• Steel and Composite Structures
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• 제36권1호
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• pp.31-45
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• 2020

The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.

• 한국습지학회지
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• 제5권1호
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• pp.41-52
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• 2003

The flood damage reduction studies have been performed by the channel improvement plan and the levee has mainly constructed with the freeboard concept. However, the freeboard concept might be an inappropriate choice as a safety factor of the levee because many uncertainties are involved in the procedure of the channel improvement plan studies. So, we considered the uncertainties In the discharge-probability, stage-discharge, and stage-damage functions and estimate the expected annual damage. The Monte Carlo technique for uncertainty analysis is used. As our results, the expected annual damage with uncertainty shows the larger value than without uncertainty. Since the expected annual damage with uncertainty already considers the safety factor it is the proper result. However, the expected annual damage without uncertainty does not consider the safety factor yet. Thus, if the expected annual damage without uncertainty considers the freeboard concept, it could be compared with the expected annual damage with uncertainty for the evaluation of the overestimation or underestimation of the levee construction.

• Smart Structures and Systems
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• 제25권3호
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• pp.345-368
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• 2020

The present work proposes a self-controlled multi-stage optimization method for damage identification of structures utilizing standard particle swarm optimization (PSO) algorithm. Damage identification problem is formulated as an inverse optimization problem where damage severity in each element of the structure is considered as optimization variables. An efficient objective function is formed using the first few frequencies and mode shapes of the structure. This objective function is minimized by a self-controlled multi-stage strategy to identify and quantify the damage extent of the structural members. In the first stage, standard PSO is utilized to get an initial solution to the problem. Subsequently, the algorithm identifies the most damage-prone elements of the structure using an adaptable threshold value of damage severity. These identified elements are included in the search space of the standard PSO at the next stage. Thus, the algorithm reduces the dimension of the search space and subsequently increases the accuracy of damage prediction with a considerable reduction in computational cost. The efficiency of the proposed method is investigated and compared with available results through three numerical examples considering both with and without noise. The obtained results demonstrate the accuracy of the present method can accurately estimate the location and severity of multi-damage cases in the structural systems with less computational cost.

• Structural Engineering and Mechanics
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• 제84권4호
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• pp.489-502
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• 2022

This paper is aimed at developing an optimization-based Finite Element model updating approach for structural damage identification and quantification. A modal flexibility-based error function is introduced, which uses modal assurance criterion to formulate the updating problem as an optimization problem. Because of the inexplicit input/output relationship between the candidate solutions and the error function's output, a robust and efficient optimization algorithm should be employed to evaluate the solution domain and find the global extremum with high speed and accuracy. This paper proposes a new multi-stage Selective Particle Swarm Optimization (SPSO) algorithm to solve the optimization problem. The proposed multi-stage strategy not only fixes the premature convergence of the original Particle Swarm Optimization (PSO) algorithm, but also increases the speed of the search stage and reduces the corresponding computational costs, without changing or adding extra terms to the algorithm's formulation. Solving the introduced objective function with the proposed multi-stage SPSO leads to a smart feedback-wise and self-adjusting damage detection method, which can effectively assess the health of the structural systems. The performance and precision of the proposed method are verified and benchmarked against the original PSO and some of its most popular variants, including SPSO, DPSO, APSO, and MSPSO. For this purpose, two numerical examples of complex civil engineering structures under different damage patterns are studied. Comparative studies are also carried out to evaluate the performance of the proposed method in the presence of measurement errors. Moreover, the robustness and accuracy of the method are validated by assessing the health of a six-story shear-type building structure tested on a shake table. The obtained results introduced the proposed method as an effective and robust damage detection method even if the first few vibration modes are utilized to form the objective function.

• Smart Structures and Systems
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• 제31권5호
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• Smart Structures and Systems
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• 제9권3호
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• pp.253-271
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• 2012

Finite element (FE) model updating is a useful tool for global damage detection technique, which identifies the damage of the structure using measured vibration data. This paper presents the application of a finite element model updating method to detect the damage of a small-scale reinforced concrete building structure using measured acceleration data from shaking table tests. An iterative FE model updating strategy using the least-squares solution based on sensitivity of frequency response functions and natural frequencies was provided. In addition, a side constraint to mitigate numerical difficulties associated with ill-conditioning was described. The test structure was subjected to six El Centro 1942 ground motion histories with different Peak Ground Accelerations (PGA) ranging from 0.06 g to 0.5 g, and analytical models corresponding to each stage of the shaking were obtained using the model updating method. Flexural stiffness values of the structural members were chosen as the updating parameters. In model updating at each stage of shaking, the initial values of the parameter were set to those obtained from the previous stage. Severity of damage at each stage of shaking was determined from the change of the updated stiffness values. Results indicated that larger reductions in stiffness values occurred at the slab members than at the wall members, and this was consistent with the observed damage pattern of the test structure.

• 대한원격탐사학회지
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• 제37권5_3호
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• pp.1435-1446
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• 2021

태풍으로 인한 풍수해는 매년 한반도에 많은 피해를 주고 있다. 재난 발생 시 피해가 최소화 되도록 신속한 의사 결정을 위해서는 예상되는 피해정보와 대피방안 등에 대한 사전 분석이 요구된다. 본 연구에서는 재난단계에 따라 필요한 정보를 제공할 수 있는 분석 모듈을 개발하고자 하였다. 태풍 대비단계에서 활용할 수 있도록 북상 중인 태풍경로와 유사한 과거태풍경로 및 과거피해정보를 확인할 수 있는 기능, 고립 위험 지역을 추출하는 기능, 저수지 붕괴 지역을 추출하는 기능을 개발하였다. 대응 및 복구 초기단계에서 활용할 수 있도록 현 침수심을 고려한 예상침수범위 추출 기능, 인구, 건물, 농지 등에 예상되는 피해정보 분석 기능, 대피정보를 제공하는 기능도 포함하였다. 또한 분석결과 표출을 위해 자동화된 웹 지도 작성 방법을 제시하였다. 분석기능은 파이썬 오픈소스 기반으로 개발하여 모듈화했으며, 웹 표출 기능은 자바스크립트 기반으로 구현하였다. 본 연구에서 개발된 도구들은 풍수해 대비 모니터링과 초기대응 단계에서 신속한 의사결정을 위해 효율적으로 활용될 수 있을 것이다.

• 한국재료학회지
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• 제20권3호
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• pp.148-154
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• 2010

It is necessary to develop new methods to prevent catastrophic failure of structural material in order to avoid accidents and conserve natural and energy resources. Design of intelligent materials with a self-diagnosing function to prevent fatal fracture of structural materials was achieved by smart composites consisting of carbon fiber tows or carbon powders with a small value of ultimate elongation and glass fiber tows with a large value of ultimate elongation. The changes in electrical resistance of CF-GFRP/GFRP (carbon fiber and glass fiber-reinforced plastics/glass fiber-reinforced plastics) composites increased abruptly with increasing strain, and a tremendous change was seen at the transition point where carbon fiber tows were broken. Therefore, the composites were not to monitor damage from the early stage. On the other hand, the change in electrical resistance of CP-GFRP/GFRP (carbon powder dispersed in glass fiber-reinforced plastics/glass fiber-reinforced plastics) composites increased almost linearly in proportion to strain. CP-GFRP/GFRP composites are superior to CF-GFRP/GFRP composites in terms of their capability to monitor damage by measuring change in electrical resistance from the early stage of damage. However, the former was inferior to the latter as an application because of the difficulties of mass production and high cost. A method based on monitoring damage by measuring changes in the electrical resistance of structural materials is promising for improved reliability of the material.

• 한국해양공학회지
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• 제33권1호
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• pp.33-41
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• 2019

Estimating fatigue damage is a very important issue in the design of ships. The springing and whipping response, which is the hydro-elastic response of the ship, can increase the fatigue damage of the ship. So, these phenomena should be considered in the design stage. However, the current studies on the the application of springing and whipping responses at the design stage are not sufficient. So, in this study, a prediction method was developed using fluid-structural interaction analysis to assess of the fatigue damage induced by springing and whipping. The stress transfer function (Stress RAO) was obtained by using the 3D FE model in the frequency domain, and the fatigue damage, including linear springing, was estimated by using the wide band damage model. We also used the 1D beam model to develop a method to estimate the fatigue damage, including nonlinear springing and whipping by the vertical bending moment in the short-term sea state. This method can be applied to structural members where fatigue strength is weak to vertical bending moments, such as longitudinal stiffeners. The methodology we developed was applied to 325K VLOC, and we analyzed the effect of the springing and whipping phenomena on the existing design.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.453-461
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• 1999

The estimation of fatigue life at the design stage is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the structure and machinery compo-nents. In this study the practical procedure of prediction of fatigue life by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function is shown with a $135,000m^3$ LNG tank being used as an example. In particular the parameters of Weibull distribution taht determine the stress spectrum are dis-cussed. At the end some of uncertainties associated with fatigue life prediction are discussed. The main results obtained from this study are as follows: 1. The practical procedure of prediction of fatigue life by use of cumulative damage factors expressed in combination of probability density function and S-N data is proposed. 2. The calculated fatigue life is influenced by the shape parameter and stress block. The conser-vative fatigue design can be achieved when using higher value of shape parameter and the stress blocks divded into more stress blocks.