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Theoretical and numerical studies of rock breaking mechanism by double disc cutters

International Journal of Mining Science and technology 2023年第7期33卷 815-828页

作者： Yiqiang Kang Renshu Yang Liyun Yang Chengxiao Li Jun Chen Haonan Zhu Ning Liu School of Mechanics and Civil Engineering China University of Mining and TechnologyBeijing 100083China School of Civil and Resource Engineering University of Science and Technology BeijingBeijing 100083China China Coal No.3 Construction(Group)Co. Ltd.Hefei 230000China

A plane mechanical model of rock breaking process by double disc cutter at the center of the cutterhead is established based on contact mechanics to analyze the stress evolution in the rock broken by cutters with different spacings. A continuous-discontinuous coupling numerical method based on zero-thickness cohesive elements is developed to simulate rock breaking using double cutters. The process, mechanism,and characteristics of rock breaking are comprehensively analyzed from five aspects: peak force, breaking form, breaking efficiency, crack mode, and breaking degree. The results show that under the penetrating action of cutters, dense cores are formed due to shear failure under respective cutters. The tensile cracks propagate in the rock, and then rock chips form with increasing penetration depth. When the cutter spacing is increased from 10 to 80 mm, the peak force gradually increases, the rock breaking range increases first and then decreases, the specific energy decreases first and then rises, and the breaking coefficient of intermediate rock decreases from 0.955 to 0.788. The area of rock breaking is positively correlated with the length of the tensile crack. Furthermore, the length of the tensile crack accounts for 14.4%–33.6% of the total crack length.

关键词： Disc cutter spacing Mechanical model Indentation experiment Continuous-discontinuous numerical method Fractal dimension

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DISPLACEMENT - CONTROLLED SEISMIC DESIGN OF R/C FRAME WITH STEEL DAMPER COLUMN

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AIJ Journal of technology and Design 2022年第68期28卷 97-102页

作者： Mukoyama, Riho Fujii, Kenji Irie, Chizuru Chiba Institute of Technology JFE Civil Engineering & Construction Corp.

This paper presents a simple displacement-based seismic design method for RC frames with steel damper column. As a numerical example, two 10-story RC frame building models are shown. The results of nonlinear time-history analysis show that the peak displacement at the equivalent height of the building models is close to the target displacement. The strength demand of the beam ends connected to the steel damper columns, and that of RC beam-damper column joints, are calculated from the nonlinear static analysis and compared to the nonlinear time-history analysis results. Then the proper overstrength ratio is discussed. © 2022 Architectural Institute of Japan. All rights reserved.

关键词： Seismic design

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Editorial

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Proceedings of Institution of civil Engineers: Management, Procurement and Law 2023年第4期176卷 139-141页

作者： Magalhães, Pedro Mêda Sousa, Hipólito Calvetti, Diego Hjelseth, Eilif Construction Institute Faculty of Engineering Porto University Porto Portugal Department of Civil and Environmental Engineering Norwegian University of Science and Technology Trondheim Norway

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Properties and Characteristics of Regolith-Based Materials for Extraterrestrial construction

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engineering 2024年第6期37卷 159-181页

作者： Cheng Zhou Yuyue Gao Yan Zhou Wei She Yusheng Shi Lieyun Ding Changwen Miao National Center of Technology Innovation for Digital Construction Huazhong University of Science and TechnologyWuhan 430074China School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Materials Science and Engineering Southeast UniversityNanjing 214135China State Key Laboratory of Materials Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

The construction of extraterrestrial bases has become a new goal in the active exploration of deep *** the construction techniques,in situ resource-based construction is one of the most promising because of its good sustainability and acceptable economic cost,triggering the development of various types of extraterrestrial construction materials.A comprehensive survey and comparison of materials from the perspective of performance was conducted to provide suggestions for material selection and *** types of typical construction materials are discussed in terms of their reliability and applicability in extreme extraterrestrial ***,thermal and optical,and radiation-shielding properties are *** influencing factors and optimization methods for these properties are *** the perspective of material properties,the existing challenges lie in the comprehensive,long-term,and real characterization of regolith-based construction ***,the suggested future directions include the application of high-throughput characterization methods,accelerated durability tests,and conducting extraterrestrial experiments.

关键词： Extraterrestrial construction Characterization Mechanical property Thermal property Optical property Radiation-shielding

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The advance integration and visualization of construction 4.0: automation, robotics, and BIM

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Asian Journal of civil engineering 2024年第7期25卷 5109-5121页

作者： Tanne, Yongki Alexander Indrayani, Ni Luh Ayu Department of Civil Engineering Universitas Komputer Indonesia Bandung 40132 Indonesia Construction Engineering and Management Bandung Institute of Technology Bandung 40132 Indonesia

Fragmentation caused by increased project complexity surely harms the construction industry’s performance, resulting in low productivity and waste. construction 4.0 technology is expected to overcome productivity but causes fragmentation due to its partial implementation. technology integration can provide more significant innovation. In recent years, there has been some research on technological integration. The study’s focus is solely on the interaction between several technologies, with no further explanation of how these technologies interact with one another, and is currently in the conceptual stage. As a result, the purpose of this study is to visualize the integration of construction technology in the form of a comprehensive and up-to-date framework among construction 4.0 technologies. The framework is constructed using link analysis from the database gathered through the systematic literature review using PRISMA Method. It highlights the dominant role of BIM in integrating construction 4.0 technology, despite the most extensive integrated set including only seven out of the 21 identified technologies from previous research. An evaluation was conducted to assess the latest advancements, leading to a proposal for developing a series of construction 4.0 technologies. This research is expected to encourage and motivate stakeholders and academics to adopt and implement integrated construction 4.0 technology, address productivity challenges and overcome fragmentation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： construction 4.0 Fragmentation Novel framework Productivity technology

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An explainable machine learning model for encompassing the mechanical strength of polymer-modified concrete

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Asian Journal of civil engineering 2025年第2期26卷 931-954页

作者： Sobuz, Md. Habibur Rahman Khatun, Mita Kabbo, Md. Kawsarul Islam Sutan, Norsuzailina Mohamed Department of Building Engineering and Construction Management Khulna University of Engineering and Technology Khulna 9203 Bangladesh Department of Civil Engineering University Malaysia Sarawak Sarawak Kota Samarahan 94300 Malaysia

Polymer-modified concrete (PMC) is an advanced building material with more excellent durability, tensile strength, adhesion, and lesser susceptibility to chemical degradation. Recent developments in machine learning (ML) have shown that prediction of compressive strength (CS) of PMC key input factors needed to obtain an optimized mix design are among the areas of applicability of ML. This study used eight machine learning models, which are Decision Tree, Support Vector Machine, K-Nearest Neighbors, Bagging Regression, XG-Boost, Ada-Boost, Linear Regression, Gradient Boosting to predict compressive strength and perform SHAP (Shapley additive explanation) analysis. These hybrid predictive PMC models were developed using a wide-ranging dataset of 382 experimental data points compiled from the literature. A SHAP interaction plot was also used to show how each feature affected predictions on the model outputs. As highlighted in the results, hybrid models had significantly higher performance than conventional models, and the XG-Boost and decision tree model had the highest accuracy. In particular, the XG-Boost and decision tree model reached R² scores of 0.987 for training and 0.577 for testing, proving its remarkable prediction ability for PMC compressive strength. The SHAP analysis confirmed that coarse aggregate, cement, and SCMs had the most significant influence on CS, with all other variables contributing lower values. The Partial Dependence Plots (PDP) analysis allowed a relatively simple interpretation of the contribution of individual inputs to the CS predictions. These results are useful for construction purposes and provide engineers and builders with first-hand knowledge and insight into the importance of individual components on PMC development and performance. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Compressive strength prediction Machine learning PDP analysis Polymer modified concrete SHAP

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Evaluating the effects of recycled concrete aggregate size and concentration on properties of high-strength sustainable concrete

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Journal of King Saud University - engineering Sciences 2024年第3期36卷 216-227页

作者： Sobuz, Md. Habibur Rahman Datta, Shuvo Dip Akid, Abu Sayed Mohammad Tam, Vivian W.Y. Islam, Shoaib Rana, Md. Jewel Aslani, Farhad Yalçınkaya, Çağlar Sutan, Norsuzailina Mohamed Department of Building Engineering and Construction Management Khulna University of Engineering and Technology Khulna9203 Bangladesh Civil Engineering Arkansas State University JonesboroAR72467 United States School of Built Environment Western Sydney University Australia School of Civil Environmental and Mining Engineering The University of Western Australia Australia Department of Civil Engineering Faculty of Engineering Dokuz Eylül University İzmir Turkey Department of Civil Engineering Universiti Malaysia Sarawak Kota Samarahan Sarawak94300 Malaysia

This paper studies the fresh and mechanical properties of high-strength concrete (HSC) by incorporating recycled concrete aggregates (RCA) of varying sizes and concentrations. The recycled aggregate concrete (RAC) was prepared by partially replacing RCA with natural coarse aggregate (NCA) at 0%, 15%, 30%, and 45%, with aggregate sizes ranging from 5 to 12 and 12–20-mm. Fresh concrete properties, such as slump, Kelly ball, compacting factor, K-slump, and fresh density, were tested to determine the influence of RCA size and concentration. In addition, the mechanical properties were studied through the execution of compressive, split-tensile, and stress-strain tests. The test results revealed that increasing the RCA concentration declines the fresh and hardened properties of HSC. In the fresh concrete experimentation, the 12–20 mm aggregate size RAC mixes exhibited greater workability than the 5–12 mm aggregate mixes. On the contrary, 5–12 mm aggregate mixes RAC had higher compressive and split-tensile strength and a higher modulus of elasticity than 12–20 mm aggregate mixes concrete. When it comes to sustainability, the study found that the smaller size range of RAC produces inferior embodied CO2 (eCO2) and provides a cost-effective and sustainable solution for the construction industry. © 2022 The Authors

关键词： Sustainable development

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Mechanical Characteristics and Energy Evolution of Limestone Under the Action of Acid Corrosion

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Iranian Journal of Science and technology - Transactions of civil engineering 2024年第1期49卷 613-628页

作者： Liu, Wang Liu, Yongsheng Wang, Cui Zhai, Maolin School of Civil Engineering and Architecture East China Jiaotong University Nanchang 330013 China Department of Civil Engineering Jiangxi Institute of Construction Nanchang 330200 China Department of Civil Engineering Nanchang institute of technology Nanchang 330044 China

This study aims to examine the impact of acid corrosion on the mechanical properties and fractal characteristics of limestone. The mineral composition of the limestone was determined using XRD testing. The mechanical properties and acoustic emission signals of limestone, which were corroded using a sulfuric acid solution at pH = 1 for 30, 60, and 90 days, were determined using uniaxial compression and acoustic emission testing methods. The causes of the structural deterioration of limestone were analyzed by examining the corrosion mechanism. The energy evolution law and fracture fractal characteristics of rock samples during the destruction process nwere studied. The results indicate that the uniaxial compressive strength and elastic modulus of limestone gradually decrease as the corrosion time increases. The cumulative acoustic emission ring counts decrease and the duration of high acoustic emission ring counts also decreases. Prior to entering the plastic phase, the dissipated energy of rock samples subjected to acid solution corrosion is found to be higher compared to rock samples exposed to natural conditions. As the plastic phase is reached, the dissipated energy decreases with the progression of the corrosion time. However, the percentage of dissipated energy increases, indicating an improvement in the ductility of the rock *** addition, the total energy and elastic strain energy peak values decrease as the corrosion time increases. This leads to a decrease in both the energy absorption capacity and the energy storage limit of the rock samples. Furthermore, the fractal dimension of comminution and the degree of comminution also decrease. This paper study offers valuable insights into the prevention and control of structural hazards in civil engineering in regions with high occurrences of acid rain. © The Author(s), under exclusive licence to Shiraz University 2024.

关键词： Acid corrosion Acoustic emission Energy evolution Limestone Mechanical properties

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Multiple machine learning models for predicting annual energy consumption and demand of office buildings in subtropical monsoon climate

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Asian Journal of civil engineering 2025年第1期26卷 293-309页

作者： Ashraf, Jawad Azam, Rafi Rifa, Asfia Akter Rana, Md Jewel Department of Building Engineering and Construction Management Khulna University of Engineering and Technology Khulna 9203 Bangladesh Department of Chemical Engineering Khulna University of Engineering and Technology Khulna 9203 Bangladesh Department of Civil Engineering Washington State University Pullman WA United States

Reducing a building’s energy use has many real-world applications. An early-stage design could have a quantitative foundation for energy-saving designs if energy consumption could be predicted quickly and accurately. The main issue that designers are currently dealing with is the incompatibility of building modelling and energy simulation software. In order to realize the flexibility of building energy systems, accurate and timely thermal load prediction for buildings is essential. Here, three machine learning (ML) models – Artificial Neural Network (ANN), Random Forest (RF) and Extreme Gradient Boosting (XGBoost) were used, for forecasting an office building’s load demand and energy usage. A case study building was selected and analysed via Autodesk Revit and Green Building Studio. For the modelling of ANN, 438 simulated data samples were created based on different design parameters considering different window, wall, roof materials and window to wall ratio, and meteorological conditions considering dew point, dry bulb, wet bulb temperature and relative humidity of seven major cities in Bangladesh. The findings show that the ANN model performs best the best in predicting annual electricity use with an R² value of 0.991 and annual load demand with an R² value of 0.995. The RMSE values ranged between 3.83 and 5.10 showing high accuracy of prediction between the three ML models. Afterwards SHAP analysis was used to analyse the input features effect on the energy consumption. Findings show that relative humidity, dry bulb temperature and pressure significantly affects the energy consumption. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Artificial neural network Autodesk Revit Energy simulation Random forest XGBoost and SHAP

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How machine learning can transform the future of concrete

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Asian Journal of civil engineering 2025年第4期26卷 1395-1411页

作者： Mouzoun, Kaoutar Bouyahyaoui, Azzeddine Abdelali, Hanane Moulay Cherradi, Toufik Baba, Khadija Masrour, Ilham Zemed, Najib Mohammed V University in Rabat Mohammadia School of Engineering Civil Engineering and Construction Laboratory (GCC) Rabat Morocco Mohammed V University in Rabat High School of Technology Civil Engineering and Environment Laboratory (LGCE) Sale Morocco

The concrete industry is confronted with persistent challenges, such as the need for extensive experimentation, time limitations, and high costs. Machine learning (ML) has become an extremely useful tool, providing diverse applications to tackle these challenges. This paper reviews the growing influence of ML on the concrete industry, highlighting its potential to revolutionize different aspects of concrete research and practical applications. The review explores the evolution of ML in this field, identifying key techniques, algorithms, and data sources commonly used in concrete related studies. It discusses the diverse applications of ML, including material characterization, mix design optimization, prediction of concrete properties, enhancement of nonlinear finite element analysis, crack detection, improvements in sustainability, and structural health monitoring. Additionally, the paper addresses challenges faced in the implementation of ML and offers recommendations to enhance its accuracy and effectiveness for concrete researchers, engineers, and practitioners. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Characterization Concrete Crack detection Machine learning Optimization Prediction Sustainability

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