• 한국구조물진단유지관리공학회 논문집
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• 제2권4호
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• pp.137-147
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• 1998

The neural net application was tried to develop the technique for monitoring the health status of a steel truss bridge which was scaled down to 1/15 of the real bridge for the laboratory experiments. The damage scenarios were chosen as 7 cases. The dynamic behavior, which was changed due to the breakage of the members, of the bridge was investigated by finite element analysis. The bridge consists of single spam, and eight (8) main structural subsystems. The loading vehicle, which weighs as 100 kgf, was operated by the servo-motor controller. The accelerometers were bonded on the surface of 7 cross-beams to measure the dynamic behavior induced by the abnormal structural condition. Artificial neural network technique was used to determine the severity of the damage. At first, the neural net was learnt by the results of finite element analysis, and also, the maximum detection error was 3.65 percents. Another neural net was also learnt, and verified by the experimental results, and in this case, the maximum detection error was 1.05 percents. In future study, neural net is necessary to be learnt and verified by various data from the real bridge.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제10권3호
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• pp.169-187
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• 2006

Ubiquitous errors in algebra like $(x+y)^2=x^2+y^2$ are a constant reminder that most students' manipulation of algebraic symbols has become detached from structural principles. The U.S. mathematics education community (NCTM, 2000) has responded by shying away from algebra as a structural study, preferring instead to ground meaning in empirical domains of reference. A new analysis of such errors shows that students' detachment from structural meaning stems from an inadequate structural curriculum, not from the inherent difficulty of adopting an abstract perspective on expressions and equations. A structural curriculum is outlined that preserves the possibility of students' engaging fully with algebra as both an empirical and a structural study.

• 한국항공우주학회지
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• 제43권9호
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• pp.781-786
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• 2015

공력탄성학적 안정성 해석에 있어서 모델링 오차 및 구조 불확도에 의해 결과의 정확도는 떨어질 수 있다. 따라서, 이러한 모델링 오차 및 구조 불확도를 고려한 공탄성 안정성 경계를 예측할 필요가 있다. 이러한 모델링 오차 및 불확도를 고려한 공탄성 안정성 예측을 위해 강건 공탄성 해석이 제안되었다. 본 연구에서는 ${\mu}$ 해석기법과 모달접근법과 MSA를 사용한 조종날개의 공탄성 모델로 부터 강건 공탄성 모델링과 해석을 수행하였다. 강건 공탄성 해석 프로그램이 개발되었고, 기존의 공탄성 해석 결과와 비교/검증하였다.

• 한국건축시공학회지
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• 제23권2호
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• pp.209-220
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• 2023

먹매김 로봇은 허용오차 이내의 정밀도를 확보하는 것이 매우 중요하다. 그러나 골조공사는 시공과정에서 철근배근의 변위가 빈번하게 발생하며, 해당오차는 먹선이나 철근위치의 수정을 요구한다. 먹매김 로봇은 정밀도 확보 및 자동화를 위해 철근의 오차를 측정하고 먹선과 철근의 수정을 스스로 판단할 수 있어야 한다. 이에 본 연구는 LiDAR 센서를 통한 철근배근의 오차 측정방안과 이를 바탕으로 먹매김 판단 프로세스를 제시하였다. LiDAR 센서를 활용한 철근인식 실험결과 평균적으로 5mm 내외의 오차를 발생하였으며, 이는 일반적으로 벽체에 적용되는 철근 수준에서 인식을 신뢰할만한 수준으로 나타났다. 또한 철근오차를 범위별로 판단하여 철근의 보정여부와 먹매김의 수행여부를 로봇이 스스로 판단할 수 있는 프로세스를 제시하였다. 본 연구결과는 시공오차를 고려한 먹매김로봇의 자동운영에 기여할 수 있으며 이를 통해 골조품질을 향상시킬 수 있을 것으로 기대된다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 가을 학술발표회 논문집
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• pp.461-468
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• 2004

Modal participation factor(MPF) is essential to analyze structural response under earthquake load. MPF of real structure differs from that of analytic mathematical model due to the error induced from analytical assumption and construction. In this study, a identification method is proposed to calculate the MPF of real structure based on H∞ optimal model reduction. The MPF is obtained from the relationship between observability, controllability matrix of realized from S.I. and typical 2-degree state space model. The proposed method is verified thorough examples.

• Computers and Concrete
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• 제14권3호
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• pp.233-245
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• 2014

In this paper, a rule based Mamdani type fuzzy logic model for prediction of slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes were discussed. In the model steel rebar diameters and development lengths were used as inputs. The FL model and experimental results, the coefficient of determination R2, the Root Mean Square Error were used as evaluation criteria for comparison. It was concluded that FL was practical method for predicting slippage at maximum tensile strength and slippage at rupture of structural lightweight concretes.

• Journal of the Korean Statistical Society
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• 제36권4호
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• pp.501-522
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• 2007

We propose an estimation procedure that can be used for detecting structural changes in the seasonal cointegrated vector autoregressive model. The asymptotic properties of the estimates and the test statistics for the parameter change are provided. A simulation example is presented to illustrate this method and its concept.

• 한국항만경제학회지
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• 제19권2호
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• pp.55-67
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• 2003

The purpose of this study is to estimate and forecast the marine trading volumes based on the structural model. We employ GPH cointegration test since the structural model must be stationary to get the accurate predicted values. The empirical results show that our model is stationary. This paper also applies variance decompositions and impulse-response functions to the structural model composed of exchange rate, domestic industrial activity, and world business. The results indicate that while both loading and unloading volumes respond positively to the shocks in income and then decay very slowly, their responses are different to the shocks in exchange tate.

• Smart Structures and Systems
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• 제31권2호
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• pp.101-111
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• 2023

Structural health monitoring (SHM) covers a range of damage detection strategies for buildings. In real-time, SHM provides a basis for rapid decision making to optimise the speed and economic efficiency of post-event response. Previous work introduced an SHM method based on identifying structural nonlinear hysteretic parameters and their evolution from structural force-deformation hysteresis loops in real-time. This research extends and generalises this method to investigate the impact of a wide range of flag-shaped or pinching shape nonlinear hysteretic response and its impact on the SHM accuracy. A particular focus is plastic stiffness (K_p), where accurate identification of this parameter enables accurate identification of net and total plastic deformation and plastic energy dissipated, all of which are directly related to damage and infrequently assessed in SHM. A sensitivity study using a realistic seismic case study with known ground truth values investigates the impact of hysteresis loop shape, as well as added noise, on SHM accuracy using a suite of 20 ground motions from the PEER database. Monte Carlo analysis over 22,000 simulations with different hysteresis loops and added noise resulted in absolute percentage identification error (median, (IQR)) in K_p of 1.88% (0.79, 4.94)%. Errors were larger where five events (Earthquakes #1, 6, 9, 14) have very large errors over 100% for resulted K_p as an almost entirely linear response yielded only negligible plastic response, increasing identification error. The sensitivity analysis shows accuracy is reduces to within 3% when plastic drift is induced. This method shows clear potential to provide accurate, real-time metrics of non-linear stiffness and deformation to assist rapid damage assessment and decision making, utilising algorithms significantly simpler than previous non-linear structural model-based parameter identification SHM methods.

• Structural Engineering and Mechanics
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• 제8권5호
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• pp.513-529
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• 1999

A concept of hierarchical modeling, the newest modeling technology, has been introduced in early 1990's. This new technology has a great potential to advance the capabilities of current computational mechanics. A first step to implement this concept is to construct hierarchical models, a family of mathematical models sequentially connected by a key parameter of the problem under consideration and have different levels in modeling accuracy, and to investigate characteristics in their numerical simulation aspects. Among representative model problems to explore this concept are elastic structures such as beam-, arch-, plate- and shell-like structures because the mechanical behavior through the thickness can be approximated with sequential accuracy by varying the order of thickness polynomials in the displacement or stress fields. But, in the numerical, analysis of hierarchical models, two kinds of errors prevail, the modeling error and the numerical approximation error. To ensure numerical simulation quality, an accurate estimation of these two errors is definitely essential. Here, a local a posteriori error estimator for elastic structures with thin domain such as plate- and shell-like structures is derived using the element residuals and the flux balancing technique. This method guarantees upper bounds for the global error, and also provides accurate local error indicators for two types of errors, in the energy norm. Compared to the classical error estimators using the flux averaging technique, this shows considerably reliable and accurate effectivity indices. To illustrate the theoretical results and to verify the validity of the proposed error estimator, representative numerical examples are provided.