• Korean Journal of Construction Engineering and Management
• /
• v.25 no.1
• /
• pp.32-41
• /
• 2024

In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.6
• /
• pp.541-554
• /
• 2023

The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.6
• /
• pp.555-567
• /
• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• Journal of the Korean GEO-environmental Society
• /
• v.25 no.6
• /
• pp.19-24
• /
• 2024

Urban densification has necessitated the development of subterranean spaces such as subway networks and underground tunnels to facilitate the dispersal and movement of populations. Development of these underground spaces requires excavation from the ground surface, which can induce groundwater flow and potentially lead to ground subsidence and sinkholes, damaging structures. To mitigate these risks, it is essential to model groundwater flow prior to construction, analyze its characteristics, and predict potential groundwater discharge during excavation. In this study, we collected meteorological, topographical, and soil conditions data for the city of ○○, where tunnel construction was planned. Using the Visual MODFLOW program, we modeled the groundwater flow. Excavation sections were set as drainage points to monitor groundwater discharge during the excavation process, and the effectiveness of seepage control measures was assessed. The model was validated by comparing measured groundwater levels with those predicted by the model, yielding a coefficient of determination of 0.87. Our findings indicate that groundwater discharge is most significant at the beginning of the excavation. Additionally, the presence of seepage barriers was found to reduce groundwater discharge by approximately 59%.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.1
• /
• pp.39-58
• /
• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.1
• /
• pp.19-37
• /
• 2024

Rockbolts are the primary-supports in NATM tunnels and are widely used at tunnel construction sites. Among the rockbolts methods applied in domestic tunnel design, fully grouted rockbolts are the most representative and frequently used. Fully grouted rockbolts exhibit relative behavior between the bolt and the ground due to the grout material. However, during numerical analysis for tunnel design, fully grouted rockbolts are often modeled in a way that does not reflect their behavior characteristics. This may result in underestimating or overestimating the force of the supports. Based on a literature review, it was analyzed that fully grouted rockbolts are modeled using truss element or cable element. To analyze the effect of grout properties of cable elements on rockbolts behavior, this paper compared the behavior of rockbolts in two models: one estimating grout properties based on rockbolt pull-out test data, and another assuming complete adhesion between the rockbolts and the ground by applying large grout properties. Under identical tunnel conditions, the numerical analysis was conducted by modeling the fully grouted rockbolts differently using truss and cable elements, and the tunnel behavior was analyzed. The research results suggest that modeling fully grouted rockbolts as a function of the interface effect between the bolts and the ground, specifically considering grout, is desirable. The use of pull-out test data to simulate the behavior of actual fully grouted rockbolts was considered as a valid approach.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.3
• /
• pp.255-280
• /
• 2024

If there are concerns about the stability of segment lining due to section deficiency or large deformation in shield TBM tunnel, reinforcement can be done through ground grouting outside the tunnel or by using steel plate reinforcement, ring beam reinforcement, or inner double layer lining inside the tunnel. Traditional analyses of shield TBM tunnels have been conducted using a continuum method that does not consider the segmented nature of segment lining. This study investigates the reinforcement mechanism for double layer reinforced sections with internal steel linings. By improving the modeling of segment lining, this study applies Break-joint mode (BJM), which considers the segmented characteristics of segment lining, to analyze the deformation characteristics of double layer reinforced sections. The results indicate that the existing concrete segment lining functioned similarly to ground reinforcement around the tunnel, rather than distribution the load. In general, both the BJM model considering the segmentation of segment lining and the continuum rigid method were similar deformation shapes and stress distributions of the lining under load. However, in terms of deformation, when the load strength exceeded the threshold, the deformation patterns of the two models differed.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.3
• /
• pp.281-301
• /
• 2024

The power cable tunnels which are part of the underground transmission line project, are constructed using the shield TBM method. The disc cutter among the shield TBM components plays an important role in breaking rock mass. Efficient tunnel construction is possible only when appropriate replacement occurs as the wear limit is reached or damage such as uneven wear occurs. A study was conducted to determine the wear conditions of disc cutter using a deep learning algorithm based on real-time measurement data of wear and rotation speed. Based on the results of full-scaled tunnelling tests, it was confirmed that measurement data was obtained differently depending on the wear conditions of disc cutter. Using real-time measurement data, an algorithm was developed to determine disc cutter wear characteristics based on a convolutional neural network model. Distributional patterns of data can be learned through CNN filters, and the performance of the model that can classify uniform wear and uneven wear through these pattern features.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.389-395
• /
• 2024

This study aims to deeply analyze the military strategies and tactics used in the battles between Israel and Hamas, to understand the military approaches, technical capabilities, and their impact on the outcomes of the conflict. To achieve this, methodologies such as literature review, data analysis, and case studies were utilized. The research findings confirm that Hamas employed asymmetric tactics, such as rocket attacks and surprise attacks through underground tunnels, to counter Israel's military superiority. On the other hand, Israel responded to Hamas's attacks with the Iron Dome interception system and intelligence-gathering capabilities, but faced difficulties due to Hamas's underground tunnel network. After six months of fighting, the casualties in the Gaza Strip exceeded 30,000, and more than 1.7 million people became refugees. Israel also suffered over 1,200 deaths. Militarily, neither side achieved a decisive victory, resulting in a war of attrition. This study suggests that the Israel-Hamas war exemplifies the complexity of modern asymmetric warfare. Furthermore, it recommends that political compromise between the two sides and active mediation efforts by the international community are necessary for the peaceful resolution of the Israel-Palestine conflict.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.17-22
• /
• 2024

The war that broke out on October 7, 2023 is prolonging and expanding into the Middle East. Although the damage from war is increasing, humanitarian aid to the Gaza Strip has been halted due to UNRWA's deviant actions. Powerful countries have suspended support, and the UN is appealing for support for the Gaza Strip. All damage is borne by civilians in the Gaza Strip, especially women, children, and the elderly. Israel has selected an evacuation zone and evacuation route in the Gaza Strip and established a humanitarian aid route in the border area. However, Hamas's resistance in underground tunnels, using civilian-dense areas and civilian facilities such as hospitals and schools as shields, further amplified civilian casualties. This Israel-Hamas war requires the international community to approach it from a human security perspective. We must strengthen the UN's functions and roles to ensure that humanitarian supplies reach the field and humanitarian intervention forces ensure human dignity and basic rights. We must restore the credibility of the UN's role through the Israel-Hamas war. In addition, Korea should urge the introduction of humanitarian aid and goods, and provide humanitarian goods such as daily necessities and medicine. We must also prepare for deployment as a member of the UN peacekeeping force in the future. These activities will help Korea develop into a model country that fulfills its role as a 'global pivotal nation' and will have a virtuous cycle of international support in the event of a future crisis on the Korean Peninsula.