간행물
한국공간구조학회지 KCI 등재 JOURNAL OF THE KOREAN ASSOCIATION FOR AND SPATIAL STRUCTURES
- 발행기관 한국공간구조학회
- 자료유형 학술지
- 간기 계간
- ISSN 1598-4095 (Print)2287-7401 (Online)
- 수록기간 2001 ~ 2025
- 주제분류 공학 > 건축공학 공학 분류의 다른 간행물
- 십진분류KDC 540DDC 690
권호리스트/논문검색
제25권 제1호 통권99호 (2025년 3월) 11건
1.
2025.03
구독 인증기관 무료, 개인회원 유료
4,000원
2.
2025.03
구독 인증기관 무료, 개인회원 유료
4,000원
4.
2025.03
구독 인증기관 무료, 개인회원 유료
This study is a preliminary investigation into a method for updating analytical models using actual vibration measurement data to improve the reliability of the seismic performance evaluations. The research was conducted on 26 models with various parameters, aiming to develop an optimal analytical model that closely matches the natural frequencies of the actual building. By identifying the dynamic characteristics of the target building through vibration measurements taken just before the demolition of the structure, the natural frequency analysis results of the analytical models were compared to the measured data. Based on this comparison, an optimized method for adjusting the parameters of the analytical models was derived. Throughout the analysis, various parameters were adjusted, and the eigenvalue analysis results were corrected by comparing them with vibration measurements. Among the comparative analytical models, the model with the lowest error rate was selected. The results showed that, in all cases, the analytical model with a concrete compressive strength of 16 MPa (based on actual measurements), pin boundary conditions, and an idealized strip footing cross-section had the closest match to the actual building's natural frequencies, with an average error of less than 8%.
4,000원
5.
2025.03
구독 인증기관 무료, 개인회원 유료
This paper aims to quantify the retrofit effect of the Bolt Prefabricated Concrete-Filled Tube reinforcement method on non-seismic school reinforced concrete building through static cyclic loading experiments. To achieve the objective, two-story specimens including a non-retrofitted frame(NRF) and a Bolt Prefabricated Concrete-Filled Tube Reinforcement Frame(BCRF) were tested under static cyclic loading, and the lateral resistant capacities were compared in terms of maximum strength, initial stiffness, effective stiffness, and total energy dissipation. In addition, the load-displacement curves were compared to the story drift limit specified in Seismic Performance Evaluation and Retrofit Manual for School Facilities to investigate if the retrofitted frame was satisfied in target performance(life safety). Experimental results showed that BCRF successfully met the target performance, with a 200% increase in maximum strength and a 300% increase in energy dissipation capacity. Additionally, both initial stiffness and effective stiffness improved by more than 30% compared to NRF. Furthermore, BCRF exhibited an effect that delayed the occurrence of bond failure.
4,000원
6.
2025.03
구독 인증기관 무료, 개인회원 유료
In this study, static and dynamic analyses were conducted on three atypical building models to evaluate the displacement response reduction performance based on the outrigger system installation location in a atypical building that incorporated both tapered and twisted shapes. Three 60-story models were developed with a fixed 3-degree taper and twist angles of 1, 2, and 3 degrees per story. Outrigger systems were installed at 10-story intervals and additionally between the 20th and 40th floor at 1-story intervals. The results indicated that, although there were variations depending on the seismic loads, the displacement response reduction performance was generally most effective when the outriggers were installed in the upper stories (41st to 60th floors) of the analytical models.
4,000원
7.
2025.03
구독 인증기관 무료, 개인회원 유료
Reinforced concrete (RC) piloti buildings are vulnerable in the event of earthquake because the stiffness in the 1st story columns is weak to compare with the members in upper stories. In this study, seismic performances of RC piloti structures were evaluated considering with different types of floor plane layouts according to core eccentricity. With four types of floor plane layouts, five stories plioti structures were evaluated by two approaches, a nonlinear pushover analysis and a nonlinear time-history analysis. In order to improve seismic performances by satisfying the collapse prevention (CP) level, two ductile reinforcing methods by carbon fiber sheets and steel jackets were applied. Due to eccentricities in stiffness and mass with directions of plane and vertical stories, piloti structures were greatly influenced by higher order modes, so the seismic performances by the time-history analysis were significantly different from by the static pushover analysis.
4,000원
8.
2025.03
구독 인증기관 무료, 개인회원 유료
In this paper, the changes of the uniaxial tensile mechanical properties of the ETFE film after the uniaxial pre-stretching stress exceeds the first yield stress and the second yield stress was investigated. The ETFE film is first pre-stretched uniaxially along the MD direction or TD direction. After the pre-stretching loading stress exceeds the first yield stress and the second yield stress to cause the ETFE film to undergo plastic deformation, rectangular uniaxial tensile specimens are cut from the pre-stretched film along the MD direction and the TD direction for subsequent uniaxial tensile tests, thereby determining the uniaxial tensile mechanical property parameters of the ETFE film after uniaxial pre-stretching, including yield stress, tensile strength and elongation at break, and discussing the changes in its uniaxial tensile mechanical properties.
4,000원
9.
2025.03
구독 인증기관 무료, 개인회원 유료
Automated structural design methods for reinforced concrete (RC) beam members have been widely studied with various techniques to date. Recently, artificial intelligence has been actively applied to various engineering fields. In this study, machine learning (ML) is adopted to make automated structural design model for RC beam members. Among various machine learning methods, a supervised learning was selected. When a supervised learning is applied to development of ML-based prediction model, datasets for training and test are required. Therefore, the datasets for rectangular and t-shaped RC beams was constructed by commercial structural design software of MIDAS. Five supervised learning algorithms, such as Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost) were used to develop the automated structural design model. Design moment (Mu), design shear force (Vu), beam length, uniform load (wu) were used for inputs of structural design model. Width and height of the designed section, diameter of top and bottom bars, number of top and bottom bars, diameter of stirrup bar were selected for outputs of structural design model. Performance evaluation of the developed structural design models was conducted using metrics sush as root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). This study presented that random forest provides the best structural design results for both rectangular and t-shaped RC beams.
4,000원
10.
2025.03
구독 인증기관 무료, 개인회원 유료
Damage to masonry walls can occur for various factors. It is often believed that heavy rains and increased rainfall cause soil and sand to flow into the stone masonry walls, leading to this damage. However, no research has definitively proven or analyzed this causal relationship.This study aims to evaluate the causes of damage to masonry walls due to severe rainfall and to propose preventive strategies to mitigate future risks. The assessment found that, as a form of cultural heritage, the stone masonry walls did not exhibit any structural or material issues that could compromise their stability. However, concerns were raised about potential problems arising from hydraulic pressure due to rising groundwater levels. Calculations and computer simulations confirmed that the risk of collapse increases with higher groundwater levels. Therefore, it is essential to carry out repairs and reinforcements to prevent a recurrence of this situation.
4,000원
11.
2025.03
구독 인증기관 무료, 개인회원 유료
Truss structures, widely used in engineering, consist of straight members transferring axial forces. Traditional analysis methods like FEM and the Force Method become computationally expensive for large-scale and nonlinear problems. Surrogate models using Artificial Neural Networks (ANNs), particularly Physics-Informed Neural Networks (PINNs), offer alternatives but require extensive training data and computational resources. Variational Quantum Algorithms (VQAs) address these challenges by leveraging quantum circuits for optimization with fewer parameters. Variational Quantum Circuits (VQCs) based on Quantum Neural Networks (QNNs) utilize quantum entanglement and superposition to approximate high-dimensional data efficiently, making them suitable for computationally intensive tasks like surrogate modeling in structural analysis. This study applies QNNs to truss analysis using 6-bar and 10-bar planar trusses, assessing their feasibility. Results indicate that residual-based loss functions enable QNNs to make reliable predictions, with increased layers improving accuracy and a higher Q-bit count contributing to performance, albeit marginally.
4,000원
