• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.4
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• pp.327-334
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• 2016

This study proposed a framework for an infrastructure asset management manual which can be adjusted by different ordering authorities to develop their own manuals. For this, The necessity of asset management manual was examined through analysis of the current status and insufficiencies and limitations in the asset management manuals of the domestic government and ordering authorities. Second, the systems and characteristics of infrastructure asset management manuals in developed countries such as Australia, the United Kingdom and the United States were examined and compared. Finally, based on the domestic infrastructure asset management characteristics and foreign infrastructure asset management manuals, a framework for an infrastructure asset management manual that can be utilized by the ordering authorities was proposed considering generality of asset management manual, asset management maturity of ordering authorities, serviceability of manual, and cyclic processes of asset management.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.363-372
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• 2012

In this study, a new information-based hybrid modeling framework is proposed. In the hybrid framework, a conventional mathematical model is complemented by the informational methods. The basic premise of the proposed hybrid methodology is that not all features of system response are amenable to mathematical modeling, hence considering informational alternatives. This may be because (i) the underlying theory is not available or not sufficiently developed, or (ii) the existing theory is too complex and therefore not suitable for modeling within building frame analysis. The role of informational methods is to model aspects that the mathematical model leaves out. Autoprogressive algorithm and self-learning simulation extract the missing aspects from a system response. In a hybrid framework, experimental data is an integral part of modeling, rather than being used strictly for validation processes. The potential of the hybrid methodology is illustrated through modeling complex hysteretic behavior of beam-to-column connections.

• Structural Engineering and Mechanics
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• v.35 no.5
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• pp.571-592
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• 2010

An energy-based fatigue life prediction framework was previously developed by the authors for prediction of axial, bending and shear fatigue life at various stress ratios. The framework for the prediction of fatigue life via energy analysis was based on a new constitutive law, which states the following: the amount of energy required to fracture a material is constant. In the first part of this study, energy expressions that construct the constitutive law are equated in the form of total strain energy and the distortion energy dissipated in a fatigue cycle. The resulting equation is further evaluated to acquire the equivalent stress per cycle using energy based methodologies. The equivalent stress expressions are developed both for biaxial and multiaxial fatigue loads and are used to predict the number of cycles to failure based on previously developed prediction criterion. The equivalent stress expressions developed in this study are further used in a new finite element procedure to predict the fatigue life for two and three dimensional structures. In the second part of this study, a new Quadrilateral fatigue finite element is developed through integration of constitutive law into minimum potential energy formulation. This new QUAD-4 element is capable of simulating biaxial fatigue problems. The final output of this finite element analysis both using equivalent stress approach and using the new QUAD-4 fatigue element, is in the form of number of cycles to failure for each element on a scale in ascending or descending order. Therefore, the new finite element framework can provide the number of cycles to failure at each location in gas turbine engine structural components. In order to obtain experimental data for comparison, an Al6061-T6 plate is tested using a previously developed vibration based testing framework. The finite element analysis is performed for Al6061-T6 aluminum and the results are compared with experimental results.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.51-66
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• 2023

In this paper, we propose a new type of process discovery framework, which is named as control-path-driven process group discovery framework, to be used for process mining and process reengineering in supporting life-cycle management of business process models. In addition, we develop a process mining system based on the proposed framework and perform experimental verification through it. The process execution event logs applied to the experimental effectiveness and verification are specially defined as Process BIG-Logs, and we use it as the input datasets for the proposed discovery framework. As an eventual goal of this paper, we design and implement a control path-driven process group discovery algorithm and framework that is improved from the ρ-algorithm, and we try to verify the functional correctness of the proposed algorithm and framework by using the implemented system with a BIG-Log dataset. Note that all the process mining algorithm, framework, and system developed in this paper are based on the structural information control net process modeling methodology.

• Journal of the Korean Society of Safety
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• v.31 no.5
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• pp.95-101
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• 2016

This study proposes a multi-scale dynamic system reliability analysis of control system as a method of quantitative evaluation of its performance in probabilistic terms. In this second paper, we discuss the control effect of the viscous damper on the seismic performance of the structure-level failure. Since the failure of one structural member does not necessarily cause the collapse of the structural system, we need to consider a set of failure scenarios of the structural system and compute the sum of the failure probabilities of the failure scenarios where the statistical dependence between the failure scenarios should be taken into account. Therefore, this computation requires additional system reliability analysis. As a result, the proposed approach takes a hierarchial framework where the failure probability of a structural member is computed using a lower-scale system reliability with the union set of time-sequential member failures and their statistical dependence, and the failure probability of the structural system is again computed using a higher-scale system reliability with the member failure probabilities obtained by the lower-scale system reliability and their statistical dependence. Numerical results demonstrate that the proposed approach can provide an accurate and stable reliability assessment of the control performance of the viscous damper system on the system failure. Also, the parametric study of damper capacity on the seismic performance has been performed to demonstrate the applicability of the proposed approach through the probabilistic assessment of the seismic performance improvement of the damper system.

• Composites Research
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• v.33 no.6
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• pp.353-359
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• 2020

In this work, a contour-based section analysis method incorporating the use of Bézier curves is attempted for the construction of optimal structural design framework of composite helicopter blades. The suggested section analysis method is able to analyze composite blades with solid cores made of arbitrary materials and geometric shapes. The contour-based section analysis method is integrated into a blade structural optimization framework to confirm the efficiency of the present approach. The numerical simulation result demonstrates that the optimized blade configurations are obtained with a reduction in mass by 52%, compared to the baseline blade. For the structural optimization of composite blades with 19 subsections, it takes about one hour for the successful optimization while satisfying all the design constraints considered in this study, which reveals the efficiency of the present approach.

• Composites Research
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• v.35 no.5
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• pp.340-346
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• 2022

In this study, an optimal structural design of composite helicopter blades is performed using the genetic algorithm-based optimizer PSGA (Particle Swarm assisted Genetic Algorithm). The blade sections consist of the skin, spar, form, and balancing weight. The sectional geometries are generated using the B-spline curves while an opensource code Gmsh is used to discretize each material domain which is then analyzed by a finite element sectional analysis program Ksec2d. The HART II blade formed based on either C- or D-spar configuration is exploited to verify the cross-sectional design framework. A numerical simulation shows that each spar model reduces the blade mass by 7.39% and 6.65%, respectively, as compared with the baseline HART II blade case, while the shear center locations being remain close (within 5% chord) to the quarter chord line for both cases. The effectiveness of the present optimal structural design framework is demonstrated, which can readily be applied for the structural design of composite helicopter blades.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• KIEAE Journal
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• v.4 no.3
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• pp.45-52
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• 2004

The purpose of this research was to identify the structural characteristics of open housing typologically and systematically. The main method of this study was content analysis and literature review on open housing. This study found that the typological analysis on terminology and the details of the constituents concerning structural patterns in open housing indicated that the main approaches were classified into three criteria such as 'Organization Element', 'Construction Element', and 'Equipment Element'. Organization Element was classified into 'Main Dwelling Unit Area and its Form', 'Room Organization Method', 'Relationship with the Main Dwelling Unit's External Constituents', and 'Combination Method of Support and Infill'. Construction Element was classified into 'Method of Structure' and 'Structural Element Technology'. Equipment Element was classified into 'Method of Using Duct' and 'Wet Zone Method'. The attributes were determined based on these classifications. The results of this study can be used to construct an evaluation tool and further to develop a framework in understanding open housing. Technical research should be conducted on the variables that affect the flexibility of space.