• Journal of Korean Society of Steel Construction
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• v.22 no.3
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• pp.229-239
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• 2010

As a new structural system, the diagrid system resists both gravity and lateral loads with diagonal columns. In current seismic design provisions, however, the response modification factor for a new structural system is not provided yet. ATC-63 provides a new methodology for defining various seismic performance factors, including the response modification factor. ATC-63 includes the collapse margin ratio in modifying the response modification factor, which can vary with many structural systems. In this paper, a non-linear static analysis and a dynamic analysis were conducted for four different diagrid models with 4-to 36-story heights. From these analyses, the response modification factor of the diagrid system was evaluated.

• Fire Science and Engineering
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• v.30 no.1
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• pp.86-95
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• 2016

Weight-bearing building materials are substantially weakened under high temperatures, and this is evident through the collapse of structures once engulfed by fire. Currently, there is no scientific or technological process of evaluating the real-time structural stability of a building whcih is engulfed by flame. There are many building design specifications which aim to reduce the risk of fire, but little consideration given to fire officer safety while operating in a dangerous building. This paper aims to provide direction within building policy in order to ensure the safe evacuation of fire-fighters in case of an impending building collapse. This paper suggests evaluation criteria for buildings which are damaged due to fire, autilizing current information on fire-resistant building design and a fire-resistant capacity.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.

• Earthquakes and Structures
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• v.12 no.3
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• pp.359-374
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• 2017

The seismic events in Northern Italy, May 2012, have revealed the seismic vulnerability of typical Italian precast industrial buildings. The aim of this paper is to present a seismic fragility model for Italian RC precast buildings, to be used in earthquake loss estimation and seismic risk assessment by comparing two building typologies and three different codes: D.M. 3-03-1975, D.M. 16-01-1996 and current Italian building code that has been released in 2008. Based on geometric characteristics and design procedure applied, ten different building classes were identified. A Monte Carlo simulation was performed for each building class in order to generate the building stock used for the development of fragility curves trough analytical method. The probabilistic distributions of geometry were mainly obtained from data collected from 650 field surveys, while the material properties were deduced from the code in place at the time of construction or from expert opinion. The structures were modelled in 2D frameworks; since the past seismic events have identified the beam-column connection as the weakest element of precast buildings, two different modelling solutions were adopted to develop fragility curves: a simple model with post processing required to detect connection collapse and an innovative modelling solution able to reproduce the real behaviour of the connection during the analysis. Fragility curves were derived using both nonlinear static and dynamic analysis.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.1294-1301
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• 2010

In this study, a case study, where a hazard management for tunnel collapses has been quantitatively undertaken based on the KICT Tunnel Hazard(KTH) index, is presented. From this, it was able to timely inform the field engineers when the more detailed investigation is required for checking if any risky factor is shown on the tunnel face. At the same time, variable additional information such as sensitivities of major influence factors are also provided to field engineers from the methodology given in this study. The additional information would be helpful for better understanding of tunnel hazard level at the current tunnelling stage and following the required actions for more detailed checks of risky factors.

• Earthquakes and Structures
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• v.15 no.3
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• pp.253-261
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• 2018

This article details a bridge-specific fragility method developed to enhance the seismic design and resilience of bridges. Current seismic design processes provide guidance for the design of a bridge that will not collapse during a design hazard event. However, they do not provide performance information of the bridge at different hazard levels or due to design changes. Therefore, there is a need for a supplement to this design process that will provide statistical information on the performance of a bridge, beyond traditional emphases on collapse prevention. This article proposes a bridge-specific parameterized fragility method to enable efficient estimation of various levels of damage probability for alternative bridge design parameters. A multi-parameter demand model is developed to incorporate bridge design details directly in the fragility estimation. Monte Carlo simulation and Logistic regression are used to determine the fragility of the bridge or bridge component. The resulting parameterized fragility model offers a basis for a bridge-specific design tool to explore the influence of design parameter variation on the expected performance of a bridge. When used as part of the design process, these tools can help to transform a prescriptive approach into a more performance-based approach, efficiently providing probabilistic performance information about a new bridge design. An example of the method and resulting fragility estimation is presented.

• Journal of the Korean Geosynthetics Society
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• v.4 no.1
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• pp.17-25
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• 2005

This paper presents a case history of a geosynthetics-reinforced segmental retaining wall, which collapsed during a sever rainfall immediately after the completion of the wall construction. In an attempt to identify possible causes for the collapse, a comprehensive investigation was carried out including physical and strength tests on the backfill, stability analyses on the as-built design based on the current design approaches, and slope stability analyses with pore pressure consideration. The investigation revealed that the inappropriate as-built design and the bad-quality backfill were mainly responsible for the collapse. This paper describes the site condition including wall design, details of the results of investigation and finally, lessons learned. Practical significance of the findings from this study is also discussed.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.3-5
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• 1994

It is shown that the power flow considering the voltage characteristic of the composite load has some difference comparing with conventional load flow in this paper. When the load flow is used in a study of the static voltage stability, it is necessary to consider the voltage characteristic of load, since the composite load of a typical power system bas constant power, constant current, and constant impedance characteristic. The load is modeled to a polynomial form in here, and used in solving the load flow problem. In this way, the effect which the voltage characteristic of the load has on several voltage collapse proximity indicator based on sensitivities is compared with the conventional load flow, or with another load model having a different voltage characteristic. In this paper, the voltage collapse proximity indicator using the sensitivity of real power for transmission loss is also proposed, and compared with other indicators.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.4
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• pp.37-44
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• 2019

According to the statistical surveys and studies, insufficient maintenance in the use of existing buildings caused fire and collapse accidents. In this respect, I analyzed the data managed by the current building maintenance and inspection system to find out the actual state of safety management and proposed two significant results. First, regarding the state of the buildings, the safety management status of the small-sized ones, where 20 years or more passed after construction, is the worst and a priority improvement plan is required. Second, there are eight deeply concerning factors for the fire incidents and collapse accidents of buildings. In the order of high risk, these factors are structural strength (seismic design), exterior wall finishing material, basement floor, interior finishing materials, other evacuation facilities, corridors stairs entrances, rooftop, fire partition. We need to have more special designs and management plans regarding high-risk factors as a system to prevent accidents in the building.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.1-12
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• 2021

Altman's Z-score is used to measure a company's financial health and to predict the probability that a company will collapse within 2 years. It is proven to be very accurate to forecast bankruptcy in a wide variety of contexts and markets. The goal of this study is to use Altman's Z-score model to forecast insolvency in non-financial publicly traded enterprises. Non-financial firms are a significant industry in Malaysia, and current trends of consolidation and long-term government subsidies make assessing the financial health of such businesses critical not just for the owners, but also for other stakeholders. The sample of this study includes 84 listed companies in the Kuala Lumpur Stock Exchange. Of the 84 companies, 52 are considered high risk, and 32 are considered low-risk companies. Secondary data for the analysis was gathered from chosen companies' financial reports. The findings of this study show that the Altman model may be used to forecast a company's financial collapse. It dispelled any reservations about the model's legitimacy and the utility of applying it to predict the likelihood of bankruptcy in a company. The findings of this study have significant consequences for investors, creditors, and corporate management. Portfolio managers may make better selections by not investing in companies that have proved to be in danger of failing if they understand the variables that contribute to corporate distress.