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  • Open Access

    ARTICLE

    Optimization of Anti-Collapse Drilling Fluid Systems with High Potassium Content

    Yu Xia1, Jian Guan4, Yong Gao5, Shanfa Tang1,2,3,*, Jialuo Rong1

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1609-1622, 2023, DOI:10.32604/fdmp.2023.025263 - 30 January 2023

    Abstract The ash mudstone in some oil formations is highly water-sensitive. The oil formation is fractured, and the risk of well leakage and collapse is not negligible. This study presents a countermeasure for well collapse prevention, based on a “force-chemistry synergistic balance” approach and the utilization of environmentally friendly and efficient hydration inhibitors. The relevance of this approach is demonstrated considering a drilling fluid system with the high potassium content. The analysis shows that the system can maintain good rheological properties, filtration loss and suspension stability even after aging at 130°C for 16 h. The primary More >

  • Open Access

    ARTICLE

    Experimental and Numerical Study on Progressive Collapse Analysis of a Glulam Frame Structure: I. Side Column Exposed to Fire

    Xiaowu Cheng, Xinyan Tao, Lu Wang*

    Journal of Renewable Materials, Vol.11, No.2, pp. 905-920, 2023, DOI:10.32604/jrm.2022.023196 - 22 September 2022

    Abstract This paper presents experimental and numerical investigations on progressive collapse behavior of a two-story glulam frame when the side column is exposed to ISO834 standard fire. The collapse mechanism initiated by fire is identified. The experimental results show that the progressive collapse of a glulam frame could be described for three stages, namely bending effect stage, catenary effect stage and failure stage, respectively. These stages are discussed in detail to understand the structural behavior before and during collapse. It is demonstrated that the entire frame slopes towards the side of the heated column, and the More >

  • Open Access

    ARTICLE

    Intelligent SLAM Algorithm Fusing Low-Cost Sensors at Risk of Building Collapses

    Dahyeon Kim, Junho Ahn*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1657-1671, 2023, DOI:10.32604/cmc.2023.029216 - 22 September 2022

    Abstract When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire, they use old architectural drawings or a simple monitoring method involving a video device attached to a robot. However, using these methods, the disaster situation inside a building at risk of collapse is difficult to detect and identify. Therefore, we investigate the generation of digital maps for a disaster site to accurately analyze internal situations. In this study, a robot combined with a low-cost camera and two-dimensional light detection and ranging (2D-lidar) traverses across a… More >

  • Open Access

    ARTICLE

    Slope Collapse Detection Method Based on Deep Learning Technology

    Xindai An1, Di Wu1,2,*, Xiangwen Xie1, Kefeng Song1

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1091-1103, 2023, DOI:10.32604/cmes.2022.020670 - 31 August 2022

    Abstract So far, slope collapse detection mainly depends on manpower, which has the following drawbacks: (1) low reliability, (2) high risk of human safe, (3) high labor cost. To improve the efficiency and reduce the human investment of slope collapse detection, this paper proposes an intelligent detection method based on deep learning technology for the task. In this method, we first use the deep learning-based image segmentation technology to find the slope area from the captured scene image. Then the foreground motion detection method is used for detecting the motion of the slope area. Finally, we More >

  • Open Access

    ARTICLE

    A New Proximity Indicator for Assessment of Voltage Stability and Critical Loadability Point

    Chandrakant Dondariya*, D. K. Sakravdia

    Energy Engineering, Vol.119, No.3, pp. 947-963, 2022, DOI:10.32604/ee.2022.019118 - 31 March 2022

    Abstract This paper presents a newly developed proximity indicator for voltage stability assessment which can be used to predict critical real system load and voltages at various load buses at critical loading point. The proximity indicator varies almost parabolic with total real load demand and reaches orthogonally to real load axis. This relation has been utilized to predict critical loading point. It has been shown that two operating points are needed for estimating critical point and proper selection of operating points and variation of proximity indicator near collapse point highly affect the accuracy of estimation. Simulation More >

  • Open Access

    ARTICLE

    Experimental and Numerical Assessment on Seismic Performance of Earth Adobe Walls

    Zele Li1, Mohammad Noori2, Wael A. Altabey1,3,*

    Structural Durability & Health Monitoring, Vol.15, No.2, pp. 103-123, 2021, DOI:10.32604/sdhm.2021.011193 - 03 June 2021

    Abstract Earth buildings are common types of structures in most rural areas in all developing countries. Catastrophic failure and destruction of these structures under seismic loads always result in loss of human lives and economic losses. Wall is an important load-bearing component of raw soil buildings. In this paper, a novel approach is proposed to improve the strength and ductility of adobe walls. Three types of analyses, material properties, mechanical properties, and dynamic properties, are carried out for the seismic performance assessment of the adobe walls. These performed studies include that, material properties of the earth… More >

  • Open Access

    ARTICLE

    Analysis of a Water-Inrush Disaster Caused by Coal Seam Subsidence Karst Collapse Column under the Action of Multi-Field Coupling in Taoyuan Coal Mine

    Zhibin Lin1, Boyang Zhang1,2,*, Jiaqi Guo1

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.1, pp. 311-330, 2021, DOI:10.32604/cmes.2021.011556 - 22 December 2020

    Abstract Minin-induced water inrush from a confined aquifer due to subsided floor karst collapse column (SKCC) is a type of serious disaster in the underground coal extraction. Karst collapse column (KCC) developed in a confined aquifer occurs widely throughout northern China. A water inrush disaster from SKCC occurred in Taoyuan coal mine on February 3, 2013. In order to analyze the effect of the KCC influence zone’s (KCCIZ) width and the entry driving distance of the water inrush through the fractured channels of the SKCC, the stress, seepage, and impact dynamics coupling equations were used to… More >

  • Open Access

    ARTICLE

    Three-Dimensional Collapse Analysis for a Shallow Cavity in Layered Strata Based on Upper Bound Theorem

    Hongtao Wang1,2,*, Ping Liu1,2, Lige Wang3,4,*, Chi Liu5, Xin Zhang1,2, Luyao Liu1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.1, pp. 375-391, 2020, DOI:10.32604/cmes.2020.08270 - 19 June 2020

    Abstract Layered rock strata are observed to be common during the excavation of tunnels or cavities, and may significantly affect the deformation and failure characteristics of surrounding rock masses due to various complex forms and mechanical properties. In this paper, we propose a three-dimensional axisymmetric velocity field for roof collapse of shallow cavities in multi rock layers, by considering the influences of roof cross-section shapes, supporting pressure, ground overload, etc. The internal energy dissipation rate and work rates of external forces corresponding to the velocity field are computed by employing the Hoek-Brown strength criterion and its… More >

  • Open Access

    ARTICLE

    Quantum Generative Adversarial Network: A Survey

    Tong Li1, Shibin Zhang1, *, Jinyue Xia2

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 401-438, 2020, DOI:10.32604/cmc.2020.010551 - 20 May 2020

    Abstract Generative adversarial network (GAN) is one of the most promising methods for unsupervised learning in recent years. GAN works via adversarial training concept and has shown excellent performance in the fields image synthesis, image super-resolution, video generation, image translation, etc. Compared with classical algorithms, quantum algorithms have their unique advantages in dealing with complex tasks, quantum machine learning (QML) is one of the most promising quantum algorithms with the rapid development of quantum technology. Specifically, Quantum generative adversarial network (QGAN) has shown the potential exponential quantum speedups in terms of performance. Meanwhile, QGAN also exhibits More >

  • Open Access

    ARTICLE

    Collapse Simulation and Response Assessment of a Large Cooling Tower Subjected to Strong Earthquake Ground Motions

    Tiancan Huang1, Hao Zhou2,*, Hamid Beiraghi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.2, pp. 691-715, 2020, DOI:10.32604/cmes.2020.09046 - 01 May 2020

    Abstract Large cooling towers in thermal power plants and nuclear power plants are likely to suffer from strong earthquakes during service periods. The resulting destructions of the cooling towers would endanger the power plants and threaten the security of the related areas. It is important to use effective means to evaluate the safety status of the cooling towers and guide further precautions as well as retrofitting efforts. This paper is therefore focused on an elaborate numerical investigation to the earthquake-induced collapses of a large cooling tower structure. A complete numerical work for simulation of material failure,… More >

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