• Smart Structures and Systems
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• v.14 no.5
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• pp.785-809
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• 2014

In this paper, an Adaptive nerou-based inference system (ANFIS) is being used for the prediction of shear strength of high strength concrete (HSC) beams without stirrups. The input parameters comprise of tensile reinforcement ratio, concrete compressive strength and shear span to depth ratio. Additionally, 122 experimental datasets were extracted from the literature review on the HSC beams with some comparable cross sectional dimensions and loading conditions. A comparative analysis has been carried out on the predicted shear strength of HSC beams without stirrups via the ANFIS method with those from the CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94 codes of design. The shear strength prediction with ANFIS is discovered to be superior to CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94. The predictions obtained from the ANFIS are harmonious with the test results not accounting for the shear span to depth ratio, tensile reinforcement ratio and concrete compressive strength; the data of the average, variance, correlation coefficient and coefficient of variation (CV) of the ratio between the shear strength predicted using the ANFIS method and the real shear strength are 0.995, 0.014, 0.969 and 11.97%, respectively. Taking a look at the CV index, the shear strength prediction shows better in nonlinear iterations such as the ANFIS for shear strength prediction of HSC beams without stirrups.

• Bulletin of the Korean Mathematical Society
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• v.29 no.1
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• pp.125-135
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• 1992

In various viscus flow problems it has been the custom to replace the convective derivative by the ordinary partial derivative in problems for which the data are small. In this paper we consider the Benard Convection problem with small data and compare the solution of this problem (assumed to exist) with that of the linearized system resulting from dropping the nonlinear terms in the expression for the convective derivative. The objective of the present work is to derive an estimate for the error introduced in neglecting the convective inertia terms. In fact, we derive an explicit bound for the L$_{2}$ error. Indeed, if the initial data are O(.epsilon.) where .epsilon. << 1, and the Rayleigh number is sufficiently small, we show that this error is bounded by the product of a term of O(.epsilon.$^{2}$) times a decaying exponential in time. The results of the present paper then give a justification for linearizing the Benard Convection problem. We remark that although our results are derived for classical solutions, extensions to appropriately defined weak solutions are obvious. Throughout this paper we will make use of a comma to denote partial differentiation and adopt the summation convention of summing over repeated indices (in a term of an expression) from one to three. As reference to work of continuous dependence on modelling and initial data, we mention the papers of Payne and Sather [8], Ames [2] Adelson [1], Bennett [3], Payne et al. [9], and Song [11,12,13,14]. Also, a similar analysis of a micropolar fluid problem backward in time (an ill-posed problem) was given by Payne and Straughan [10] and Payne [7].

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.9
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• pp.711-723
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• 2017

This paper proposes a flight control system for an organic flight array(OFA) which has a new configuration to consist of multi modularized ducted-fan unmanned aerial vehicles (UAVs). The OFA is able to apply to various missions such as indoor reconnaissance, communication relay, and radar jamming by using capability of hover flight. The OFA has a distinguished advantage due to reconfigurable structure to assemble or separate with respect to its missions or operational conditions. A dynamic modelling of the OFA is derived based on equations of motion of the single ducted-fan modules. In order to apply nonlinear control method, an affine system of attitude dynamics is derived. Moreover, the control system is composed of a back-stepping controller for attitude control and a PID controller for position control. Then the performance of the proposed controller is verified via a numerical simulation under wind disturbance.

• Earthquakes and Structures
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• v.11 no.6
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• pp.1001-1025
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• 2016

Building structures generally have inherent low damping capability and hence are vulnerable to seismic excitations. Control devices therefore play a useful role in providing safety to building structures subject to seismic events. In recent years semi-active dampers have gained considerable attention as structural control devices in the building construction industry. Magneto-rheological (MR) damper, a type of semi-active damper has proven to be effective in seismic mitigation of building structures. MR dampers contain a controllable MR fluid whose rheological properties vary rapidly with the applied magnetic field. Although some research has been carried out on the use of MR dampers in building structures, optimal design of MR damper and combined use of MR and passive dampers for real scale buildings has hardly been investigated. This paper investigates the use of MR dampers and incorporating MR-passive damper combinations in building structures in order to achieve acceptable levels of seismic performance. In order to do so, it first develops the MR damper model by integrating control algorithms commonly used in MR damper modelling. The developed MR damper is then integrated in to the seismically excited structure as a time domain function. Linear and nonlinear structure models are evaluated in real time scenarios. Analyses are conducted to investigate the influence of location and number of devices on the seismic performance of the building structure. The findings of this paper provide information towards the design and construction of earthquake safe buildings with optimally employed MR dampers and MR-passive damper combinations.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.2 s.42
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• pp.7-15
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• 2005

Numerical analysis model is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system is composed of friction pendulum systems (FPS) and a magnetorheological (MR) damper. A neuro-fuzzy model is used to represent dynamic behavior of the MR damper. Fuzzy model of the MR damper is trained by ANFIS (Adaptive Neuro-Fuzzy Inference System) using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses of experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.48-59
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• 2002

TSK(Takagi-Sugeno-Kang) fuzzy models with linear equations consequents, which represent complex nonlinear systems very well with a few rules, can be easily identified systematically by using input-output data. Many algorithms designing TSK fuzzy controllers based on TSK fuzzy models, which guarantees the stability of the closed system, have been suggested. On the contrary, singleton fuzzy models with singleton consequents can be easily understood and adjusted. In this paper, in order to utilize the merits of TSK fuzzy systems and singleton fuzzy systems, an algorithm transforming a TSK fuzzy model into a singleton fuzzy model having the same input-output relation is suggested. The suggested algorithm is applied to a fuzzy modelling example and a fuzzy controller design example.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• Earthquakes and Structures
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• v.17 no.5
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• pp.447-462
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• 2019

This present paper concerned with the analytic modelling for vibration of the functionally graded (FG) plates resting on non-variable and variable two parameter elastic foundation, based on two-dimensional elasticity using higher shear deformation theory. Our present theory has four unknown, which mean that have less than other higher order and lower theory, and we denote do not require the factor of correction like the first shear deformation theory. The indeterminate integral are introduced in the fields of displacement, it is allowed to reduce the number from five unknown to only four variables. The elastic foundations are assumed a classical model of Winkler-Pasternak with uniform distribution stiffness of the Winkler coefficient (kw), or it is with variables distribution coefficient (kw). The variable's stiffness of elastic foundation is supposed linear, parabolic and trigonometry along the length of functionally plate. The properties of the FG plates vary according to the thickness, following a simple distribution of the power law in terms of volume fractions of the constituents of the material. The equations of motions for natural frequency of the functionally graded plates resting on variables elastic foundation are derived using Hamilton principal. The government equations are resolved, with respect boundary condition for simply supported FG plate, employing Navier series solution. The extensive validation with other works found in the literature and our results are present in this work to demonstrate the efficient and accuracy of this analytic model to predict free vibration of FG plates, with and without the effect of variables elastic foundations.

• Advances in environmental research
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• v.3 no.3
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• pp.231-251
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• 2014

The present study examines the phosphate adsorption potential and behavior of mixture of Ground Burnt Patties (GBP), a solid waste generated from cooking fuel used in earthen stoves and Red Soil (RS), a natural substance in fixed bed column mode operation. The characterization of adsorbent was done by Proton Induced X-ray Emission (PIXE), and Proton Induced ${\gamma}$-ray Emission (PIGE) methods. The FTIR spectroscopy of spent adsorbent reveals the presence of absorbance peak at $1127cm^{-1}$ which appears due to P = O stretching, thus confirming phosphate adsorption. The effects of bed height (10, 15 and 20 cm), flow rate (2.5, 5 and 7.5 mL/min) and initial phosphate concentration (5 and 15 mg/L) on breakthrough curves were explored. Both the breakthrough and exhaustion time increased with increase in bed depth, decrease in flow rate and influent concentration. Thomas model, Yoon-Nelson model and Modified Dose Response model were used to fit the column adsorption data using nonlinear regression analysis while Bed Depth Service Time model followed linear regression analysis under different experimental condition to evaluate model parameters that are useful in scale up of the process. The values of correlation coefficient ($R^2$) and the Sum of Square Error (SSE) revealed the Modified Dose Response model as the best fitted model to the experimental data. The adsorbent mixture responded effectively to the desorption and reusability experiment. The results of this finding advocated that mixture of GBP and RS can be used as a low cost, highly efficient adsorbent for phosphate removal from aqueous solution.