Article
Geosciences, Multidisciplinary
Hoang Nguyen, Xuan-Nam Bui
Summary: In recent years, researchers and scholars have made significant efforts in developing soft computing models (SCMs), especially for problems in the mining industry. A novel SCM called HGS-ANN model, based on a robust meta-heuristic algorithm and artificial neural network, has been proposed in this study for predicting ground vibration intensity (BIGV) with high accuracy. The HGS-ANN model has shown the best performance compared to other benchmark models, and it should be widely applied across open-pit mines to optimize blast patterns and reduce environmental effects.
NATURAL RESOURCES RESEARCH
(2021)
Article
Geosciences, Multidisciplinary
Shahab Hosseini, Masoud Monjezi, Ezzeddin Bakhtavar, Amin Mousavi
Summary: This study developed a new perspective of artificial neural networks using dimensional analysis to improve prediction of blast-induced dust emission. Additionally, it investigated the impact of region's winds on dust emissions in detail.
NATURAL RESOURCES RESEARCH
(2021)
Article
Mining & Mineral Processing
Abbas Khajouei Sirjani, Farhang Sereshki, Mohammad Ataei, Mohammad Ameri Hosseini
Summary: Backbreak is an undesirable phenomenon in blasting operations, and accurate prediction is necessary to prevent its adverse effects. This study collected data from 66 blasting operations and used multiple models to predict backbreak. The results showed that parameters such as hole height, burden, spacing, and uniaxial compressive strength significantly affected backbreak.
ARCHIVES OF MINING SCIENCES
(2022)
Article
Environmental Sciences
Man Wang, Jianguo Zhang, Xinyi Wang, Bo Zhang, Zhenwei Yang
Summary: This study successfully addressed the problem of locating water sources in a complex multiaquifer mine using hydrochemical analysis and the multilayer perceptron neural network approach. The results showed that this method performed better in processing hydrochemical data.
Article
Polymer Science
Francisco M. Monticeli, Roberta M. Neves, Heitor L. Ornaghi Jr, Jose Humberto S. Almeida
Summary: The study focuses on the fabrication of high-performance 3D printable CF/epoxy composites, using approaches based on artificial neural networks, analysis of variance, and response surface methodology for data prediction and analysis. The predicted results show high reliability and low error level, approaching experimental results. Various parameters influencing the fabrication of the composites are considered, and fast and streamlined fabrications of different composite materials with tailor-made properties are demonstrated.
Article
Geochemistry & Geophysics
Bo Ke, Ruohan Pan, Jian Zhang, Wei Wang, Yong Hu, Gao Lei, Xiuwen Chi, Gaofeng Ren, Yuhao You
Summary: Through experiments and simulations, the deep hole blasting parameters of San-Xin gold and copper mine were determined, and the block rate was predicted using a neural network method. It was found that the optimized blasting parameters could reduce the block rate, improve blasting efficiency, and save costs, providing guidance for other mines with similar problems.
Article
Engineering, Geological
Guopeng Lyu, Chuanbo Zhou, Nan Jiang
Summary: This study investigates the damage characteristics and distribution of grouted surrounding rock induced by tunnel blasting through ultrasonic testing and numerical simulation analysis. The results show that there is a certain pattern in the depth and degree of damage to the surrounding rock along the tunnel cross-section. Based on the findings, recommendations for reinforcement are proposed.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Geosciences, Multidisciplinary
Chengyu Xie, Hoang Nguyen, Xuan-Nam Bui, Yosoon Choi, Jian Zhou, Thao Nguyen-Trang
Summary: Four intelligent models were proposed in this study to predict the size of rock distribution in mining blasting, with the FFA-GBM model providing the highest accuracy. The combination of nature-inspired and machine learning algorithms is effective in optimizing blasting parameters and improving blasting efficiency in open mines.
GEOSCIENCE FRONTIERS
(2021)
Review
Engineering, Chemical
Mohammad Hemmat Esfe, Mohammad Hassan Kamyab, Davood Toghraie
Summary: The purpose of this study was to evaluate the studies on estimating the thermophysical properties of nanofluids using artificial neural network (ANN) technique. The research method, target population, and article collection process were presented. The most frequent keywords and the categorization of articles based on publication year were identified. The study showed that the highest number of studies were conducted during 2019, 2020, and 2021. Commonly used nanoparticles and ANN algorithms were identified. The study also examined the contribution of different countries in terms of the number of studies and found that India, Iran, Vietnam, and China had the most published studies. The most frequent post-processing studies with ANN were related to viscosity, thermal conductivity, and heat transfer properties.
Article
Geosciences, Multidisciplinary
Bo Ke, Hoang Nguyen, Xuan-Nam Bui, Romulus Costache
Summary: This study proposed a novel intelligent model, AutoencoderNN-SVR, to accurately predict Ground Vibration Intensity (GVI) in mine blasting, demonstrating high reliability and superior performance compared to traditional models.
NATURAL RESOURCES RESEARCH
(2021)
Article
Agricultural Engineering
Indrajeet Yadav, Akhil Rautela, Agendra Gangwar, Lokesh Wagadre, Shweta Rawat, Sanjay Kumar
Summary: An engineered Synechococcus elongatus UTEX 2973-IspS.IDI strain was used to increase isoprene production by inhibiting CrtE and optimizing process parameters. With the addition of 20 μg/mL alendronate, a cumulative isoprene production of 1.21 mg/gDCW and productivity of 12.6 μg/gDCW/h were achieved. The use of alendronate as an inhibitor and machine learning based optimization showed a 29.52-fold increase in isoprene production compared to unoptimized cultures without alendronate.
BIORESOURCE TECHNOLOGY
(2023)
Article
Engineering, Multidisciplinary
Manuel J. Barros-Daza, Kray D. Luxbacher, Brian Y. Lattimer, Jonathan L. Hodges
Summary: This article introduces a conveyor belt fire classification model to determine effective firefighting strategies and investigate the impact of belt design parameters on fire classification. By using numerical simulations and artificial neural networks, the computational fluid dynamics model was calibrated and validated to achieve highly accurate model results.
JOURNAL OF FIRE SCIENCES
(2022)
Article
Environmental Sciences
Raid Alrowais, Mahmoud M. Abdel Daiem, Renyuan Li, Mohamed Ashraf Maklad, Ahmed M. Helmi, Basheer M. Nasef, Noha Said
Summary: This study aims to assess the groundwater quality for drinking and irrigation purposes in the Al-Jouf region, Saudi Arabia. Physicochemical characteristics of groundwater were determined, and statistical tests and FFNN modeling were applied to evaluate the correlation between parameters and predict water quality indicators. The results showed that most samples were suitable for drinking and irrigation, except for samples from the Al Qaryat region. The dominant ions in the groundwater were alkali metals (K+ and Na+), and the quality indicators for irrigation and drinking could be predicted accurately using the FFNN model.
Article
Energy & Fuels
Zizhuo Xiang, Zexin Yu, Won-Hee Kang, Guangyao Si, Joung Oh, Ismet Canbulat
Summary: This study aims to improve the conventional empirical rock strength estimation method in the Australian coal mining industry by developing artificial neural network (ANN) models. The ANN models provide more accurate predictions for rock uniaxial compression strength (UCS) based on laboratory-measured UCS data and geophysical logs. The accuracy of the ANN models was evaluated and compared to conventional fitting equations, and lithology-specific models were found to be the most accurate. The outcomes of this study have significant implications for geotechnical analysis in underground constructions.
INTERNATIONAL JOURNAL OF COAL GEOLOGY
(2023)
Article
Engineering, Multidisciplinary
Ibham Veza, Asif Afzal, M. A. Mujtaba, Anh Tuan Hoang, Dhinesh Balasubramanian, Manigandan Sekar, I. M. R. Fattah, M. E. M. Soudagar, Ahmed EL-Seesy, D. W. Djamari, A. L. Hananto, N. R. Putra, Noreffendy Tamaldin
Summary: Artificial Neural Network (ANN) is considered as a beneficial prediction tool in automotive applications, especially when the system is complicated and costly to model using simulation programs. However, further examination and improvement are required for the use of ANN in engine applications.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohammad Rezaei, Morteza Rajabi
Summary: This research investigates plastic zones around the powerhouse caverns using numerical analysis, fuzzy inference system, and multivariate regression models. A new predictive equation has been developed, showing that FIS and NA models provide more precise and satisfactory results compared to the MVR model. Key parameters influencing plastic zone estimation around a cavern have been identified.
ENGINEERING WITH COMPUTERS
(2021)
Article
Engineering, Environmental
Seyed Zanyar Seyed Mousavi, Hossein Tavakoli, Parviz Moarefvand, Mohammad Rezaei
COLD REGIONS SCIENCE AND TECHNOLOGY
(2020)
Article
Soil Science
Seyed Zanyar Seyed Mousavi, Mohammad Rezaei
Summary: The influence of freezing-thawing process on the physico-mechanical characteristics of three main rocks of Angouran mine was investigated. The results showed that increasing freezing-thawing cycles led to a decrease in compressive strength, hardness, and dry density, while water absorption and porosity increased. The degradation of UCS was related to the losses of other physic-mechanical properties.
Article
Engineering, Mechanical
Mostafa Asadizadeh, Jamshid Shakeri, Nima Babanouri, Mohammad Rezaei
Summary: Structural defects are inherent characteristics of rock masses, which can be divided into persistent or non-persistent ones. Non-persistent cracks may coalesce to form persistent joints, leading to rock mass instability. The mechanical behavior of non-persistent jointed disks under tensile stress has important implications for rock structures.
THEORETICAL AND APPLIED FRACTURE MECHANICS
(2023)
Article
Green & Sustainable Science & Technology
Yuzhen Wang, Mohammad Rezaei, Rini Asnida Abdullah, Mahdi Hasanipanah
Summary: The intact rock elastic modulus (E) is a key parameter in the design of projects related to rock mechanics and engineering geology. This study aims to evaluate the effectiveness of two meta-heuristic-driven approaches, ANFIS-DE and ANFIS-FA, in predicting E. The ANFIS-FA model outperformed ANFIS-DE, ANFIS, and NN models in terms of predicting E value, based on data collected from the Azad and Bakhtiari dam sites in Iran. Sensitivity analysis showed that P-wave velocity had a larger influence on E compared to other independent variables.
Article
Geosciences, Multidisciplinary
Mohammad Rezaei, Siavash Fallahi
Summary: Resource estimation is an important step in mining and has a significant impact on mine planning and scheduling. This research focuses on optimizing the block model and resource estimation of the Angouran Mine using the UTM global coordinate system. The results show that the new models, with the waste removal and the application of SK, have lower estimation errors compared to the previous estimations.
RUDARSKO-GEOLOSKO-NAFTNI ZBORNIK
(2023)
Article
Engineering, Civil
Seyed Zanyar Seyed Mousavi, Mohammad Rezaei
Summary: This research investigates the degradation rate of physical properties of the Angouran pit bedrock (calc-schist) under specific freeze-thaw cycles. The durability of calc-schist specimens against the number of freeze-thaw cycles is examined using decay function and half-time techniques. Exponential regression models are developed for the mechanical parameters of different rock types and the decay function and half-time techniques are used to study the long-term durability of each rock type.
GEOMECHANICS AND ENGINEERING
(2023)
Article
Engineering, Civil
Mohammad Rezaei, Hazhar Habibi
Summary: This research investigates the stability analysis and support system estimation of the Beheshtabad water transmission tunnel using a combination approach based on rock mass rating (RMR) and rock mass quality index (Q). The study collects 40 datasets related to the petrological, structural, hydrological, physical, and mechanical properties of the tunnel host rocks. The results show that the proposed RMR-Q relations have better accuracy and consistency with actual data compared to previous similar relations, making them suitable for designing tunneling projects with an acceptable level of accuracy and reliability.
STRUCTURAL ENGINEERING AND MECHANICS
(2023)
Article
Mining & Mineral Processing
Mohammad Rezaei, Milad Ghasemi
Summary: This study proposes a new methodology for resource estimation of the Angouran underground mine, which integrates the indicator kriging (IK), simple kriging (SK), and inverse distance weighted (IDW) methods. Waste blocks are first removed using the IK method, and then the amount of mineral resource is estimated using the SK and IDW methods. Variograms are developed to estimate the grade of zinc minerals, and the results show the resource is anisotropic. The correlation coefficients between the measured and estimated zinc values by the SK and IDW methods are 0.76 and 0.75, respectively. The calculated resource using the SK method is 1373962.5 tons with an average grade of 30.11%, whereas the estimated resource using the IDW approach is 1349325 tons with an average grade of 31.88%. The suggested methodology can be successfully applied for resource modeling and grade estimating of the Angouran underground mine.
JOURNAL OF MINING AND ENVIRONMENT
(2023)
Article
Mining & Mineral Processing
Mohammad Rezaei, Navid Nyazyan
Summary: Rock drilling is a crucial and costly process in mining operations. This study investigates the relationship between rock properties and horizontal drilling rate (HDR) to improve drilling efficiency and mining productivity. Through measurements at a marble quarry in Iran and laboratory tests on core samples, it is found that certain physical properties like density and porosity have inverse relationships with HDR, while others like water content and abrasion have direct relationships. New empirical equations are proposed to predict HDR with good accuracy.
JOURNAL OF MINING AND ENVIRONMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Mohammad Rezaei, Masoud Monjezi, Fariborz Matinpoor, Shadman Mohammadi Bolbanabad, Hazhar Habibi
Summary: This study introduces a simulation model that integrates CART analysis and PCA to predict flyrock occurrences during mine blasting operations. Using the Sangan iron ore mine as a case study, the researchers propose 21 key guidelines for designing blasting patterns and highlight the varying importance of input variables through sensitivity analysis.
SIMULATION MODELLING PRACTICE AND THEORY
(2023)
Article
Engineering, Civil
Morteza Rajabi, Reza Rahmannejad, Mohammad Rezaei
Summary: An optimal equation for displacement estimation and a predictive equation for predicting displacement at key point in a powerhouse cavern sidewall under elasto-plastic condition are proposed based on numerical experiments. The location of key point on the sidewall of the cavern is studied, with different positions depending on the cavern's cross section and geo-engineering conditions. Verification of the proposed equations shows good agreement with real values and higher accuracy compared to existing equations.
STRUCTURAL ENGINEERING AND MECHANICS
(2021)
Article
Engineering, Geological
Mostafa Asadizadeh, Mohammad Rezaei
Summary: The strength and deformational behavior of non-persistent jointed rock mass were studied through physical tests, with the development of gene expression programming and linear regression analysis models. It was found that gene expression programming outperformed linear regression, with joint inclination and joint roughness coefficient having the highest and lowest effects on the test outcomes respectively.
INTERNATIONAL JOURNAL OF GEOTECHNICAL ENGINEERING
(2021)
Article
Mining & Mineral Processing
M. Rezaei, M. Asadizadeh
JOURNAL OF MINING AND ENVIRONMENT
(2020)
Article
Engineering, Geological
Mohammad Rezaei
INTERNATIONAL JOURNAL OF GEOTECHNICAL ENGINEERING
(2020)