. The higher values of crown resulted in increased flying height, pitching angle and damping and decreased stiffness.

• 한국연소학회:학술대회논문집
• /
• 1999.10a
• /
• pp.155-163
• /
• 1999

A numerical study for simulating a swirling pulverized coal combustion in axisymmetric geometry is done here by applying the weighted sum of gray gases model (WSGGM) approach with the discrete ordinate method (DOM) to model the radiative heat transfer equation. In the radiative transfer equation, the same polynomial equation and coefficients for weighting factors as those for gas are adopted for the coal/char particles as a function of partial pressure and particle temperature. The Eulerian balance equations for mass, momentum, energy, and species mass fractions are adopted with the standard ${\kappa}-{\varepsilon}$ turbulence model, whereas the Lagrangian approach is used for the particulate phase for soot. The eddydissipation model is employed for the reaction rate for gaseous mixture, and the single-step first-order reaction model for the devolatilization process for coal. By comparing the numerical results with experimental ones, the models used here are confirmed and found to be one of good alternatives for simulating the combustion as well as radiative characteristics.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.797-799
• /
• 1999

In this paper, we design the Multi-FNN(Fuzzy-Neural Networks) using HCM Method. The proposed Multi-FNN uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. Also, We use HCM(Hard C-Means) method of clustering technique for improvement of output performance from pre-processing of input data. The parameters such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. We use the training and testing data set to obtain a balance between the approximation and the generalization of our model. Several numerical examples are used to evaluate the performance of the our model. From the results, we can obtain higher accuracy and feasibility than any other works presented previously.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.824-826
• /
• 1999

In this paper, we design an Fuzzy-Neural Networks(FNN) by means of divisions of fuzzy input space with multi-input variables. Fuzzy input space of Yamakawa's FNN is divided by each separated input variable, but that of the proposed FNN is divided by mutually combined input variables. The membership functions of the proposed FNN use both triangular and gaussian membership types. The parameters such as apexes of membership functions, learning rates, momentum coefficients, weighting value, and slope are adjusted using genetic algorithms. Also, an aggregate objective function(performance index) with weighting value is utilized to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the data of sewage treatment process.