• Smart Structures and Systems
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• v.10 no.6
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• pp.573-591
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• 2012

In this study, a procedure to design an optimal LCVA that maximizes the equivalent damping ratio added to the primary structure subjected to along-wind excitation is proposed. That design procedure does not only consider the natural frequency and damping ratio of the LCVA, but also the proportion of the U-shaped liquid, which is closely related to the participation ratio of the liquid mass in inertial force. In addition, constraints to ensure the U-shape of the liquid are considered in the design process, so that suboptimal solutions that violate the optimal tuning law partly are adopted as a candidate of the optimal LCVA. The proposed design procedure of the LCVA is applied to the control of the 76-story benchmark building, and the optimal proportions of the liquid shape under various design conditions are compared.

• Smart Structures and Systems
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• v.12 no.2
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• pp.157-179
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• 2013

We present an approach, based on the state dependent Riccati equation, for designing non-collocated seismic response control strategies for buildings accounting for physical constraints, with particular attention to force saturation. We consider both cases of active control using general actuators and semi-active control using magnetorheological dampers. The formulation includes multi control devices, acceleration feedback and time delay compensation. In the active case, the proposed approach is a generalization of the classic linear quadratic regulator, while, in the semi-active case, it represents a novel generalization of the well-established modified clipped optimal approach. As discussed in the paper, the main advantage of the proposed approach with respect to existing strategies is that it allows to naturally handle a broad class of non-linearities as well as different types of control constraints, not limited to force saturation but also including, for instance, displacement limitations. Numerical results on a typical building benchmark problem demonstrate that these additional features are achieved with essentially the same control effectiveness of existing saturation control strategies.

• Journal of Information Processing Systems
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• v.14 no.3
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• pp.727-739
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• 2018

This study evaluates the viewpoints of user focus incidents using microblog sentiment analysis, which has been actively researched in academia. Most existing works have adopted traditional supervised machine learning methods to analyze emotions in microblogs; however, these approaches may not be suitable in Chinese due to linguistic differences. This paper proposes a new microblog sentiment analysis method that mines associated microblog emotions based on a popular microblog through user-building combined with spectral clustering to analyze microblog content. Experimental results for a public microblog benchmark corpus show that the proposed method can improve identification accuracy and save manually labeled time compared to existing methods.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.463-470
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• 2006

이 논문에서는 신경망 제어기와 MR 댐퍼를 이용하여 지진하중을 받는 지진격리 벤치마크 구조물의 응답 감소를 위한 반능동 제어방법이 제안되었다. 제안방법 중 신경망 제어기에는 적절한 제어력을 산출하기 위해 가격함수를 기반으로한 학습 알고리즘과 간편한 민감도 계산기법이 도입되었다. MR 댐퍼가 계산되어진 제어력과 비슷한 제어력을 낼 수 있도록 clipped 알고리즘을 이용하였고, 제안된 반능동 신경망 제어방법이 지진격리 장치가 설치된 벤치마크 구조물에 적용되었다. 수치해석에서는 벤치마크 문제를 정의한 논문에서 제공된 수동제어방법이나 예시제어방법과 제안 방법의 제어성능을 비교하였다. 수치해석 결과 제안방법은 지하 변위를 약간 증가시키지만, 각층의 가속도, base shear, building corner drift 등을 매우 효과적으로 줄이는 것으로 판명되었다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.292-297
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• 2020

자연어 추론 모델은 전제와 가설 사이의 의미 관계를 함의와 모순, 중립 세 가지로 판별한다. 영어에서는 RTE(recognizing textual entailment) 데이터셋과 다양한 NLI(Natural Language Inference) 데이터셋이 이러한 모델을 개발하고 평가하기 위한 벤치마크로 공개되어 있다. 본 연구는 국외의 텍스트 추론 데이터 주석 가이드라인 및 함의 데이터를 언어학적으로 분석한 결과와 함의 및 모순 관계에 대한 의미론적 연구의 토대 위에서 한국어 자연어 추론 벤치마크 데이터 구축 방법론을 탐구한다. 함의 및 모순 관계를 주석하기 위하여 각각의 의미 관계와 관련된 언어 현상을 정의하고 가설을 생성하는 방안에 대하여 제시하며 이를 바탕으로 실제 구축될 데이터의 형식과 주석 프로세스에 대해서도 논의한다.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.304-310
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• 2011

The populations of major cities in Australia are increasing rapidly and facing an acute housing shortage. Traditional apartment procurement techniques involve lengthy lead-times and factory-based, or offsite manufactured (OSM) multi-storey apartment buildings may offer the opportunity to help fulfill the need by significantly reducing build times. Other advantages of OSM may include superior quality, low weight ratios, economies of scale achieved through repetition of prefabricated units, use on infill sites, sustainable design standards and better occupational health and safety. There are also positive labour and training implications, which may help to alleviate an industry-wide shortage of skills through use of semi-skilled labour. Previous uncertainties about the adoption of offsite due to the high capital costs and perception issues were generally based on pre-cast concrete structures, which are quite a different building type in terms of flexibility, construction, delivery and finishes. Identification of drivers and constraints assists in the determination of current industry status, allows for a benchmark to be established and future opportunities and directions for OSM to be determined.

• Smart Structures and Systems
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• v.8 no.1
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• pp.119-137
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• 2011

A bio-inspired two-mode structural health monitoring (SHM) system based on the Na$\ddot{i}$ve Bayes (NB) classification method is discussed in this paper. To implement the molecular biology based Deoxyribonucleic acid (DNA) array concept in structural health monitoring, which has been demonstrated to be superior in disease detection, two types of array expression data have been proposed for the development of the SHM algorithm. For the micro-vibration mode, a two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded structural time history while an ARX process is applied for the analysis of the earthquake mode. The health condition of the structure is then determined using the NB classification method. In addition, the union concept in probability is used to improve the accuracy of the system. To verify the performance and reliability of the SHM algorithm, a downscaled eight-storey steel building located at the shaking table of the National Center for Research on Earthquake Engineering (NCREE) was used as the benchmark structure. The structural response from different damage levels and locations was collected and incorporated in the database to aid the structural health monitoring process. Preliminary verification has demonstrated that the structure health condition can be precisely detected by the proposed algorithm. To implement the developed SHM system in a practical application, a SHM prototype consisting of the input sensing module, the transmission module, and the SHM platform was developed. The vibration data were first measured by the deployed sensor, and subsequently the SHM mode corresponding to the desired excitation is chosen automatically to quickly evaluate the health condition of the structure. Test results from the ambient vibration and shaking table test showed that the condition and location of the benchmark structure damage can be successfully detected by the proposed SHM prototype system, and the information is instantaneously transmitted to a remote server to facilitate real-time monitoring. Implementing the bio-inspired two-mode SHM practically has been successfully demonstrated.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.37-46
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• 2006

In this study, the efficacy of the newly developed smart passive control system to improve seismic performance of base isolated building structures is numerically verified. The smart passive control system consists of a magnetorheological (MR) damper and an electromagnetic induction (EMI) part. The damping characteristics of an MR damper can be controlled by the current generated in an EMI part according to the Faraday's law of electromagnetic induction. An EMI part consisting of a permanent magnet and a solenoid coil could substitute a control system including sensors, a controller and an external power supply in a conventional smart control system. The benchmark control problem for a base isolated building presented by the american society of civil engineers is considered for numerical simulation. The control performance of the smart passive control system is compared to that of the conventional smart control system using MR dampers. It is demonstrated from the numerical simulation results that the smart passive control system is useful to improve the seismic performance of base isolated buildings.

• Wind and Structures
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• v.36 no.6
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• pp.393-404
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• 2023

Skewness and kurtosis are important higher-order statistics for simulating non-Gaussian wind pressure series on low-rise buildings, but their predictions are less studied in comparison with those of the low order statistics as mean and rms. The distribution gradients of skewness and kurtosis on roofs are evidently higher than those of mean and rms, which increases their prediction difficulty. The conventional artificial neural networks (ANNs) used for predicting mean and rms show unsatisfactory accuracy in predicting skewness and kurtosis owing to the limited capacity of shallow learning of ANNs. In this work, the deep neural networks (DNNs) model with the ability of deep learning is introduced to predict the skewness and kurtosis on a low-rise building. For obtaining the optimal generalization of the DNNs model, the hyper parameters are automatically determined by Bayesian Optimization (BO). Moreover, for providing a benchmark for future studies on predicting higher order statistics, the data sets for training and testing the DNNs model are extracted from the internationally open NIST-UWO database, and the prediction errors of all taps are comprehensively quantified by various error metrices. The results show that the prediction accuracy in this study is apparently better than that in the literature, since the correlation coefficient between the predicted and experimental results is 0.99 and 0.75 in this paper and the literature respectively. In the untrained cornering wind direction, the distributions of skewness and kurtosis are well captured by DNNs on the whole building including the roof corner with strong non-normality, and the correlation coefficients between the predicted and experimental results are 0.99 and 0.95 for skewness and kurtosis respectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.429-436
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• 2014

This paper presents the seismic performance of a geometrically unsymmetrical reinforced concrete building considering torsional effect and material nonlinearity of concrete and steel. The reinforced concrete building is a structure for seismic performance evaluation in the SMART-2013 international benchmark program. Nonlinear constitutive models for concrete and steel were constructed, and their numerical performance was demonstrated by various local tests. Modal analysis showed that the first three natural frequencies and mode shapes were close to the experimental results from the SMART-2013 program. In the time history analysis for low-intensity seismic loadings, displacement and acceleration responses at sampling points were similar to the experimental results. In the end, nonlinear time history analysis was conducted for Northridge earthquake to predict the behavior of the reinforced concrete structure under high-intensity seismic loadings.