• Geomechanics and Engineering
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• v.35 no.2
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• pp.109-119
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• 2023

Ground subsidence in urban areas due to excessive development and degraded underground facilities is a serious problem. Geophysical surveys have been conducted to estimate the distribution and scale of cavities and subsidence. In this study, electrical resistivity tomography (ERT) was performed near an area of road subsidence in an urban area. The subsidence arose due to groundwater leakage that carried soil into a neighboring excavation site. The ERT survey line was located between the main subsidence area and an excavation site. Because ERT data are affected by rapid topographic changes and surrounding structures, the influence of the excavation site on the data was analyzed through field-scale numerical modeling. The effect of an excavation should be considered when interpreting ERT data because it can lead to wrong anomalous results. A method for performing 2D inversion after correcting resistivity data for the effect of the excavation site was proposed. This method was initially tested using a field-scale numerical model that included the excavation site and subsurface anomaly, which was a loosened zone, and was then applied to field data. In addition, ERT data were interpreted using an existing in-house 3D algorithm, which considered the effect of excavation sites. The inversion results demonstrated that conductive anomalies in the loosened zone were greater compared to the inversion that did not consider the effects of excavation.

• Geomechanics and Engineering
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• v.16 no.4
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• pp.399-413
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• 2018

This paper addresses the issue of field measurement of excavation damage zone (EDZ) and its numerical simulation method considering both excavation unloading and blasting load effects. Firstly, a 2000 m-deep rock cavern in China is focused. A detailed analysis is conducted on the field measurement data regarding the mechanical response of rock masses subjected to excavation and blasting operation. The extent of EDZ is revealed 3.6 m-4.0 m, accounting for 28.6% of the cavern span, so it is significantly larger than rock caverns at conventional overburden depth. The rock mass mechanical response subjected to excavation and blasting is time-independent. Afterwards, based on findings of the field measurement data, a numerical evaluation method for EDZ determination considering both excavation unloading and blasting load effects is presented. The basic idea and general procedures are illustrated. It features a calibration operation of damage constant, which is defined in an elasto-plastic damage constitutive model, and a regression process of blasting load using field blasting vibration monitoring data. The numerical simulation results are basically consistent with the field measurement results. Further, some issues regarding the blasting loads, applicability of proposed numerical method, and some other factors are discussed. In conclusion, the field measurement data collected from the 2000 m-deep rock cavern and the corresponding findings will broaden the understanding of tunnel behavior subjected to excavation and blasting at great depth. Meanwhile, the presented numerical simulation method for EDZ determination considering both excavation unloading and blasting load effects can be used to evaluate rock caverns with similar characteristics.

• Journal of Drive and Control
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• v.18 no.2
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• pp.20-31
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• 2021

An excavator is a construction machine that can perform various tasks such as trenching, piping, excavating, slope cutting, grading, and rock demolishing. In the 2010s, unmanned construction equipment using ICT technology was continuously developed. In this paper, the path design process was studied to implement the output data of the decision stage, and the path design algorithm was developed. For example, the output data of the decision stage were terrain data around the excavator, excavator mechanism information, excavator hydraulic information, the position and posture of the bucket at key points, the speed of the desired bucket path, and the required excavation volume. The result of the path design was the movement of the hydraulic cylinder, boom arm, bucket, and bucket edge. The core functions of the path design algorithm are the function of avoiding impact during the excavation process, the function to calculate the excavation depth that satisfies the required excavation volume, and the function that allows the bucket to pass through the main points of the excavation process while maintaining the speed of the desired path. In particular, in the process of developing the last function, the node tracking method expressed in the path design table was newly developed. The path design algorithm was verified as this path design satisfied the JCMAS H02 requirement.

• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.289-311
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• 1991

Analysis of supported excavation system by Elasto-Plastic Isoparametric Finite Element Method and Elasto-Plastic Beam Method have been conducted for the simulation of stepwise underground excavation. Conventional methods, fixed Supported Beam and Spring Supported Beam method, also have been examined and compared with the results of elasto-plastic beam method and field data. Except unavoidable result of upward ground settlement near the top of retaining wall and relatively high bending moment of wall at each excavation level, satisfactory results have been derived using elasto-plastic isopara metric finite element method. The results from elasto-plastic beam analysis program, developed by the author, are proved to be fit field data in acceptable variance as shown in the paper. Displacement and bending moment, of the wall by conventional methods, both fixed supported beam and spring supported beam, are always underestimated than field data, and attention must be given that the diffence increases with deeper excavation depth and lower horizontal subgrade reaction of the ground.

• Journal of the Korea Institute of Building Construction
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• v.7 no.3
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• pp.131-137
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• 2007

To predict deep excavation wall movements is important in the urban areas considering the cost and the safety in construction. Failing to estimate deep excavation wall movements in advance causes too many problems in the projects. The purpose of this study is to propose the forecast model of deep excavation wall movements using artificial neural networks. The data of the Deep Excavation Wall Movements which were done form Long research is used of Artificial neural networks training and apply the real construction work measured data to the Artificial neural networks model. Applying the artificial neural networks to forecast the deep excavation wall movements can significantly contribute to identifying and preventing the accident in the overall construction work.

• Journal of the Korean Geotechnical Society
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• v.16 no.1
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• pp.83-97
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• 2000

In the present study, artificial neural network based on the multi-layer perceptron is used and an optimum model is chosen through the process of efficiency evaluation in order to develop a system predicting maximum displacements of the earth retaining walls at various excavation stages. By analyzing the measured field data collected at various urban excavation sites in Korea, factors influencing on the behaviors of the excavation wall are examined. Among the measured data collected, reliable data are further selected on the basis of the performance ratio and are used as a data base. Data-based measurements are also utilized for both teaming and verifying the artificial neural network model. The learning is carried out by using the back-propagation algorithm based on the steepest descent method. Finally, to verify a validity of the formulated artificial neural network system, both the magnitude and the occurring position of the maximum horizontal displacement are predicted and compared with measured data at real excavation sites not included in the teaming process.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.669-670
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• 2015

Efficient management of the construction heavy equipment is required to reduce the rate of carbon emissions and on-site accidents. The intelligent excavation system (IES) will improve the construction quality and productivity through information technologies and efficient equipment operation, especially in large earthwork projects. Three-dimensional digitized ground data should be required for identifying the path of heavy equipment and work-site environment. Rapid development of terrain laser scanners (TLS) is more readily to acquire the digital data. This study suggests the '3D ground terrain processing platform (3DGTPP)' including data manipulating module and analyzing module of the scanned data for intelligent earthmoving equipment operation. The processing platform consists of six modules, including scanning, registering, manipulating, analyzing, transmitting, and storing. 3D ground terrain processing platform presented in this study will provide fundamental information for intelligent excavation system (IES), which will increase the efficiency of earthworks and safety of workers in significant.

• Geomechanics and Engineering
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• v.21 no.4
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• pp.371-377
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• 2020

There are currently three common methods for selecting excavation supports in Polish hard coal mines. While many factors are considered when choosing appropriate support, these do not include layering or cracking in the excavation ceiling. Although global classifications of rock mass are rarely used in hard coal mines, they are utilised much more frequently during the construction of underground structures such as tunnels. Mining classifications of rock mass have been developed (e.g., in Germany) and they rely on a number of factors but are often related to local mining and geological conditions. This paper discusses the selected findings of a study carried out on seven excavation sites with diverse mining and geological characteristics. Based on the collected data, two indicators were developed to describe rock mass quality. The first indicator is referred to as the roof lithology index WL and describes the quality of the excavation roof in terms of its layering and lithology. The second indicator is the crack intensity factor n and represents the amount of cracks in an excavation's roof. The correctness of the developed indicators was supported by reliable data from the excavation in which the designed support did not fulfill its task but was changed at a later stage, after calculating the proposed indicators.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.303-308
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• 2004

It is recently reported that the importance of environmental impact assessment(EIA) about groundwater outflow problems is beingy raised in the case of tunnel excavation during railroad construction. The EIA about groundwater outflow into railroad tunnel is generally performed using the results of numerical analysis embodied through groundwater flow modeling program like MODFLOW. The basic data for this modeling include (1) the geological and hydrogeological investigation data along the planned block of tunnel excavation, (2) total amount of outflowed groundwater during tunnel excavation, and (3) the status of groundwater level fluctuation in the water-supply wells distributed in the planned block of tunnel excavation. In this study, the authors analyzed the cases of the computational modeling about groundwater outflow in three planned blocks of railroad tunnel, and suggest the environmental impact factors and mitigation plan during EIA of tunnel excavation in railroad construction.

• Geotechnical Engineering
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• v.26 no.9
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• pp.33-47
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• 2010

Underground constructions continue to provide challenges to Geotechnical Engineers yet they pose the best opportunities for development and deployment of advance technologies for analysis, design and construction. The reason for this is that, by virtue of the nature of underground constructions, more data and information on ground characteristics and response become available as the construction progresses. However, due to several barriers, these data and information are rarely, if ever, utilized to modify and improve project design and construction during the construction stage. To enable the use of evolving realtime data and information, and adaptively modify and improve design and construction, the paper presents an analysis and design system, called AMADEUS, for underground projects. AMADEUS stands for Adaptive, real-time and geologic Mapping, Analysis and Design of Underground Space. AMADEUS relies on recent advances in IT (Information Technology), particularly in digital imaging, data management, visualization and computation to significantly improve analysis, design and construction of underground projects. Using IT and remote sensors, real-time data on geology and excavation response are gathered during the construction using non-intrusive techniques which do not require expensive and time-consuming monitoring. The real-time data are then used to update geological and geomechanical models of the excavation, and to determine the optimal, construction sequences and stages, and structural support. Virtual environment (VE) systems are employed to allow virtual walk-throughs inside an excavation, observe geologic conditions, perform virtual construction operations, and investigate stability of the excavation via computer simulation to steer the next stages of construction.