• Smart Structures and Systems
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• v.15 no.3
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• pp.683-698
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• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• Smart Structures and Systems
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• v.24 no.1
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• pp.27-35
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• 2019

This paper proposes a quantitative criterion for optimization of actuator placement for the Prestress-Accumulation Release (PAR) strategy of mitigation of vibrations. The PAR strategy is a recently developed semi-active control approach that relies on controlled redistribution of vibration energy into high-order modes, which are high-frequency and thus effectively dissipated by means of the natural mechanisms of material damping. The energy transfer is achieved by a controlled temporary removal of selected structural constraints. This paper considers a short-time decoupling of rotational degrees of freedom in a frame node so that the bending moments temporarily cease to be transferred between the involved beams. We propose and test a quantitative criterion for placement of such actuators. The criterion is based on local modal strain energy that can be released into high-order modes. The numerical time complexity is linear with respect to the number of actuators and potential placements, which facilitates quick analysis in case of large structures.

• Smart Structures and Systems
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• v.30 no.3
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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.

• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.47-52
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• 2003

To determine the effect of transverse open crack on the dynamic behavior of simply-supported Euler-Bernoulli beam with the moving masses, an iterative modal analysis approach is developed. The influence of depth and position of the crack in the beam, on the dynamic behavior of the simply supported beam system, have been studied by numerical method. The cracked section is represented by a local flexibility matrix, connecting two undamaged beam segments that is, the crack is modeled as a rotational spring. This flexibility matrix defines the relationship between the displacements and forces across the crack section, and is derived by applying a fundamental fracture mechanics theory. As the depth of the crack is increased, the mid-span deflection of the simply-supported beam, with the moving mass, is increased. The crack is positioned in the middle point of the pipe, and the mid-span defection of the simply-supported pipe represents maximum deflection.

• Smart Structures and Systems
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• v.1 no.3
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• pp.309-324
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• 2005

This paper presents an efficient and accurate coupled beam model for piezoelectric bimorphs based on improved first-order shear deformation theory (FSDT). The model combines the equivalent single layer approach for the mechanical displacements and a layerwise modeling for the electric potential. General electric field function is proposed to reasonably approximate the through-the-thickness distribution of the applied and induced electric potentials. Layerwise defined shear correction factor (k) accounting for nonlinear shear strain distribution is introduced into both the shear stress resultant and the electric displacement integration. Analytical solutions for free vibrations and forced response under electromechanical loads are obtained for the simply supported piezoelectric bimorphs with series or parallel arrangement, and the numerical results for various length-to-thickness ratios are compared with the exact two-dimensional piezoelasticity solution. Excellent predictions with low error estimates of local and global responses as well as the modal frequencies are observed.

• Earthquakes and Structures
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• v.20 no.1
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• pp.109-122
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• 2021

Significant progress in the oil and gas industry advances the application of pipeline into an intelligent era, which poses rigorous requirements on pipeline safety, reliability, and maintainability, especially when crossing seismic zones. In general, strike-slip faults are prone to induce large deformation leading to local buckling and global rupture eventually. To evaluate the performance and safety of pipelines in this situation, numerical simulations are proved to be a relatively accurate and reliable technique based on the built-in physical models and advanced grid technology. However, the computational cost is prohibitive, so one has to wait for a long time to attain a calculation result for complex large-scale pipelines. In this manuscript, an efficient and accurate surrogate model based on machine learning is proposed for strain demand prediction of buried X80 pipelines subjected to strike-slip faults. Specifically, the support vector regression model serves as a surrogate model to learn the high-dimensional nonlinear relationship which maps multiple input variables, including pipe geometries, internal pressures, and strike-slip displacements, to output variables (namely tensile strains and compressive strains). The effectiveness and efficiency of the proposed method are validated by numerical studies considering different effects caused by structural sizes, internal pressure, and strike-slip movements.

• Journal of Microbiology and Biotechnology
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• v.30 no.4
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• pp.526-532
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• 2020

A bacterial strain, designated B301^T and isolated from raw chicken meat obtained from a local market in Korea, was characterized and identified using a polyphasic taxonomic approach. Cells were gram-negative, non-motile, obligate-aerobic coccobacilli that were catalase-positive and oxidase-negative. The optimum growth conditions were 30℃, pH 7.0, and 0% NaCl in tryptic soy broth. Colonies were round, convex, smooth, and cream-colored on tryptic soy agar. Strain B301^T has a genome size of 3,102,684 bp, with 2,840 protein-coding genes and 102 RNA genes. The 16S rRNA gene analysis revealed that strain B301^T belongs to the genus Acinetobacter and shares highest sequence similarity (97.12%) with A. celticus ANC 4603^T and A. sichuanensis WCHAc060041^T. The average nucleotide identity and digital DNA-DNA hybridization values for closely related species were below the cutoff values for species delineation (95-96% and 70%, respectively). The DNA G+C content of strain B301^T was 37.0%. The major respiratory quinone was Q-9, and the cellular fatty acids were primarily summed feature 3 (C_16:1 ω6c/C_16:1 ω7c), C_16:0, and C_18:1 ω9c. The major polar lipids were phosphatidylethanolamine, diphosphatidyl-glycerol, phosphatidylglycerol, and phosphatidyl-serine. The antimicrobial resistance profile of strain B301^T revealed the absence of antibiotic-resistance genes. Susceptibility to a wide range of antimicrobials, including imipenem, minocycline, ampicillin, and tetracycline, was also observed. The results of the phenotypic, chemotaxonomic, and phylogenetic analyses indicate that strain B301^T represents a novel species of the genus Acinetobacter, for which the name Acinetobacter pullorum sp. nov. is proposed. The type strain is B301^T (=KACC 21653^T = JCM 33942^T).

• Nuclear Engineering and Technology
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• v.44 no.7
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• pp.791-798
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• 2012

Since standardized fracture test specimens cannot be easily extracted from in-service components, several alternative fracture toughness test methods have been proposed to characterize the deformation and fracture resistance of materials. One of the more promising alternatives is the local approach employing the SP(Small Punch) testing technique. However, this process has several limitations such as a lack of anisotropic yield potential and tediousness in the damage parameter calibration process. The present paper investigates estimation of ductile fracture resistance(J-R) curve by FE(Finite Element) analyses using an anisotropic damage model and enhanced calibration procedure. In this context, specific tensile tests to quantify plastic strain ratios were carried out and SP test data were obtained from the previous research. Also, damage parameters constituting the Gurson-Tvergaard-Needleman model in conjunction with Hill's 48 yield criterion were calibrated for a typical nuclear reactor material through a genetic algorithm. Finally, the J-R curve of a standard compact tension specimen was predicted by further detailed FE analyses employing the calibrated damage parameters. It showed a lower fracture resistance of the specimen material than that based on the isotropic yield criterion. Therefore, a more realistic J-R curve of a reactor material can be obtained effectively from the proposed methodology by taking into account a reduced load-carrying capacity due to anisotropy.

• Journal of Welding and Joining
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• v.23 no.3
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• pp.68-75
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• 2005

The fatigue life of welded joints is associated with crack initiation and propagation life. Theses cannot be easily separated, since the definition of crack initiation is vague due to the initiation of multiple cracks that are distributed randomly along the weld toes. In this paper a method involving a notch strain and fracture mechanical approach, which considers the characteristics of welded joints, e.g. welding residual stress and statistical characteristics of multiple cracks, is proposed, in an attempt to reasonably estimate these fatigue lives. The fatigue crack initiation life was evaluated statistically, e.g. the probability of failure occurrence in 2.3, 50 and $97.7\%$, in which the cyclic response of the local stress/strain hi the vicinity of the weld toes and notch factors derived by the irregular shape of the weld bead are taken into account. The fatigue crack propagation life was simulated by using Monte-Carlo method in consideration of the Ad-factor and the mechanical behavior of mutual interaction/coalescence between two adjacent cracks. The estimated total fatigue life, $(N_T)_{P50\%}$, as a sum of crack initiation and propagation life under the probability of failure occurrence in $50\%$ showed a good agreement with the experimental results. The developed technique for fatigue lift estimation enables to provide a quantitative proportion of crack initiation and propagation life in the total fatigue life due to the nominal stress range, ${\Delta}S$.

• Tribology and Lubricants
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• v.28 no.4
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• pp.173-177
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• 2012

We used contact resonance force microscopy (CRFM) technique to determine the quantitative elastic properties of multiple materials integrated on the sub micrometer scale. The CRFM approach measures the frequencies of an AFM cantilever's first two flexural resonances while in contact with a material. The plain strain modulus of an unknown or test material can be obtained by comparing the resonant spectrum of the test material to that of a reference material. In this study we examined the following bumping materials for flip chip by using copper electrode as a reference material: NiP, Solder (Sn-Au-Cu alloy) and under filled epoxy. Data were analyzed by conventional beam dynamics and contact dynamics. The results showed a good agreement (~15% difference) with corresponding values determined by nanoindentaion. These results provide insight into the use of CRFM methods to attain reliable and accurate measurements of elastic properties of materials on the nanoscale.