• Smart Structures and Systems
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• 제31권4호
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• pp.325-334
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• 2023

Computer vision-based damage detection enables non-contact, efficient and low-cost bridge health monitoring, which reduces the need for labor-intensive manual inspection or that for a large number of on-site sensing instruments. By leveraging recent semantic segmentation approaches, we can detect regions of critical structural components and identify damages at pixel level on images. However, existing methods perform poorly when detecting small and thin damages (e.g., cracks); the problem is exacerbated by imbalanced samples. To this end, we incorporate domain knowledge to introduce a hierarchical semantic segmentation framework that imposes a hierarchical semantic relationship between component categories and damage types. For instance, certain types of concrete cracks are only present on bridge columns, and therefore the noncolumn region may be masked out when detecting such damages. In this way, the damage detection model focuses on extracting features from relevant structural components and avoid those from irrelevant regions. We also utilize multi-scale augmentation to preserve contextual information of each image, without losing the ability to handle small and/or thin damages. In addition, our framework employs an importance sampling, where images with rare components are sampled more often, to address sample imbalance. We evaluated our framework on a public synthetic dataset that consists of 2,000 railway bridges. Our framework achieves a 0.836 mean intersection over union (IoU) for structural component segmentation and a 0.483 mean IoU for damage segmentation. Our results have in total 5% and 18% improvements for the structural component segmentation and damage segmentation tasks, respectively, compared to the best-performing baseline model.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.307-314
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• 2006

Missile system. which requires high speed/high maneuverability is getting more important as a defensive weapon system. Integrated design environment which includes all related resources during the missile development process, is a very useful development tool, Therefor the design framework can perform the operation analysis and utilize design information for the efficient missile design. For this purpose, various analysis computer codes under heterogeneous platforms and operating systems, the database, the optimization module, and Ideas a commercial CAD are integrated using distributed. middleware. and the complicated GUI design has been made for the specific missile system design. Under the various constraint, maximize missile range and loadfactor with missile design computer framework.

• 한국전산구조공학회논문집
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• 제27권6호
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• pp.551-555
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• 2014

본 논문에서는 견고표적 피해분석 무기효과 계산 SW의 Framework에 대하여 기술하였다. 탄두의 침투이력, 기폭에 의해 발생되는 폭압, 폭압에 의한 구조 및 비구조 구성품 파괴가 이론식 및 경험식을 통해 계산되었다. 또한 사용자의 편의를 위해 손쉬운 UI가 설계되었으며, 각 해석 단계는 모듈화되어 향후 개선 및 보완이 용이하게 하였다.

• Smart Structures and Systems
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• 제17권3호
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• pp.445-470
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• 2016

In this study, the Bayesian probabilistic framework is investigated for modal identification and modal identifiability based on the field measurements provided in the structural health monitoring benchmark problem of an instrumented cable-stayed bridge named Ting Kau Bridge (TKB). The comprehensive structural health monitoring system on the cable-stayed TKB has been operated for more than ten years and it is recognized as one of the best test-beds with readily available field measurements. The benchmark problem of the cable-stayed bridge is established to stimulate investigations on modal identifiability and the present paper addresses this benchmark problem from the Bayesian prospective. In contrast to deterministic approaches, an appealing feature of the Bayesian approach is that not only the optimal values of the modal parameters can be obtained but also the associated estimation uncertainty can be quantified in the form of probability distribution. The uncertainty quantification provides necessary information to evaluate the reliability of parametric identification results as well as modal identifiability. Herein, the Bayesian spectral density approach is conducted for output-only modal identification and the Bayesian model class selection approach is used to evaluate the significance of different modes in modal identification. Detailed analysis on the modal identification and modal identifiability based on the measurements of the bridge will be presented. Moreover, the advantages and potentials of Bayesian probabilistic framework on structural health monitoring will be discussed.

• Earthquakes and Structures
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• 제7권3호
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• pp.271-294
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• 2014

In recent years, along with the advances made in performance-based design optimization, the need for fast calculation of response parameters in dynamic analysis procedures has become an important issue. The main problem in this field is the extremely high computational demand of time-history analyses which may convert the solution algorithm to illogical ones. Two simplifying strategies have shown to be very effective in tackling this problem; first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication, second, wavelet analysis of earthquake records decreasing the number of acceleration points involved in time-history loading. In this paper, we try to develop an efficient framework, using both strategies, to solve the performance-based multi-objective optimal design problem considering the initial cost and the seismic damage cost of steel moment-frame structures. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency (FEMA) recommended design specifications. The results from numerical application of the proposed framework demonstrate the capabilities of the framework in solving the present multi-objective optimization problem.

• Smart Structures and Systems
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• 제32권3호
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• pp.179-193
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• 2023

This study explores an alternative to the existing centralized process for data anomaly detection in modern Internet of Things (IoT)-based structural health monitoring (SHM) systems. An edge intelligence framework is proposed for the early detection and classification of various data anomalies facilitating quality enhancement of acquired data before transmitting to a central system. State-of-the-art deep neural network pruning techniques are investigated and compared aiming to significantly reduce the network size so that it can run efficiently on resource-constrained edge devices such as wireless smart sensors. Further, depthwise separable convolution (DSC) is invoked, the integration of which with advanced structural pruning methods exhibited superior compression capability. Last but not least, quantization-aware training (QAT) is adopted for faster processing and lower memory and power consumption. The proposed edge intelligence framework will eventually lead to reduced network overload and latency. This will enable intelligent self-adaptation strategies to be employed to timely deal with a faulty sensor, minimizing the wasteful use of power, memory, and other resources in wireless smart sensors, increasing efficiency, and reducing maintenance costs for modern smart SHM systems. This study presents a theoretical foundation for the proposed framework, the validation of which through actual field trials is a scope for future work.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.275-283
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• 2004

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive Approximation, is a competent strategy via MDO framework systems.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2004년도 봄 학술발표회 논문집
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• pp.81-86
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• 2004

For the development of system framework which provides multidisciplinary design environment, the integration of analysis codes written in various computer languages, the integration of CAD and DBMS, and the development of complex GUI are indispensible In this study, three different design frameworks which have been developed in Konkuk University with the aids of a company and other university, are compared and analyzed with respect to the analysis code integration method and the module interface technique. Moreover, the way to develop an efficient framework is proposed.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2010년도 춘계 학술대회 제22권1호
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• pp.471-472
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• 2010

In this study, a new modeling framework for predicting temperature and structural behaviors of structures under fire condition is proposed. The proposed modeling framework including fire simulation, heat transfer and structural analysis is applied to simulate fire tests performed on the steel-concrete composite structures in Cardington, UK, for model validations. Good predictions are shown for spatial-temporal temperatures and deflections of fire-damaged steel-concrete structures.

• 대한가정학회지
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• 제39권10호
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• pp.69-81
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• 2001

This study focused on the necessity and structural framework of tentative draft of "Act on Family Welfare". The background of this study started from the necessity that we need a holistic family welfare system to enhance the family function. The suggested act of family welfare is consisted on 4 parts, General Provisions, Arrangements of Basic Plan and Policy, Organizations and Facilities for Family Wefare and certified Personnel.