Seawater reverse osmosis membrane fouling causes in a full scale desalination plant; through the analysis of environmental issues: raw water quality

Background: Membrane clogging is one of the most important problem for desalination plant operators in Iran, therefore, this study was conducted to investigate the main causes of this problem using field analysis. Methods: In this study, six continuous membranes in a reverse osmosis (RO) pressure vessel under the 33-month service period (April 2017 to November 2019) were selected. The membranes were analyzed through visual evaluation of the outer and inner membrane surface, analyzing the damages and physical harms, oxidative stress tests, iron spot test, fouling chemical analysis using loss on ignition (LOI) tests, X-ray fluorescence (XRF), and Fourier-transform infrared (FTIR) spectroscopy. Results: Particle size distribution in raw seawater (EC = 55 000 μs/cm, turbidity = 11 NTU) was 66.4% smaller than 1 μ and 28.3% between 1 to 1.9 μm. Physical damages were not seen on the membranes but telescopic damages were observed which was due to membrane fouling. Removal efficiencies of turbidity and silt density index (SDI) were 84% and 18%, respectively. Membrane oxidation was also seen. Most of the sediments compositions on the membranes were SiO2, Al2O3, MgO, and Fe2O3. Biological fouling was detected on the membranes surface. Conclusion: Inaccurate use of chlorine neutralizer caused the residual chlorine to be present in the membrane entering water, which damaged the membrane. Accumulation of clogging agents on membrane surface showed malfunction of pretreatment function, therefore, revision of design and operation of units is necessary. Biological fouling is due to non-effective pre-chlorination of drinking water. Metallic compounds sedimentation on the membrane is due to improper use of anti-fouling chemicals. High SDI in the influent shows the need to change the cartridge filters. Keywords: Seawater, Drinking, Chlorides, Particle size, Chloride, Spectroscopy, Fourier transform infrared, Ira

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

Modeling of causes and consequences of human error in mining processes design: A qualitative study

This research was funded by the Hamedan University of Medical Sciences and Health Services and grant number 140008257113.Peer ReviewedObjectius de Desenvolupament Sostenible::3 - Salut i BenestarObjectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

A Mimic Model Approach for Impact Assessment of Mining Activities on Sustainable Development Indicators

This study was supported by the Hamedan University of Medical Sciences and Health and ethical code IR.UMSHA.REC.1400.617. The study program was approved by the national committee for ethics in medical research (IR.UMSHA.REC.1400.617).Peer ReviewedObjectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats SosteniblesObjectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (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

Causal analysis of safety risk perception of Iranian coal mining workers using Fuzzy Delphi and DEMATEL

Underground coal mines, one of the most dangerous work environments, have experienced accidents and disasters. One of the main reasons for those unsafe events is the workers’ poor understanding of the hazards and risks of working in this work environment. Therefore, the present study aims to identify factors affecting the safety risk perception of underground coal mine workers in Iran and investigate their cause-and-effect relationships. By reviewing the literature, 40 variables were identified in five categories: individual, organizational, environmental, task, and external factors. The identified variables were ranked according to the expert group’s opinion in the form of a fuzzy Delphi study regarding their effects on risk perception. In the next step, 23 variables were selected to investigate the cause-and-effect relationships using the DEMATEL method. The study’s findings showed that organizational factors and some individual factors play a fundamental role in workers’ risk perception. The variables of safety culture, safety management style, and safety attitude had the most significant impact, and the variables of personal protective equipment and risk aversion had the smallest impact on workers’ risk perception. The present study’s findings can be used as a guideline to provide effective solutions for managers and workers in improving safety risk perception, subsequently reducing unsafe behaviors and increasing the safety status of underground coal mines.This research was funded by the KASHAN University of Medical Sciences and Health Services and grant number 140008257113.Peer ReviewedObjectius de Desenvolupament Sostenible::8 - Treball Decent i Creixement EconòmicPostprint (published version

Equine Adipose-Derived Mesenchymal Stem Cells: Phenotype and Growth Characteristics, Gene Expression Profile and Differentiation Potentials

Objective: Because of the therapeutic application of stem cells (SCs), isolation and characterization of different types of SCs, especially mesenchymal stem cells (MSCs), have gained considerable attention in recent studies. Adipose tissue is an abundant and accessible source of MSCs which can be used for tissue engineering and in particular for treatment of musculoskeletal disorders. This study was aimed to isolate and culture equine adipose-derived MSCs (AT-MSCs) from little amounts of fat tissue samples and determine some of their biological characteristics. Materials and Methods: In this descriptive study, only 3-5 grams of fat tissue were collected from three crossbred mares. Immediately, cells were isolated by mechanical means and enzymatic digestion and were cultured in optimized conditions until passage 3 (P3). The cells at P3 were evaluated for proliferative capacities, expression of specific markers, and osteogenic, chondrogenic and adipogenic differentiation potentials. Results: Results showed that the isolated cells were plastic adherent with a fibroblast-like phenotype. AT-MSCs exhibited expression of mesenchymal cluster of differentiation (CD) markers (CD29, CD44 and CD90) and not major histocompatibility complex II (MHC-II) and CD34 (hematopoietic marker). Cellular differentiation assays demonstrated the chondrogenic, adipogenic and osteogenic potential of the isolated cells. Conclusion: Taken together, our findings reveal that equine MSCs can be obtained easily from little amounts of fat tissue which can be used in the future for regenerative purposes in veterinary medicine

Prediction of fly-rock using gene expression programming and teaching– learning-based optimization algorithm

Peer ReviewedObjectius de Desenvolupament Sostenible::12 - Producció i Consum ResponsablesObjectius de Desenvolupament Sostenible::12 - Producció i Consum Responsables::12.2 - Per a 2030, assolir la gestió sostenible i l’ús eficient dels recursos naturalsPostprint (published version