• Journal of Korean Society on Water Environment
• /
• v.29 no.1
• /
• pp.19-28
• /
• 2013

Artificial neural networks were used for time series modelling of algal dynamics of whole year and by season at the Paldang dam station (confluence area). The modelling was based on comprehensive weekly water quality data from 1997 to 2004 at the Paldang dam station. The results of validation of seasonal models showed that the timing and magnitude of the observed chlorophyll a concentration was predicted better, compared with the ANN model for whole year. Internal weightings of the inputs in trained neural networks were obtained by sensitivity analysis for identification of the primary driving mechanisms in the system dynamics. pH, COD, TP determined most the dynamics of chlorophyll a, although these inputs were not the real driving variable for algal growth. Short-term prediction models that perform one or two weeks ahead predictions of chlorophyll a concentration were designed for the application of Harmful Algal Alert System in Lake Paldang. Short-term-ahead ANN models showed the possibilities of application of Harmful Algal Alert System after increasing ANN model's performance.

• Journal of Platform Technology
• /
• v.9 no.1
• /
• pp.3-14
• /
• 2021

Cognitive Radio network (CR) is a promising paradigm that helps the unlicensed user (Secondary User) to analyse the spectrum and coordinate the spectrum access to support the creation of common control channel (CCC). The cooperation of secondary users and broadcasting between them is done through transmitting messages in CCC. In case, if the control channels may get jammed and it may directly degrade the network's performance and under such scenario jammers will devastate the control channels. Hopping sequences may be one of the predominant approaches and it may be used to fight against this problem to confront jammer. The jamming attack can be alleviated using one of the game modelling approach and in this proposed scheme stochastic games has been analysed with more single users to provide the flexible control channels against intrusive attacks by mentioning the states of each player, strategies ,actions and players reward. The proposed work uses a modern player action and better strategic view on game theoretic modelling is stochastic game theory has been taken in to consideration and applied to prevent the jamming attack in CR network. The selection of decision is based on Q learning approach to mitigate the jamming nodes using the optimal MDP decision process

• Coupled systems mechanics
• /
• v.11 no.1
• /
• pp.79-91
• /
• 2022

Models for water treatment processes include simulation, i.e., modelling of water quality, flow hydraulics, process controls and design. Water treatment processes are inherently dynamic because of the large variations in the influent water flow rate, concentration and composition. Moreover, these variations are to a large extent not possible to control. Mathematical models and computer simulations are essential to describe, predict and control the complicated interactions of the water treatment processes. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. The main objective is to combine knowledge of the process dynamics with mathematical methods for processes estimation and identification. Good modelling practice is way to obtain this objective and to improve water treatment processes(its understanding, design, control and performance- efficiency). By synthesize of existing knowledge and experience on good modelling practices and principles the aim is to help address the critical strategic gaps and weaknessesin water treatment models application.

• Smart Structures and Systems
• /
• v.30 no.5
• /
• pp.447-462
• /
• 2022

The viscosity of a shear-thickening fluid damper (STFD) can increase dramatically when the STFD undergoes high-rate of excitation. Therefore, accurate numerical modelling of the STFD has been considered difficult due to this distinct feature. This study aims to develop a numerical model to accurately simulate the response of the STFD. First, a STFD is designed, fabricated, and installed in the laboratory. Then, performance tests are conducted in which sine waves with nine frequencies at three amplitude levels are adopted as the displacement excitations to the STFD. A novel numerical model which contains two parameter sets of the discrete Bouc-Wen model as well as two parameters for transiting the two parameter sets. Therefore, a total number of eighteen parameters need to be identified in the damper model. The symbiotic organisms search is applied to optimize the parameters. Numerical simulation results demonstrate that the proposed STFD model with transit parameter sets outperforms the conventional discrete Bouc-Wen model. The proposed STFD model can be applied to analyses of structures in which STFDs are installed in the future.

• Structural Engineering and Mechanics
• /
• v.21 no.6
• /
• pp.659-676
• /
• 2005

The novel form of composite walling system consists of two skins of profiled steel sheeting with an in-fill of concrete. The behaviour of such walling under in-plane shear is important in order to utilise this system as shear elements in a steel framed building. Steel sheet-concrete interface governs composite action, overall behaviour and failure modes of such walls. This paper describes the finite element (FE) modelling of the shear behaviour of walls with particular emphasis on the simulation of steel-concrete interface. The modelling of complex non-linear steel-concrete interaction in composite walls is conducted by using different FE models. Four FE models are developed and characterized by their approaches to simulate steel-concrete interface behaviour allowing either full or partial composite action. Non-linear interface or joint elements are introduced between steel and concrete to simulate partial composite action that allows steel-concrete in-plane slip or out of plane separation. The properties of such interface/joint elements are optimised through extensive parametric FE analysis using experimental results to achieve reliable and accurate simulation of actual steel-concrete interaction in a wall. The performance of developed FE models is validated through small-scale model tests. FE models are found to simulate strength, stiffness and strain characteristics reasonably well. The performance of a model with joint elements connecting steel and concrete layers is found better than full composite (without interface or joint elements) and other models with interface elements. The proposed FE model can be used to simulate the shear behaviour of composite walls in practical situation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2010.11a
• /
• pp.795-796
• /
• 2010

• Earthquakes and Structures
• /
• v.4 no.5
• /
• pp.451-470
• /
• 2013

It generally accepted that most building structures shall exhibit a nonlinear response when subjected to medium-high intensity earthquakes. It is currently known, however, that this phenomenon is not properly modelled in the majority of cases, especially at the design stage, where only simple linear methods have effectively been used. Recently, as a result of the exponential progress of computational tools, nonlinear modelling and analysis have gradually been brought to a more promising level. A wide range of modelling alternatives developed over the years is hence at the designer's disposal for the seismic design and assessment of engineering structures. The objective of the study presented herein is to test some of these models in an existing structure, and observe their performance in nonlinear static and dynamic analyses. This evaluation is done by the use of two of a known range of advanced computer programs: SAP2000 and SeismoStruct. The different models will focus on the element flexural mechanism with both lumped and distributed plasticity element models. In order to appraise the reliability and feasibility of each alternative, the programs capabilities and the amount of labour and time required for modelling and performing the analyses are also discussed. The results obtained show the difficulties that may be met, not only in performing nonlinear analyses, but also on their dependency on both the chosen nonlinear structural models and the adopted computer programs. It is then suggested that these procedures should only be used by experienced designers, provided that they are aware of these difficulties and with a critical stance towards the result of the analyses.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.10 no.11
• /
• pp.2008-2013
• /
• 2006

In numerical analysis on evaluating the thermal performance of the thermal equipment, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table itself cannot be used without modelling. In this study applicability of neural networks in modelling the wide temperature range of wet saturated vapor region was examined. the multi-layer neural network consists of a input layer with 1 node, two hidden layers with 10 and 20 nodes respectively and a output layer with 6 nodes. Quadratic and cubic spline interpoations methods were also applied for comparison. Neural network model revealed similar percentage error to spline interpolation. From these results, it is confirmed that the neural networks could be powerful method in modelling the wide range of the steam table.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.12 no.4
• /
• pp.685-690
• /
• 2008

In numerically evaluating the thermal performance of the heat exchanger, numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But the steam table or diagram itself cannot be directly used without modelling. In this study the applicability of neural networks in modelling superheated water vapor was examined. The multi-layer neural networks consist of an input layer with 2 nodes, two hidden layers with 15 and 25 nodes respectively and an output layer with 3 nodes. Quadratic spline interpolation was also applied for comparison. Neural networks model revealed smaller percentage error compared with spline interpolation. From this result, it is confirmed that the neural networks could be a powerful method in modelling the superheated water vapor.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.425-428
• /
• 1998

This paper proposes a new fuzzy controller using variable structure control theory. In this paper, after the time-varying fuzzy sliding surface is designed, the fuzzy rules are defined based on the variable structure control theory. This design method makes the fuzzy controller design more structured and can guarantee the stability and robustness of the fuzzy controller and overcome the shortcoming of the variable structure system. Through computer simulation and experiment of nonlinear inverted pendulum system, this thesis demonstrate that system has the robustness against disturbance and modelling error, and the tracking performance of it is improved.