• Journal of the Korea Concrete Institute
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• v.17 no.4 s.88
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• pp.587-594
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• 2005

The purpose of seismic design is to ensure the serviceability of buildings against earthquake, which might be occurred during the service life of buildings, and to minimize the loss of life by preventing their failure under strong earthquake. The lack resistance of walls resulting from a tendency toward high-rise apartment buildings with shear walls and use of piloti would lead to a concentration of inelastic behaviors in their weak story. In this study, the seismic performance of reinforced concrete shear wall buildings haying piloti was analyzed by using the evaluation techniques which was proposed by FEMA 273 and ATC-40. The results from comparison with these two techniques are summarized as follows.; The results of elastic analysis method for seismic performance evaluation show that the effect of piloti and building height decrease performance index. In case of shear wall building, the state of insufficient shear stress governs their overall performance and it becomes evident in the case of the buildings with more than 25 stories. For the buildings of piloti, the change of mass, weak story, as well as insufficient shear stress, decrease the performance index rapidly compared with the performance index of the buildings without piloti. The results, obtained from the nonlinear static analysis using capacity spectrum method, indicate that the performance Point increases for the structure having Piloti and high story. Also, deformation limits of buildings satisfy the allowable criteria at the life safety level, but the immediate occupancy level is exceeded in buildings which have more than 25 stories.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.97-110
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• 2019

Piles that support offshore wind turbine structures are dominantly subjected to cyclic lateral loads of wind, waves, and tidal forces. For a successful design, it is imperative to investigate the behavior of the cyclic laterally loaded piles; the p-y curve method, in which the pile and soil are characterized as an elastic beam and nonlinear springs, respectively, has been typically utilized. In this study, model pile tests were performed in a 1 g gravitational field so as to investigate the p-y behaviors of cyclic laterally loaded piles installed in saturated dense silty sand. Test results showed that cyclic lateral loads gradually reduced the overall stiffness of the p-y curves (initial stiffness and ultimate soil reaction). This is because the cyclic lateral loads disturbed the surrounding soil, which led to the decrement of the soil resistance. The decrement effects of the overall stiffness of the p-y curves became more apparent as the magnitude of cyclic lateral load increased and approached the soil surface. From the test results, the cyclic p-y curve was developed using a p-y backbone curve method. Pseudo-static analysis was also performed with the developed cyclic p-y curve, confirming that it was able to properly predict the behaviors of cyclic laterally loaded pile installed in saturated dense silty sand.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.3 s.49
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• pp.57-64
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• 2006

Seismic design codes are mainly based on the research results for the inelastic response of structures in high seismicity regions. Since wind loads and gravity loads may govern the design in low seismicity regions in many cases, structures subjected to design seismic loads will have larger overstrength compared to those of high seismicity regions. Therefore, it is necessary to verify if the response modification factor based on high seismicity would be adequate for the design of structures in low seismicity regions. In this study, the adequacy of the response modification factor was verified based on the ductility and overstrength of building structures estimated from the result of nonlinear static analysis. Framed structures are designed for the seismic zones 1, 2A, 4 in UBC-97 representing the low, moderated and high seismicity regions and the overstrength factors and ductility demands of the example structures are investigated. When the same response modification factor was used in the design, inelastic response of structures in low seismicity regions turned out to be much smaller than that in high seismicity regions because of the larger overstrength of structures in low seismicity regions. Demands of plastic rotation in connections and ductility in members were much lower in the low seismicity regions compared to those of the high seismicity regions when the structures are designed with the same response modification factor.

• Earthquakes and Structures
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• v.15 no.6
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• pp.667-685
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• 2018

In eccentrically braced steel frames (EBFs), the links are fuse members which enter inelastic phase before other structure members and dissipate the seismic energy. Based on the force-based seismic design method, damages and plastic deformations are limited to the links, and the main structure members are required tremendous sizes to ensure elastic with limited or no damage. Force-based seismic design method is very common and is found in most design codes, it is unable to determine the inelastic response of the structure and the damages of the members. Nowadays, methods of seismic design are emphasizing more on performance-based seismic design concept to have a more realistic assessment of the inelastic response of the structure. Links use ordinary steel Q345 (the nominal yielding strength $f_y{\geq}345MPa$) while other members use high strength steel (Q460 $f_y{\geq}460MPa$ or Q690 $f_y{\geq}690MPa$) in eccentrically braced frames with high strength steel combination (HSS-EBFs). The application of high strength steels brings out many advantages, including higher safety ensured by higher strength in elastic state, better economy which results from the smaller member size and structural weight as well as the corresponding welding work, and most importantly, the application of high strength steel in seismic fortification zone, which is helpful to popularize the extensive use of high strength steel. In order to comparison seismic behavior between HSS-EBFs and ordinary EBFs, on the basis of experimental study, four structures with 5, 10, 15 and 20 stories were designed by PBSD method for HSS-EBFs and ordinary EBFs. Nonlinear static and dynamic analysis is applied to all designs. The loading capacity, lateral stiffness, ductility and story drifts and failure mode under rare earthquake of the designs are compared. Analyses results indicated that HSS-EBFs have similar loading capacity with ordinary EBFs while the lateral stiffness and ductility of HSS-EBFs is lower than that of EBFs. HSS-EBFs and ordinary EBFs designed by PBSD method have the similar failure mode and story drift distribution under rare earthquake, the steel weight of HSS-EBFs is 10%-15% lower than ordinary EBFs resulting in good economic efficiency.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.9-16
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• 2020

A CFRP sheet has been applied as a structural reinforcement in the field, and various studies are conducted to evaluate the effect of CFRP sheets on reinforced concrete. Although many experiments were performed from previous studies, there are still limitations to analyze structural behaviors with various parameters in experiments directly. This study shows the FEA on structural behaviors of RC beams reinforced with CFRP sheets using ABAQUS software. To simulate debonding failure of CFRP sheets which is a major failure mode of RC beam with CFRP sheets, a cohesive element was applied between the bottom surface of RC beam and CFRP sheets. Both quasi-static method and 2-D symmetric FE model technique were performed to solve nonlinear problems. Results obtained from the FE models show good agreements with experimental results. It was found that reinforcement level of CFRP sheets is closely related to structural behavior of reinforced concrete including maximum strength, initial stiffness and deflection at failure. Also, as over-reinforcement of CFRP sheets could give rise to the brittle failure of RCstructure using CFRP sheets, an appropriate measure should be required when installing CFRP sheets in the structure.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.601-609
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• 2022

Jack-up drilling rigs are mobile offshore platforms widely used in the offshore oil and gas exploration industry. These are independent, three-legged, self-elevating units with a cantilevered drilling facility for drilling and production. A typical jack-up rig includes a triangular hull, a tower derrick, a cantilever, a jackcase, living quarters and legs which comprise three-chord, open-truss, X-braced structure with a spudcan. Generally, jack-up rigs can only operate in water depths ranging from 130m to 170m. Recently, there has been an increasing demand for jack-up rigs for operating at deeper water levels and harsher environmental conditions such as waves, currents and wind loads. All static and dynamic loads are supported through legs in the jack-up mode. The most important issue by society is to secure the safety of the leg structure against collision that causes large instantaneous impact energy. In this study, nonlinear FE -analysis and verification of the requirement against collision for 35MJ recommended by DNV was performed using LS-Dyna software. The colliding ship used a 7,500ton of shore supply vessel, and five scenarios of collisions were selected. From the results, all conditions do not satisfy the class requirement of 35MJ. The loading conditions associated with chord collision are reasonable collision energy of 15M and brace collisions are 6MJ. Therefore, it can be confirmed that the identical collision criteria by DNV need to be modified based on collision scenarios and colliding members.