Application of artificial intelligence techniques for predicting the flyrock, Sungun mine, Iran

Flyrock is known as one of the main problems in open pit mining operations. This phenomenon can threaten the safety of mine personnel, equipment and buildings around the mine area. One way to reduce the risk of accidents due to flyrock is to accurately predict that the safe area can be identified and also with proper design of the explosion pattern, the amount of flyrock can be greatly reduced. For this purpose, 14 effective parameters on flyrock have been selected in this paper i.e. burden, blasthole diameter, sub-drilling, number of blastholes, spacing, total length, amount of explosives and a number of other effective parameters, predicting the amount of flyrock in a case study, Songun mine, using linear multivariate regression (LMR) and artificial intelligence algorithms such as Gray Wolf Optimization algorithm (GWO), Moth-Flame Optimization algorithm (MFO), Whale Optimization Algorithm (WOA), Ant Lion Optimizer (ALO) and Multi-Verse Optimizer (MVO). Results showed that intelligent algorithms have better capabilities than linear regression method and finally method MVO showed the best performance for predicting flyrock. Moreover, the results of the sensitivity analysis show that the burden, ANFO, total rock blasted, total length and blast hole diameter are the most significant factors to determine flyrock, respectively, while dynamite has the lowest impact on flyrock generation.Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

Developing new models for flyrock distance assessment in open-pit mines

Peer ReviewedObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

Development of new comprehensive relations to assess rock fragmentation by blasting for different open pit mines using GEP algorithm and MLR procedure

The fragment size of blasted rocks considerably affects the mining costs and production efficiency. The larger amount of blasthole diameter (ϕh) indicates the larger blasting pattern parameters, such as spacing (S), burden (B), stemming (St), charge length (Le), bench height (K), and the larger the fragment size.  In this study, the influence of blasthole diameter, blastability index (BI), and powder factor (q) on the fragment size were investigated. First, the relation between each of X20, X50, and X80 with BI, ϕh, and q as the main critical parameters were analyzed by Table curve v.5.0 software to find better input variables with linear and nonlinear forms. Then, the results were analyzed by multivariable linear regression (MLR) procedure using SPSS v.25 software and gene expression programming (GEP) algorithm for prepared datasets of four open-pit mines in Iran. Relations between each of X20, X50, and X80 with the combination of adjusted BI, ϕh, and q were obtained by MLR procedure with good correlations of determination (R2) and less root mean square error (RMSE) values of (0.811, 1.4 cm), (0.874, 2.5 cm) and (0.832, 5.4 cm) respectively. Moreover, new models were developed to predict X20, X50, and X80 by the GEP algorithm with better correlations of R2 and RMSE values (0.860, 1.3 cm), (0.913, 2.49 cm), and (0.885, 5.6 cm) respectively and good agreement with actual field results. The developed GEP models can be used as new relations to estimate the fragment sizes of blasted rocks

Tensile Behavior of Layered Rock Disks under Diametral Loading: Experimental and Numerical Investigations

The Tensile Strength and Cracking Behavior of Layered Rocks in a Tensile Stress Field Are One of the Most Significant Characteristics of Rock Masses, Which May Strongly Affect the Stability of Rock Structures. the Study Presented Here Investigated the Effect of Layer Spacing and Inclination Angle on the Indirect Tensile Strength, Crack Development, Failure Pattern, and Contact Force Chain of Layered Disks under Diametral Loading using Experimental and Numerical Investigations. Numerous Experimental Models Made from Plaster Were Examined under Diametral Loading, and a Two-Dimensional Particle Flow Code (PFC2D) Was Adopted for in Depth Simulation of the Failure Process. Both Numerical and Experimental Results Were Found to Be in Great Agreement and Showed that the Increase in the Layer Orientation Up to 15° Results in the Peak in the Tensile Strength Followed by a Decrease. Specimens with the Spacing Ratio (SR) of 0.5 and 0.1 Showed the Highest and Lowest Tensile and Compressive Stresses at the Disk Center, respectively. Moreover, the Numerical Analysis Indicated the Formation of Three Failure Pattern Types: TL, PB, and TL-PB. Tensile Cracks Mainly Formed in the Direction of Diametral Loading, and their Maximum Number Formed at 15° and SR = 0.5. Additionally, the Shear Ones Formed in a Conjugate System and Had Negligible Numbers. the Analysis of the Contact Force Chain Showed that the Layers Do Not Affect the Compressive Force Chain at Α \u3c 45° But at Higher Angles, the Stronger Layers Transfer Compressive Force. However, when Α Ranges from 0° to 30°, Tensile Forces Are Distributed in Stronger Layers, and with an Increase in Α, the Concentration of These Forces in These Layers Diminishes and the Forces Are Reoriented in the Direction of Diametral Loading

Optimal Compressive Strength of RHA Ultra-High-Performance Lightweight Concrete (UHPLC) and Its Environmental Performance Using Life Cycle Assessment

Frequent laboratory needs during the production of concrete for infrastructure development purposes are a factor of serious concern for sustainable development. In order to overcome this trend, an intelligent forecast of the concrete properties based on multiple data points collected from various concrete mixes produced and cured under different conditions is adopted. It is equally important to consider the impact of the concrete components in this attempt to take care of the environmental risks involved in this production. In this work, 192 mixes of an ultra-high-performance lightweight concrete (UHPLC) were collected from literature representing different mixes cured under different periods and laboratory conditions. These mix proportions constitute measured variables, which are curing age (A), cement content (C), fine aggregate (FAg), plasticizer (PL), and rice husk ash (RHA). The studied concrete property was the unconfined compressive strength (Fc). This exercise was necessary to reduce multiple dependence on laboratory examinations by proposing concrete strength equations. First, the life cycle assessment evaluation was conducted on the rice husk ash-based UHPLC, and the results from the 192 mixes show that the C-783 mix (87 kg/m3 RHA) has the highest score on the environmental performance evaluation, while C-300 (75 kg/m3 RHA) with life cycle indices of 289.85 kg CO2eq. Global warming potential (GWP), 0.66 kg SO2eq. Terrestrial acidification and 5.77 m3 water consumption was selected to be the optimal choice due to its good profile in the LCA and the Fc associated with the mix. Second, intelligent predictions were conducted by using six algorithms (ANN-BP), (ANN-GRG), (ANN-GA), (GP), (EPR), and (GMDH-Combi). The results show that (ANN-BP) with performance indices of R; 0.989, R2; 0.979, mean square error (MSE); 2252.55, root mean squared error (RMSE); 42.46 MPa and mean absolute percentage error (MAPE); 4.95% outclassed the other five techniques and is selected as the decisive model. However, it also compared well and outclassed previous models, which had used gene expression programming (GEP) and random forest regression (RFR) and achieved R2of 0.96 and 0.91, respectively. Doi: 10.28991/CEJ-2022-08-11-03 Full Text: PD

Intelligent prediction of coefficients of curvature and uniformity of hybrid cement modified unsaturated soil with NQF inclusion

The cost and sophisticated equipment required to conduct earthwork laboratory experiments have been of concern to the design and performance monitoring of infrastructures in recent times. Lateritic soils especially those under unsaturated conditions are erratic and deserve close attention in terms of laboratory studies. In order to overcome the rigors and time consumed during experimental procedures, soft computing has been used to predict soil parameters for the purpose of design and construction. In this work, the ANN, GEP and LMR were employed to predict the coefficients of curvature and uniformity of lateritic soil treated with multiple binders locally generated, which were hybrid cement (HC) and nanostructured quarry fines (NQF). The effect of the varying dosages of HC and NQF added to the soil were studied and the behavior of clay activity, clay content, frictional angle, coefficients of curvature and uniformity were measure. 121 datasets were generated from the experimental exercise for the selected parameter both for the predictors and for the targets. These datasets were deployed in the ratio of 70 is to 30% for training and testing of the models predictions respectively. The performances of the models were evaluated using error analysis (VAF, RMSE, MAE) and accuracy (R2) indices and it was observed that the ANN outclassed both GEP and LMR due to its speed and robustness in adopting back-propagation and feed-forward algorithms. Furthermore, the sensitivity analysis showed that F, C, H (HC), NQF and Ac in that order of most influential to least influential influenced the behavior of the Cc model with H (HC) and NQF showing equal effect on the Cc. Also, H (HC), NQF, F, C and Ac in that order of influence from most to least affected the behavior of the Cu predicted model also with HC and NQF having equal effect on the Cu. Generally, the learning techniques showed good performance in predicting the outputs hence are good techniques to be utilized in design and performance evaluation

Prediction of blast-induced ground vibration using gene expression programming (GEP), artificial neural networks (ANNS), and linear multivariate regression (LMR)

In this paper, an attempt was made to find out two empirical relationships incorporating linear mul-tivariate regression (LMR) and gene expression programming (GEP) for predicting the blast-induced ground vibration (BIGV) at the Sarcheshmeh copper mine in south of Iran. For this purpose, five types of effective parameters in the blasting operation including the distance from the blasting block, the burden, the spacing, the specific charge, and the charge per delay were considered as the input data while the output parameter was the BIGV. The correlation coefficient and root mean squared error for the LMR were 0.70 and 3.18 respectively, while the values for the GEP were 0.91 and 2.67 respectively. Also, for evaluating the validation of these two methods, a feed-forward artificial neural network (ANN) with a 5-20-1 structure has been used for predicting the BIGV. Comparisons of these parameters revealed that both methods successfully suggested two empirical relationships for predicting the BIGV in the case study. However, the GEP was found to be more reliable and more reasonable

The Evolution of Dynamic Energy during Drop Hammer Testing of Brazilian Disk with Non-Persistent Joints: An Extensive Experimental Investigation

Rock mass is well known as a discontinuous, heterogeneous, and anisotropic material. The behavior and strength of rock mass is heavily controlled by the condition and orientation of discontinuities (faults, joints, bedding planes) and discontinuity sets. Under dynamic loading conditions, rock bridges along non-persistent discontinuity planes may crack, and a fully persistent discontinuity may form, potentially affecting the stability of a rock structure. The study of the dynamic behavior of rock discontinuities has critical implications for civil engineering, the mining industry, and any other areas where rock mass is utilized as a structural foundation in areas prone to dynamic loading conditions, such as those formed during earthquake events. In this paper, cement-mortar-based Brazilian disks containing open, non-persistent joints were constructed and subjected to impact loading to investigate their impact energy behavior. The effect of some parameters, such as joint continuity factor (the relationship between joint length and rock bridge length), bridge angle, joint spacing, joint orientation, and impact angle were investigated to estimate the required Dynamic Energy for Crack Initiation (DECI), Dynamic Energy for Crack Coalescence (DECC) and failure pattern of specimens. The results of the experiments revealed an increasingly continuous joint reduces the DECI and DECC, while larger joint spacings past the middle value of those experimented increase the DECI and DECC. The bridge angle and loading direction do not affect DECI, but by increasing bridge angle DECC decreases, and it increases by increasing loading direction angle. Finally, an optimization analysis was conducted which showed that joint spacing and joint continuity factors significantly affects DECI, and joint continuity factor and loading direction have significant effect on DECC

Evaluating the Level of Observance of Patient Charter of Rights from the Perspective of Patients Admitted to Shahid Beheshti Hospital in Qom

Background and Objectives: The objective of this study was to evaluate the observance rate of patient charter of rights from the perspective of patients admitted to Shahid Dr Beheshti research and treatment training center affiliated to Qom University of Medical Sciences in an effort to enhance and promote medical care, defend patients' rights and ensure adequate medical and health care. Methods: The current cross-sectional study was conducted on 467 patients in the year 2014. The data were collected using a Likert scale questionnaire with 28 questions whose validity and reliability had been tested and approved in previous studies. Data analysis was performed using T-test analysis of variance via SPSS software Ver. 19. Results: The results obtained from this research indicated that the patient charter of rights was observed based on the overall score of patient charter of rights in 64.62% of cases. Patient rights was observed to be 71.00 % in the category of “optimal receipt of information,”, “patient privacy,” 71 .52 %, “optimal receipt of health services,” 71.44 %, and access to complaints handling system, 44.53 %. Conclusion: According to the findings, the patient charter of rights has been observed satisfactorily according to the admitted patients in the statistical population under investigation, yet it has not been desirable regarding access to the complaint handling system, thus it is suggested that necessary measures be conducted to expand patients and service recipients’ access to complaint handling system

Quercetin and its role in modulating endoplasmic reticulum stress : a review

The endoplasmic reticulum (ER) is the place where proteins and lipids are biosynthesized and where transmembrane proteins are folded. Both pathological and physiological situations may disturb the function of the ER, resulting in ER stress. Under stress conditions, the cells initiate a defensive procedure known as the unfolded protein response (UPR). Cases of severe stress lead to autophagy and/or the induction of cell apoptosis. Many studies implicate ER stress as a major factor contributing to many diseases. Therefore, the modulation of ER stress pathways has become an attractive therapeutic target. Quercetin is a plant-derived metabolite belonging to the flavonoids class which presents a range of beneficial effects including anti-inflammatory, cardioprotective, anti-oxidant, anti-obesity, anti-carcinogenic, anti-atherosclerotic, anti-diabetic, anti-hypercholesterolemic, and anti-apoptotic activities. Quercetin also has anti-cancer activity, and can be used as an adjuvant to decrease resistance to cancer chemotherapy. Furthermore, the effect of quercetin can be increased with the help of nanotechnology. This review discusses the role of quercetin in the modulation of ER stress (and related diseases) and provides novel evidence for the beneficial use of quercetin in therapy