Optimization of Flue Gas Composition to Maximize Base Gas Replacement During UGS Process     

Namdar  Hamed  Khodapanah  Elnaz  Tabatabaei-Nejad  Seyyed Alireza 《Natural Resources Research》2020,29(6):4175-4197

Natural Resources Research - Base gas replacement by a cheap gas is one of the approved methods to reduce the cost of investment in underground gas storage process. Maximizing the amount of...  相似文献   

Disaggregating radar-derived rainfall measurements in East Azarbaijan,Iran, using a spatial random-cascade model     

Fouladi Osgouei  Hojjatollah  Zarghami  Mahdi  Ashouri  Hamed 《Theoretical and Applied Climatology》2017,129(1-2):427-435

Theoretical and Applied Climatology - The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely...  相似文献   

Evaluating the generalizability of GEP models for estimating reference evapotranspiration in distant humid and arid locations     

Kiafar  Hamed  Babazadeh  Hosssien  Marti  Pau  Kisi  Ozgur  Landeras  Gorka  Karimi  Sepideh  Shiri  Jalal 《Theoretical and Applied Climatology》2017,130(1-2):377-389

Evapotranspiration estimation is of crucial importance in arid and hyper-arid regions, which suffer from water shortage, increasing dryness and heat. A modeling study is reported here to cross-station assessment between hyper-arid and humid conditions. The derived equations estimate ET₀ values based on temperature-, radiation-, and mass transfer-based configurations. Using data from two meteorological stations in a hyper-arid region of Iran and two meteorological stations in a humid region of Spain, different local and cross-station approaches are applied for developing and validating the derived equations. The comparison of the gene expression programming (GEP)-based-derived equations with corresponding empirical-semi empirical ET₀ estimation equations reveals the superiority of new formulas in comparison with the corresponding empirical equations. Therefore, the derived models can be successfully applied in these hyper-arid and humid regions as well as similar climatic contexts especially in data-lack situations. The results also show that when relying on proper input configurations, cross-station might be a promising alternative for locally trained models for the stations with data scarcity.

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An efficient artificial intelligence model for prediction of tropical storm surge   总被引：1，自引：0，他引：1  

M. Reza Hashemi  Malcolm L. Spaulding  Alex Shaw  Hamed Farhadi  Matt Lewis 《Natural Hazards》2016,80(1):471-486

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Groundwater travel time computation for two-layer islands     

Hamed?KetabchiEmail author  Davood?Mahmoodzadeh  Behzad?Ataie-Ashtiani 《Hydrogeology Journal》2016,24(4):1045-1055

A closed-form analytical computation of groundwater travel time (GWTT) for two-layer oceanic small island aquifers is developed assuming steady-state and sharp-interface conditions. The two-layer geology impacts on the GWTT are investigated using the developed analytical solution to achieve a greater transparency of such conceptualizations. The results demonstrate that the inclusion of geologic layering leads to large changes in the GWTT. Sensitivity analyses, using specified dimensionless parameters, are employed to assess the influences of hydraulic conductivity, recharge rate, upper layer thickness, and seawater/freshwater density difference parameters, which influence the GWTT. These evaluations reveal that the GWTT is mainly influenced by the recharge rate and the upper layer thickness compared to the other influential parameters when the typical parameter ranges are considered.  相似文献   

Carbon dynamic in sandy soil artificially contaminated with petroleum in the presence of various forms of inorganic nitrogen for bioremediation     

Hamed Azari Moghaddam  Nor Kartini Abu Bakar 《Environmental Earth Sciences》2016,75(3):224

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Compounding effects of human activities and climatic changes on surface water availability in Iran     

Ashraf  Samaneh  AghaKouchak  Amir  Nazemi  Ali  Mirchi  Ali  Sadegh  Mojtaba  Moftakhari  Hamed R.  Hassanzadeh  Elmira  Miao  Chi-Yuan  Madani  Kaveh  Mousavi Baygi  Mohammad  Anjileli  Hassan  Arab  Davood Reza  Norouzi  Hamid  Mazdiyasni  Omid  Azarderakhsh  Marzi  Alborzi  Aneseh  Tourian  Mohammad J.  Mehran  Ali  Farahmand  Alireza  Mallakpour  Iman 《Climatic change》2019,152(3-4):379-391

Climatic Change - By combining long-term ground-based data on water withdrawal with climate model projections, this study quantifies the compounding effects of human activities and climate change...  相似文献   

On the Performance of Computational Methods for the Assessment of Risk from Ground-Water Contamination   总被引：1，自引：0，他引：1  

Maged M. Hamed  Philip B. Bedient 《Ground water》1997,35(4):638-646

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An efficient tool for accelerating the numerical solution of the stochastic subsurface flow problem using neural networks     

K. H. Hamed  A. E. Hassan 《Stochastic Environmental Research and Risk Assessment (SERRA)》2000,14(6):428-448

 An efficient numerical solution for the two-dimensional groundwater flow problem using artificial neural networks (ANNs) is presented. Under stationary velocity conditions with unidirectional mean flow, the conductivity realizations and the head gradients, obtained by a traditional finite difference solution to the flow equation, are given as input-output pairs to train a neural network. The ANN is trained successfully and a certain level of recognition of the relationship between input conductivity patterns and output head gradients is achieved. The trained network produced velocity realizations that are physically plausible without solving the flow equation for each of the conductivity realizations. This is achieved in a small fraction of the time necessary for solving the flow equations. The prediction accuracy of the ANN reaches 97.5% for the longitudinal head gradient and 94.7% for the transverse gradient. Head-gradient and velocity statistics in terms of the first two moments are obtained with a very high accuracy. The cross covariances between head gradients and the fluctuating log-conductivity (log-K) and between velocity and log-K obtained with the ANN approach match very closely those obtained by a traditional numerical solution. The same is true for the velocity components auto-covariances. The results are also extended to transport simulations with very good accuracy. Spatial moments (up to the fourth) of mean-concentration plumes obtained using ANNs are in very good agreement with the traditional Monte Carlo simulations. Furthermore, the concentration second moment (concentration variance) is very close between the two approaches. Considering the fact that higher moments of concentration need more computational effort in numerical simulations, the advantage of the presented approach in saving long computational times is evident. Another advantage of the ANNs approach is the ability to generalize a trained network to conductivity distributions different from those used in training. However, the accuracy of the approach in cases with higher conductivity variances is being investigated.  相似文献   

A Comparative Study of Adaptive Neuro-Fuzzy Inference Systems in Object Detection of Complex City Scenes Using Digital Aerial Images and LiDAR Data     

Siamak Talebi Nahr  Parham Pahlavani  Hamed Amini Amirkalayi 《Journal of the Indian Society of Remote Sensing》2015,43(4):787-799

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