• Journal of the Korean Geosynthetics Society
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• v.7 no.3
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• pp.31-40
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• 2008

The deformation behavior of the excavated behind ground due to the displacement shape of retention walls is predicted by numerical analysis, which can be performed using the artificial displacement method with elasto-plastic constitutive model. The displacement shape of the behind ground around the retention wall is similar to the displacement shape of the retention wall. However, far from the retention wall, it changes to the displacement shape of cantilever. The deformation (the settlement, the lateral movement) of the excavated behind ground can be decreased by restraining the upper displacement of the retention wall. The displacement shape of the retention wall due to excavation affects on the plastic failure zone and decreasing zone of stability of the excavated behind ground.

• Geomechanics and Engineering
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• v.13 no.5
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• pp.845-860
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• 2017

It is very important to study displacement prediction in geotechnical engineering. Nowadays, the grey system method, time series analysis method and artificial neural network method are three main methods. Based on the brief introduction, the three methods are analyzed comprehensively. Their merits and demerits, applied ranges are revealed. To solve the shortcomings of the artificial neural network method, a new prediction method based on new evolutionary neural network is proposed. Finally, through two real engineering applications, the analysis of three main methods and the new evolutionary neural network method all have been verified. The results show that, the grey system method is a kind of exponential approximation to displacement sequence, and time series analysis is linear autoregression approximation, while artificial neural network is nonlinear autoregression approximation. Thus, the grey system method can suitably analyze the sequence, which has the exponential law, the time series method can suitably analyze the random sequence and the neural network method almostly can be applied in any sequences. Moreover, the prediction results of new evolutionary neural network method is the best, and its approximation sequence and the generalization prediction sequence are all coincided with the real displacement sequence well. Thus, the new evolutionary neural network method is an acceptable method to predict the measurement displacements of geotechnical engineering.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.2
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• pp.156-163
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• 2005

A monoleaflet polymer artificial heart valve showed the remarkable improvement in pressure drop compared with other types of artificial valve. So, in this study we designed a monoleaflet polymer artificial valve with two supporting members to minimize the deformation and bending stress of the valve with respect to the variation of the gap between two supporting members using nonlinear contact analysis. The marginal valve thickness was also predicted in accordance with the relationship between the thickness and horizontal displacement in order to prevent the dislocation of the valve tip from the frame wall.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.135-136
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• 2022

As a recent technology, it is possible to partially grasp the occurrence of displacement of the entire building through artificial intelligence technology for big data through scanning. However, scanning and data processing take a lot of time, so there is a limit to constant monitoring, so constant monitoring technology of building behavior that combines wireless remote sensors and 3D shape scanning is required. Therefore, in this study, artificial intelligence program coding technology is linked. In addition, a technology capable of real-time wireless remote measurement of structure displacement will be developed through technology development in response to safety management that combines existing building technologies such as sensors. Through this, it is possible to establish an integrated management system for safety inspection and diagnosis.

• Korean Journal of Veterinary Research
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• v.52 no.2
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• pp.141-146
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• 2012

Calving records of Holstein dairy cows from 2005 to 2010 comprising Goyang and Paju cities herd with 2,362 calving events representing 240 twin births were used to evaluate the effect of abomasal displacement and retained placenta after single or twin births on fertility. In retained placenta cows, the period of twin pregnancy (mean 270.5 days) was shorter than that of single pregnancy (mean 274.8 days), however first artificial insemination period (twin: mean 107.4 days, single: mean 92.0 days), non-pregnant period (twin: 154.8 days, single: 132.2 days), and number of insemination (twin: mean 2.00 times, single: mean 1.87 times) of twin pregnancy were increased as compared with single pregnancy. In abomasal displacement cows, first artificial insemination period (twin: mean 122.9 days, single: mean 106.0 days), non-pregnant period (twin: 172.4 days, single: 152.0 days), and number of insemination (twin: mean 2.16 times, single: mean 1.89 times) of twin pregnancy were increased as compared with single pregnancy. The prevalence of complication such as retained placenta, abomasal displacement with single or twin births increased first artificial insemination period, non-pregnant period, and number of insemination period.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.43-44
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• 2022

Recently, there is a demand for a fast and efficient method for measuring displacement during construction or maintenance of new buildings. As the number of safety accidents caused by structural collapse increases, the integrated management plan of the measurement and management system has become a platform and data is shared with stakeholders, so that it is possible to establish safety management in advance according to the displacement of the structure.

• KCI Concrete Journal
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• v.13 no.2
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• pp.3-9
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• 2001

Pseudo dynamic test for seven circular RC bridge piers has been carried out to investigate their seismic performance subjected to expected artificial earthquake motions. The objective of this experimental study is to investigate the hysteretic behavior of reinforced concrete bridge piers, which have been widely used for railway and urban transportation facilities. Important test parameters are confinement steel ratio, and input ground motion. The seismic behavior of circular RC bridge piers under artificial ground motions has been evaluated through displacement ductility, cumulative energy input, and dissipation capacity. It can be concluded that RC bridge piers designed in a limited ductile behavior provision of Eurocode 8 have been determined to show good seismic performance even under moderate artificial earthquakes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1033-1039
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• 2012

Artificial joints are used when joints lose their function because of either the destruction or damage of the composing bones of the joints. To evaluate the primary stability of a femur-implant system, the relative displacement caused by a repeated load is measured immediately after the insertion of the artificial joint. For more accurate stability evaluation, the accurate measurement of the penetration displacement of the artificial joint to the bone and the rotation angle of the artificial joint is essential. In this study, to evaluate the primary stability of the femur-implant system, we propose a new relative displacement measurement method. By using this new method, we comparatively evaluate the primary stability for various surgical methods and the varying stiffness of the cadaver femur-implant itself.

• Wind and Structures
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• v.34 no.6
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• pp.525-538
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• 2022

High-rise wooden pagodas generate large displacement responses under wind action. It is necessary and wise to reduce the wind loads and wind-induced responses on the architectural heritage using artificial plants, which do not damage ancient architecture and increase greenery. This study calculates and analyzes the wind loads and wind-induced responses on the Yingxian Wooden Pagoda, in China, using artificial plants via the finite element analysis (FEA). A three-dimensional wind-loading field was simulated using a wind tunnel test. Wind loads and wind-induced responses, including the displacement and acceleration of the pagoda with and without artificial plants, were analyzed. In addition, three types of tree arrangements were discussed and analyzed using the score method. The results revealed that artificial plants can effectively control wind loads and wind-induced displacements, but the wind-induced accelerations are enlarged to some extent during the process. The height of the tree significantly affected the shelter effects of the structure. The distance of trees from the pagoda and arrangement width of the tree had less influence on shelter effects. This study extends the understanding of the nondestructive method based on artificial plants, for controlling the wind base loads and structural responses of wooden pagodas and preserving architectural heritage via FEA.

• Structural Engineering and Mechanics
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• v.71 no.5
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• pp.545-552
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• 2019

The analysis and design of complex structures like sandwich-panel elements are difficult; the use of finite element method for the analysis is complicated and time consuming when non-linear effects are considered. On the other hand, artificial neural network (ANN) models can capture the non-linear effects and its application requires lesser computational demand. Two ANN models were trained, tested and validated to compute the force for a given displacement of a sandwich-type roof element; 2555 force and element deformation pairs were used for training the ANN models. For the models trained without considering the damping effect, there were two values in the input layer: maximum displacement and current displacement, and for the model considering damping, displacement from the previous step was used as an additional input. Totally, 400 ANN models were trained. Results show that there is a good agreement between the experimental and simulated data, and the models showed a good performance with a mean square error value of 4548.85. Both the ANN models could simulate the inelastic behaviour, loss of rigidity, and evolution of permanent displacements. The models could also interpolate and extrapolate, which enables them to be used as an analysis and design tool for such complex elements.