• Smart Structures and Systems
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• 제9권4호
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• pp.335-353
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• 2012

This study suggests a simple two-step method for structural vibration-based health monitoring for beam-like structures which only utilizes mode shape curvature and few natural frequencies of the structures in order to detect and localize cracks. The method is firstly based on the application of wavelet transform to detect crack locations from mode shape curvature. Then particle swarm optimization is applied to evaluate crack depth. As the Rayleigh quotient is introduced to estimate natural frequencies of cracked beams, the relationship of natural frequencies and crack depths can be easily obtained with only a simple formula. The method is demonstrated and validated numerically, using the numerical examples (cantilever beam and simply supported shaft) in the literature, and experimentally for a cantilever beam. Our results show that mode shape curvature and few estimated natural frequencies can be used to detect crack locations and depths precisely even under a certain level of noise. The method can be extended for health monitoring of other more complicated structures.

• 대한안전경영과학회지
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• 제17권2호
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• pp.1-11
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• 2015

Enterprise Risk Management(ERM) is aiming at the establishment of the risk management process to prevent and cope with risks in advance and is composed of Risk Identification, Risk Assessment, Risk Response and Monitoring. It is feedback through the Risk Re-identification. This study has analysed a sample of the risk management system of an airport operating corporation, for this purpose, relevant documents and examples of overseas airports have been reviewed. It has found that corporations establishing ERM have been performing identical procedures such as the process of Identification, Assessment, Effective Reporting, Communication and monitoring and so on. The A corporation has established the process for risk management and crisis management and organized for its organization and system. The risk management has the same process such as above. In this process, when the symptoms of critical crisis have been recognized, it has been transformed into crisis management system, through which, corporate-wide response has been conducted in the process of crisis status analysis, response and follow-up management. This study expects to contribute to systematic foundation for future business continuity on the basis of risks and response procedures acknowledged by this study.

• Smart Structures and Systems
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• 제5권1호
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• pp.1-21
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• 2009

A two-stage damage detection method is proposed and demonstrated for structural health monitoring. In the first stage, the subset selection method is applied for the identification of the multiple damage locations. In the second stage, the damage severities of the identified damaged elements are determined applying SSGA to solve the optimization problem. In this method, the sensitivities of residual force vectors with respect to damage parameters are employed for the subset selection process. This approach is particularly efficient in detecting multiple damage locations. The SEREP is applied as needed to expand the identified mode shapes while using a limited number of sensors. Uncertainties in the stiffness of the elements are also considered as a source of modeling errors to investigate their effects on the performance of the proposed method in detecting damage in real-life structures. Through a series of illustrative examples, the proposed two-stage damage detection method is demonstrated to be a reliable tool for identifying and quantifying multiple damage locations within diverse structural systems.

• Smart Structures and Systems
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• 제24권4호
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• pp.435-446
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• 2019

The existing piezoelectric spherical transducers with fixed prescribed dynamic characteristics limit their application in scenarios with multi-frequency or frequency variation requirement. To address this issue, this work proposes an improved design of piezoelectric spherical transducers using the resistance tuning method. Two piezoceramic shells are the functional elements with one for actuation and the other for tuning through the variation of load resistance. The theoretical model of the proposed design is given based on our previous work. The effects of the resistance, the middle surface radius and the thickness of the epoxy adhesive layer on the dynamic characteristics of the transducer are explored by numerical analysis. The numerical results show that the multi-frequency characteristics of the transducer can be obtained by tuning the resistance, and its electromechanical coupling coefficient can be optimized by a matching resistance. The proposed design and derived theoretical solution are validated by comparing with the literature given special examples as well as an experimental study. The present study demonstrates the feasibility of using the proposed design to realize the multi-frequency characteristics, which is helpful to improve the performance of piezoelectric spherical transducers used in underwater acoustic detection, hydrophones, and the spherical smart aggregate (SSA) used in civil structural health monitoring, enhancing their operation at the multiple working frequencies to meet different application requirements.

• Structural Engineering and Mechanics
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• 제72권2호
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• pp.217-227
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• 2019

The methodology known as "shape sensing" allows the reconstruction of the displacement field of a structure starting from strain measurements, with considerable implications for structural monitoring, as well as for the control and implementation of smart structures. An approach to shape sensing is based on the inverse Finite Element Method (iFEM) that uses a variational principle enforcing a least-squares compatibility between measured and analytical strain measures. The structural response is reconstructed without the knowledge of the mechanical properties and load conditions but based only on the relationship between displacements and strains. In order to efficiently apply iFEM to the most common structural typologies of civil engineering, its formulation according to the kinematical assumptions of the Bernoulli-Euler theory is presented. Two beam inverse finite elements are formulated for different loading conditions. Depending on the type of element, the relationship between the minimum number of required measurement stations and the interpolation order is defined. Several examples representing common applications of civil engineering and involving beams and frames are presented. To simulate the experimental strain data at the station points and to verify the accuracy of the displacements obtained with the iFEM shape sensing procedure, a direct FEM analysis of the considered structures is performed using the LUSAS software.

• Nuclear Engineering and Technology
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• 제55권11호
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• pp.4039-4047
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• 2023

This contribution describes the application of HPGe detector for the airborne quantitative analysis. The hardware of the airborne HPGe system was designed from the commercial components with only exception of the newly designed AirHPGeSpec special software to control, measure and process the data. The system was calibrated for the local air kerma rates measured on helicopter board and its conversion to the air kerma rates at 1 m above the ground was proposed. Two examples of the air kerma rates measured over the former uranium mining areas are presented and compared with the results of other airborne system on the board. This airborne HPGe system could be also used for measuring the surface activities in a radiation event. The nuclides of ¹³¹I, ¹³²Te - ¹³²I, ¹³³I, ¹³⁴I, ¹³⁵I, ¹³⁷Cs, ¹³⁴Cs, ⁸⁸Rb and ¹⁰³Ru were selected from possible nuclear power plant emergency scenarios. The Monte Carlo simulation was used to calculate HPGe detector efficiencies for the flight altitudes from 25 to 300 m for the energies from 300 keV to 3 MeV of the nuclides in question. Also, the detection limits according to the Currie method as well as ISO 11929-2010 for selected nuclides are presented.

• Nuclear Engineering and Technology
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• 제47권2호
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• pp.204-211
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• 2015

Probabilistic safety assessment (PSA) has had a significant role in quantitative decision-making by finding design and operational vulnerabilities and evaluating cost-benefit in improving such weak points. In particular, it has been widely used as the core methodology for risk-informed applications (RIAs). Even though the nature of PSA seeks realistic results, there are still "conservative" aspects. One of the sources for the conservatism is the assumptions of safety analysis and the estimation of failure frequency. Surveillance, diagnosis, and prognosis (SDP), utilizing massive databases and information technology, is worth highlighting in terms of its capability for alleviating the conservatism in conventional PSA. This article provides enabling techniques to solidify a method to provide time- and condition-dependent risks by integrating a conventional PSA model with condition monitoring and prognostics techniques. We will discuss how to integrate the results with frequency of initiating events (IEs) and probability of basic events (BEs). Two illustrative examples will be introduced: (1) how the failure probability of a passive system can be evaluated under different plant conditions and (2) how the IE frequency for a steam generator tube rupture (SGTR) can be updated in terms of operating time. We expect that the proposed model can take a role of annunciator to show the variation of core damage frequency (CDF) depending on operational conditions.

• 한국구조물진단유지관리공학회 논문집
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• 제19권3호
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• pp.10-21
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• 2015

구조물 건전성 모니터링은 센서로부터 구조물의 응답을 수집하고 분석하여 구조물의 정확한 상태를 진단하는 기술이다. 최근 노후화된 구조물의 증가로 인하여, 지속가능한 사회 발전을 위해 더욱 발달된 구조물 건전성 모니터링 기술이 요구되고 있다. 최신 구조물 건전성 모니터링 기술 중 하나인 무선 스마트 센서와 센서 네트워크 기술은 기존의 유선 방식의 모니터링 시스템과 비교하여 더욱 효율적이며 경제적인 모니터링 시스템의 구축을 가능하게 하는 기술이다. 최근까지도 관련 연구자들은 스마트 센서의 성능 및 확장성 향상을 위하여 연구개발을 진행하고, 다양한 실내, 실외 실험을 통한 성능 테스트를 진행하였다. 본 논문에서는 최근 (2010년 이후를 중심으로)에 개발된 스마트 센서의 하드웨어, 소프트웨어, 그리고 응용 사례들을 정리함으로써, 구조물 건전성 모니터링을 위한 스마트 센서의 최신 연구동향에 대해 소개하고자 한다.

• Geomechanics and Engineering
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• 제30권2호
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

• Computers and Concrete
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• 제31권5호
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.