• Structural Engineering and Mechanics
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• v.88 no.5
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• pp.501-519
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• 2023

This paper introduces a new hybrid structural connection joint that combines shear walls with section steel beams, fundamentally resolving the construction complexity issue of requiring pre-embedded connectors in the connection between shear walls and steel beams. Initially, a quasi-static loading scheme with load-deformation dual control was employed to conduct low-cycle repeated loading experiments on five new connection joints. Data was acquired using displacement and strain gauges to compare the energy dissipation coefficients of each specimen. The destruction process of the new connection joints was meticulously observed and recorded, delineating it into three stages. Hysteresis curves and skeleton curves of the joint specimens were plotted based on experimental results, summarizing the energy dissipation performance of the joints. It's noteworthy that the addition of shear walls led to an approximate 17% increase in the energy dissipation coefficient. The energy dissipation coefficients of dog-bone-shaped connection joints with shear walls and cover plates reached 2.043 and 2.059, respectively, exhibiting the most comprehensive hysteresis curves. Additionally, the impact of laminated steel plates covering composite concrete floors on the stiffness of semi-rigid joint ends under excessive stretching should not be disregarded. A comparison with finite element analysis results yielded an error of merely 2.2%, offering substantial evidence for the wide-ranging application prospects of this innovative joint in seismic performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.718-723
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• 2017

When structural analysis modelling methods of practical fields are investigated, a slab is generally modeled by a finite element mesh using plate elements and a shear wall is modeled using a shell element or wall element for 3-D structural analysis. The point worthy of notice in this practice is that a shear wall is modelled using only one wall or shell element divided by floors and column lines to produce structural models. The modeling method like this can cause analysis errors according to the type of computer programs in use, and these errors reduce the reliability of the analysis results. Therefore, to secure the reliability of structural analysis, studies of the causes of errors and finding reasonable modeling methods are necessary. In this study, the causes of analysis errors according to the modelling methods of a shear wall, which are used in practical fields, were investigated and some considering matters for modelling a shear wall are presented to reduce the analysis errors on these analysis results.

• KIEAE Journal
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• v.10 no.5
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• pp.159-164
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• 2010

High-rising buildings are a sort of solution to recent cities. Till now real estate development was concentrated in new development on vacant lots, and it resulted urban sprawl. Generally large cities are confronted with the exodus of industry and population from city. High-rising buildings solve many problems associated with this problem. The purpose of this research is to identify the effect of super high-rise mixed use building project process on apartment price. For this study, the hypothesis is that price of apartments is influenced by project process of super high-rise mixed use building. The study concerned 4 variations of project process that is building permits stage, sale stage, construction starting stage and stage of moving into building. The target projects of buildings are selected by number of floor(over 40 floors) and construction time. And 48 apartment complex are selected around super high-rise mixed use building. This study uses hedonic price function to analysis effect of project process of super high-rise mixed use building. A price of apartments is defined as a dependent variable. Characteristics of residence, complex, district and super high-rise building are defined as independent variables. The results are as follows; first, there is no error in price model of this study. Second, it is found that apartment price was influenced negatively by building permit stage and sale stage of super high-rise mixed use building. But that was influenced positively by construction starting stage and stage of moving into building of that. Third, as the project process of super high-rise mixed use building was proceeded, price of apartments was increased.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.4
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• pp.271-277
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• 2020

There are increasing cases of monitoring the structural response of structures using multiple sensors. However, owing to cost and management problems, limited sensors are installed in the structure. Thus, few structural responses are collected, which hinders analyzing the behavior of the structure. Therefore, a technique to predict responses at a location where sensors are not installed to a reliable level using limited sensors is necessary. In this study, a numerical study is conducted to predict the seismic response of low-rise buildings using limited information. It is assumed that the available response information is only the acceleration responses of the first and top floors. Using both information, the first natural frequency of the structure can be obtained. The acceleration information on the first floor is used as the ground motion information. To minimize the error on the acceleration history response of the top floor and the first natural frequency error of the target structure, the method for predicting the mass and stiffness information of a structure using the genetic algorithm is presented. However, the constraints are not considered. To determine the range of design variables that mean the search space, the parameter prediction method based on artificial neural networks is proposed. To verify the proposed method, a five-story structure is used as an example.

• The Journal of the Acoustical Society of Korea
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• v.30 no.2
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• pp.92-99
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• 2011

In Japan, bang machine has been considered to have problems about not only the impact force and frequency response which are different from the real impact sources such as children's jumping and running, but also damage in the wooden structure housing. Therefore, a new impactor for lower impact force to prevent demage in wooden structure housing was developed. The impact ball was adopted as the second standard impact source in JIS A 1418-2 and ISO 140-11. In the present study, floor impact sounds generated by impact ball with drop heights in four floors of mock-up building of Building Research Institute (BRI) similar to typical Japanese wooden structure housing were investigated and also compared to jumping sound. The results show that Impact ball sound dropped at 10 cm to 30 cm was most similar to jumping sound. And The impact sound levels at 250 and 500 Hz were more sensitive to drop height than other lower frequencies. The error that may occur from the difference of height of 10 cm up and down based on the standard drop height caused by the impact ball operated by human hands was approx. 1 dB or less only in its value of characteristic, but it must be carefully taken into Impact ball in the Korea Standard.

• Journal of the Society of Disaster Information
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• v.17 no.4
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• pp.684-693
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• 2021

Purpose: The purpose is to establish a safe facility environment from abnormal voltages such as lightning by developing a smart land resistance measuring device that can acquire real-time land resistance data using Arduino. Method: This paper studied design models and application cases by developing a land resistance acquisition and analysis system with Arduino and a power line communication (PLC) system. Some sites in the wind power generation complex in Gyeongsangnam-do were selected as test beds, and real-time land resistance data applied with new technologies were obtained. The electrode arrangement adopted a smart electrode arrangement using a combination of a Wenner four electrode arrangement and a Schlumberger electrode arrangement. Result: First, the characteristic of this technology is that the depth of smart multi-electrodes is organized differently to reduce the error range of the acquired data even in the stratigraphic structure with specificity between floors. Second, IT convergence technology was applied to enable real-time transmission and reception of information on land resistance data acquired from smart ground electrodes through the Internet of Things. Finally, it is possible to establish a regular management system and analyze big data accumulated in the server to check the trend of changes in various elements, and to model the optimal ground algorithm and ground system design for the IT convergence environment. Conclusion: This technology will reduce surge damage caused by lightning on urban infrastructure underlying the 4th industrial era and design an optimized ground system model to protect the safety and life of users. It is also expected to secure intellectual property rights of pure domestic technology to create jobs and revitalize our industry, which has been stagnant as a pandemic in the post-COVID-19 era.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.101-108
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• 2024

Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.