• Earthquakes and Structures
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• 제22권2호
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• Smart Structures and Systems
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• 제30권6호
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• pp.613-626
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• 2022

Guaranteeing the quality and integrity of structural health monitoring (SHM) data is very important for an effective assessment of structural condition. However, sensory system may malfunction due to sensor fault or harsh operational environment, resulting in multiple types of data anomaly existing in the measured data. Efficiently and automatically identifying anomalies from the vast amounts of measured data is significant for assessing the structural conditions and early warning for structural failure in SHM. The major challenges of current automated data anomaly detection methods are the imbalance of dataset categories. In terms of the feature of actual anomalous data, this paper proposes a data anomaly detection method based on data-level and deep learning technique for SHM of civil engineering structures. The proposed method consists of a data balancing phase to prepare a comprehensive training dataset based on data-level technique, and an anomaly detection phase based on a sophisticatedly designed network. The advanced densely connected convolutional network (DenseNet) and Transformer encoder are embedded in the specific network to facilitate extraction of both detail and global features of response data, and to establish the mapping between the highest level of abstractive features and data anomaly class. Numerical studies on a steel frame model are conducted to evaluate the performance and noise immunity of using the proposed network for data anomaly detection. The applicability of the proposed method for data anomaly classification is validated with the measured data of a practical supertall structure. The proposed method presents a remarkable performance on data anomaly detection, which reaches a 95.7% overall accuracy with practical engineering structural monitoring data, which demonstrates the effectiveness of data balancing and the robust classification capability of the proposed network.

• Steel and Composite Structures
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• 제47권2호
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• pp.147-165
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• 2023

The paper contrasts conventional seismic design with a design that incorporates buckling-restrained bracing in three-dimensional reinforced concrete buildings (BRBs). The suboptimal structures may be found using the multi-objective chimp optimization algorithm (MEN-ChOA). Given the constraints and dimensions, ChOA suffers from a slow convergence rate and tends to become stuck in local minima. Therefore, the ChOA is improved by niching and evolutionary operators to overcome the aforementioned problems. In addition, a new technique is presented to compute seismic and dead loads that include all of a structure's parts in an algorithm for three-dimensional frame design rather than only using structural elements. The performance of the constructed multi-objective model is evaluated using 12 standard multi-objective benchmarks proposed in IEEE congress on evolutionary computation. Second, MEN-ChOA is employed in constructing several reinforced concrete structures by the Mexico City building code. The variety of Pareto optimum fronts of these criteria enables a thorough performance examination of the MEN-ChOA. The results also reveal that BRB frames with comparable structural performance to conventional moment-resistant reinforced concrete framed buildings are more cost-effective when reinforced concrete building height rises. Structural performance and building cost may improve by using a nature-inspired strategy based on MEN-ChOA in structural design work.

• 한국공간구조학회논문집
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• 제22권4호
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• pp.15-22
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• 2022

Micro-climate measurements and computational fluid analysis were conducted to use it as basic data for the preservation and management of the old house of Kim Myung-kwan, a traditional building that is National Folk Cultural Property No. 26. As a result of the actual measurement, the temperature and humidity are relatively evenly distributed indoors unlike outdoors, but the temperature and humidity vary depending on the time change and the installation location in the outdoors. It was found that the temperature increases after dawn and the temperature varies depending on the installation position around 14:00-15:00, when the temperature becomes the highest. In particular, the temperature was high at the outdoor measurement point adjacent to the building and the fence. As a result of the computational fluid analysis, the temperature was high in the buildings and fences in the old house or in the area adjacent to the building, and it was about 1℃ higher than the surrounding area. In this area, it is judged that the thickening of wood will occur more severely than in other locations, and special preservation management is required.

• Smart Structures and Systems
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• 제31권3호
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• pp.229-245
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• 2023

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

• Earthquakes and Structures
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• 제25권1호
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• pp.1-13
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• 2023

Reinforced concrete (RC) moment frames are used as lateral seismic load resisting systems in mid- and high-rise buildings in different regions of the world. Based on the seismic design provisions and construction details presented in design codes, RC frames with different levels of ductility (ordinary, intermediate, and special) can be designed and constructed. In Iran, there are RC buildings with various uses which have been constructed based on different editions of design codes. The seismic performance of RC structures (particularly moment frames) in real seismic events is of great importance. In this paper, the observations made on damaged RC moment frames after the destructive Sarpol-e Zahab earthquake with a moment magnitude of 7.3 are reported. Different levels of damage from the development of cracks in the structural and non-structural elements to the total collapse of buildings were observed. Furthermore, undesirable failure modes which are not expected in ductile seismic-resistant buildings were frequently observed in the damaged buildings. The RC moment frames built based on the previous editions of the design codes showed partial or total collapse in this seismic event. The extensive destruction of RC moment frames compared with the other structural systems (such as braced steel frames and confined masonry buildings) was attributed not only to the deficiencies in the construction practice of these buildings but also to the design procedure. In addition, the failure and collapse of masonry infills in RC moment frames were frequent modes of failure in this seismic event. In this paper, the main reasons related to design practice which led to extensive damage in the RC moment frames and their collapse are addressed.

• Earthquakes and Structures
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• 제26권3호
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• pp.203-218
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• 2024

Beam-column joints in the frame structure are at high risk of brittle shear failure which would lead to significant residual deformation and even the collapse of the structure during an earthquake. In order to improve the damage issue and enhance the recoverability of the beam-column joints, a sector lead rubber damper (SLRD) has been developed. The SLRD can increase the bearing capacity and energy dissipation capacity, and also demonstrating recoverability of seismic performance following cyclic loading. In this paper, the hysteretic behavior of SLRD was experimentally investigated in terms of the regular hysteretic behavior, large deformation behavior and fatigue behavior. Furthermore, a parametric analysis was performed to study the influence of the primary design parameters on the hysteretic behavior of SLRD. The results show that SLRD resist the exerted loading through the shear capacity of both rubber parts coupled with the lead cores in the pre-yielding stage of lead cores. In the post-yielding phase, it is only the rubber parts of the SLRD that provide the shear capacity while the lead cores primarily dissipate the energy through shear deformation. The SLRD possesses a robust capacity for large deformation and can sustain hysteretic behavior when subjected to a loading rotation angle of 1/7 (equivalent to 200% shear strain of the rubber component). Furthermore, it demonstrates excellent fatigue resistance, with a degradation of critical behavior indices by no more than 15% in comparison to initial values even after 30 cycles. As for the designing practice of SLRD, it is recommended to adopt the double lead core scheme, along with a rubber material having the lowest possible shear modulus while meeting the desired bearing capacity and a thickness ratio of 0.4 to 0.5 for the thin steel plate.

• 한국구조물진단유지관리공학회 논문집
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• 제10권3호
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• pp.203-210
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• 2006

미래의 지진을 예측하는 것은 거의 불가능하지만 코드에서는 설계스펙트럼을 이용하여 미래 지진의 최소한의 일반적인 현상을 나타내고자 노력하고 있다. 기존의 고차모드의 영향을 반영하기 위한 방법은 조건이 맞는 지진을 선택하고 응답스펙트럼을 산정해야 하는 단점을 지니고 있다. 따라서 본 논문에서는 이러한 단점을 보완하고자 코드의 설계응답스펙트럼을 이용하여 바로 고차모드의 영향을 반영한 횡력 분배형태을 결정하는 방법을 제시하고 있다. 본 논문에서는 비정형적인 철골모멘트 골조를 이용하여 ATC-40, FEMA 273 그리고 본 논문에서 제안한 방법을 시간이력해석결과와 비교하여 우수성을 검증하였다. 하지만 제안한 방법은 시간이력해석결과에 비해 다소 보수적인 결과를 나타내었다.

• 콘크리트학회논문집
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• 제21권3호
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• pp.327-335
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• 2009

지진이 빈번하게 발생하는 지역에서는 비내진상세구조물은 지진 발생시 연약층을 형성하고 취성적 붕괴를 일으키게 된다. 그러나, 기존 구조물을 해체하고 내진상세 구조물을 신축하는 방법은 건설폐기물, 환경오염 및 민원 등 여러가지 문제들을 가지는 등 비경제적 방법이라 할 수 있다. 따라서 기존 구조물이 내진성능을 만족하도록 내진보강에 관한 많은 연구가 이루어졌으며, 이러한 내진보강방법에는 끼움벽, 철골브레이스, 연속벽, 부벽, 날개벽, 기둥/보의 자켓팅 등이 있다. 이 중 끼움벽 골조는 큰 변형과 접합부에서의 회전이 발생하는 골조와, 비교적 작은 변형에서도 전단파괴를 야기하는 끼움전단벽 등 복합적인 거동특성을 나타낸다. 따라서, 이러한 시스템의 거동특성은 개개의 골조나 벽에서 나타나는 거동특성과 매우 다르게 된다. 본 연구에서는 끼움벽의 내진성능을 평가하고자 하였으며, 손상에너지의 효과적 흡수를 위해 변형경화형 시멘트 복합체 (SHCC)를 사용하였다. 실험은 1/3 축소모형의 끼움벽을 반복가력하는 것으로 계획하였다. 실험 결과, SHCC 끼움벽에서는 섬유의 가교작용을 통해 시멘트 복합체 내 응력을 재분배함으로써 미세균열이 발생하였으며, 강도 및 에너지소산능력이 우수한 것으로 나타났다.

• 한국산학기술학회논문지
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• 제21권6호
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• pp.103-108
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• 2020

일반적으로 LPG 운반선의 화물창은 국제해사기구(IMO)에서 정의한 독립형 탱크 Type A에 해당하며, 탱크의 외부는 폴리우레탄 폼으로 단열하고, 탱크는 영하 50도에서도 견딜 수 있는 값비싼 저온 강으로 제작된다. 따라서, 화물창 재료의 절감은 많은 비용의 절감으로 직결된다. 화물창은 외판, 격벽, 보강재, 웨브 프레임 및 스트링거로 구성된다. 그 중에서 외판, 격벽과 보강재는 구조해석 없이 선급 규정에 의해 설계될 수 있어 용이하게 최적 설계를 통해 설계된다. 하지만, 웨브 프레임과 스트링거는 구조해석을 통해 설계하고 선급승인을 받아야 하므로, 수없이 많은 구조해석을 포함하는 최적 설계는 사실상 수행하지 못하고, 수 십 번의 구조해석을 통해 설계치수를 결정하는 적정설계만을 수행하는 실정이다. 본 연구에서는 유한요소해석을 위해 2번 화물창을 대표 화물창으로 선정하여 8개의 하중조건을 적용하였고, 각 하중조건에 대한 선박 전체의 변형을 고려하였다. 또한, 탐색시간이 효과적인 미분 기반 최적화 기법을 통해 82,000 ㎥ LNG 운반선의 웨브 프레임을 대상으로 최소중량설계를 수행하였다. 본 연구를 통해 총 48개의 설계변수 치수를 결정하였고, 척 당 약 108 톤의 강재를 절감하였다.