• Earthquakes and Structures
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• 제12권5호
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• pp.569-581
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• 2017

The Monte Carlo Simulation (MCS) based seismic fragility analysis (SFA) approach allows defining more realistic relationship between failure probability and seismic intensity. However, the approach requires simulating large number of nonlinear dynamic analyses of structure for reliable estimate of fragility. It makes the approach computationally challenging. The response surface method (RSM) based metamodeling approach which replaces computationally involve complex mechanical model of a structure is found to be a viable alternative in this regard. An adaptive moving least squares method (MLSM) based RSM in the MCS framework is explored in the present study for efficient SFA of existing structures. In doing so, the repetition of seismic intensity for complete generation of fragility curve is avoided by including this as one of the predictors in the response estimate model. The proposed procedure is elucidated by considering a non-linear SDOF system and an existing reinforced concrete frame considered to be located in the Guwahati City of the Northeast region of India. The fragility results are obtained by the usual least squares based and the proposed MLSM based RSM and compared with that of obtained by the direct MCS technique to study the effectiveness of the proposed approach.

• Wind and Structures
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• 제27권3호
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• pp.199-211
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• 2018

This paper deals with wind fragility and risk analysis of high rise buildings subjected to stochastic wind load. Conventionally, such problems are dealt in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, to make the procedure computationally efficient, application of metamodelling technique in fragility analysis is explored in the present study. Since, accuracy by the conventional Least Squares Method (LSM) based metamodelling is often challenged, an efficient Moving Least Squares Method based adaptive metamodelling technique is proposed for wind fragility analysis. In doing so, artificial time history of wind load is generated by three wind field models: i.e., a simple one based on alongwind component of wind speed; a more detailed one considering coherence and wind directionality effect, and a third one considering nonstationary effect of mean wind. The results show that the proposed approach is more accurate than the conventional LSM based metamodelling approach when compared to full simulation approach as reference. At the same time, the proposed approach drastically reduces computational time in comparison to the full simulation approach. The results by the three wind field models are compared. The importance of non-linear structural analysis in fragility evaluation has been also demonstrated.

• 한국전산구조공학회논문집
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• 제20권4호
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• pp.501-507
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• 2007

본 연구의 전편에서는 이동최소제곱 유한차분법을 이용한 고체역학문제의 정식화 과정이 소개되었다. 후편에서는 수치예제를 통해 이동최소제곱 유한차분법의 정확성, 강건성, 효율성을 검증했다. 탄성론 문제의 해석을 통해 개발된 해석기법의 우수한 수렴률을 확인했다. 탄성균열문제에 적용하여 간편한 불연속면 모델링이 가능하고, 적응적 절점배치를 통해 특이 응력해를 정확하고 효율적으로 계산할 수 있음을 보였다. 국소화 밴드문제 해석결과를 통해 변위나 응력이 급격하게 변화하는 특수문제에 대한 정확성과 효율성을 확인했으며, 본 해석기법이 다양한 특수 공학적 문제로 확장될 수 있을 것으로 기대된다.

• 대한기계학회논문집A
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• 제30권12호
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• pp.1626-1633
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• 2006

In the present paper, in the context of the meshless interpolation of a moving least squares (MLS) type, a novel method which uses primary and secondary nodes in the domain and on the global boundary is introduced, in order to improve the accuracy of solution. The secondary nodes can be placed at any location where one needs to obtain a better resolution. The support domains for the shape functions in the MLS approximation are defined from the primary nodes, and the secondary nodes use the same support domains. The shape functions based on the MLS approximation, in an integration domain, have a single type of a rational function, which reduces the difficulty of numerical integration to evaluate the weak form. The present method is very useful in an adaptive calculation, because the secondary nodes can be easily added and moved without an additional mesh. Several numerical examples are presented to illustrate the effectiveness of the present method.

• 한국컴퓨터그래픽스학회논문지
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• 제19권3호
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• pp.1-11
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• 2013

FLIP 기반의 유체 시뮬레이션은 품질에 대비 높은 효율을 자랑하기 때문에 Visual Effect(VFX)산업에 널리 사용되고 있다. FLIP 기술에서는 바다와 같은 대규모의 물을 시뮬레이션 할 때 시각적으로 중요하지 않은 물의 안쪽까지도 파티클을 할당해야 하기 때문에 보이는 파티클보다 보이지 않는 파티클의 개수가 훨씬 많은 경우에는 시뮬레이션 작업의 효율성이 떨어진다. 본 논문에서는 이러한 단점을 보완하기 위하여 레벨셋 (Level Set)과 Fluid Implicit Particle(FLIP) 기반의 유체 시뮬레이션 기법을 혼합(hybrid)한 효율적인 유체 시뮬레이션 기법을 제안한다. 파티클들을 물의 안쪽 표면 근처의 얇은 층에만 배치함으로써 사용되는 파티클의 갯수를 줄여서 결과적으로 시뮬레이션의 효율성을 크게 높일 수 있었다. 또한 [1]의 표면 재구성 기법과 moving least squares(MLS) [2] 기법을 결합한 새로운 유체 표면 재구성 기법을 적용하여 FLIP을 통해 격자(Grid) 기반 시뮬레이션에서 발생하는 수치적 소실을 줄이고 동시에 유체의 부드러운 표면을 유지할 수 있다. 본 논문의 혼합 시뮬레이션 기술은 높은 품질의 유체 시뮬레이션을 효율적으로 수행하여 다양한 규모의 유체를 표현할 수 있었다.

• Journal of Positioning, Navigation, and Timing
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• 제5권1호
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• pp.1-9
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• 2016

Range-based wireless localization system must measure accurate range between a mobile node (MN) and reference nodes. However, non-line-of-sight (NLOS) error caused by the spatial structures disturbs the localization system obtaining the accurate range measurements. Localization methods using the range measurements including NLOS error yield large localization error. But filter-based localization methods can provide comparatively accurate location solution. Motivated by the accuracy of the filter-based localization method, a filter residual-based NLOS error estimation method is presented in this paper. Range measurement-based residual contains NLOS error. By considering this factor with NLOS error properties, NLOS error is mitigated. Also a process noise covariance matrix tuning method is presented to reduce the time-delay estimation error caused by the single dynamic model-based filter when the speed or moving direction of a MN changes, that is the used dynamic model is not fit the current dynamic of a MN. The presented methods are evaluated by simulation allowing direct comparison between different localization methods. The simulation results show that the presented filter is more accurate than the iterative least squares- and extended Kalman filter-based localization methods.

• 전기학회논문지
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• 제60권1호
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• pp.205-213
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• 2011

The Long Term Evolution (LTE) system is designed to provide a high quality data service for fast moving mobile users. It is based on the Orthogonal Frequency Division Multiplexing (OFDM) and relies its channel estimation on the training samples which are systematically built within the transmitting data. Either a preamble or a lattice type is used for the distribution of training samples and the latter suits better for the multipath fading channel environment whose channel frequency response (CFR) fluctuates rapidly with time. In the lattice-type structure, the estimation of the CFR makes use of the least squares estimate (LSE) for each pilot samples, followed by an interpolation both in time-and in frequency-domain to fill up the channel estimates for subcarriers corresponding to data samples. All interpolation schemes should rely on the pilot estimates only, and thus, their performances are bounded by the quality of pilot estimates. However, the additive noise give rise to high fluctuation on the pilot estimates, especially in a communication environment with low signal-to-noise ratio. These high fluctuations could be monitored in the alternating high values of the first forward differences (FFD) between pilot estimates. In this paper, we analyzed statistically those FFD values and propose a postprocessing algorithm to suppress high fluctuations in the noisy pilot estimates. The proposed method is based on a localized adaptive moving-average filtering. The performance of the proposed technique is verified on a multipath environment suggested on a 3GPP LTE specification. It is shown that the mean-squared error (MSE) between the actual CFR and pilot estimates could be reduced up to 68% from the noisy pilot estimates.