En
  • دکتری (1394)

    مهندسی عمران

    دانشگاه صنعتی شریف،

  • کارشناسی‌ارشد (1388)

    مهندسی عمران - مهندسی محیط زیست

    دانشگاه صنعتی شریف،

  • کارشناسی (1386)

    مهندسی عمران - عمران

    دانشگاه صنعتی شریف،

  • مدلسازی عددی انتقال و انتشار آلاینده ها
  • تحلیل عدم قطعیت و روش های مونت کارلو
  • داده گواری و فیلترهای بیزی
  • روش های شبیه سازی - بهینه سازی استوکستیک

    دکتر محمد مهدی رجبی از سال 1395 به عنوان عضو هیات علمی گروه مهندسی محیط زیست مشغول به کار می باشند. ایشان هر سه مقطع تحصیلی کارشناسی، کارشناسی ارشد و دکترا را در دانشکده مهندسی عمران دانشگاه صنعتی شریف در سال های 1386، 1388 و 1394 به اتمام رسانید. زمینه های پژوهشی ایشان عمدتاً حول موضوعات مرتبط با مدل سازی عددی انتقال و انتشار آلاینده ها می باشد و مباحثی چون تحلیل عدم قطعیت، واسنجی و شبیه سازی - بهینه سازی استوکستیک بر پایه این مدل ها را در بر می گیرد. ایشان سابقه همکاری در پروژه های متعدد را دارند، که به برخی از آنها در رزومه اشاره شده است.

    ارتباط

    رزومه

    Analyzing the efficiency and robustness of deep convolutional neural networks for modeling natural convection in heterogeneous porous media

    MM Rajabi, MRH Javaran, A Bah, G Frey, F Le Ber, F Lehmann, M Fahs
    Journal Papers , , {Pages }

    Abstract

    Simultaneous identification of contaminant source location, initial contaminant concentration, horizontal and vertical hydraulic conductivity in a three-dimensional coastal?…

    Arezou Dodangeh, Mohammad Mahdi Rajabi, Marwan Fahs
    Journal Papers , Issue EGU21-10890, 2021 March 3, {Pages }

    Abstract

    In coastal aquifers, we face the problem of salt water intrusion, which creates a complex flow field. Many of these coastal aquifers are also exposed to contaminants from various sources. In addition, in many cases there is no information about the characteristics of the aquifer. Simultaneous identification of the contaminant source and coastal aquifer characteristics can be a challenging issue. Much work has been done to identify the contaminant source, but in the complex velocity field of coastal aquifer, no one has resolved this issue yet. We want to address that in a three-dimensional artificial coastal aquifer.To achieve this goal, we have developed a method in which the contaminant source can be identified and the characteristics of t

    Evaluation of CO2 sequestration and circulation in fault-bounded thin geothermal reservoirs in North Oman using response surface methods

    Mingjie Chen, Ali Al-Maktoumi, Mohammad Mahdi Rajabi, Azizallah Izady, Hilal Al-Mamari, Jianchao Cai
    Journal PapersJournal of Hydrology , 2021 May 4, {Pages 126411 }

    Abstract

    In the past decade, techno-economic feasibility of using CO2 as a working fluid to harvest geothermal energy has been studied and demonstrated in both hot-dry rock and deep brine aquifers. Potential geothermal resources have been suggested by hydrogeological surveys in North Oman area. Many depleting petroleum reservoirs in this area provide excellent candidates as CO2 geologic storage and geothermal reservoirs, considering well-characterized and sealed geological structures and existing on-site infrastructure. In this study, we aim to conduct a comprehensive evaluation of reservoir performances during CO2 sequestration and circulation with possible field conditions in North Oman foreland basin. Continuous response surfaces of performance i

    Stochastic Techno-economic Analysis of CO2-circulated Geothermal Energy Production in a Closed Reservoir System

    MM Rajabi, M Chen, A Bozorgpour, A Al-Maktoumi, A Izady
    Journal Papers , , {Pages }

    Abstract

    A Probabilistic Multiperiod Simulation–Optimization Approach for Dynamic Coastal Aquifer Management

    A Al-Maktoumi, MM Rajabi, S Zekri, C Triki
    Journal Papers , , {Pages }

    Abstract

    Simultaneous identification of contaminant source location, initial contaminant concentration, horizontal and vertical hydraulic conductivity in a three-dimensional coastal …

    A Dodangeh, M Mahdi Rajabi, M Fahs
    Journal Papers , , {Pages }

    Abstract

    Uncertainty quantification and global sensitivity analysis of double-diffusive natural convection in a porous enclosure

    Mohammad Mahdi Rajabi, Marwan Fahs, Aref Panjehfouladgaran, Behzad Ataie-Ashtiani, Craig T Simmons, Benjamin Belfort
    Journal PapersInternational Journal of Heat and Mass Transfer , Volume 162 , 2020 December 1, {Pages 120291 }

    Abstract

    In this paper, detailed uncertainty propagation analysis (UPA) and variance-based global sensitivity analysis (GSA) are performed on the widely adopted double-diffuse convection (DDC) benchmark problem of a square porous cavity with horizontal temperature and concentration gradients. The objective is to understand the impact of uncertainties related to model parameters on metrics characterizing flow, heat and mass transfer processes, and to derive spatial maps of uncertainty and sensitivity indices which can provide physical insights and a better understanding of DDC processes in porous media. DDC simulations are computationally expensive and UPA and GSA require large number of simulations, so an appropriate strategy is developed to reduce

    An improved Kalman filtering approach for the estimation of unsaturated flow parameters by assimilating photographic imaging data

    Mohammad Mahdi Rajabi, Benjamin Belfort, Fran?ois Lehmann, Sylvain Weill, Behzad Ataie-Ashtiani, Marwan Fahs
    Journal PapersJournal of Hydrology , Volume 590 , 2020 November 1, {Pages 125373 }

    Abstract

    As a non-invasive method, photographic imaging techniques offer some interesting potentials for characterization of soil moisture content in unsaturated porous media, enabling mapping at very fine resolutions in both space and time. Although less explored, the wealth of soil moisture data provided by photographic imaging is also appealing for the estimation of unsaturated soil hydraulic parameters through inverse modeling. However, imaging data have some unique characteristics, including high susceptibility to noise, which can negatively affect the parameter estimation process. In this study a sequential data assimilation approach is developed to simultaneously update soil moisture content and soil hydraulic parameters using photographic im

    Review and comparison of two meta-model-based uncertainty propagation analysis methods in groundwater applications: polynomial chaos expansion and Gaussian process emulation

    Mohammad Mahdi Rajabi
    Journal PapersStochastic Environmental Research and Risk Assessment , 2019 January , {Pages 25-Jan }

    Abstract

    Gaussian process emulation (GPE) and polynomial chaos expansion (PCE) are tools for meta-model-based uncertainty propagation analysis (UPA) that have gained increasing attention in recent groundwater literature. Previous studies have shown that these two meta-models can provide satisfactorily accurate estimations of the model response in a wide range of groundwater UPA problems. However, PCE and GPE are based on very different mathematical concepts, and a question that arises is which one of these is more suitable for groundwater UPA. The current paper aims to provide an answer to this question by first presenting a theoretical comparison of the two meta-models, then reviewing previous comparisons of the two in other fields of

    Improving model-data interaction in hydrogeology: Insights from different disciplines

    Behzad Ataie-Ashtiani, Mohammad Mahdi Rajabi, Craig T Simmons
    Journal Papers , 2019 October 24, {Pages 124275 }

    Abstract

    Computer simulation models are playing an increasing role in decision making processes in hydrogeology, and the new models that are emerging are more sophisticated than ever. The mounting sophistication of models has brought with it the challenge of estimating more input parameters and more detailed model structures, from data that is often imperfect (ie subject to uncertainty, imprecision and granularity), and heterogeneous (ie consisting of quantitatively and qualitatively dissimilar data). The past decade has also seen significant progress in technologies that enable the collection, transfer and storage of hydrogeologic data. These technologies which include new measurement devices, remote sensing tools, wireless communication networks,

    Model-data interaction in groundwater studies: Review of methods, applications and future directions

    Mohammad Mahdi Rajabi, Behzad Ataie-Ashtiani, Craig T Simmons
    Journal PapersJournal of Hydrology , Volume 567 , 2018 December 1, {Pages 457-477 }

    Abstract

    We define model-data interaction (MDI) as a two way process between models and data, in which on one hand data can serve the modeling purpose by supporting model discrimination, parameter refinement, uncertainty analysis, etc., and on the other hand models provide a tool for data fusion, interpretation, interpolation, etc. MDI has many applications in the realm of groundwater and has been the topic of extensive research in the groundwater community for the past several decades. This has led to the development of a multitude of increasingly sophisticated methods. The progress of data acquisition technologies and the evolution of models are continuously changing the landscape of groundwater MDI, creating new challenges and opportunities that

    Uncertainty-based simulation-optimization using Gaussian process emulation: Application to coastal groundwater management

    Mohammad Mahdi Rajabi, Hamed Ketabchi
    Journal PapersJournal of Hydrology , Volume 555 , 2017 December 1, {Pages 518-534 }

    Abstract

    Combined simulation-optimization (S/O) schemes have long been recognized as a valuable tool in coastal groundwater management (CGM). However, previous applications have mostly relied on deterministic seawater intrusion (SWI) simulations. This is a questionable simplification, knowing that SWI models are inevitably prone to epistemic and aleatory uncertainty, and hence a management strategy obtained through S/O without consideration of uncertainty may result in significantly different real-world outcomes than expected. However, two key issues have hindered the use of uncertainty-based S/O schemes in CGM, which are addressed in this paper. The first issue is how to solve the computational challenges resulting from the need to perform massive

    Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

    Mohammad Mahdi Rajabi, Behzad Ataie-Ashtiani
    Journal PapersJournal of Hydrology , Volume 536 , 2016 May 1, {Pages 255-272 }

    Abstract

    Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is ‘fuzzy Bayesian inference’ which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process

    AN UNCERTAINTY-BASED DECISION MODEL FOR MANAGING COASTAL GROUNDWATER RESOURCES

    MOHAMMAD MAHDI RAJABI, HAMED KETABCHI, ASHTIANI BEHZAD ATAIE
    Journal Papers , Volume 12 , 2016 January , {Pages }

    Abstract

    1. INTRODUCTION: AS HIGHLIGHTED BY THE BARCELONA CONVENTION [1], AN IMPORTANT OBJECTIVE OF INTEGRATED COASTAL ZONE MANAGEMENT (ICZM) IS TO ENSURE THE SUSTAINABLE USE OF NATURAL RESOURCES, PARTICULARLY WITH REGARD TO WATER USE.…

    Efficiency enhancement of optimized Latin hypercube sampling strategies: application to Monte Carlo uncertainty analysis and meta-modeling

    Mohammad Mahdi Rajabi, Behzad Ataie-Ashtiani, Hans Janssen
    Journal PapersAdvances in water resources , Volume 76 , 2015 February 1, {Pages 127-139 }

    Abstract

    The majority of literature regarding optimized Latin hypercube sampling (OLHS) is devoted to increasing the efficiency of these sampling strategies through the development of new algorithms based on the combination of innovative space-filling criteria and specialized optimization schemes. However, little attention has been given to the impact of the initial design that is fed into the optimization algorithm, on the efficiency of OLHS strategies. Previous studies, as well as codes developed for OLHS, have relied on one of the following two approaches for the selection of the initial design in OLHS: (1) the use of random points in the hypercube intervals (random LHS), and (2) the use of midpoints in the hypercube intervals (midpoint LHS). Bot

    Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations

    Mohammad Mahdi Rajabi, Behzad Ataie-Ashtiani, Craig T Simmons
    Journal PapersJournal of Hydrology , Volume 520 , 2015 January 1, {Pages 101-122 }

    Abstract

    Real world models of seawater intrusion (SWI) require high computational efforts. This creates computational difficulties for the uncertainty propagation (UP) analysis of these models due the need for repeated numerical simulations in order to adequately capture the underlying statistics that describe the uncertainty in model outputs. Moreover, despite the obvious advantages of moment-independent global sensitivity analysis (SA) methods, these methods have rarely been employed for SWI and other complex groundwater models. The reason is that moment-independent global SA methods involve repeated UP analysis which further becomes computationally demanding. This study proposes the use of non-intrusive polynomial chaos expansions (PCEs) as a mea

    Sampling efficiency in Monte Carlo based uncertainty propagation strategies: application in seawater intrusion simulations

    Mohammad Mahdi Rajabi, Behzad Ataie-Ashtiani
    Journal PapersAdvances in water resources , Volume 67 , 2014 May 1, {Pages 46-64 }

    Abstract

    The implementation of Monte Carlo simulations (MCSs) for the propagation of uncertainty in real-world seawater intrusion (SWI) numerical models often becomes computationally prohibitive due to the large number of deterministic solves needed to achieve an acceptable level of accuracy. Previous studies have mostly relied on parallelization and grid computing to decrease the computational time of MCSs. However, another approach which has received less attention in the literature is to decrease the number of deterministic simulations by using more efficient sampling strategies. Sampling efficiency is a measure of the optimality of a sampling strategy. A more efficient sampling strategy requires fewer simulations and less computational time to r

    MANAGING GROUNDWATER RESOURCES WITHIN THE FRAMEWORK OF INTEGRATED COASTAL ZONE MANAGEMENT

    MOHAMMAD MAHDI RAJABI, HAMED KETABCHI, ASHTIANI BEHZAD ATAIE
    Journal Papers , Volume 11 , 2014 January , {Pages }

    Abstract

    INTRODUCTION: AS HIGHLIGHTED BY THE BARCELONA CONVENTION [1], AN IMPORTANT OBJECTIVE OF INTEGRATED COASTAL ZONE MANAGEMENT (ICZM) IS TOENSURE THE SUSTAINABLE USE OF NATURAL RESOURCES, PARTICULARLY WITH REGARD TO WATER USE. FOR NUMEROUS REASONS DESCRIBED IN THE FOLLOWING, GROUNDWATER IS ONE OF THE MOST CRITICAL NATURAL RESOURCES OF COASTAL AREAS….

    Optimal management of a freshwater lens in a small island using surrogate models and evolutionary algorithms

    Behzad Ataie-Ashtiani, Hamed Ketabchi, Mohammad Mahdi Rajabi
    Journal PapersJournal of Hydrologic Engineering , Volume 19 , Issue 2, 2013 February 27, {Pages 339-354 }

    Abstract

    This paper examines a linked simulation-optimization procedure based on the combined application of an artificial neural network (ANN) and genetic algorithm (GA) with the aim of developing an efficient model for the multiobjective management of groundwater lenses in small islands. The simulation-optimization methodology is applied to a real aquifer in Kish Island of the Persian Gulf to determine the optimal groundwater-extraction while protecting the freshwater lens from seawater intrusion. The initial simulations are based on the application of SUTRA, a variable-density groundwater numerical model. The numerical model parameters are calibrated through automated parameter estimation. To make the optimization process computationally feasible

    Inverse modelling for freshwater lens in small islands: Kish Island, Persian Gulf

    Behzad Ataie‐Ashtiani, Mohammad Mahdi Rajabi, Hamed Ketabchi
    Journal PapersHydrological Processes , Volume 27 , Issue 19, 2013 September 15, {Pages 2759-2773 }

    Abstract

    A number of challenges including instability, nonconvergence, nonuniqueness, nonoptimality, and lack of a general guideline for inverse modelling have limited the application of automatic calibration by generic inversion codes in solving the saltwater intrusion problem in real‐world cases. A systematic parameter selection procedure for the selection of a small number of independent parameters is applied to a real case of saltwater intrusion in a small island aquifer system in the semiarid region of the Persian Gulf. The methodology aims at reducing parameter nonuniqueness and uncertainty and the time spent on inverse modelling computations. Subsequent to the automatic calibration of the numerical model, uncertainty is analysed by constra

    دروس نیمسال جاری

    • كارشناسي ارشد
      مباني انتقال و انتشار و مدلسازي آلاينده ها ( واحد)
      دانشکده مهندسی عمران و محیط زیست، گروه مهندسي محيط زيست

    دروس نیمسال قبل

    • كارشناسي ارشد
      مديريت كيفيت منابع آب ( واحد)
      دانشکده مهندسی عمران و محیط زیست، گروه مهندسي محيط زيست
    • 1397
      دودانگه, ارزو
      شناسايي هم زمان منبع آلاينده و خصوصيات آبخوان ساحلي با استفاده از فيلترهاي بيزي
    • 1397
      نوري نژاد, شاهين
    • 1398
      بزرگ پور, علي
    • 1398
      حاجي زاده جواران, محمدرضا
    • 1398
      صبوري نوقابي, مسعود
      داده ای یافت نشد
      داده ای یافت نشد

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