• Geomechanics and Engineering
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• v.23 no.5
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• pp.441-454
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• 2020

The tunnel collapse, large deformation of surrounding rock, water and mud inrush are the major geological disasters in soft rock tunnel construction. Among them, tunnel collapse has the most serious impact on tunnel construction. Current research backed theories have certain limitations in identifying the collapse risk of soft rock tunnels. Examining the Zhengwan high-speed railway tunnel, eight soft rock tunnel collapse influencing factors were selected, and the combination of indicator weights based on the analytic hierarchy process and entropy weighting methods was obtained. The results show that the groundwater condition and the integrity of the rock mass are the main influencing factors leading to a soft rock tunnel collapse. A comprehensive fuzzy evaluation model for the collapse risk of soft rock tunnels is being proposed, and the real-time collapse risk assessment of the Zhengwan tunnel is being carried out. The results obtained via the fuzzy evaluation model agree well with the actual situation. A tunnel section evaluated to have an extremely high collapse risk and experienced a local collapse during excavation, verifying the feasibility of the collapse risk evaluation model. The collapse risk evaluation model proposed in this paper has been demonstrated to be a promising and innovative method for the evaluation of the collapse risk of soft rock tunnels, leading to safer construction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.5
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• pp.421-433
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• 2024

As the utilization of underground space increases, preventing collapse accidents during tunnel construction has become a significant challenge. This study aims to quantitatively assess the risk of tunnel collapse during construction by analyzing various influencing factors and proposing a tunnel collapse risk index based on these factors. For the 14 major influencing factors affecting tunnel collapse, weights were calculated using the analytic hierarchy process (AHP) method. Data from 27 collapse cases were collected, and Monte Carlo simulation was used to calculate the grade scores for each influencing factor. These scores were then synthesized to derive the tunnel collapse risk index. The average value of the tunnel collapse risk index was analyzed to be 49.359 points. Future comparisons with section-by-section evaluation results of tunnel collapse risk will allow for the assessment of whether a specific section has a lower or higher collapse risk. This study provides a systematic method for quantitatively evaluating the key factors of tunnel collapse risk, thereby contributing to the prevention of collapse accidents during tunnel construction and the establishment of appropriate countermeasures. Future research is expected to enhance the reliability of the tunnel collapse risk index by incorporating more field data and improving the accuracy of tunnel collapse risk assessment based on this index.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.255-261
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• 2018

In the field of excavation, it is important to recognize and analyze the factors that cause the ground collapse in order to predict and cope with the ground subsidence. However, it is difficult for field engineers to predict ground collapse due to insufficient knowledge of ground subsidence influence factors. Although there are many cases and studies related to the ground subsidence, there is no manual to help practitioners. In this study, we present the criteria for describing and quantifying the influential factors to help the practitioners understand the existing ground collapse cases and classification of the ground subsidence factors revealed through the research. This study aims to improve the understanding of the factors affecting the ground collapse and to provide a GSRp for the ground subsidence risk assessment which can be applied quickly in the field.

• Journal of Korean Neurosurgical Society
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• v.62 no.4
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• pp.450-457
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• 2019

Objective : Anterior cervical discectomy and fusion (ACDF) is commonly used surgical procedure for cervical degenerative disease. Among the various intervertebral spacers, the use of allografts is increasing due to its advantages such as no harvest site complications and low rate of subsidence. Although subsidence is a rare complication, graft collapse is often observed in the follow-up period. Graft collapse is defined as a significant graft height loss without subsidence, which can lead to clinical deterioration due to foraminal re-stenosis or segmental kyphosis. However, studies about the collapse of allografts are very limited. In this study, we evaluated risk factors associated with graft collapse. Methods : We retrospectively reviewed 33 patients who underwent two level ACDF with anterior plating using allogenous bone graft from January 2013 to June 2017. Various factors related to cervical sagittal alignment were measured preoperatively (PRE), postoperatively (POST), and last follow-up. The collapse was defined as the ratio of decrement from POST disc height to follow-up disc height. We also defined significant collapses as disc heights that were decreased by 30% or more after surgery. The intraoperative distraction was defined as the ratio of increment from PRE disc height to POST disc height. Results : The subsidence rate was 4.5% and graft collapse rate was 28.8%. The pseudarthrosis rate was 16.7% and there was no association between pseudarthrosis and graft collapse. Among the collapse-related risk factors, pre-operative segmental angle (p=0.047) and intra-operative distraction (p=0.003) were significantly related to allograft collapse. The cut-off value of intraoperative distraction ${\geq}37.3%$ was significantly associated with collapse (p=0.009; odds ratio, 4.622; 95% confidence interval, 1.470-14.531). The average time of events were as follows: collapse, $5.8{\pm}5.7months$; subsidence, $0.99{\pm}0.50months$; and instrument failure, $9.13{\pm}0.50months$. Conclusion : We experienced a higher frequency rate of collapse than subsidence in ACDF using an allograft. Of the various preoperative factors, intra-operative distraction was the most predictable factor of the allograft collapse. This was especially true when the intraoperative distraction was more than 37%, in which case the occurrence of graft collapse increased 4.6 times. We also found that instrument failure occurs only after the allograft collapse.

• Tunnel and Underground Space
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• v.21 no.5
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• pp.333-340
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• 2011

RMR is most strongly adopted rock classification method to scheme support system in domestic tunnel. However the RMR, which is based on geological survey during design stage of tunnel, can't present the real ground accurately. In this study, authors suggested Weighted-RMR (W-RMR) which is considered weighted value of risk factors of collapse due to prevent collapse and roof falls during tunneling. According to the application of W-RMR to Bye-Gye tunnel, we could change support type flexibly by the risk factors on a face of tunnel.

• Earthquakes and Structures
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• v.18 no.3
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• pp.367-377
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• 2020

Incremental dynamic analysis (IDA) widely uses for the collapse risk assessment procedures of buildings. In this study, an IDA-based collapse risk assessment methodology is proposed, which employs a novel approach for detecting the near-collapse (NC) limit state. The proposed approach uses the modal pushover analysis results to calculate the maximum inter-story drift ratio of the structure. This value, which is used as the upper-bound limit in the IDA process, depends on the structural characteristics and global seismic responses of the structure. In this paper, steel midrise intermediate moment resisting frames (IMRFs) have selected as case studies, and their collapse risk parameters are evaluated by the suggested methodology. The composite action of a concrete floor slab and steel beams, and the interaction between the infill walls and the frames could change the collapse mechanism of the structure. In this study, the influences of the metal deck floor and autoclaved aerated concrete (AAC) masonry infill walls with uniform distribution are investigated on the seismic collapse risk of the IMRFs using the proposed methodology. The results demonstrate that the suggested modified IDA method can accurately discover the near-collapse limit state. Also, this method leads to much fewer steps and lower calculation costs rather than the current IDA method. Moreover, the results show that the concrete slab and the AAC infill walls can change the collapse parameters of the structure and should be considered in the analytical modeling and the collapse assessment process of the steel mid-rise intermediate moment resisting frames.

• Geomechanics and Engineering
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• v.18 no.5
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• pp.515-525
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• 2019

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

• Journal of Korean Neurosurgical Society
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• v.61 no.1
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• pp.1-9
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• 2018

Posttraumatic delayed vertebral collapse, known as Kummell's disease, is increasing in number of patients. This disease is already progressive kyphosis due to vertebral collapse at the time of diagnosis and it causes intractable pain or neurologic deficit due to intravertebral instability. Treatment is very difficult after progression of the disease, and the range of treatment, in hospital day, and cost of treatment are both increased. Clinical features, pathogenesis and radiologic findings of these disease groups were reviewed to determine risk factors for delayed vertebral collapse. The purpose of this article is to suggest appropriate treatment before vertebral collapse for patients with osteoporotic vertebral compression fracture who have risk factors for posttraumatic delayed vertebral collapse.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.41-52
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• 2005

The high density of population and building; can cause catastrophe in urban areas when natural or artificial disasters break out. The aim of this paper is to assess comprehensive disasters risk of urban areas by Geospatial Information System. For this purpose, we classified disasters risk of urban areas into low categories: flood, fire, building-collapse, and shelter, and then determined factors for hazard risk assessment respectively. The results of hazard assessment can be applied to minimize the demage of disasters in establishing the urban management planning. For more systematic and professional approach the further research is need to consider more disaster assessment factors and join with related experts.