• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.534-539
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• 2015

The DC overhead line voltage of an electric railway substation swings depending on the accelerating and regenerative-braking energy of trains, and it deteriorates the energy quality of the electric facility in the DC railway substation and restricts the powering and braking performance of subway trains. Recently, an energy storage system or a regenerative inverter has been introduced into railway traction substations to diminish both the variance of the overhead line voltage and the peak power consumption. In this study, the variance of the overhead line voltage in a DC railway substation is modelled by RC parallel circuits in each feeder, and the RC parameters are estimated using the recursive least mean square (RLMS) scheme. The forgetting factor values for the RLMS are selected using simulated annealing optimization, and the modelling scheme of the overhead line voltage variation is evaluated through raw data measured in a downtown railway substation.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.151-157
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• 2010

This paper presents the modelling of an MR damper system through extensive experimental studies. The hysteresis of the MR damper is modelled by using the improved Bouc-wen model. A test bed for experimental studies of measuring parameters of the MR damper is designed and implemented. Based on the experimental data, the Bouc-Wen Model is modified for the MR damper system. To check the modelling property, a vehicle suspension system is controlled using a PID controller for the verification of the MR damper model.

• Structural Engineering and Mechanics
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• v.5 no.6
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• pp.817-837
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• 1997

In the present contribution an interface crack model is introduced which is capable of modelling crack initialisation and growth in aluminium as well as in Fibre Metal Laminates. Interface elements are inserted in a finite element mesh with a yield function which bounds all states of stress in the interface. Hardening occurs after a state of stress exceeds the yield stress of the material. The hardening branch is bounded by the ultimate stress of the material. Thereafter, the state of stress is reduced to zero while the inelastic deformations grow. The energy dissipated by the inelastic deformations in this process equals the fracture energy of the material. The model is applied to calculate the onset and growth of cracking in centre cracked plates made of aluminium and GLARE$^{(R)}$. The impact of the model parameters on the performance of the crack model is studied by comparisons of the numerical results with experimental data.

• Computers and Concrete
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• v.15 no.4
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• pp.547-562
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• 2015

A two-dimensional multi-layered finite elements modeling of reinforced concrete structures at non-linear behaviour under monotonic and cyclical loading is presented. The non-linearity material is characterized by several phenomena such as: the physical non-linearity of the concrete and steels materials, the behaviour of cracked concrete and the interaction effect between materials represented by the post-cracking filled. These parameters are taken into consideration in this paper to examine the response of the reinforced concrete structures at the non-linear behaviour. Four examples of application are presented. The numerical results obtained, are in a very good agreement with available experimental data and other numerical models of the literature.

• The Korean Journal of Ecology
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• v.28 no.6
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• pp.405-415
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• 2005

This paper considers the advantage of Machine Learning (ML) implemented to freshwater ecosystem research. Currently, many studies have been carried out to find the patterns of environmental impact on dynamics of communities in aquatic ecosystems. Ecological models popularly adapted by many researchers have been a means of information processing in dealing with dynamics in various ecosystems. The up-to-date trend in ecological modelling partially turns to the application of ML to explain specific ecological events in complex ecosystems and to overcome the necessity of complicated data manipulation. This paper briefly introduces ML techniques applied to freshwater ecosystems in Korea. The manuscript provides promising information for the ecologists who utilize ML for elucidating complex ecological patterns and undertaking modelling of spatial and temporal dynamics of communities.

• Nuclear Engineering and Technology
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• v.43 no.6
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• pp.489-498
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• 2011

UK National Nuclear Laboratory's (NNL's) version of the ENIGMA fuel performance code is described, including details of the development history, the system modelled, the key assumptions, the thermo-mechanical solution scheme, and the various incorporated models. The recent development of ENIGMA in the areas of whole core analysis and dry storage applications is then discussed. With respect to the former, the NEXUS code has been developed by NNL to automate whole core fuel performance modelling for an LWR core, using ENIGMA as the underlying fuel performance engine. NEXUS runs on NNL's GEMSTONE high performance computing cluster and utilises 3-D core power distribution data obtained from the output of Studsvik Scandpower's SIMULATE code. With respect to the latter, ENIGMA has been developed such that it can model the thermo-mechanical behaviour of a given LWR fuel rod during irradiation, pond cooling, drying, and dry storage - this involved: (a) incorporating an out-of-pile clad creep model for irradiated Zircaloy-4; (b) including the ability to simulate annealing out of the clad irradiation damage; (c) writing of additional post-irradiation output; (d) several other minor modifications to allow modelling of post-irradiation conditions.

• Geomechanics and Engineering
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• v.19 no.3
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• pp.229-240
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• 2019

The physical models are useful to understand the soil behaviour. Hence, these tools allow validating analytical theories and numerical data. This paper addresses the design, construction and implementation of a physical model able to simulate the soil liquefaction under different cyclic actions. The model was instrumented with a piezoelectric actuator and a set of transducers to measure the porewater pressures, displacements and accelerations of the system. The soil liquefaction was assessed in three different grain size particles of a natural sand by applying a sinusoidal signal, which incorporated three amplitudes and the fundamental frequencies of three different earthquakes occurred in Colombia. In addition, such frequencies were scaled in a micro shaking table device for 1, 50 and 80 g. Tests allowed identifying the liquefaction susceptibility at various frequency and displacement amplitude combinations. Experimental evidence validated that the liquefaction susceptibility is higher in the fine-grained sands than coarse-grained sands, and showed that the acceleration of the actuator controls the phenomena trigging in the model instead of the displacement amplitude.

• Structural Engineering and Mechanics
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• v.78 no.2
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• pp.145-161
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• 2021

Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.51-61
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• 2022

Gas separation via hollow fibre membrane modules (HFMM) is deemed to be a promising technology for natural gas sweetening, particularly for lowering the level of carbon dioxide (CO₂) in natural gas, which can cause various problems during transportation and process operation. Separation performance via HFMM is affected by membrane properties, module specifications and operating conditions. In this study, a mathematical model for HFMM is developed, which can be used to assess the effects of the aforementioned variables on separation performance. Appropriate boundary conditions are imposed to resolve steady-state values of permeate variables and incorporated in the model equations via an iterative numerical procedure. The developed model is proven to be reliable via model validation against experimental data in the literature. Also, the model is capable of capturing axial variations of process variables as well as predicting key performance indicators. It can be extended to simulate a large-scale plant and identify an optimal process design and operating conditions for improved separation efficiency and reduced cost.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.145-152
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• 2022

One of the impacts of Covid-19 on education systems has been the shift to online education. This shift has changed the way education is consumed and perceived by students. However, the exact nature of student perception about online education is not known. The aim of this study was to understand the perceptions of Saudi higher education students (e.g., post-school students) about online education during the Covid-19 pandemic. Various aspects of online education including benefits, features and cybersecurity were explored. The data collected were analysed using statistical techniques, especially artificial neural networks, to address the research aims. The key findings were that benefits of online education was perceived by students with positive experience or when ensured of safe use of online platforms without the fear cyber security breaches for which recruitment of a cyber security officer was an important predictor. The issue of whether perception of online education as a necessity only for Covid situation or a lasting option beyond the pandemic is a topic for future research.