En
  • دکتری (1380)

    مهندسی معدن

    انستیتو تکنولوژی هندوستان، بنارس هندو، وارانسی، هندوستان

  • کارشناسی‌ارشد (1371)

    مهندسی معدن - استخراج معدن

    دانشگاه تهران، تهران، ایران

  • کارشناسی (1367)

    مهندسی معدن - استخراج معدن

    دانشگاه تهران، تهران، ایران

  • چالزنی و آتشباری
  • طراحی و برنامه ریزی در معادن سطحی
  • شبیه سازی و مدلسازی در معادن
  • تحلیل پایداری در معادن

    دکتر منجزی در سال 1381 به عنوان استادیار (در حال حاضر استاد) در بخش مهندسی معدن دانشگاه تربیت مدرس مشغول به کار شد. زمینه‌های تحقیقاتی ایشان آتشباری در معادن و طراحی و برنامه‌ریزی در معادن روباز است. دکتر منجزی مشارکت چشمگیری در برنامه درسی گروه استخراج مواد معدنی داشته و علاوه بر این خروجی تحقیقات انجام شده در قالب مقالات نشانگر میزان تلاش ایشان در حوزه مهندسی معدن است. دکتر منجزی توجه خاصی به امر آموزش داشته و در این امر ضمن تعریف پروژه‌های کاربردی، با انجام بازدید از معادن در افزایش کیفی تدریس تلاش می‌نماید. دکتر منجزی تحقیقات قابل توجهی در زمینه آتشباری در معادن و طراحی و برنامه‌ریزی در معادن روباز که دو موضوع مهم در مهندسی معدن محسوب می‌شوند، انجام داده است. بطور کلی ایشان بیش از 100 مقاله علمی پژوهشی در نشریات معتبر داخلی و خارجی با ضریب تاثیر بالا به چاپ رسانده است. در حال حاضر اچ ایندکس ایشان در سیستم اسکوپوس 26 و ارجاعات 1645 عدد است. دکتر منجزی یک کتاب با عنوان مهندسی انفجار در معادن روباز با استفاده از سیستم‌های هوشمند تالیف کرده است.

    ارتباط

    رزومه

    Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations

    Parichehr Bayat, Masoud Monjezi, Amirhossein Mehrdanesh, Manoj Khandelwal
    Journal PapersEngineering with Computers , 2021 March 4, {Pages 10-Jan }

    Abstract

    Blast-induced ground vibration is considered as one of the most hazardous phenomena of mine blasting, which can even cause casualties and severe damages to the adjacent properties. Measuring peak particle velocity (PPV) is helpful to know the actual vibration level but prediction of blast vibration prior to the blast is a tedious job due to involvement of blast design, explosive and rock parameters. Nowadays, efficient application of intelligent systems has been approved in different branches of science and technology. In this paper, a gene expression programming (GEP) model was developed to predict PPV using various blasting patterns as model inputs, which showed a high level of accuracy for the implemented model. Also, to optimize blast p

    Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation

    A Mehrdanesh, M Monjezi, M Khandelwal, P Bayat
    Journal Papers , , {Pages }

    Abstract

    Prediction of Dust Emission Due to Open Pit Mine Blasting Using a Hybrid Artificial Neural Network

    S Hosseini, M Monjezi, E Bakhtavar, A Mousavi
    Journal Papers , , {Pages }

    Abstract

    Performance of Hybrid SCA-RF and HHO-RF Models for Predicting Backbreak in Open-Pit Mine Blasting Operations

    J Zhou, Y Dai, M Khandelwal, M Monjezi, Z Yu, Y Qiu
    Journal Papers , , {Pages }

    Abstract

    Optimization of prediction of flyrock using linear multivariate regression (LMR) and gene expression programming (GEP)—Topal Novin mine, Iran

    M Monjezi, H Dehghani, J Shakeri, A Mehrdanesh
    Journal Papers , , {Pages }

    Abstract

    Optimized Support Vector Machines Combined with Evolutionary Random Forest for Prediction of Back-Break Caused by Blasting Operation

    Q Yu, M Monjezi, AS Mohammed, H Dehghani, DJ Armaghani, DV Ulrikh
    Journal Papers , , {Pages }

    Abstract

    Factors Influencing Pile Friction Bearing Capacity: Proposing a Novel Procedure Based on Gradient Boosted Tree Technique

    CY Huat, SMH Moosavi, AS Mohammed, DJ Armaghani, DV Ulrikh, ...
    Journal Papers , , {Pages }

    Abstract

    Development of an integrated mathematical model to optimize waste rock dumping satisfying environmental aspects

    Tayebeh Ramezanalizadeh, Masoud Monjezi, Ahmad Reza Sayadi, Amin Mousavinogholi
    Journal PapersJournal of Mining and Environment , Volume 11 , Issue 2, 2020 April 1, {Pages 577-586 }

    Abstract

    Waste rock dumping is very important in the production planning of open-pit mines. This subject is more crucial when there is a potential of acid-forming (PAF) by waste rocks. In such a type of mines, to protect the environment, the PAF materials should be encapsulated by non-harmful rocks. Therefore, block sequencing of the mined materials should be in such a way that both the environmental and economic considerations are considered. If non-acid forming (NAF) rocks are not mined in a proper time, then a stockpile is required for the NAF materials, which later on would be re-handled for encapsulation of PAF rocks. In the available models, the focus is on either block sequencing or waste dumping strategy. In this work, an attempt has been ma

    Development of a Group Method of Data Handling Technique to Forecast Iron Ore Price

    Diyuan Li, Mohammad Reza Moghaddam, Masoud Monjezi, Danial Jahed Armaghani, Amirhossein Mehrdanesh
    Journal PapersApplied Sciences , Volume 10 , Issue 7, 2020 January , {Pages 2364 }

    Abstract

    Iron is one of the most applicable metals in the world. The global price of iron ore is determined based on demand and supply. There are numerous parameters (eg, price of steel, steel production, oil price, gold price, interest rate, inflation rate, iron production, and aluminum price) affecting the global iron ore price. Considering the high number of effective parameters and existence of complex relationship among them, artificial intelligence-based approaches can be employed to predict iron ore price. In this paper, a new intelligence system namely group method of data handling (GMDH) was developed and introduced to predict the price of iron ore. For comparison purposes, four other techniques ie, autoregressive integrated moving average

    Optimization of blasting design in open pit limestone mines with the aim of reducing ground vibration using robust techniques

    Afsaneh Rezaeineshat, Masoud Monjezi, Amirhossein Mehrdanesh, Manoj Khandelwal
    Journal PapersGEOMECHANICS AND GEOPHYSICS FOR GEO-ENERGY AND GEO-RESOURCES , Volume 6 , Issue 2, 2020 June 2, {Pages }

    Abstract

    Blasting operations create significant problems to residential and other structures located in the close proximity of the mines. Blast vibration is one of the most crucial nuisances of blasting, which should be accurately estimated to minimize its effect. In this paper, an attempt has been made to apply various models to predict ground vibrations due to mine blasting. To fulfill this aim, 112 blast operations were precisely measured and collected in one the limestone mines of Iran. These blast operation data were utilized to construct the artificial neural network (ANN) model to predict the peak particle velocity (PPV). The input parameters used in this study were burden, spacing, maximum charge per delay, distance from blast face to monit

    Artificial Neural Network and Firefly Algorithm for Estimation and Minimization of Ground Vibration Induced by Blasting in a Mine

    Parichehr Bayat, Masoud Monjezi, Mojtaba Rezakhah, Danial Jahed Armaghani
    Journal PapersNATURAL RESOURCES RESEARCH , 2020 May 22, {Pages }

    Abstract

    It is of a high importance to introduce intelligent systems for estimation and optimization of blasting-induced ground vibration because it is one the most unwanted phenomena of blasting and it can damage surrounding structures. Hence, in this paper, estimation and minimization of blast-induced peak particle velocity (PPV) were conducted in two separate phases, namely prediction and optimization. In the prediction phase, an artificial neural network (ANN) model was developed to forecast PPV using as model inputs burden, spacing, distance from blast face, and charge per delay. The results of prediction phase showed that the ANN model, with coefficient of determinations of 0.938 and 0.977 for training and testing stages, respectively, can pro

    Development of a MIP model to maximize NPV and minimize adverse environmental impact—a heuristic approach

    Tayebeh Ramezanalizadeh, Masoud Monjezi, Ahmad Reza Sayadi, Amin Mousavi
    Journal PapersEnvironmental Monitoring and Assessment , Volume 192 , Issue 9, 2020 September , {Pages 15-Jan }

    Abstract

    Block sequencing is of great importance in an open-pit mining operation. Sequencing is usually performed to maximize the net present value (NPV). Also, from the environmental viewpoint, the sequence of dumping mined materials is of significant value in the sulfide mines. The potential acid-forming (PAF) waste rocks in these mines can seriously damage the environment due to the formation of acid mine drainage (AMD). To prevent the exposition of the PAF materials, it is essential to design suitable block sequencing. For this purpose, encapsulation of the PAF rocks by non-acid forming (NAF) rocks should be considered during waste dumping. However, this method can impose unnecessary re-handling costs. This issue is due to the determination of t

    Mathematical modeling for optimized mine waste rock disposal: Establishing more effective acid rock drainage management

    Vahid Vaziri, Ahmad Reza Sayadi, Amin Mousavi, Anita Parbhakar-Fox, Masoud Monjezi
    Journal PapersJournal of Cleaner Production , 2020 November 17, {Pages 125124 }

    Abstract

    Acid rock drainage (ARD), produced from sulfide-bearing mine waste (e.g., waste rock, tailings) at active and abandoned mine sites, continues to be a global concern due to the significant impacts on water, soil, biodiversity, and the creation of public health risks. Many examples demonstrate that it is technically challenging to control and manage ARD, with common methods including costly additive treatments. Instead, an improved approach to ARD management is to minimize opportunities for generation from the outset. In this paper, a new mixed-integer programming (MIP) model is proposed to optimize the placement of waste rock into waste dumps with the objective of minimizing ARD formation. The MIP model considers the net neutralizing potenti

    Determination of Rock Fragmentation Based on Longitude Wave Velocity and Fractal Dimension

    Morteza Baghestani, Masoud Monjezi, Alireza Yarahmadi Bafghi, Peyman Afzal
    Journal PapersJournal of Analytical and Numerical Methods in Mining Engineering , Volume 10 , Issue 24, 2020 October 22, {Pages 105-117 }

    Abstract

    In this paper, the blasting data and rock mass characteristics of Chogart, Chadormalu, and Sechahum mines were used to predict the size distribution of rock fragmentation (D80). Rock fragmentation is affected by various parameters such as rock mass properties, in-situ blocks shape, blasting geometry, etc. To quantify the shape of in-situ blocks, fractal geometry is a suitable method. To predict the rock fragmentation (D80) based on independent variables (rock mass characteristics, in-situ block shape, and blasting geometry); linear/nonlinear regression and neural networks were used. The results showed that the nonlinear regression and neural network were the ability to predict the size distribution of rock fragmentation.? ? Introduction Due

    Ranking the Effective Factors of Blasting Incidents Using Analytical Hierarchy Process

    M Monjezi, H Dehghani, MR Ajamzadeh, S Ahmadiyan
    Journal PapersJournal of Mineral Resources Engineering , Volume 5 , Issue 3, 2020 September 22, {Pages 77-92 }

    Abstract

    In each project, there is always a possibility of occurrence of hazards and risks. Accidents cause many damages such as financial and psychological problems, that may have a negative effect on the workers life. To prevent or reduce the occurrence of incidents, it is necessary to identify and manage the relevant affecting factors. Blasting is one of the events that has frequently led to accidents. In this paper, 13 factors affecting the occurrence of blasting related accidents in the mining and construction projects, have been selected according to the opinion of experts and ranked to identify the most important one. For this purpose, Monte Carlo simulation method and analytical hierarchy process method were implemented. The factors were ran

    A comparative study of different artificial intelligence techniques in predicting blast-induced air over-pressure

    Hoang Nguyen, Xuan-Nam Bui, Panagiotis G Asteris, Quang Hieu-Tran, Danial Jahed Armaghani, Masoud Monjezi, Manoj Khandelwal, Phonepaserth Sukhanouvong
    Journal Papers1 , Volume 1 , Issue 2, 2020 December , {Pages 187 }

    Abstract

    Blasting is known as the most common approach for fragmenting rock in open-pit mines. Nevertheless, its side effects are not insignificant, for example, fly rock, ground vibration, dust, toxic by-products, air over-pressure, and back-break. These effects considerably alter the circumambient environment, particularly when pressure is higher than usual. This study proposed and compared four artificial intelligence models for predicting blast-induced air over-pressure, namely multi-layer perceptron (MLP), Random Forest (RF), isotonic regression (IR), and M5-Rules. The air over-pressure was selected as the output variable based on the input variables, ie, stemming length (T), explosive charge per delay (W), burden (B), monitoring distance (R),

    The integrated optimization of underground stope layout designing and production scheduling incorporating a non-dominated sorting genetic algorithm (NSGA-II)

    Sorayya Foroughi, Jafar Khademi Hamidi, Masoud Monjezi, Micah Nehring
    Journal PapersResources Policy , Volume 63 , 2019 October 1, {Pages 101408 }

    Abstract

    Stope layout designing and production scheduling are main phases to determine the profitability of an underground mining project. These are mainly related to the output of one phase, which has a significant impact on generating of the next phase. Individual optimization of these two phases results only in a local optimal solution. To date, the integrated optimization of these phases has been carried out to maximize net present value (NPV). In this paper, a multi-objective integer programming model (MOIP) was developed to optimize this integrated problem in a sublevel stoping operation. The non-dominated sorting genetic algorithm (NSGA-II) was incorporated to solve the objective functions. The Pareto front generated by NSGA-II showed good co

    An investigation of the relationship between muck geometry, TBM performance, and operational parameters: A case study in Golab II water transfer tunnel

    Sasan Heydari, Jafar Khademi Hamidi, Masoud Monjezi, Abbas Eftekhari
    Journal PapersTunnelling and Underground Space Technology , Volume 88 , 2019 June 1, {Pages 73-86 }

    Abstract

    An attempt was made to examine the relationship between various TBM operational factors, its performance, and muck geometry during the excavation of a short geologically uniform section of Golab II water transfer tunnel. A database based on nine field testing data derived from machine operating and performance parameters along with muck shape and size was formed. Subsequently, it was used for analyzing the correlation among variables. The analysis results point out that there is a strong inverse correlation between specific energy (SE), an indicator parameter of rock cutting efficiency, and three muck size indicators including: coarseness index (CI), mean particle size, and absolute grain size (last one is the correlation with R 2= 0.93). T

    A mathematical model to optimize allocation sequence in dispatching problem

    Mohammad Ghobadi Samani, Masoud Monjezi, Jafar Khademi Hamidi, Amin Mousavinogholi
    Journal PapersJournal of Mining and Environment , 2019 October 14, {Pages }

    Abstract

    Truck-Shovel fleet, as the most common transportation system in open-pit mines, has a significant part of mining costs, for which optimal management can lead to substantial cost reductions. Among the available dispatch mathematical models, the multi-stage approach is well suited for allocating trucks to respected shovels in a dynamic dispatching program. However, with this kind of modeling sequencing of the allocated trucks is not possible though it is important to find out the best solution so that getting the minimum accrued cost. To comply with the shortcoming of the traditional model, in this paper, a new hybrid model is developed and applied in Copper Mine of Iran, in which for each truck an allocation matrix is considered as input to

    Airflow Simulation in Pulmonary Conducting Airways

    Mojdeh Monjezi, Hamidreza Jamaati
    Journal PapersAnnals of biomedical engineering , 2019 September 18, {Pages 02-Jan }

    Abstract

    We read the interesting paper by Oakes et al. 1 which present a 3D-0D model for airflow simulations in infant, child, and adult pulmonary conducting airways. However, we found some problems in their model. One of them is about their updating 0D resistance through

    دروس نیمسال جاری

    • كارشناسي ارشد
      معدن كاري سطحي ( واحد)
      دانشکده فنی و مهندسی، گروه استخراج

    دروس نیمسال قبل

    • كارشناسي ارشد
      چالزني و انفجار پيشرفته ( واحد)
      دانشکده فنی و مهندسی، گروه استخراج
    • 1397
      اماني, علي
      تاثير خصوصيات توده‌سنگ بر نتايج حاصل از انفجار در معادن روباز
    • 1397
      خليلي, سجاد
    • 1397
      محمدزاده, عقيل
    • 1397
      نعمتي وردين, علي
    • 1398
      زارع نژاد, سجاد
    • 1398
      ازادپور, هومن
    • 1396
      پيرمراديان, حكيمه
      بهينه‌سازي مسئله گسيل ناوگان حمل و نقل معادن روباز با در نظر گرفتن عدم قطعيت خرابي كاميون
    • رئیس بخش مهندسی معدن
    • مدیر گروه استخراج
    • عضو هیئت تحریریه مجله تکنولوژی بهره برداری از منابع معدنی
    • مدیر گروه آموزشی استخراج معدن
    • عضو کمیسیون ارزشیابی مدارک خارجی
      داده ای یافت نشد

    مهم

    جدید

      اطلاعیه ای درج نشده است