• Structural Engineering and Mechanics
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• v.70 no.4
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• pp.479-497
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• 2019

In the current code design, the use of a uniform internal pressure coefficient of cooling towers as internal suction cannot reflect the 3D characteristics of flow field inside the tower body with different ventilation rate of shutters. Moreover, extreme weather such as heavy rain also has a direct impact on aerodynamic force on the internal surface and changes the turbulence effect of pulsating wind. In this study, the world's tallest cooling tower under construction, which stands 210m, is taken as the research object. The algorithm for two-way coupling between wind and rain is adopted. Simulation of wind field and raindrops is performed iteratively using continuous phase and discrete phase models, respectively, under the general principles of computational fluid dynamics (CFD). Firstly, the rule of influence of 9 combinations of wind speed and rainfall intensity on the volume of wind-driven rain, additional action force of raindrops and equivalent internal pressure coefficient of the tower body is analyzed. The combination of wind velocity and rainfall intensity that is most unfavorable to the cooling tower in terms of distribution of internal pressure coefficient is identified. On this basis, the wind/rain loads, distribution of aerodynamic force and working mechanism of internal pressures of the cooling tower under the most unfavorable working condition are compared between the four ventilation rates of shutters (0%, 15%, 30% and 100%). The results show that the amount of raindrops captured by the internal surface of the tower decreases as the wind velocity increases, and increases along with the rainfall intensity and ventilation rate of the shutters. The maximum value of rain-induced pressure coefficient is 0.013. The research findings lay the basis for determining the precise values of internal surface loads of cooling tower under extreme weather conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• Computers and Concrete
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• v.27 no.4
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• pp.319-332
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• 2021

The performance of gene expression programming (GEP) in predicting the compressive strength of bacteria-incorporated geopolymer concrete (GPC) was examined in this study. Ground-granulated blast-furnace slag (GGBS), new bacterial strains, fly ash (FA), silica fume (SF), metakaolin (MK), and manufactured sand were used as ingredients in the concrete mixture. For the geopolymer preparation, an 8 M sodium hydroxide (NaOH) solution was used, and the ambient curing temperature (28℃) was maintained for all mixtures. The ratio of sodium silicate (Na2SiO3) to NaOH was 2.33, and the ratio of alkaline liquid to binder was 0.35. Based on experimental data collected from the literature, an evolutionary-based algorithm (GEP) was proposed to develop new predictive models for estimating the compressive strength of GPC containing bacteria. Data were classified into training and testing sets to obtain a closed-form solution using GEP. Independent variables for the model were the constituent materials of GPC, such as FA, MK, SF, and Bacillus bacteria. A total of six GEP formulations were developed for predicting the compressive strength of bacteria-incorporated GPC obtained at 1, 3, 7, 28, 56, and 90 days of curing. 80% and 20% of the data were used for training and testing the models, respectively. R2 values in the range of 0.9747 and 0.9950 (including train and test dataset) were obtained for the concrete samples, which showed that GEP can be used to predict the compressive strength of GPC containing bacteria with minimal error. Moreover, the GEP models were in good agreement with the experimental datasets and were robust and reliable. The models developed could serve as a tool for concrete constructors using geopolymers within the framework of this research.

• Smart Structures and Systems
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• v.23 no.6
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• pp.565-577
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• 2019

One of the most effective countermeasures for mitigating cable vibration is to install mechanical dampers near the anchorage of the cable. Most of the dampers used in the field are so-called passive dampers where their parameters cannot be changed once designed. The parameters of passive dampers are usually determined based on the optimal damper force obtained from the universal design curve for linear dampers, which will provide a maximum additional damping for the cable. As the optimal damper force is chosen based on a predetermined principal vibration mode, passive dampers will be most effective if cable undergoes single-mode vibration where the vibration mode is the same as the principal mode used in the design. However, in the actual engineering practice, multi-mode vibrations are often observed for cables. Therefore, it is desirable to have dampers that can suppress different modes of cable vibrations simultaneously. In this paper, MR dampers are proposed for controlling multi-mode cable vibrations, because of its ability to change parameters and its adaptability of active control without inquiring large power resources. Although the highly nonlinear feature of the MR material leads to a relatively complex representation of its mathematical model, effective control strategies can still be derived for suppressing multi-mode cable vibrations based on nonlinear modelling, as proposed in this paper. Firstly, the nonlinear Bouc-wen model is employed to accurately portray the salient characteristics of the MR damper. Then, the desired optimal damper force is determined from the universal design curve of friction dampers. Finally, the input voltage (current) of MR damper corresponding to the desired optimal damper force is calculated from the nonlinear Bouc-wen model of the damper using a piecewise linear interpolation scheme. Numerical simulations are carried out to validate the effectiveness of the proposed control algorithm for mitigating multi-mode cable vibrations induced by different external excitations.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.2
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• pp.136-141
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• 2021

Heating cables, widely used in office buildings, factories, streets and railways, deteriorate in electrical insulation during operation. The insulation deterioration of heating cables leads to electric discharges that can cause electrical fires. With this background, this paper dealt with a condition monitoring technique for heating cables by the analysis of discharge signals to prevent electrical fires. Insulation deterioration was simulated using an arc generator specified in UL1699 under AC operation, and the characteristic and propagation of discharge signals were analyzed on a 100 meter-long heating cable. Discharge signals produced by insulation deterioration were detected as a voltage pulse because they are as small as a few mV and they are attenuated through propagation path. The frequency spectrum of discharge signals mainly existed in the range from 70 kHz to 110 kHz, and the maximum attenuation of the signal was 84.8% at 100 meters away from the discharge point. Based on the experimental results, a monitoring device, which is composed of a high pass filter with the cut-off frequency of 70 kHz, a comparator, a wave shaper and a microprocessor, was designed and fabricated. Also, an algorithm was designed to discriminate the discharge signal in the presence of noise, compared with the pulse repetition period and the number of pulse counts per 100ms. In the experiment, the result showed that the prototype monitoring device could detect and discriminate the discharge signals produced at every discharge point on a heating cable.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2148-2167
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• 2021

The proliferation of the Internet of Things (IoT) technologies and applications, especially the rapid rise in the use of mobile devices, from individuals to organizations, has led to the fundamental role of secure wireless networks in all aspects of services that presented with many opportunities and challenges. To ensure the CIA (confidentiality, integrity and accessibility) security model of the networks security and high efficiency of performance results in various resource-constrained applications and environments of the IoT platform, DDO-(data-driven operation) based constructions have been introduced as a primitive design that meet the demand of high speed encryption systems. Among of them, the TMN-family ciphers which were proposed by Tuan P.M., Do Thi B., etc., in 2016, are entirely suitable approaches for various communication applications of wireless mobile networks (WMNs) and advanced wireless sensor networks (WSNs) with high flexibility, applicability and mobility shown in two different algorithm selections, TMN64 and TMN128. The two ciphers provide strong security against known cryptanalysis, such as linear attacks and differential attacks. In this study, we demonstrate new probability results on the security of the two TMN construction versions - TMN64 and TMN128, by proposing efficient related-key recovery attacks. The high probability characteristics (DCs) are constructed under the related-key differential properties on a full number of function rounds of TMN64 and TMN128, as 10-rounds and 12-rounds, respectively. Hence, the amplified boomerang attacks can be applied to break these two ciphers with appropriate complexity of data and time consumptions. The work is expected to be extended and improved with the latest BCT technique for better cryptanalytic results in further research.

• Atmosphere
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• v.31 no.1
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• pp.45-60
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• 2021

The synoptic structures and precipitation impact of extratropical cyclones (ETCs) influencing on the three adjacent megacities in East Asia, i.e., Beijing (Beijing ETCs), Seoul (Seoul ETCs) and Tokyo (Tokyo ETCs), are analyzed using ERA-interim reanalysis data from 1979 to 2018. Individual ETC tracks are identified with the automated tracking algorithm applied to 850-hPa relative vorticity field. Among four seasons, ETCs are the most frequent in spring. In this season, Beijing ETCs are mainly generated at the leeside of Altai-Sayan Mountains and primarily develop through interaction between the upper-level trough and lower-level cyclonic circulation. For Seoul ETCs, the leesides of Altai-Sayan Mountains (Seoul-N ETCs) and Tibetan Plateau (Seoul-S ETCs) are main genesis regions and the features of ETCs are different according to the genesis regions. While Seoul-N ETCs mainly develope by the same mechanism of Beijing ETCs, strong diabatic heating due to vapor transport is responsible for the genesis of Seoul-S ETCs. Tokyo ETCs are originated from the leesides of Tibetan Plateau and Kuroshio-Oyashio Extension regions, and strong diabatic heating as well as interaction between upper and lower levels determines the genesis of these ETCs. The precipitation impact resulting from ETCs become strong in the order of Beijing ETCs, Seoul-N ETCs, Seoul-S ETCs, and Tokyo ETCs and accounts for up to 40%, 27%, 52%, and 70% of regional precipitation, respectively.

• Transactions of Materials Processing
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• v.31 no.4
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• pp.214-228
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• 2022

The yield criterion, or called yield function, plays an important role in the study of plastic working of a sheet because it governs the plastic deformation properties of the sheet during plastic forming process. In this paper, we propose a novel anisotropic yield function useful for describing the plastic behavior of various anisotropic sheets. The proposed yield function includes the anisotropic version of the second stress invariant J₂ and the third stress invariant J₃. The anisotropic yield function newly proposed in this study is as follows. F(J₂)+ αG(J₃)+ βH (J₂ × J₃) = k^m The proposed yield function well explains the anisotropic plastic behavior of various sheets by introducing the parameters α and β, and also exhibits both symmetrical and asymmetrical yield surfaces. The parameters included in the proposed model are determined through an optimization algorithm from uniaxial and biaxial experimental data under proportional loading path. In this study, the validity of the proposed anisotropic yield function was verified by comparing the yield surface shape, normalized uniaxial yield stress value, and Lankford's anisotropic coefficient R-value derived with the experimental results. Application for the proposed anisotropic yield function to aluminum sheet shows symmetrical yielding behavior and to pure titanium sheet shows asymmetric yielding behavior, it was shown that the yield curve and yield behavior of various types of sheet materials can be predicted reasonably by using the proposed new yield anisotropic function.

• Journal of KIBIM
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• v.12 no.2
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• pp.49-59
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• 2022

The main idea of this study is to propose a BIM-based automation system drawing up a report of energy conservation plan in the architecture division. In order to obtain a building permit, an energy conservation plan must be prepared for buildings with a total floor area of 500m² or more under the current law. Currently, it is adopted as a general method to complete a report by obtaining data and drawings necessary for an energy conservation plan through manual work and input them directly into the verification system. This method takes a lot of effort and time in the design phase which ultimately increases the initial cost of the business, including the services of companies specialized in the environmental field. However, in preparation for mandatory BIM work process in the future, it is necessary to introduce BIM-based automatic creation system that has an advantage for shortening the whole process to enable rapid permission of energy-saving designs for buildings. There may be many methods of automation, but this study introduces how to build an application using Dynamo of Revit, in terms of utilizing BIM, and write an energy conservation plan by automatic completion of report through Dynamo and Excel's VBA algorithm, which can save time and cost in preparing the report of energy conservation plan compared with the manual process. Also we have insisted that the digital transformation of architectural process is a necessary for an efficient use of our automation system in the current energy conservation plan workflow.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.