• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.3-11
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• 2002

A moment-curvature relationship to simulate the behavior of reinforced concrete (RC) columns under cyclic loading is introduced. Unlike previous moment-curvature models and the layered section approach, the unposed model takes into account the bond-slip effect by using a monotonic moment-curvature relationship constructed on the basis of the bond-slip relation and corresponding equilibrium equation at each nodal point. In addition, the use of curved unloading and reloading branches inferred from the stress-strain relation of steel gives more exact numerical result. The pinching enact caused by axial force is considered with an assumption that the absorbing energy corresponding to any deformation level maintains constant regardless of the magnitude of applied axial force. The advantages of the proposed model, comparing tn layered section approach, may be on the reduction in calculation time and memory space in case of its application to large structures.. Finally, correlation studies between analytical results and experimental studies are conducted to establish the validity of the proposed mood.

• Steel and Composite Structures
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• 제38권3호
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• pp.257-270
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• 2021

This paper presents a displacement-based numerical methodology following the Euler-Bernoulli theory to simulate the 2 nonlinear behavior of steel structures. It is worth emphasizing the adoption of co-rotational finite element formulations considering large displacements and rotations and an inelastic material behavior. The numerical procedures proposed considers plasticity concentrated at the finite elements nodes, and the simulation of the steel nonlinear behavior is approached via the Strain Compatibility Method (SCM), where the material constitutive relation is used explicitly. The SCM is also applied in determining the sections bearing capacity. Moreover, the present numerical approach is not limited to a specific structural member cross-sectional typology, with the residual stress models introduced explicitly in subareas of steel cross-sections generated by a 2D discretization. Finally, results consistent with the literature and with low processing time are presented.

• Steel and Composite Structures
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• 제23권1호
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• pp.41-51
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• 2017

A $C^0$ FE model developed based on an efficient higher order zigzag theory is used for hygrothermal analysis of laminated composite plates. The $C^0$ FE model satisfies the inter-laminar shear stress continuity at the interfaces and zero transverse shear stress conditions at plate top and bottom. In this model the first derivatives of transverse displacement have been treated as independent variables to circumvent the problem of $C^1$ continuity associated with the above plate theory. In the present theory the above mentioned $C^0$ continuity of the present element is compensated in the stiffness matrix formulation by using penalty parameter approach. In order to avoid stress oscillations observed in the displacement based finite element, the stress field derived from temperature/moisture fields (initial strains) must be consistent with total strain field. Special steps are introduced by field consistent approach (e.g., sampling at gauss points) to compensate this problem. A nine noded $C^0$ continuous isoparametric element is used in the proposed FE model. Comparison of present numerical results with other existing solutions shows that the proposed FE model is efficient, accurate and free of locking.

• 소성∙가공
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• 제26권4호
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• pp.210-215
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• 2017

In this paper, utilizing the theory of ductile fracture a chevron crack in a 4-stage open cold extrusion process is predicted by the finite element methods and then compared with previous experiments. The normalized Cockcroft-Latham damage model is employed and the material is identified using a tensile test based material identification technique that gives fracture information as well as flow stress at large strain. A large difference between the predicted cracks and actual experiments is observed, specifically narrower width and greater maximum height of the crack. This reveals the limitation of this approach based on the conventional theory of ductile fracture. Based on the observations and the related criticisms, a new approach for predicting the chevron crack is proposed, suggesting that either the critical damage should not be a fixed material constant, or that the conventional fracture theory should be considered with the effects of embrittlement due to accumulated plastic deformation while the duration of crack generation and plastic deformation should be reduced.

• Smart Structures and Systems
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• 제18권3호
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• pp.375-387
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• 2016

The classical Kalman filter (KF) can provide effective state estimation for structural identification and vibration control, but it is applicable only when external inputs are measured. So far, some studies of Kalman filter with unknown inputs (KF-UI) have been proposed. However, previous KF-UI approaches based solely on acceleration measurements are inherently unstable which leads to poor tracking and fictitious drifts in the identified structural displacements and unknown inputs in the presence of measurement noises. Moreover, it is necessary to have the measurements of acceleration responses at the locations where unknown inputs applied, i.e., with collocated acceleration measurements in these approaches. In this paper, it aims to extend the classical KF approach to circumvent the above limitations for general real time estimation of structural state and unknown inputs without using collocated acceleration measurements. Based on the scheme of the classical KF, an improved Kalman filter with unknown excitations (KF-UI) and without collocated acceleration measurements is derived. Then, data fusion of acceleration and displacement or strain measurements is used to prevent the drifts in the identified structural state and unknown inputs in real time. Such algorithm is not available in the literature. Some numerical examples are used to demonstrate the effectiveness of the proposed approach.

• Smart Structures and Systems
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• 제30권3호
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• pp.303-315
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• 2022

The degradation of wheel tread may result in serious hazards in the railway operation system. Therefore, timely wheel defect diagnosis of in-service trains to avoid tragic events is of particular importance. The focus of this study is to develop a novel wheel defect detection approach based on the relevance vector machine (RVM) which enables online detection of potentially defective wheels with trackside monitoring data acquired under different running-speed conditions. With the dynamic strain responses collected by a trackside monitoring system, the cumulative Fourier amplitudes (CFA) characterizing the effect of individual wheels are extracted to formulate multiple probabilistic regression models (MPRMs) in terms of multi-kernel RVM, which accommodate both variables of vibration frequency and running speed. Compared with the general single-kernel RVM-based model, the proposed multi-kernel MPRM approach bears better local and global representation ability and generalization performance, which are prerequisite for reliable wheel defect detection by means of data acquired under different running-speed conditions. After formulating the MPRMs, we adopt a Bayesian null hypothesis indicator for wheel defect identification and quantification, and the proposed method is demonstrated by utilizing real-world monitoring data acquired by an FBG-based trackside monitoring system deployed on a high-speed trial railway. The results testify the validity of the proposed method for wheel defect detection under different running-speed conditions.

• Structural Monitoring and Maintenance
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• 제8권4호
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2823-2834
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• 2023

Austenitic stainless steel welds (ASSWs) of nuclear components undergo aging-related degradations caused by high temperature and neutron radiation. Since irradiation leads to the change of material characteristics, relevant quantification is important for long-term operation, but limitations exist. Although ion irradiation is utilized to emulate neutron irradiation, its penetration depth is too shallow to measure bulk properties. In this study, a systematic approach was suggested to estimate mechanical properties of ion irradiated 308 ASSW. First of all, weld specimens were irradiated by 2 MeV proton to 1 and 10 dpa. Microstructure evolutions due to irradiation in δ-ferrite and austenite phases were characterized and micropillar compression tests were performed. In succession, dislocation density based stress-strain (S-S) relationships and quantification models of irradiation defects were adopted to define phases in finite element analyses. Resultant microscopic S-S curves were compared to verify material parameters. Finally, macroscopic behaviors were calculated by multiscale simulations using real microstructure based representative volume element (RVE). Validity of the approach was verified for the unirradiated specimens such that the estimated S-S curves and 0.2% offset yield strengths (YSs) which was 363.14 MPa were in 10% agreement with test. For irradiated specimens, the estimated YS were 917.41 MPa in 9% agreement.

• Journal of Microbiology and Biotechnology
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• 제23권8호
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• pp.1123-1132
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• 2013

The removal of toxic Cr(VI) by microorganisms is a promising approach for Cr(VI) pollution remediation. In the present study, four indigenous bacteria, named LY1, LY2, LY6, and LY7, were isolated from Cr(VI)-contaminated soil. Among the four Cr(VI)-resistant isolates, strain LY6 displayed the highest Cr(VI)-removing ability, with 100 mg/l Cr(VI) being completely removed within 144 h. It could effectively remove Cr(VI) over a wide pH range from 5.5 to 9.5, with the optimal pH of 8.5. The amount of Cr(VI) removed increased with initial Cr(VI) concentration. Data from the time-course analysis of Cr(VI) removal by strain LY6 followed first-order kinetics. Based on the 16S rRNA gene sequence, strain LY6 was identified as Pseudochrobactrum asaccharolyticum, a species that had never been reported for Cr(VI) removal before. Transmission electron microscopy and energy dispersive X-ray spectroscopy analysis further confirmed that strain LY6 could accumulate chromium within the cell while conducting Cr(VI) removal. The results suggested that the indigenous bacterial strain LY6 would be a new candidate for potential application in Cr(VI) pollution bioremediation.

• Journal of Microbiology and Biotechnology
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• 제22권3호
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• pp.311-315
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• 2012

A novel ${\beta}$-proteobacterium, designated BXN5-$27^T$, was isolated from soil of a ginseng field of Baekdu Mountain in China, and was characterized using a polyphasic approach. The strain was Gram-staining-negative, aerobic, motile, non-spore-forming, and rod shaped. Strain BXN5-$27^T$ exhibited ${\beta}$-glucosidase activity that was responsible for its ability to transform ginsenoside $Rb_1$ (one of the dominant active components of ginseng) to compound Rd. Phylogenetic analysis based on 16S rRNA gene sequences showed that this strain belonged to the family Comamonadaceae; it was most closely related to Ramlibacter henchirensis $TMB834^T$ and Ramlibacter tataouinensis$TTB310^T$ (96.4% and 96.3% similarity, respectively). The G+C content of the genomic DNA was 68.1%. The major menaquinone was Q-8. The major fatty acids were $C_{16:0}$, summed feature 4 (comprising $C_{16:1}$ ${\omega}7c$ and/or iso-$C_{15:0}$ 2OH), and $C_{17:0}$ cyclo. Genomic and chemotaxonomic data supported the affiliation of strain BXN5-$27^T$ to the genus Ramlibacter. However, physiological and biochemical tests differentiated it phenotypically from the other established species of Ramlibacter. Therefore, the isolate represents a novel species, for which the name Ramlibacter ginsenosidimutans sp. nov. is proposed, with the type strain being BXN5-$27^T$ (=DSM $23480^T$ = LMG $24525^T$ = KCTC $22276^T$).