Volume 12 (2021)
Volume 11 (2020)
Volume 10 (2019)
Volume 9 (2018)
Volume 8 (2017)
Volume 7 (2016)
Volume 6 (2015)
Volume 5 (2014)
Volume 4 (2013)
Volume 3 (2012)
Volume 2 (2011)
Volume 1 (2010)
1. Probabilistic Prediction of Acid Mine Drainage Generation Risk Based on Pyrite Oxidation Process in Coal Washery Rejects - A Case Study

F. Hadadi; B. Jodeiri Shokri; M. Zare Naghadehi; F. Doulati Ardejani

Volume 12, Issue 1 , Winter 2021, , Pages 127-137


  In this paper, we investigate a probabilistic approach in order to predict how acid mine drainage is generated within coal waste particles in NE Iran. For this, a database is built based on the previous studies that have investigated the pyrite oxidation process within the oldest abandoned pile during ...  Read More

2. Prediction of Acid Mine Drainage Generation Potential of A Copper Mine Tailings Using Gene Expression Programming-A Case Study

B. Jodeiri Shokri; H. Dehghani; R. Shamsi; F. Doulati Ardejani

Volume 11, Issue 4 , Autumn 2020, , Pages 1127-1140


  This work presents a quantitative predicting likely acid mine drainage (AMD) generation process throughout tailing particles resulting from the Sarcheshmeh copper mine in the south of Iran. Indeed, four predictive relationships for the remaining pyrite fraction, remaining chalcopyrite fraction, sulfate ...  Read More

3. Application of Phytoremediation to Reduce Environmental Pollution of Copper Smelting and Refinery Factories: a Review

R. Siyar; F. Doulati Ardejani; M. Farahbakhsh; M. Yavarzadeh; S. Maghsoudy

Volume 11, Issue 2 , Spring 2020, , Pages 517-537


  Copper smelting and refinery factories are the final stages of a pyrometallurgical processing chain, and they cause many environmental challenges around the world. One of the most common environmental problems of these factories is toxic emissions. These toxic gases have harmful effects on the vegetation, ...  Read More

4. Application of non-linear regression and soft computing techniques for modeling process of pollutant adsorption from industrial wastewaters

A. Aryafar; R. Mikaeil; F. Doulati Ardejani; S. Shaffiee Haghshenas; A. Jafarpour

Volume 10, Issue 2 , Spring 2019, , Pages 327-337


  The process of pollutant adsorption from industrial wastewaters is a multivariate problem. This process is affected by many factors including the contact time (T), pH, adsorbent weight (m), and solution concentration (ppm). The main target of this work is to model and evaluate the process of pollutant ...  Read More

5. A new stochastic 3D seismic inversion using direct sequential simulation and co-simulation in a genetic algorithm framework

H. Sabeti; A. Moradzadeh; F. Doulati Ardejani; A. Soares

Volume 8, Issue 3 , Summer 2017, , Pages 321-335


  Stochastic seismic inversion is a family of inversion algorithms in which the inverse solution was carried out using geostatistical simulation. In this work, a new 3D stochastic seismic inversion was developed in the MATLAB programming software. The proposed inversion algorithm is an iterative procedure ...  Read More

6. Determining fractal parameter and depth of magnetic sources for ardabil geothermal area using aeromagnetic data by de-fractal approach

A. Khojamli; F. Doulati Ardejani; A. Moradzadeh; A. Nejati Kalateh; A. Roshandel Kahoo; S. Porkhial

Volume 8, Issue 1 , Winter 2017, , Pages 93-101


  The Ardabil geothermal area is located in the northwest of Iran, which hosts several hot springs. It is situated mostly around the Sabalan Mountain. The Sabalan geothermal area is now under investigation for the geothermal electric power generation. It is characterized by its high thermal gradient and ...  Read More

7. Application of artificial neural network and genetic algorithm to modelling the groundwater inflow to an advancing open pit mine

S. Bahrami; F. Doulati Ardejani

Volume 6, Issue 1 , Winter 2015, , Pages 21-30


  In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius ...  Read More