• Proceedings of the Computational Structural Engineering Institute Conference
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• 2002.10a
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• pp.255-262
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• 2002

In this paper, an improved multi-objective optimmum design method is proposed. And it is applied to steel frames under seismic loads. The multi-objective optimization problem is formulated with three optimality criteria, namely, minimum structural weight and maximum strain energy and stability. The Pareto curve can be obtained by performing the multi-objective optimization for multistory shear buildings. In order to efficiently solve the multi-objective optimization problem the decomposition method that separates both system-level and element-level is used. In addition, various techniques such as effective reanalysis technique with respect to intermediate variables and sensitivity analysis using an automatic differentiation (AD) we incorporated. Moreover, the relationship function among section properties induced from the profile is used in order to link system-level and element level. From the results of numerical investigation, it may be stated that the proposed method will lead to the more rational design compared with the conventional one.

• Computational Structural Engineering
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• v.8 no.2
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• pp.115-121
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• 1995

The object of this study is to propose a rational method of resistance strength and flexural deformation for structures using high strength concrete(400-700kgf/cm/sup 2/). The material property(stress-strain relationship) is to be modelize using regression analysis of experimental result. And the applicability of trapezoidal stress model is to be verified. An analytical method is used by the moment-curvature relationship which is based on stress-strain relationships of material for discreted element of section. The evaluation method of moment-curvature of high strength concrete structures is also proposed by using the Monte Carlo Simulation based on a probabilistic concept that could minimize an error due to iterated calculations and random variable of material properties.

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.6
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• pp.215-219
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• 2010

The evaluation of the mechanical properties and behavior is very important for the design of embankment using granular materials. In this research, the lab. tests with Nak-dong river sand were conducted to find out mechanical properties related to stress-strain behavior. Also, numerical simulations which can express the behavior of granular material were conducted by distinct element method. Distinct element method can play a import role to predict stress-strain behavior for different confining stress and loading condition if micro-parameters can be estimated in specific condition.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.2
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• pp.135-143
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• 2002

This study is to investigate its use by applying stainless steel wire mash reinforcement method of construction, which is newly developed, on the high strength concrete beam mixed with polymer-steel fiber. In this test, it is investigated and observed such as follows: the ultimate load, the initial flexure crack load, the initial diagonal tension crack load, the relation between load and deflection, load-strain relation, and also crack growth and fracture aspect by increasing load. The results of this test are; first, the stainless steel wire showed some useful reinforcement effects in multiplying the steel's resisting force of moment to the tensile force of beam or slab: second, the promoting strength and internal force was made in the process of the integration at the same reaction by using the penetrating polymer-mortar with an excellent durability and physical property. On the basis of this results, because such instances in applying stainless steel wire Mash reinforcement method of construction have been few so far, through the experimental investigation such as this test over and over again, the efficient and useful method must be developed for the practice.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.3
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• pp.147-156
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• 2003

In this paper, a damage detection method using mode shapes of truss structures is presented. The theory is formulated based on the changes in the modal strain energy in a truss type structures due to damage. To examine the feasibility, the theory is applied to an experimental data of a 1:6 scale model of a typical hexagonal truss structure. The experiment consists of 17 damage scenarios subjected to three different types of damage. The damage evaluation results show that the proposed method detects successfully damage in truss elements and also show that the performance of proposed method can be significantly impacted by the noise in the measurement data for small damage.

• Smart Structures and Systems
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• v.30 no.6
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• pp.673-686
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• 2022

Deep learning algorithms for Structural Health Monitoring (SHM) have been extracting the interest of researchers and engineers. These algorithms commonly used loss functions and evaluation indices like the mean square error (MSE) which were not originally designed for SHM problems. An updated loss function which was specifically constructed for deep-learning-based structural damage detection problems has been proposed in this study. By tuning the coefficients of the loss function, the weights for damage localization and quantification can be adapted to the real situation and the deep learning network can avoid unnecessary iterations on damage localization and focus on the damage severity identification. To prove efficiency of the proposed method, structural damage detection using convolutional neural networks (CNNs) was conducted on a truss bridge model. Results showed that the validation curve with the updated loss function converged faster than the traditional MSE. Data augmentation was conducted to improve the anti-noise ability of the proposed method. For reducing the training time, the normalized modal strain energy change (NMSEC) was extracted, and the principal component analysis (PCA) was adopted for dimension reduction. The results showed that the training time was reduced by 90% and the damage identification accuracy could also have a slight increase. Furthermore, the effect of different modes and elements on the training dataset was also analyzed. The proposed method could greatly improve the performance for structural damage detection on both the training time and detection accuracy.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.2
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• pp.64-73
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• 2014

This study proposes a load identification for the safety monitoring of the steel structure based on measured strain data. Instead of parameterizing the stiffness of structure in the existing system identification researches, the loads on a structure and a matrix (the unit strain matrix) defined by the relationship between strain and load on structure are parameterized in this study. The error function is defined by the difference between measured strain and strain estimated by parameters. In order to minimize this error function, the genetic algorithm which is one of the optimization algorithm is applied and the parameters are found. The loads on the structure can be identified through the founded parameters and measured strain data. When the loads are changed, the unmeasured strains are estimated based on founded parameters and measured strains on changed state of structure. To verify the load identification algorithm in this paper, the static experimental test for 3 dimensional steel frame structure was implemented and the loads were exactly identified through the measured strain data. In case of loading changes, the unmeasured strains which are monitoring targets on the structure were estimated in acceptable error range (0.17~3.13%). It is expected that the identification method in this study is applied to the safety monitoring of steel structures more practically.

• Structural Engineering and Mechanics
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• v.90 no.6
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• pp.543-549
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• 2024

The utilization of the fabric materials for lightweight building structures has attracted considerable attention due to the multiple functions and high strength-to-weight ratio. The mechanical properties of the fabric materials evolve with the loading cycle, especially for the Poisson's ratio that requires the full cyclic strain to determine the accurate values. The digital image correlation method has been justified but needs to meet the flexibility and complexity requirements of the fabric materials. This paper thus proposes a modified digital image correlation method to quantify the Poisson's ratio of fabric materials. To obtain the accurate Poisson's ratio of fabric materials in the cyclic experiments using non-contact measuring method, a speckle generation of the digital image correlation method is implemented to obtain the strain distribution and strain characteristics. The uniaxial cyclic experiments for the fabric materials are carried out in the warp, weft and 45° directions. The digital image correlation photos are taken when the material properties become stable in the cyclic loading. The results show that the strain distributions are non-uniform and dependent on the specimen directions. The reliable Poisson's ratios of the fabric materials in the warp, weft and 45° directions are 0.016, 1.2 and 2.6. The strain asymmetry at the maximum strain position is related with the weaving architecture. These observations and results are indispensable to understand the Poisson's ratios of fabric materials and to guide the proper analysis of the large-span membrane structures.

• Structural Engineering and Mechanics
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• v.64 no.6
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• pp.683-693
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• 2017

According to a generalized nonlocal strain gradient theory (NSGT), dynamic modeling and free vibrational analysis of nanoporous inhomogeneous nanoplates is presented. The present model incorporates two scale coefficients to examine vibration behavior of nanoplates much accurately. Porosity-dependent material properties of the nanoplate are defined via a modified power-law function. The nanoplate is resting on a viscoelastic substrate and is subjected to hygro-thermal environment and in-plane linearly varying mechanical loads. The governing equations and related classical and non-classical boundary conditions are derived based on Hamilton's principle. These equations are solved for hinged nanoplates via Galerkin's method. Obtained results show the importance of hygro-thermal loading, viscoelastic medium, in-plane bending load, gradient index, nonlocal parameter, strain gradient parameter and porosities on vibrational characteristics of size-dependent FG nanoplates.