• 한국지반환경공학회 논문집
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• 제16권5호
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• pp.13-25
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• 2015

This paper proposes an extended model evaluation method that considers not only the model performance but also the model structure and parameter uncertainties in hydrologic modeling. A simple reservoir model (SFM) and distributed kinematic wave models (KWMSS1 and KWMSS2 using topography from 250-m, 500-m, and 1-km digital elevation models) were developed and assessed by three evaluative criteria for model performance, model structural stability, and parameter identifiability. All the models provided acceptable performance in terms of a global response, but the simpler SFM and KWMSS1 could not accurately represent the local behaviors of hydrographs. Moreover, SFM and KWMSS1 were structurally unstable; their performance was sensitive to the applied objective functions. On the other hand, the most sophisticated model, KWMSS2, performed well, satisfying both global and local behaviors. KMSS2 also showed good structural stability, reproducing hydrographs regardless of the applied objective functions; however, superior parameter identifiability was not guaranteed. A number of parameter sets could result in indistinguishable hydrographs. This result indicates that while making hydrologic models complex increases its performance accuracy and reduces its structural uncertainty, the model is likely to suffer from parameter uncertainty.

• Structural Engineering and Mechanics
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• 제77권2호
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• pp.197-215
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• 2021

Under a severe environment of multiple hazards such as earthquakes and winds, the life-cycle performance of engineering structures may inevitably be deteriorated due to the fatigue effect caused by long-term exposure to wind loads, which would further increase the structural vulnerability to earthquakes. This paper presents a framework for evaluating the lifetime structural seismic performance under the effect of wind-induced fatigue considering different sources of uncertainties. The seismic behavior of a high-rise steel-concrete composite frame with buckling-restrained braces (FBRB) during its service life is systematically investigated using the proposed approach. Recorded field data for the wind hazard of Fuzhou, Fujian Province of China from Jan. 1, 1980 to Mar. 31, 2019 is collected, based on which the distribution of wind velocity is constructed by the Gumbel model after comparisons. The OpenSees platform is employed to establish the numerical model of the FBRB and conduct subsequent numerical computations. Allowed for the uncertainties caused by the wind generation and structural modeling, the final annual fatigue damage takes the average of 50 groups of simulations. The lifetime structural performance assessments, including static pushover analyses, nonlinear dynamic time history analyses and fragility analyses, are conducted on the time-dependent finite element (FE) models which are modified in lines with the material deterioration models. The results indicate that the structural performance tends to degrade over time under the effect of fatigue, while the influencing degree of fatigue varies with the duration time of fatigue process and seismic intensity. The impact of wind-induced fatigue on structural responses and fragilities are explicitly quantified and discussed in details.

• Structural Monitoring and Maintenance
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• 제9권3호
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• pp.271-287
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• 2022

This study investigates the bending behavior of a composite concrete slab roof with different methods of externally strengthing using steel plates and carbon fiber reinforced polymer (CFRP) strips. First, the concrete slab model which was reinforced with CFRP strips on the bottom surface of it is validated using experimental data, and then, using numerical modeling, 7 different models of square-shaped composite slab roofs are developed in ABAQUS software using the finite element modeling. Developed models include steel rebar reinforced concrete slab with variable thickness of CFRP and steel plates. Considering the control sample which has no external reinforcement, a set of 8 different reinforcement states has been investigated. Each of these 8 states is examined with 6 different uncertainties in terms of the properties of the materials in the construction of concrete slabs, which make 48 numerical models. In all models loading process is continued until complete failure occurs. The results from numerical investigations showed using the steel plates as an executive method for strengthening, the bending capacity of reinforced concrete slabs is increased in the ultimate bearing capacity of the slab by about 1.69 to 2.48 times. Also using CFRP strips, the increases in ultimate bearing capacity of the slab were about 1.61 to 2.36 times in different models with different material uncertainties.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.251-257
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• 2007

For the modern aircraft, uncertainty has bee an important issue to its aeroelastic stability. Therefore, many researches have been conducted regarding this topic. The uncertainties in the aeroelastic system amy consist of the structural and aerodynamic uncertainty. In this paper, we suggest a parametric uncertainty modeling and conduct the aeroelastic stability analysis of a typical wing including the uncertainty.

• Earthquakes and Structures
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• 제23권6호
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• pp.549-580
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• 2022

This paper assesses the influences of modeling assumptions and uncertainties on the performance of the non-linear finite element (FE) model updating procedure and model clustering method. The results of a shaking table test on a four-story steel moment-resisting frame are employed for both calibrations and clustering of the FE models. In the first part, simple to detailed non-linear FE models of the test frame is calibrated to minimize the difference between the various data features of the models and the structure. To investigate the effect of the specified data feature, four of which include the acceleration, displacement, hysteretic energy, and instantaneous features of responses, have been considered. In the last part of the work, a model-based clustering approach to group models of a four-story frame with similar behavior is introduced to detect abnormal ones. The approach is a composition of property derivation, outlier removal based on k-Nearest neighbors, and a K-means clustering approach using specified data features. The clustering results showed correlations among similar models. Moreover, it also helped to detect the best strategy for modeling different structural components.

• Structural Engineering and Mechanics
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• 제85권3호
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• pp.369-379
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• 2023

Reliability-Based Design Optimization (RBDO) is an appropriate framework for obtaining optimal designs by taking uncertainties into account. Large-scale problems with implicit limit state functions and problems with discrete design variables are two significant challenges to traditional RBDO methods. To overcome these challenges, this paper proposes a hybrid method to perform RBDO of structures that links Firefly Algorithm (FA) as an optimization tool to advanced (finite element) reliability methods. Furthermore, the Genetic Algorithm (GA) and the FA are compared based on the design cost (objective function) they achieve. In the proposed method, Weighted Simulation Method (WSM) is utilized to assess reliability constraints in the RBDO problems with explicit limit state functions. WSM is selected to reduce computational costs. To performing RBDO of structures with finite element modeling and implicit limit state functions, a First-Order Reliability Method (FORM) based on the Direct Differentiation Method (DDM) is utilized. Four numerical examples are considered to assess the effectiveness of the proposed method. The findings illustrate that the proposed RBDO method is applicable and efficient for RBDO problems with discrete and continuous design variables and finite element modeling.

• Geomechanics and Engineering
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• 제36권5호
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• pp.475-487
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• 2024

Many uncertainties affect the stability assessment of rock structures. Some of these factors significantly influence technology decisions. Some of these factors belong to the geological domain, and spatial uncertainty measurements are useful for structural stability analysis. This paper presents an integrated approach to study the stability of rock structures, including spatial factors. This study models two main components: discrete structures (fault zones) and well known geotechnical parameters (rock quality indicators). The geostatistical modeling criterion are used to quantify geographic uncertainty by producing simulated maps and RQD values for multiple equally likely error regions. Slope stability theorem would be demonstrated by modeling local failure zones and RQDs. The approach proided is validated and finally, the slope stability analysis method and fuzzy Laypunov criterion are applied to mining projects with limited measurement data. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and fuzzy theory.

• Smart Structures and Systems
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• 제22권5호
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.241-248
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• 2024

사회적으로, 조직이 보유한 정보 자원에 대한 엄격한 관리를 요구하고 있다. 조직들은 기술적으로 외부 정보 침입에 대처해야 할 뿐 아니라, 내부자에 의한 정보 노출 가능성까지 관리해야 하는 상황에 직면해 있다. 하지만, 조직이 도입한 정보보안 정책, 기술 등은 조직 내부의 보안 수준 달성에 도움을 주지만, 과도하거나 체계적이지 못한 보안 구조는 조직원의 불확실성을 높일 수 있다. 본 연구는 정보보안 관련 조직의 구조적인 불확실성 요인을 제시하고 행동에 미치는 영향을 제시한다. 즉, 정보보안 정책, 기술, 그리고 커뮤니케이션 불확실성이 구조적으로 존재할 수 있음을 밝힌다. 정보보안 환경 관련 선행연구를 통해 연구 모델과 가설을 제시하였으며, 구조방정식 모델링을 적용하여 가설을 검정하였다. 가설 검정 결과, 정보보안 정책, 기술, 그리고 커뮤니케이션 불확실성이 조직원의 역할 정체성과 준수 의도를 감소시켰다. 연구 결과는 조직 내 정보보안 관련 구조적인 불확실성 개선 조건을 제시하였기 때문에, 조직 내부의 정보보안 목표 달성을 위한 환경 전략 방향을 제언한다.

• Earthquakes and Structures
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• 제8권4호
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.