• Steel and Composite Structures
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• v.42 no.4
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• pp.513-538
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• 2022

This paper reports on experiments addressing the buckling and collapse behavior of an innovative built-up cold-formed steel (CFS) columns. The built-up column consists of four individual CFS lipped channels, two of them placed back-to-back at the web using two self-drilling screw fasteners at specified spacing along the column length, while the other two channels were connected flange-to-flange using one self-drilling screw fastener at specified spacing along the column length. In total, 12 experimental tests are reported, covering a wide range of column lengths from stub to slender columns. The initial geometric imperfections and material properties were determined for all test specimens. The effect of screw spacing, load-versus axial shortening behaviour and buckling modes for different lengths and screw spacing were investigated. Nonlinear finite element (FE) models were also developed, which included material nonlinearities and initial geometric imperfections. The FE models were validated against the experimental results, both in terms of axial capacity and failure modes of built-up CFS columns. Furthermore, using the validated FE models, a parametric study was conducted which comprises 324 models to investigate the effect of screw fastener spacing, thicknesses and wide range of lengths on axial capacity of back-to-back and flange-to-flange built-up CFS channel sections. Using both the experimental and FE results, it is shown that design in accordance with the American Iron and Steel Institute (AISI) and Australia/New Zealand (AS/NZS) standards is slightly conservative by 6% on average, while determining the axial capacity of back-to-back and flange-to-flange built-up CFS channel sections.

• Geomechanics and Engineering
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• v.27 no.5
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• pp.447-463
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• 2021

Caisson-type structures are widely used as quay walls in coastal areas. In Korea, for a long time, many caisson-type quay walls have been constructed with a low front water depth. These facilities can no longer meet the requirements of current development. This study developed a new technology for deepening existing caisson-type quay walls using grouting and rubble mound excavation to economically reuse them. With this technology, quay walls could be renovated by injecting grout into the rubble mound beneath the front toe of the caisson to secure its structure. Subsequently, a portion of the rubble mound was excavated to increase the front water depth. This paper reports the results of an investigation of the seismic behavior of a renovated quay wall in comparison to that of an existing quay wall using centrifuge tests and numerical simulations. Two centrifuge model tests at a scale of 1/120 were conducted on the quay walls before and after renovation. During the experiments, the displacements, accelerations, and earth pressures were measured under five consecutive earthquake input motions with increasing magnitudes. In addition, systematic numerical analyses of the centrifuge model tests were also conducted with the PLAXIS 2D finite element (FE) program using a nonlinear elastoplastic constitutive model. The displacements of the caisson, response accelerations, deformed shape of the quay wall, and earth pressures were investigated in detail based on a comparison of the numerical and experimental results. The results demonstrated that the motion of the caisson changed after renovation, and its displacement decreased significantly. The comparison between the FE models and centrifuge test results showed good agreement. This indicated that renovation was technically feasible, and it could be considered to study further by testbed before applying in practice.

• Computers and Concrete
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• v.28 no.5
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• pp.521-532
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• 2021

Present paper focuses on the modeling of size effect on the compressive strength of normal concrete with the application of Discrete Element Method (DEM). Test specimens with different size and shape were cast and uniaxial compressive strength test was performed on each sample. Five different concrete mixes were used, all belonging to a different normal strength concrete class (C20/25, C30/37, C35/45, C45/55, and C50/60). The numerical simulations were carried out by using the PFC 5 software, which applies rigid spheres and contacts between them to model the material. DEM modeling of size effect could be advantageous because the development of micro-cracks in the material can be observed and the failure mode can be visualized. The series of experiments were repeated with the model after calibration. The relationship of the parallel bond strength of the contacts and the laboratory compressive strength test was analyzed by aiming to determine a relation between the compressive strength and the bond strength of different sized models. An equation was derived based on Bazant's size effect law to estimate the parallel bond strength of differently sized specimens. The parameters of the equation were optimized based on measurement data using nonlinear least-squares method with SSE (sum of squared errors) objective function. The laboratory test results showed a good agreement with the literature data (compressive strength is decreasing with the increase of the size of the specimen regardless of the shape). The derived estimation models showed strong correlation with the measurement data. The results indicated that the size effect is stronger on concretes with lower strength class due to the higher level of inhomogeneity of the material. It was observed that size effect is more significant on cube specimens than on cylinder samples, which can be caused by the side ratios of the specimens and the size of the purely compressed zone. A limit value for the minimum size of DE model for cubes and cylinder was determined, above which the size effect on compressive strength can be neglected within the investigated size range. The relationship of model size (particle number) and computational time was analyzed and a method to decrease the computational time (number of iterations) of material genesis is proposed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.775-786
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• 2022

In the plant structures including nuclear power plants, penetrations are frequently installed in walls and slabs to reinforce facilities during operation, and reinforcing bars are sometimes cut off during concrete coring. Since these penetrations are not considered at the design or construction stage, cutting of reinforcing bar during opening installation is actually damage to the structure, structural integrity evaluation considering the stress transition range or effective width around the new penetration is necessary. In this study, various nonlinear analyses and static loading experiments are performed to evaluate the effect of reinforcing bar cutting that occurs when a penetration is newly installed in the shear wall of wall-type building of operating nuclear power plant. In addition, the decrease in wall stiffness due to the installed new penetration and cutting of reinforcing bars is evaluated and the stress and strain distributions of rebars around penetration are also measured.

• Tribology and Lubricants
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• v.37 no.6
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• pp.261-272
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• 2021

This study investigates the structural characteristics of oil-free, gas beam foil journal bearings (GBFJBs) for use in high speed motors. Mathematical modeling was carried out, and reaction force modeling for static load was performed to predict the structural characteristics of the GBFJB. Mathematical modeling and reaction force modeling for static load are performed to predict the structural characteristics of GBFJBs. The reaction force of the test bearing against static loads was measured during experiments and compared with the predicted results. The measured experimental data reveal the nonlinear stiffness characteristics of the GBFJB against varying displacement and agree well with the predictions. Dynamic load tests using an exciter allow to identify the vibration characteristics of the GBFJB. Test results show that the vibration displacement, dynamic force, and acceleration measured on the test bearing are most dominant at the applied dynamic load (synchronization) frequency. Futhermore, the test results show that the hysteresis area recorded during the dynamic tests increases with the excitation amplitude and frequency, and that the beam stick phenomena occurr at high excitation frequencies. The single degree of freedom (DOF) vibration model aids to identify the stiffness and damping coefficient of the GBFJB, which decrease as the excitation frequency increases.

• Structural Engineering and Mechanics
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• v.85 no.1
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• pp.65-80
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• 2023

To explore the effect of Engineered Cementitious Composite (ECC) on improving the progressive collapse resistance of reinforced concrete frames under a middle column removal scenario, six beam-column substructures were tested by quasistatic vertical loading. Among the six specimens, four were ECC-concrete composite specimens consisting of different depth of ECC at the bottom or top of the beam and concrete in the rest of the beam, while the other two are ordinary reinforced concrete specimens with different concrete strength grades for comparison. The experimental results demonstrated that ECC-concrete composite specimens can improve the bearing capacity of a beam-column substructure at the stages of compressive arch action (CAA) and catenary action in comparison with ordinary concrete specimen. Under the same depth of ECC, the progressive collapse resistance of a specimen with ECC at the beam bottom was superior to that at the beam top. With the increase of the proportion of ECC arranged at the beam bottom, the bearing capacity of a composite substructure was increased, but the increase rate slows down with the proportion. Meanwhile, the nonlinear numerical analysis software MSC Marc was used to simulate the whole loading process of the six specimens. Theoretical formulas to calculate the capacities of ECC-concrete composite specimens at the stages of flexural action, CAA and catenary action are proposed. Based on the research results, this study suggests that ECC should be laid out at the beam bottom and the layout depth should be within 25% of the total beam depth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• Geomechanics and Engineering
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• v.35 no.4
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• pp.449-464
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• 2023

Advanced nonlinear effective stress constitutive models are started to be frequently used in one-dimensional (1D) and two-dimensional (2D) site response analysis for assessment of porewater generation and liquefaction potential in soft soil deposits. The emphasis of this research is on the assessment of the implementation of this category of models at the element stage. Initially, the performance of a coupled porewater pressure (PWP) and constitutive models were evaluated employing a catalogue of 40 unidirectional cyclic simple shear tests with a variety of relative densities between 35% and 80% and effective vertical stresses between 40 and 80 kPa. The authors evaluated three coupled constitutive models (PDMY02, PM4SAND and PDMY03) using cyclic direct simple shear tests and for decide input parameters used in the model, procedures are recommended. The ability of the coupled model to capture dilation as strength is valuable because the studied models reasonably capture the cyclic performance noted in the experiments and should be utilized to conduct effective stress-based 1D and 2D site response analysis. Sandy soils may become softer and liquefy during earthquakes as a result of pore-water pressure (PWP) development, which may have an impact on seismic design and site response. The tested constitutive models are mathematically coupled with a cyclic strain-based PWP generation model and can capture small-strain stiffness and large-strain shear strength. Results show that there are minor discrepancies between measured and computed excess PWP ratios, indicating that the tested constitutive models provide reasonable estimations of PWP increase during cyclic shear (r_u) and the banana shape is reproduced in a proper way indicating that dilation and shear- strain behavior is well captured by the models.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.2
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• pp.77-83
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• 2024

The design shear strength equations of RC shear walls have been developed based on their performance under in-plane (IP) loads, thereby failing to account for the potential performance degradation of shear strength when subjected to simultaneous out-of-plane (OOP) loading. Most of the previous experimental studies on RC walls have been conducted in one direction under quasi-static conditions, and due to the difficulty in experimental planning, there is a lack of research on cyclic loading and results under multi-axial loading conditions. During an earthquake, shear walls may yield earlier than their design strength or fail unexpectedly when subjected to multi-directional forces, deviating from their intended failure mode. In this paper, nonlinear analysis in finite element models was performed based on the results of cyclic loading experiments on reinforced concrete shear walls of auxiliary buildings. To investigate the reduction trend in IP shear capacity concerning the OOP load ratio, parametric analysis was conducted using the shear wall FEM. The analysis results showed that as the magnitude of the OOP load increased, the IP strength decreased, with a more significant effect observed as the size of the opening increased. Thus, the necessity to incorporate this strength reduction as a factor for the OOP load effect in the wall design strength equation should be discussed by performing various parametric studies.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.397-402
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• 2007

In this paper, we apply a support vector machine(SVM) that incorporates an optimized nonlinear decision rule over different sets of feature vectors to improve the performance of statistical model-based voice activity detection(VAD). Conventional method performs VAD through setting up statistical models for each case of speech absence and presence assumption and comparing the geometric mean of the likelihood ratio (LR) for the individual frequency band extracted from input signal with the given threshold. We propose a novel VAD technique based on SVM by treating the LRs computed in each frequency bin as the elements of feature vector to minimize classification error probability instead of the conventional decision rule using geometric mean. As a result of experiments, the performance of SVM-based VAD using the proposed feature has shown better results compared with those of reported VADs in various noise environments.