• Computers and Concrete
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• v.26 no.6
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• pp.467-482
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• 2020

This research focused on analyzing the post-fire behavior of high-performance concrete-filled steel tube (CFST) columns, with the concrete containing tire rubber and steel fibers, under axial compressive loading. The finite element (FE) modeling of such heated columns containing recycled aggregate is a branch of this field which has not received the proper attention of researchers. Better understanding the post-fire behavior of these columns by measuring their residual strength and deformation is critical for achieving the minimum repair level required for structures damaged in the fire. Therefore, to develop this model, 19 groups of confined and unconfined specimens with the variables including the volume ratio of steel fibers, tire rubber content, diameter-to-thickness (D/t) ratio of the steel tube, and exposure temperature were considered. The ABAQUS software was employed to model the tested specimens so that the accurate behavior of the FE-modeled specimens could be examined under test conditions. To achieve desirable results for the modeling of the specimens, in addition to the novel procedure described in this research, the modified versions of models presented by previous researchers were also utilized. After the completion of modeling, the load-axial strain and load-lateral strain relationships, ultimate strength, and failure mode of the modeled CFST specimens were evaluated against the test data, through which the satisfactory accuracy of this modeling procedure was established. Afterward, using a parametric study, the effect of factors such as the concrete core strength at different temperatures and the D/t ratio on the behavior of the CFST columns was explored. Finally, the compressive strength values obtained from the FE model were compared with the corresponding values predicted by various codes, the results of which indicated that most codes were conservative in terms of these predictions.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.241-257
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• 2020

The rapid proliferation of oil/gas drilling and wind turbine installations with jack-up rig-formed structures increases structural safety requirements, due to the greater risks of operational collisions during use of these structures. Therefore, current industrial practices and regulations have tended to increase the required accidental collision design loads (impact energies) for jack-up rigs. However, the existing simplified design approach tends to be limited to the design and prediction of local members due to the difficulty in applying the increased uniform impact energy to a brace member without regard for the member's position. It is therefore necessary to define accidental load estimation in terms of a reasonable collision scenario and its application to the structural response analysis. We found by a collision probabilistic approach that the kinetic energy ranged from a minimum of 9 MJ to a maximum 1049 MJ. Only 6% of these values are less than the 35 MJ recommendation of DNV-GL (2013). This study assumed and applied a representative design load of 196.2 MN for an impact load of 20,000 tons. Based on this design load, the detailed design of a leg structure was numerically verified via an FE analysis comprising three categories: linear analysis, buckling analysis and progressive collapse analysis. Based on the numerical results from this analysis, it was possible to predict the collapse mode and position of each member in relation to the collision load. This study provided a collision strength assessment between attendant vessels and a jack-up rig based on probabilistic collision scenarios and nonlinear structural analysis. The numerical results of this study also afforded reasonable evaluation criteria and specific evaluation procedures.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.200-206
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• 2022

This study is to develop database by an experimental method for the development of condition based maintenance for auxiliary equipment in marine engine systems. Existing ships have been performing regular maintenance, so the actual measurement data development is very incomplete. Therefore, it is best to develop a database on land tests. In this paper, a database developed by an experimental method is presented. First, failure case analysis and reliability analysis were performed to select a failure mode. For the failure simulation test, a test bed for land testing was developed. The failure simulation test was performed based on the failure simulation scenario in which the failure simulation test plan was defined. A 1.5TB failure simulation database has been developed, and it is expected to serve as a basis for ship failure diagnosis and prediction algorithm model development.

• Steel and Composite Structures
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• v.42 no.3
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• pp.407-426
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• 2022

Superior to traditional welded studs, high strength friction-grip bolted shear connectors facilitate the assembling and demounting of the composite members, which maximizes the potential for efficiency in the construction and retrofitting of new and old structures respectively. Hence, it is necessary to investigate the structural properties of high strength friction-grip bolts used in steel concrete composite beams. By means of push-out tests, an experimental study was conducted on post-installed high strength friction-grip bolts, considering the effects of different bolt size, concrete strength, bolt tensile strength and bolt pretension. The test results showed that bolt shear fracture was the dominant failure mode of all specimens. Based on the load-slip curves, uplifting curves and bolt tensile force curves between the precast concrete slab and steel beam obtained by push-out tests, the anti-slip performance of steel-concrete interface and shear behavior of bolt shank were studied, including the quantitative analysis of anti-slip load, and anti-slip stiffness, frictional coefficient, shear stiffness of bolt shank and ultimate shear capacity. Meanwhile, the interfacial anti-slip stiffness and shear stiffness of bolt shank were defined reasonably. In addition, a total of 56 push-out finite element models verified by the experimental results were also developed, and used to conduct parametric analyses for investigating the shear behavior of high-strength bolted shear connectors in steel-concrete composite beams. Finally, on ground of the test results and finite element simulation analysis, a new design formula for predicting shear capacity was proposed by nonlinear fitting, considering the bolt diameter, concrete strength and bolt tensile strength. Comparison of the calculated value from proposed formula and test results given in the relevant references indicated that the proposed formulas can give a reasonable prediction.

• Journal of the Society of Naval Architects of Korea
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• v.58 no.3
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• pp.158-166
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• 2021

In this paper, a numerical analysis technique using a body force model is investigated to estimate the available net thrust of multi-pod-driven ice-breaking vessels under bollard pull and overload conditions. To employ the body force model in present flow simulations, drag and thrust components acting on the pod unit are calculated by using Propeller Open Water (POW) test data. The available net thrusts according to the direction of operation are evaluated in both bollard pull and overload conditions under deep water. The simulation results are compared with the model test data. The available net thrusts, calculated by the present analysis for ahead operating modes at 3~6 knots which are typical speeds of the target vessel in arctic field, are agreed well with the model test results. It is also found that the present result for astern operating mode appears approximately 6 % larger than the model test result. In addition, the available net thrusts are calculated under the both operating conditions accompanied by shallow water effects, and the main cause of the difference is studied. Based on the result of the present study, it is confirmed that the body force model can be applied to the performance evaluation of multi-pod propulsion system and the main engine selection in early design stage of the vessel.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.133-142
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• 2021

Travel pattern recognition is widely used in many aspects such as user trajectory query, user behavior prediction, interest recommendation based on user location, user privacy protection and municipal transportation planning. Because the current recognition accuracy cannot meet the application requirements, the study of travel pattern recognition is the focus of trajectory data research. With the popularization of GPS navigation technology and intelligent mobile devices, a large amount of user mobile data information can be obtained from it, and many meaningful researches can be carried out based on this information. In the current travel pattern research method, the feature extraction of trajectory is limited to the basic attributes of trajectory (speed, angle, acceleration, etc.). In this paper, permutation entropy was used as an eigenvalue of trajectory to participate in the research of trajectory classification, and also used as an attribute to measure the complexity of time series. Velocity permutation entropy and angle permutation entropy were used as characteristics of trajectory to participate in the classification of travel patterns, and the accuracy of attribute classification based on permutation entropy used in this paper reached 81.47%.

• Steel and Composite Structures
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• v.45 no.6
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• pp.907-929
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• 2022

Compression experiments were conducted to investigate the compressive behavior of built-up open-section columns consisting of four cold-formed steel channels (BOCCFSs) of different lengths, thicknesses, and cross-section sizes (OB90 and OB140). The load-displacement curves, failure modes, and maximum compression strength values were analyzed in detail. The tests showed that the failure modes of the OB90 specimens transformed from a large deformation concentration induced by local buckling to flexural buckling with the increase in the slenderness ratio. The failure modes of all OB140 specimens were deformation concentration, except for one long specimen, whose failure mode was flexural buckling. When the slenderness ratios of the specimens were less than 55, the failure modes were controlled by local buckling. Finite element models were built using ABAQUS software and validated to further analyze the mechanical behavior of the BOCCFSs. A parametric study was conducted and used to explore a wide design space. The numerical analysis results showed that when the screw spacing was between 150 mm and 450 mm, the difference in the maximum compression strength values of the specimens was less than 4%. The applicability and effectiveness of the design methods in Chinese GB50018-2002 and AISI-S100-2016 for calculating the compression strength values of the BOCCFSs were evaluated. The prediction methods based on the assumptions produced predictions of the strength that were between 33% to 10% conservative as compared to the tests and the finite element analysis.

• Composites Research
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• v.19 no.4
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• pp.15-22
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• 2006

One of the primary factors limiting the application of composite-metal adhesively bonded joints in structural design is the lack of a good evaluation tool for the interfacial strength to predict the load bearing capacity of boned joints. In this paper composite-steel adhesion strength is evaluated in terms of stress intensity factor and fracture toughness of the interface corner. The load bearing capacity of double lap joints, fabricated by co-cured bonding of composite-steel adherends has been determined using fracture mechanical analysis. Bi-material interface comer stress singularity and its order are presented. Finally stress intensities and fracture toughness of the wedge shape bi-material interface corner are determined. Double lap joint failure locus and its mixed mode crack propagation criterion on $K_1-K_{11}$ plane have been developed by tension tests with different bond lengths.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.