ORIGINAL_ARTICLE
Sensitizing influenced factors on discharge of labyrinth weirs using ANFIS model
In the article, through the adaptive neuro-fuzzy inference system (ANFIS), a sensitivity analysis is conducted on the variables affecting the discharge capacity of the weir. To this end, the variables affecting the discharge capacity of labyrinth weirs are initially identified. Then, using these input parameters, seven ANFIS models are developed for conducting the sensitivity analysis. After that, the most optimal membership function number for the ANFIS model is chosen. In other words, by conducting the trial and error process, the best number of the membership functions in terms of time and modeling accuracy are selected. Then, the sensitivity analysis is performed for the ANFIS models and the superior ANFIS model is chosen finally. The accuracy of the superior model in both the validation and testing artificial intelligence (AI) methods is in an acceptable range. For example, the scatter index (SI), correlation coefficient (R) and the Nash-Sutcliff efficiency coefficient (NSC) for the model in the testing mode are obtained 0.049, 0.964 and 0.924, respectively. It should be noticed that the outcomes of the sensitivity analysis show that the ratio of the weir head to the weir crest and the Froude number are introduced as the most effective input parameters. Eventually, a computer code is proposed to estimate the discharge capacity of labyrinth weirs by this model.
https://arww.razi.ac.ir/article_1284_618e69f3a9a09d922deef06037228390.pdf
2020-06-30
1
13
10.22126/arww.2020.4578.1146
ANFIS
Discharge Coefficient
Labyrinth Weir
Sensitivity analysis
Modeling
Mohammad Ali
Izadbakhsh
izadbakhsh.mohammad.ali@gmail.com
1
Department of Water Engineering, Faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
LEAD_AUTHOR
Reza
Hajiabadi
reza.hajiabadi@gmail.com
2
Department of Water Engineering, Faculty of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
AUTHOR
Akhbari A., Zaji A.H., Azimi H., Vafaeifard M., Predicting the discharge
1
coefficient of triangular plan form weirs using radian basis function
2
and M5’methods, Jo urnal of Applied Research in Water and
3
Wastewater 4 (2017) 281-289.
4
Azimi H., Heydari M., Shabanlou S., Numerical simulation of the effects
5
of downstream obstacles on malpasset dam break pattern, Journal of
6
Applied Research in Water and Wastewater 5 (2018) 441-446.
7
Azimi H., Bonakdari H., Ebtehaj I., Design of radial basis function-based
8
support vector regression in predicting the discharge coefficient of a
9
side weir in a trapezoidal channel, Applied Water Science 9 (2019)
10
Azimi H., Shabanlou S., Ebtehaj I., Bonakdari H., Kardar S.,
11
Combination of computational fluid dynamics, adaptive neuro-fuzzy
12
inference system, and genetic algorithm for predicting discharge
13
coefficient of rectangular side orifices, Journal of Irrigation and
14
Drainage Engineering 143 (2017) 1-3.
15
Baylar A., Hanbay D., Ozpolat E., An expert system for predicting
16
aeration performance of weirs by using ANFIS, Expert Systems with
17
Applications 35 (2008) 1214-1222.
18
Bagheri S., and Heidarpour M., Application of free vortex theory to
19
estimate discharge coefficient for sharp-crested weirs, Biosystems
20
Engineering 105 (2010) 423-427.
21
Carollo F.G., Ferro V., Pampalone V., Testing the Outflow Process over
22
a Triangular Labyrinth Weir, Journal of Irrigation and Drainage
23
Engineering 143 (2017) 06017007.
24
Crookston B.M., Paxson G.S., Savage B.M., Hydraulic performance of
25
labyrinth weirs for high headwater ratios, In The 4th IAHR
26
International Symposium on Hydraulic Structures, Porto, Portugal
27
(2012) 1-8.
28
Crookston B.M., and Tullis B.P., Hydraulic design and analysis of
29
labyrinth weirs. I: Discharge relationships, Journal of Irrigation and
30
Drainage Engineering 139 (2012) 363-370.
31
Ebtehaj I., Bonakdari H., Zaji A.H., Azimi H., Sharifi A., Gene
32
expression programming to predict the discharge coefficient in
33
rectangular side weirs, Applied Soft Computing 35 (2015) 618-628.
34
Emiroglu M.E., and Baylar A., Inf luence of included angle and sill slope
35
on air entrainment of triangular planform labyrinth weirs, Journal of
36
Hydraulic Engineering 131 (2005) 184-189.
37
Haghiabi A.H., Parsaie A., Ememgholizadeh S., Prediction of discharge
38
coefficient of triangular labyrinth weirs using Adaptive Neuro Fuzzy
39
Inference System, Alexandria Engineering Journal 5 (2017) 21-29.
40
Hay N., and Taylor G., A computer model for the determination of the
41
performance of labyrinth weirs, 13th Congress of IAHR, Koyoto, Japan
42
(1969) 361-378.
43
Jang J.S.R., ANFIS: adaptive-network-based fuzzy inference system,
44
IEEE Transactions on Cybernetics 23 (1993) 665–685.
45
Khoshbin F., Bonakdari H., Ashraf Talesh S.H., Ebtehaj I., Zaji A.H.,
46
Azimi H. Adaptive neuro-fuzzy inference system multi-objective
47
optimization using the genetic algorithm/singular value
48
decomposition method for modelling the discharge coefficient in
49
rectangular sharp-crested side weirs, Engineering Optimization 48
50
(2016) 933-948.
51
Kumar S., Ahmad Z., Mansoor T., A new approach to improve the
52
discharging capacity of sharp-crested triangular plan form weirs,
53
Journal of Flow Measurement and Instrumentation 22 (2011) 175-
54
Parsaei A., and Haghiabi A.H., Hydraulic analysis of compound open
55
channel, Journal of Applied Research in Water and Wastewater 2
56
(2015) 137-142.
57
Roushangar K., Alami M.T., Majedi Asl M., Shiri J. Modeling discharge
58
coefficient of normal and inverted orientation labyrinth weirs using
59
machine learning techniques, Journal of Hydraulic Engineering 23
60
(2017) 331-340.
61
Roushangar K., Alami M.T., Shiri J., Asl M.M., Determining discharge
62
coefficient of labyrinth and arced labyrinth weirs using support vector
63
machine, Hydrology Research 49 (2018) 924-938.
64
Taylor G., The performance of labyrinth weir. Ph.D. thesis, University of
65
Nottingham, Nottingham, England (1968).
66
Tullis B.P., Amanian N., Waldron D., Design of labyrinth spillways,
67
Journal of Hydraulic Engineering 121 (1995) 247-255.
68
Tullis B.P., and Young J.C., Chandler M.A., Head-discharge relationships for submerged Labyrinth weirs, Journal of Hydraulic Engineering 133 (2007) 248-253.
69
Wormleaton P.R., and Soufiani E., Aeration performance of triangular planform labyrinth weirs, Jour nal of Environmental Engineering 124 (1998) 709-719.
70
Wormleaton P.R., and Tsang C.C., Aeration performance of rectangular planform labyrinth weirs, Journal of Environmental Engineering 126 (2000) 456-465.
71
ORIGINAL_ARTICLE
Use of a mathematical modeling approach to investigate interaction between groundwater and river: A case study on the north of the Dezful- Andimeshk plain, southwest of Iran
Alluvial rivers interact mostly with underlying groundwater bodies. These interactions that varies spatially and temporally, have recently received more attentions. This paper aims to evaluate the interaction between groundwater and surface water along the Dez river in the north part of the Dezful-Andimeshk district through developing a numerical simulation. For this purpose, the groundwater flow and river- groundwater interaction were simulated using a mathematical model in MODFLOW/GMS environment. The WetSpass model was used to estimate the groundwater recharge. The cluster analysis method, also, was utilized to identify the different zones of aquifer hydraulic characteristics. The results show that the Dez river has a losing connected nature and recharges groundwater. The river recharge to the aquifer was about 12 MCM during the 2013 and 2014. This recharge varies spatially and temporally and its maximum amount occurs during the 2014 March to June. Furthermore, the recharge rate was affected by the water release pattern from the Dez dam and topographic characteristics of the riverbed sediments. So that the maximum water exchanges occur in areas near the Chamgolak town and Dezful city with an average rate of 3.2 MCM per year.
https://arww.razi.ac.ir/article_1285_40f4bf395eccd569e4d837ac9d490863.pdf
2020-06-30
14
22
10.22126/arww.2020.4247.1128
River-aquifer interaction
Groundwater modeling
Dezful- Andimeshk area
Mohammad
Faryabi
faryabi753@yahoo.com
1
Department of Natural Science, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran.
LEAD_AUTHOR
Manouchehr
Chitsazan
chitsazaan35@gmail.com
2
Department of Geology, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
AUTHOR
Alireza
Zarasvaandei
zarasvandei.ar@scu.ac.ir
3
Department of Geology, Faculty of Earth Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
AUTHOR
Allen R.G., Using the FAO-56 dual crop coefficient method over an irrigated region as part of an evapotranspiration intercomparison study, Journa of Hydrology 11 (2000) 748-756.
1
Andersen M.S., Stream-aquifer interactions in the Maules Creek catchment, Naomi Valley, New South Wales, Australia, Hydrogeology Journal 17 (2009) 2005-2021.
2
Anderson M.P., and Woessner W., Applied groundwater modeling- Simulation of flow and advective transport. San Diego: California, Academic Press; (1992).
3
Barthel R., and Banzhaf S., Groundwater and surface water interaction at the regional-scale – A review with focus on regional integrated models, Water Resource Management 30 (2016) 1–32
4
Batelaan O., and De Smedt F., WetSpass: a flexible, GIS based, distributed recharge methodology for regional groundwater modeling, International Association of Hydrogeologists 269 (2001) 11-17.
5
Batelaan O., and De Smedt F., GIS-based recharge estimation by coupling surface-subsurface water balances, Journal of Hydrology 3 (2007) 337-355.
6
Batelaan O., Woldeamlak S.T., Arcview interface for WetSpass, user manual, Department of hydrology and hydraulic engineering, Vrije University, Brussel, Belgium; (2003).
7
Brunner P., Cook P.G., Simmons C.T., Modeling surface water-groundwater interaction with MODFLOW: Some Considerations, Groundwater 48 (2010) 174-80.
8
Calver A., Riverbed permeabilities: Information from pooled data, Groundwater 39 (2001) 546-553.
9
Cey E., Rudolph D.L., Parkin G.W., Aravena R., Quantifying groundwater discharge to a small perennial stream in southern Ontario, Canada, Journal of Hydrology 210 (1998) 21–37.
10
Chitsazan M., Faryabi M., Zarrasvandi A.R., Evaluation of river–aquifer interaction in the north part of Dezful–Andimeshk district, SW of Iran, Arabian Journal of Geoscience 8 (2015) 7177–7189.
11
Cremeans M., Devlin M., McKnight J.F., Bjerg, P.L., Application of new point measurement device to quantify groundwater‐surface water interactions, Contaminant Hydrology 211 (2018) 85– 93.
12
Dade W.B., and Friend P.F., Grain size, sediment transport regime and channel slope in alluvial rivers, Journal of Geology 106 (1998) 661-675.
13
Faryabi M., Evaluation of river – aquifer interaction using water quality methods, the north part of Dezful – Andimeshk district, PhD dissertation, Shahid Chamran University of Ahvaz; (2014).
14
Guggenmos M.R., Jackson B.M., Daughney C.J., Investigation of groundwater-surface water interaction using hydrochemical sampling with high temporal resolution, Mangatarere catchment, New Zealand, Hydrology and Earth System Science 8 (2011) 10225–10273.
15
Harbaugh A.W., Banta .ER., Hill M.C., McDonald M.G., MODFLOW, the U.S., Geological Survey modular ground-water model—User guide to modularization concepts and the groundwater flow process. U.S. Geological Survey, open-file report 00-92, (2000).
16
Harish Kumar S., and Nagaraj M. K., Assessment of interactions between river and aquifer in the Gowri-hole sub-catchment, Journal of the Geological Society of India 92 (2018) 435–440.
17
Ivkovic K.M., Letcher R.A., Croke B.F.W., Use of a simple surface–groundwater interaction model to inform water management, Australian Journal of Earth Science 56 (2009) 71-80.
18
Jing M., Hebe F., Kumar R., Wang W., Fischer T., Walther M., Zink M., Zech A., Samaniego L., Kolditz O., Attinger S., Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS), Geoscience Model Development 11 (2018) 1989–2007.
19
Joo J., Tian Y., Zheng C., Zheng Y., Sun Z., Zhang A., Chang H., An integrated modeling approach to study the surface water-groundwater interactions and influence of temporal damping effects on the hydrological cycle in the Miho catchment in south Korea, Water 10 (2018) 2-24.
20
Kalbus E., Reinstorf F., Schirmer M., Measuring methods for groundwater, surface water and their interactions: a review, Hydrology and Earth System Science 3 (2006) 1809–1850
21
Khuzestan water and power authority, Hydrogeological studies in the Dezful-Andimeshk district, (2010).
22
Kresic N., Quantitative solutions in hydrogeology and ground water modeling. USA: CRC press; (1997).
23
Larkin R.G., and Sharp J.M., On the relationship between river basin geomorphology, aquifer hydraulics, and groundwater flow direction in alluvial aquifers, Geological Society of America Bulletin 104 (1992) 1608-1620.
24
May R., and Binti Mazlan N.S., Numerical simulation of the effect of heavy groundwater abstraction on groundwater–surface water interaction in Langat Basin, Selangor, Malaysia, Environmental Earth Science 71 (2013) 1239–1248.
25
McCarthy K.A., McFarland W.D., Wilkinson W.D., White L.D., The dynamic relationship between ground water and the Columbia river—using deuterium and oxygen-18 as tracers, Journal of Hydrology 135 (1992) 1–12.
26
Paricio A.P., Hunink J.E., Kupper E., Quintana J.R., Estimation of the river conductance coefficient using streambed slope for modeling of regional river-aquifer interaction. XVIII international conference on water resources, Barcelona, Spain (2010).
27
Prudic D.E., Documentation of a computer program to simulate stream-aquifer relations using the modular finite difference ground water flow model, U.S., Geological Survey open file report 88–729, (1989).
28
Rautio A.L., Kivimaki A., Korkka-Niemi K., Nygard M., Salonen V.P., Lahti K., Vahtera H., Vulnerability of groundwater resources to interaction with river water in a boreal catchment, Hydrology and Earth System Science 19 (2015) 3015–3032.
29
Roholamin Kasmaei A., Nezhad Naderi M., Bahrami z., Water pollution management in wells of Zawar village for investigation of effects of nitrogen fertilizers in nitrate entry into groundwater, Journal of Applied Research in Water and Wastewater 8(2017) 354-357.
30
Rosenberg D.O., Labaugh J.W., Field techniques for estimating water fluxes between surface water and ground water, U.S. Geological Survey Techniques and Methods 4–D2 (2008).
31
Safarzadeh A., and Mohajeri S.H., On the fine sediment deposition patterns in a gravel bed open-channel flow, Journal of Applied Research in Water and Wastewater 5 (2016) 188-192.
32
Sanz D., Castano S., Cassiraga E., Sahuquillo A., Jose Gomez-Alday J., Pena S., Calera A., Modeling aquifer–river interactions under the influence of groundwater extraction in the Mancha Oriental System (SE Spain), Hydrogeology Journal 19 (2011) 475–487.
33
Shahsavari A.A., Khodaei K., Hatefi R., Asadian F., Zamanzadeh S.M., Distribution of total petroleum hydrocarbons in Dezful aquifer, Southwest of Iran, Arabian Journal of Geoscience 7 (2013) 2367–2375.
34
Sophocleous M., Interactions between groundwater and surface water: the state of the science, Hydrogeology Journal 10 (2002) 52–67.
35
Ward J.H., Hierarchical grouping to optimize an objective function, Journal of American Statistical Association 58 (1963) 236-244.
36
Winter T.C., Harvey J.W., Franke O.L., Alley W.M., Ground water and surface water a single resource, U.S., Geological Survey Circular 1139 (1998).
37
Vazquez-Sune E., Capino B., Abarca E., Carrera J., Estimation of recharge from floods in disconnected stream-aquifer systems, Groundwater 45(2007) 579-89.
38
ORIGINAL_ARTICLE
Optimization of ANFIS model using wavelet transform for simulating groundwater level variations
In this study, for the first time, groundwater level (GWL) variations of the Sarab-e Qanbar well located in the city of Kermanshah, are simulated over a 13-year period by a hybrid model named WANFIS (wavelet-adaptive neuro fuzzy inference system). In order to develop the hybrid model, the wavelet transform and the adaptive neuro fuzzy inference system (ANFIS) model are utilized. Furthermore, the 9 and 4 year data are used for training and testing the artificial intelligence models, respectively. Moreover, the effective lags are detected by the autocorrelation function (ACF) and then eight different models are developed for each of the ANFIS and WANFIS models using them. After that, all mother wavelets are evaluated and Dmey mother wavelet is chosen as the most optimal. For this mother wavelet, the values of scatter index (SI), variance account for (VAF) and Root mean square error (RMSE) are obtained 0.192, 94.951 and 3.117, respectively. Next, the superior model is detected through the analysis of the results obtained by all ANFIS and WANFIS models. The superior model estimates the objective function values with reasonable accuracy. For example, the correlation coefficient (R), Scatter Index (SI) and variance account for (VAF) for this model are obtained 0.974, 0.192 and 94.951, respectively. The modeling results indicate that the wavelet transform noticeably enhances the ANFIS model accuracy. Finally, the lags of the time series data for the Sarab-e Qanbar well including (t-1), (t-2), (t-3) and (t-4) are introduced as the most effective lags.
https://arww.razi.ac.ir/article_1286_95483031448af62bee478bc7b648f2ec.pdf
2020-06-30
23
29
10.22126/arww.2020.4150.1123
Groundwater level variations
Hybrid artificial intelligence technique
Wavelet transform
ANFIS
Optimization
Simulation
Fariborz
Yosefvand
fariborzyosefvand@gmail.com
1
Department of Water Engineering, Faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
LEAD_AUTHOR
Saeid
Shabanlou
saeid.shabanlou@gmail.com
2
Department of Water Engineering, Faculty of Agriculture, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
Adamowski J., and Sun K., Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds, Journal of Hydrology 390 (2010) 85–91.
1
Akhbari A., Zaji A.H., Azimi H., Vafaeifard M., Predicting the discharge coefficient of triangular plan form weirs using radian basis function and M5’methods, Journal of Applied Research in Water and Wastewater 4 (2017) 281-289.
2
Azimi H., Heydari M., Shabanlou S., Numerical simulation of the effects of downstream obstacles on malpasset dam break pattern, Journal of Applied Research in Water and Wastewater 5 (2018) 441-446.
3
Barzegar R., Fijani E., Moghaddam A.A., Tziritis E., Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models, Science of The Total Environment 599 (2017) 20-31.
4
Chitsazan M., Rahmani G., Neyamadpour A., Groundwater level simulation using artificial neural network: a case study from Aghili plain, urban area of Gotvand, south-west Iran, Geopersia 3 (2013) 35-46.
5
Dash N.B., Panda S.N., Remesan R., Sahoo N., Hybrid neural modeling for groundwater level prediction, Neural Computing and Applications 19 (2010) 1251-1263.
6
Ebrahimi H., and Rajaee, T., Simulation of groundwater level variations using wavelet combined with neural network, linear regression and support vector machine, Global and Planetary Change 148 (2017) 181-191.
7
Grossmann A., Morlet J., Decomposition of hardy functions into square integrable wavelets of constant shape, SIAM Journal on Mathematical Analysis 15 (1984) 723–736
8
Jang J.S., ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics: System 23 (1993) 665-685.
9
Jang J.S.R., Sun C.T., Mizutani E., Neuro-Fuzzy and soft computing: a computational approach to learning and machine intelligence, IEEE Transactions on Automatic Control 42 (1997) 1482-1484.
10
Kisi O., and Shiri J., Wavelet and neuro-fuzzy conjunction model for predicting water table depth fluctuations, Hydrology Research 43 (2012) 286-300.
11
Khaki M., Yusoff I., Islami, N., Simulation of groundwater level through artificial intelligence system, Environmental Earth Sciences 73 (2015) 8357-8367.
12
Liu D., Li G., Fu Q., Li M., Liu C., Faiz M.A., Cui S., Application of particle swarm optimization and extreme learning machine forecasting models for regional groundwater depth using nonlinear prediction models as preprocessor, Journal of Hydrologic Engineering 23 (2018) 04018052.
13
Singh R.M., Wavelet-ANN model for flood events, Proceedings of the International Conference on Soft Computing for Problem Solving, India 20-22 (2012) 165–175.
14
ORIGINAL_ARTICLE
Optimization of water distribution networks using developed binary genetic algorithm and hydraulic model software
The optimal design of urban water distribution networks is a significant issue that has been of critical interest in the water industry for many years. The optimal design of the distribution network aims to find the best solution for transferring water from the reservoir to consumers at the lowest cost. In this study, optimization of the water distribution network (ZONE 1 of Ilam city, Iran) was performed using the fast messy genetic algorithms (FMGA) tool in the hydraulic model for three different pipe networks. Also, these networks were optimized by using a combination of EPANET and an in-house developed binary genetic algorithm in MATLAB. The costs of the optimized hydraulic networks of polyethylene and polypropylene pipes were lower, respectively, by 20.56 % and 52.94 % compared to the consulting company's original designs, while for the glass fiber reinforced plastic pipe (GRP) pipe network the cost increased by 12.61 %. Also, the results of a developed algorithm for polyethylene pipe decreased by 22.13 %.
https://arww.razi.ac.ir/article_1492_5b2bd82485a6d03fda3ee7b9dc2bb48f.pdf
2020-06-30
30
35
10.22126/arww.2020.5061.1159
Genetic Algorithm
Optimization
Water Distribution Network
Hydraulic Model
MATLAB
Setareh
Heydari
heidari1269@gmail.com
1
Department of Water Engineering, Faculty of Agriculture, Ilam University, Ilam, Iran.
AUTHOR
Jafar
Mamizadeh
jafarmami@gmail.com
2
Department of Water Engineering, Faculty of Agriculture, Ilam University, Ilam, Iran.
LEAD_AUTHOR
Javad
Sarvarian
j.sarvarian@gmail.com
3
Department of Water Engineering, Faculty of Agriculture, Ilam University, Ilam, Iran.
AUTHOR
Goodarz
Ahmadi
g.ahmadi@clarkson.edu
4
Department of Mechanical and Aeronautical Engineering, Faculty of Engineering, Clarkson University, Potsdam, USA.
AUTHOR
Abebe A.J., and Solomatine D.P., Application of global optimization to the design of pipe networks, Proc. 3rd International Conference on Hydroinformatics Copenhagen, Rotterdam, (1998) 1-8.
1
Alperovits E., and Shamir U., Design of optimal water distribution systems, Water Resources Research,13 (1977) 885–900.
2
Bi W., Dandy G.C., Maier H.R., Improved genetic algorithm optimization of water distribution system design by incorporating domain knowledge, Environmental Modelling & Software 69 (2015) 370-381.
3
Cunha M.C., and Sousa J., Water distribution network design optimization: simulated annealing approach, Journal of water Resource Planning and Management 125 (1999) 215–221.
4
Dandy G.C., Simpson A.R., Murphy L. J., An improved genetic algorithm for pipe network optimization, Water Resources Research 32 (1996) 449-458.
5
Do N., Simpson A., Deuerleinc J., Pillerd O., Demand estimation in water distribution systems: solving underdetermined problems using genetic algorithms, Procedia Engineering 186 (2017) 193 – 201.
6
Eusuff M.M., and Lansey E.K., Optimization of water distribution network design using the shuffled frog leaping algorithm, Journal of Water Resource Planning and Management 129 (2003) 210-225.
7
Fujiwara O., and Khang D.B., A two-phase decomposition method for optimal design of looped water distribution networks, Water Resources Research 26 (1990) 539–549.
8
Geem Z.W., Optimal cost design of water distribution networks using harmony search, Engineering Optimization 38 (2006) 259–280.
9
Ghajarnia N., Haddad O.B., Mariño M.A., Performance of a novel hybrid algorithm in the design of water networks, Proceedings of the Institution of Civil Engineers - Water Management 164(2011) 173-191.
10
Goldberg D., and Kuo C., Genetic Algorithm in pipeline optimization, Journal of Computing in Civil Engineering 1 (1987) 128-141.
11
Halhal D., Walters G.A., Ouazar D., Savic D.A., Water network rehabilitation with structured messy genetic algorithm, Journal of Water Resource Planning and Management Division, American Society of Civil Engineers 123 (1997) 137-146.
12
Kadu M.S., Gupta R., Bhave P.R., Optimal design of water networks using a modified genetic algorithm with reduction in search space, Journal of water Resource Planning and Management 134 (2008) 147-160.
13
Moeini R., and Moulaei S.A.M., Simulation-optimization model for design of water distribution system using ant based algorithms, The Journal of Engineering Research 15 (2018) 42-60.
14
Montesinos P., Garcia-Guzman A., Ayuso J.L., Water distribution network optimization using a modified genetic algorithm, Water Resources Research 35 (1999) 3467-3473.
15
Mora-Meli D., Martínez-Solano F.J., Iglesias-Rey P.L., Gutiérrez-Bahamondes J.H., Population size influence on the efficiency of evolutionary algorithms to design water networks, XVIII International Conference on Water Distribution Systems Analysis, Procedia Engineering 186 (2017) 341 – 348.
16
Morley M.S., and Tricarico C., A comparison of population-based optimization techniques for water distribution system expansion and operation, 16th Conference on Water Distribution System Analysis, Procedia Engineering 89 (2014) 13 – 20.
17
Muranho J., Ferreira A., Sousa J., Gomes A., Sá Marques A., WaterNetGen - an EPANET extension for automatic water distribution networks models generation and pipe sizing, Water Science and Technology: Water Supply 12 (2012) 117-123.
18
Ostfeld A. and Salomons E., Optimal disinfection of water distribution networks following a contamination event, 16th Conference on Water Distribution System Analysis, Procedia Engineering 89 (2014)168 – 172.
19
Savic D.A., and Walters G.A., Genetic Algorithms for Least Cost Design of Water Distribution Networks, Journal of Water Resource Planning and Management 123 (1997) 67–77.
20
Shende Sachin, and Chau K.W., Design of water distribution systems using an intelligent simple benchmarking algorithm with respect to cost optimization and computational efficiency, Water Supply Journal 19 (2019) 1892-1898.
21
Shamir U., and Howard C.D., An analytic approach to scheduling pipe replacement, Journal of American Water Works Association 71 (1979) 248-58.
22
ORIGINAL_ARTICLE
Development of the governing equation on the behavior of radial flows in coarse porous media and its numerical solution
The hydrous bed of the rivers covered with coarse alluvial materials is a goodresource along with other resources to provide the needs of the water. Therefore,studying and investigating the flow behavior around wells excavated in these bedsand determining their discharge capacity is very important. Since the flow to thewells is radial and previous research on coarse, porous media, there has beenmainly for parallel flows, and yet any equation replacing the Laplace relationship incoarse, porous media, is not provided for non-Darcy radial flows with a free surface,Therefore, the extraction of the differential equation ruling on these types of flowsin the cylindrical coordinates and a method for numerical solution of them in thisresearch has been followed. Based on the research carried out in this research, thepower (exponential) equation as the most suitable basic relation for the analysis ofradial flows was determined and used. Also, in order to solve the governingequations a numerical model was developed using finite volume method. Thedeveloped numerical model act well for the analysis of radial flows in the coarsealluvial beds. The results of the implementation of the numerical model indicate thatthe pressure distribution can be considered hydrostatic.
https://arww.razi.ac.ir/article_1300_ba64396dda2adbd5c15c168a6320dffe.pdf
2020-06-01
36
47
10.22126/arww.2019.4374.1135
radial flow
coarse porous media
Numerical model
Non-Darcy flow
Jalal
Sadeghian
j.sadeghian@basu.ac.ir
1
Department of Civil Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.
LEAD_AUTHOR
Mohammad Reza
Mihani
jeison7192@yahoo.com
2
Department of Civil Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.
AUTHOR
Adrian D.D., Turbulent flow in porous media, Journal of the Hydraulics Division 91 (1965) 1847-1857.
1
Bazargan J., and Shoaei S.M., Application of gradually varied flow algorithms to simulate buried streams, Hydraulic Research 44 (2006) 138-141.
2
Bazargan J., and Shoaie M., Non-Darcy flow analysis of rockfill materials using gradually varied flow theory, Civil Engineering and Surveying 44 (201 0) 131-139.
3
Bazargan J., Zamanisabzi H., Application of new dimensionless number for analysis of laminar, transitional and turbulent flow through rock-fill materials, Canadian Journal on Environmental, Construction and Civil Engineering 2 (2011) 147-154.
4
Bingjum Li., Vindo K., Michel H.D., Relationship for non-Darcy flow in rockfill, Journal of the Hydraulics Division 120 (1998) 451-467.
5
Bordier C., and Zimmer C., Drainage Eq.s and non-Darcian modeling in coarse porous media or geosynthetic materials, Hydrology 228 (2000) 174–187.
6
Curtis R.P., Lawson J.D., Flow over and through rock fill bank, Journal of the Hydraulics Division 93 (1967) 1-21.
7
Fourar M., and Lenormand R., A new model for two-phase flows at high velocities through porous media and fractures, Petroleum Science and Engineering 895 (2001) 231-238.
8
Freez R.A., Three-dimensional, transient, saturated-unsaturated flow in a groundwater basin, Water Resources Research 7 (1971) 347-366.
9
Hansen D., Garga V.K., Townsend D.R., Selection and application of a one-dimensional non- Darcy flow equation for two- dimensional flow through Rock-fill embankments, Canadian Geotechnical Journal 32 (1994) 223-232.
10
Harr M.E., Groundwater and seepage, First Ed., McGraw Hill: New York; (1962).
11
Harrera N.M., Felton G.K., Hydraulics of flow through a rock fills dam using sediment free water, Transactions of the ASABE 34 (1991) 871-875.
12
Hosseini S.M., Variability of hydraulic parameters in coarse porous media, IUST, International Journal of Engineering Science 13 (2002) 49-59.
13
James A., Liggett G., Location of free surface in porous media, Journal of the Hydraulics Division 128 (1977) 353-365.
14
Kohji M., Shiro M., Takaaki F., Masanori H., Discharge through a permeable rubble mound weir, Journal of Hydraulic Engineering 131 (2005) 1-10.
15
Lam L., Fredlund D.G., Barbour S.L., Transient seepage model for saturated unsaturated soil systems: a geotechnical engineering approach, Canadian Geotechnical Journal 24 (1987) 565-580.
16
Li B., Garga V.K., Davies M.H., Relationships for non-Darcy flow in rockfill, Journal of the Hydraulics Division 128 (1998) 206-212.
17
McCorquodal J.A., Hannoura A.A., Nasser M.S., Hydraulic conductivity of rockfill, Journal of Hydraulic Research 16 (1964) 123-137.
18
Rajabi M.A., Hatamkhani E., Sadeghian J., An experimental study on hydraulic behavior of free-surface radial flow in coarse-grained porous media, Hydraulic Structures 3 (2017) 10-21.
19
Parkin A.K., Trollope D.H., Lawson J.D., Rockfill structures subject to water flow, Soil Mechanic Found, Journal of the Hydraulics Division 6 (1960) 135-140.
20
Sadeghian J., Khayat Kholghi M., Horfar A., Bazargan J., Comparison of binomial and power relations in radial non-Darcy flows in coarse porous media, Journal of Water Sciences Research 5 (2013) 65-75.
21
Sadegian J., Nonlinear analysis of radial flow in coarse alluvial beds, Ph.D Thesis, College of Agriculture, University of Tehran, Iran (2013).
22
Samani H.M.V., Samani J.M.V., Shaiannejad M., Reservoir routing using steady and unsteady flow through rock fill dams, Journal of Hydraulic Engineering 129 (2003) 448-454.
23
Stephenson D., Rock fill in hydraulic engineering, First Ed., Elsevier Science Publishers: USA; (1979).
24
Thiruvengadam M., and Pradip k., Validity of Forchheimer in radial flow through coarse granular media, Journal of Engineering Mechanics 123 (1997) 696-704.
25
ORIGINAL_ARTICLE
An approach to reduce water consumption by optimizing and determining of crop cultivation pattern using meta-heuristic algorithms: A case study on Moghan plain
Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. Optimizing the crop cultivation pattern, in order to reduce water consumption, in arid and semi-arid regions such as Iran, due to water scarcity and food intake, is an essential solution for food intakes needs. In this study, new methods based on the election algorithms (EA) and gray wolf optimizer (GWO) algorithms were used to determine the optimal cultivation pattern in Moghan plain during the statistical years of 2007-2016. The objective function in the agricultural sector was based on each product and its yield, net from each product and the cultivar. Then, maximization of the objective function was performed using GWO and EA algorithm. The results of using GWO algorithm in determining the optimal crop pattern in Moghan plain showed that using economic policies such as changing the cultivar pattern, we can obtain a better result compared to EA algorithm in the agricultural sector. In general, the results of GWO algorithm showed that in the Moghan plain with 0.9, 140 billion rials, that is, about 42 % will have economic growth. In sum, the results showed that GWO algorithm with high values of statistical criteria (R2=0.96, RMSE=0.022 and NSE=0.75) has a higher efficiency in optimizing the crop cultivation pattern of Moghan plain, which can be applied to the correct planning for other cultivation areas to be employed.
https://arww.razi.ac.ir/article_1299_617011ac2114b91dc5df39e96a9d99de.pdf
2020-06-30
48
56
10.22126/arww.2020.4076.1119
Cultivation Pattern
Election Algorithm
Gray Wolf Optimizer algorithm
Economic Net
Yahya
Choopan
yahyachoopan68@gmail.com
1
Department of Water Engineering, Faculty of Agriculture, University of Agricultural Sciences & Natural Resources, Gorgan, Iran.
AUTHOR
Somayeh
Emami
somayehemami70@gmail.com
2
Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
LEAD_AUTHOR
Alabdulkader A.M., Al-Amoud A.I., Awad F.S., Optimization of the cropping pattern in Saudi Arabia using a mathematical programming sector model, Agricultural Economics/Zemedelska Ekonomika 12 (2012) 58-69.
1
Alizadeh A., Majidi N., Ghorbani M., Mohammadian F., Cultivation pattern optimization to balance groundwater resource (case study: Mashhad-Chenaran plain), Iranian Journal of Irrigation and Drainage 1 (2012) 55-68.
2
Amantaray S., Rath A., Sahu A., Swain P., Derivation of optimal cropping pattern in sambalpur distributary using genetic algorithm, International Journal of Soft Computing and Artificial Intelligence 5 (2017) 1-6.
3
Asadi A., Keramatzade A., Eshraghi F., Determination of optimal crop cultivation pattern (Case study: Gorgan city), 4th International Congress on Advanced Research in Management, Accounting and Economics Studies, 28 May, Hall of Conferences of Cultures, Shiraz, Iran, (2017).
4
Barikani A., Ahmadian M., Khalilian S., Optimal operation of groundwater resources in agriculture sector (Case study: agriculture subsection of Qazvin plain), Journal of Agricultural Economic and Development 25 (2012) 253-262.
5
Borhani Darian A.R., and Farahmandfar Z., Calibration of rainfall-runoff models using MBO algorithm, Iranian of Irrigation and Water Engineering 1 (2011) 60-71.
6
Daniel T., and Larose C.D., Discovering knowledge in data: an introduction to data mining, Jhon Wiley & Sons Inc, 240 pages; (2004).
7
Dutta S., Sahoo B., Mishra R., Acharya S., Fuzzy stochastic genetic algorithm forobtaining optimum crops pattern and water balance in a farm, Water Resource Management 30 (2016) 4097–4123.
8
Emami H., and Derakhshan F., Election algorithm: A new socio-politically inspired strategy, AI Communications 28 (2015) 591–603.
9
Ghahraman B., and Sepaskhah A.R., Optimal allocation of water from a single purpose reservoir to an irrigation project with pre-determined multiple cropping patterns, Irrigation Science 21 (2002) 127–137.
10
Gorgani J., Determining the risk-based crop cultivation pattern with agricultural water management using a combination of agricultural pattern, MSc. Thesis of Economic, Mgamotad Department, Ferdosi Mashhad University (2014).
11
Gopi A., Land allocation strategies through genetic algorithm approach–a case study, Global Journal of Research in Engineering 11 (2011) 6-14.
12
Khanjari Sadati S., Speelman M., Sabouhi M., Gitizadeh M., Ghahraman B., Optimal irrigation water allocation using a genetic algorithm under various weather conditions, Water 6 (2014) 3068-3084.
13
Khasheie-Siuki A., Ghahreman B., Khochekzadeh M., Determine optimal crop cultivation pattern to prevent groundwater level, Iranian Journal of Water Research 8 (2014) 137-146.
14
Majidi N., Alizadeh A., Ghorbani M., Determining the optimum cropping pattern in same direction with water resources management of Mashhad-CHenaran plain, Journal of Water and Soil 25 (2011) 776-785.
15
Mech L.D., Alpha status, dominance, and division of labor in wolf packs, Canadian Journal of Zoology 77 1999) 1196-1203.
16
Mirjalili S., Mirjalili S.M., Lewis A., Grey wolf optimizer, Advances in Engineering Software 69 (2014) 46-61.
17
Mirzaie S., Zakerinia M., Sharifan H., Shahabifar M., The determination of optimal crop pattern operation with max-mim ant system method (MMAS) (Case study: Golestan dam irrigation and drainage network), Iranian Journal of Irrigation and Drainage 9 (2015) 66-74.
18
Mirzaie S., Zakerinia M., Shahabifar M., Sharifan H., Determining optimum cropping pattern using genetic algorithm (Case study: Golestan dam irrigation and drainage network, Journal of Irrigation Sciences and Engineering (JISE) 40 (2017) 181-190.
19
ORIGINAL_ARTICLE
Investigation of scour around the dual bridge piers under unsteady flow conditions using experimental model
The local scour around the bridge piers is the main cause of their destruction. Based on this, extensive studies have been done to understand this phenomenon. Most of these studies have been done under steady flow conditions. This is while the flow in the river is unsteady. Therefore, the experiments of this research were carried out under unsteady flow conditions. The purpose of this research is to investigate the scour around the dual bridge piers at different distances of the piers from each other in a uniform flow as well as unsteady flow using symmetric hydrographs. The hydrographs used in the experiments are stepped hydrographs in 5 steps. The experiments were conducted under clear water conditions and U/UC=0.95. In all experiments, the diameter of the bridge pier (D) was constant and equal to 2.5 cm. The center-to-center distance between the dual bridge piers (S) was selected as 2D, 3D, 4D and 5D. In the unsteady flow, with increasing relative distance between the dual bridge piers, the maximum dimensionless scour depth of the first and second piers was increased and its maximum was measured at a relative distance of S/D=5 (in the range of relative distances studied in the research). But in the uniform flow, the maximum dimensionless scour depth of the first and second pier was observed at S/D=3 and S/D=4, respectively. Also, at a constant distance between the piers, increasing the peak and base flow of the hydrographs step-by-step, increased the maximum dimensionless scour depth of the first pier of dual bridge piers with an increasing rate. However, increasing the peak and base flow of the hydrographs step-by-step, increased the maximum dimensionless scour depth of the second pier with a decreasing and increasing rate, respectively.
https://arww.razi.ac.ir/article_1404_ec7f8054fb62c32b10cf57e88c885dfd.pdf
2020-06-30
57
63
10.22126/arww.2020.4213.1127
clear water
scour
bridge pier
base flow
peak flow
Saeedeh
Mohammadi Givshad
s.mohamady71@yahoo.com
1
Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
AUTHOR
Yousef
Ramezani
y.ramezani@birjand.ac.ir
2
Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
LEAD_AUTHOR
Hossein
Khozeymehnezhad
hkhozeymeh@birjand.ac.ir
3
Department of Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
AUTHOR
Ataie-Ashtiani B., and Beheshti A.A., Experimental investigation of clear-water local scour at pile groups, Journal of Hydraulic Engineering 132 (2006) 1100-1104
1
Barbhuiya A.K., and Dey S., Local scour at abutments: A review, Sadhana, 29 (2004) 449-476.
2
Bateni S.M., Vosoughifar H.R., Truce B., Jeng D.S., Estimation of clear-water local scour at pile groups using genetic expression programming and multivariate adaptive regression splines, Journal of Waterway, Port, Coastal, and Ocean Engineering 145 (2018) 1-11.
3
Briaud J.L., Chen H.C., Kwak K.W., Han S.W., Ting F.C.K., Multiflood and multilayer method for scour rate prediction at bridgepiers, Journal of Geotechnical and Geoenvironmental Engineering 127 (2001) 114-125.
4
Chang W.Y., Lai J.S., Yen C.L., Evolution of scour depth at circular bridge piers, Journal of Hydraulic Engineering 130 (2004) 905-913.
5
Chiew Y.M., Mechanics of riprap failure at bridge piers, Journal of Hydraulic Engineering 121 (1995) 635-643.
6
Chiew Y.M., and Melville B.W., Local scour around bridge piers, Journal of Hydraulic Research 25 (1987) 15-26.
7
Chiew Y.M., Scour protection at bridge piers, Journal of Hydraulic Engineering 118 (1992) 1260-1269.
8
Dey S., and Barbhuiya A.K., Time variation of scour at abutments, Journal of Hydraulic Engineering 131 (2005) 11-23.
9
EL-Ghorab E.A., Reduction of scour around bridge piers using a modified method for vortex reduction, Alexandria Engineering Journal 52 (2013) 467-478.
10
Guney M., and BorTurkben A., Experimental study of local scour around circular pier under hydrographs succeeding steady flow, In 36th IAHR World Congress, The Hague, Netherlands (2015).
11
Hamill L., Bridge Hydraulics, First Ed., CRC Press: USA; (1998).
12
Hannah C.R., Scour at pile groups, M.Sc. Thesis. Department of Civil Engineering, University of Canterbury, Christchurch, New Zealand, (1978).
13
Karimaei Tabarestani M., Zarrati A.R., Impact of flood hydrograph peak flow occurrence time on local scour around the bridge pier, Journal of Hydraulic Engineering 9 (2014) 15-32.
14
Kothyari U.C., Garde R.C.J., Ranga Raju K.G., Temporal variation of scour around circular bridge piers, Journal of Hydraulic Engineering 118 (1992) 1091-1106.
15
Lai J.S., Chang W.Y., Yen C.L., Maximum local scour depth at bridge piers under unsteady flow, Journal of Hydraulic Engineering 135 (2009) 609-614.
16
Lu J.Y., Hong J.H., Su C.C., Wang C.Y., Lai J.S., Field measurements and simulation of bridge scour depth variations during floods, Journal of Hydraulic Engineering 134 (2008) 810-821.
17
Lu J.Y., Shi Z.Z., Hong J.H., Lee J.J., Raikar R.V., Temporal variation of scour depth at nonuniform cylindrical piers, Journal of Hydraulic Engineering 137 (2010) 45-56.
18
Melville B.W., Coleman S.E., Bridge Scour, First Ed., Water Resources Publication: USA; (2000).
19
Nazariha M., Design relationships for maximum local scour depth for bridge pier groups, University of Ottawa, Ottawa, Ontario, Canada (1996).
20
Oliveto G., and Hager W.H., Temporal evolution of clear-water pier and abutment scour, Journal of Hydraulic Engineering 128 (2002) 811-820.
21
Raudkivi A.J., Ettema R., Clear-water scour at cylindrical piers, Journal of Hydraulic Engineering 109 (1983) 338-350.
22
Sadeghi F., Ramezani Y., Khozeymehnezhad H., Effect of submergence ratio of parallel wall on bridge abutment scour, Alexandria Engineering Journal 57 (2018) 2659-65.
23
Salamatian S.A., KarimaeiTabarestani M., Zarrati A.R., Local scour at a cylindrical bridge pier under a flood hydrograph, River Flow 2014 – the 7th International Conference on Fluvial Hydraulics, Lausanne, Switzerland (2014).
24
Sumer B.M., and Fredsoe J., The mechanics of scour in the marine environment, World Scientific (2002).
25
ORIGINAL_ARTICLE
A study on estimation of greenhouse gas emissions from industrial wastewater sector in Iran
Industrial activities are one of the most important emission sources of greenhouse gases at a global level. The process of production, transportation, electricity consumption, and industrial wastewater are the four major components in producing greenhouse gases. Industrial wastewater management (collection, treatment, and disposal) results in direct emission of greenhouse gases (including carbon dioxide, methane, and nitrous oxide). Also, energy consumption in the wastewater treatment process causes indirect carbon dioxide emissions. The present study aimed to estimate the contribution of industrial wastewater treatment plants in Iran from this emission, in addition to identifying sources of greenhouse gas emissions in the industrial wastewater treatment plant and estimating greenhouse gas emissions from the industrial wastewater sector in Iran. In this research, the emission calculations were conducted by using the methodology of Intergovernmental Panel on Climate Change (IPCC) guidelines for calculating greenhouse gases emission. Based on the estimations performed in this study, 1,305.98 kt of CH4 were emitted directly from wastewater in 2017 in the entire industrial wastewater sector. Further, the results indicated that industrial wastewater treatment plants in Iran’s industrial parks generate 46.53 kt of CH4 directly and 259.5 kt of CO2 indirectly. According to the studies, the food industry, especially the industries involved in processing agricultural products (with 48.74 % of total methane emissions) has the highest greenhouse gas emissions in the country, followed by the paper production industry (with 27.46 % of total methane emissions) in the second place. One of the best strategies for reducing greenhouse gas emissions in industrial wastewater treatment plants is energy production from methane produced in large treatment plants and implementing necessary amendments in production processes to decrease wastewater production.
https://arww.razi.ac.ir/article_1353_e7f116ec4f6bcdaf3947469967930285.pdf
2020-06-30
64
69
10.22126/arww.2020.4301.1129
industrial wastewater treatment plants
Greenhouse gases
Global warming
methane emission
Hossein
Nayeb
pirnia.nayeb@gmail.com
1
Department of Environmental Engineering, Faculty of Water and Environment, Shahid Beheshti University, Tehran, Iran.
AUTHOR
Maryam
Mirabi
m_mirabi@sbu.ac.ir
2
Department of Environmental Engineering, Faculty of Water and Environment, Shahid Beheshti University, Tehran, Iran.
LEAD_AUTHOR
Homayoon
Motiee
h_motiei@sbu.ac.ir
3
Department of Environmental Engineering, Faculty of Water and Environment, Shahid Beheshti University, Tehran, Iran.
AUTHOR
Abolghasem
Alighardashi
a_ghardashi@sbu.ac.ir
4
Department of Environmental Engineering, Faculty of Water and Environment, Shahid Beheshti University, Tehran, Iran.
AUTHOR
Ahmad
Khoshgard
ahkhoshgard@gmail.com
5
Department of Chemical Engineering, Faculty of Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran.
AUTHOR
Ashrafi O., Yerushalmi L., Haghighat F., Wastewater treatment in the pulp-and-paper industry: A review of treatment processes and the associated greenhouse gas emission, Journal of Environmental Management 158 (2015) 146-157.
1
Broecker W.S., Climatic change: Are we on the brink of a pronounced global warming?, Science 189 (1975) 460-463.
2
Climate change, The scientific basis, Intergovernmental Panel on Climate Change, Cambridge, United Kingdom, (2001).
3
Czepiel P., Crill P., Harriss R., Nitrous oxide emissions from municipal wastewater treatment, Environmental Science & Technology 29 (1995) 2352-2356.
4
Daelman M.R., van Voorthuizen E.M., van Dongen U.G., Volcke E.I., van Loosdrecht M.C., Methane emission during municipal wastewater treatment, Water Research 46 (2012) 3657-3670.
5
Desloover J., De Clippeleir H., Boeckx P., Du Laing G., Colsen J., Verstraete W., Vlaeminck S.E., Floc-based sequential partial nitritation and anammox at full scale with contrasting N2O emissions, Water Research 45 (2011) 2811-2821.
6
Desloover J., Vlaeminck S.E., Clauwaert P., Verstraete W., Boon N., Strategies to mitigate N2O emissions from biological nitrogen removal systems, Current Opinion in Biotechnology 23 (2012) 474-482.
7
Dietz T., and Rosa E.A., Effects of population and affluence on CO2 emissions, Proceedings of the National Academy of Sciences 94 (1997) 175-179.
8
Doorn M.R.J., Strait R.P., Barnard W.R., Eklund B., Estimates of global greenhouse gas emissions from industrial and domestic wastewater treatment, Pechan (EH) and Associates, Inc., Durham, NC: United States; (1997).
9
Eggleston H.S., Buendia L., Miwa K., Ngara T., Anabe K., Intergovernmental panel on climate change guidelines for national greenhouse gas inventories, Prepared by the National Greenhouse Gas Inventories Programme, Japan (2006). http://www.ipcc-nggip.iges.or.jp/public/2006gl/.
10
Gupta D., and Singh S.K., Greenhouse gas emissions from wastewater treatment plants: A case study of Noida, Journal of Water Sustainability 2 (2012)131-139.
11
Iran Fisheries Organization, Statistics and Information, http://fisheries.ir/; 2017.
12
Iran Small Industries and Industrial Parks Organization (ISIPO), Statistics and Information http://isipo.ir/index.jsp?siteid=1&fkeyid =& siteid=1&pageid=417/; 2017.
13
Iran Water Resources Management Corporation, Statistics and Information, http://wrbs.wrm.ir/; 2017.
14
Iran's Third National Communication to UNFCCC, Chapter 2, National GHGs Emission Inventory, http://en.climatechange.ir/my_doc/climate change/Climate%20Change%20in%20Iran/TNC/English/Industrial%20Process.pdf/; 2018.
15
Kampschreur M.J., Poldermans R., Kleerebezem R., van Der Star W.R.L., Haarhuis R., Abma W.R., Jetten M.S.M., van Loosdrecht M.C.M., Emission of nitrous oxide and nitric oxide from a full-scale single-stage nitritation-anammox reactor, Water Science and Technology 60 (2009) 3211-3217.
16
Kampschreur M.J., Temmink H., Kleerebezem R., Jetten M.S., van Loosdrecht M.C., Nitrous oxide emission during wastewater treatment, Water Research 43 (2009) 4093-4103.
17
Koutsou O.P., Gatidou G., Stasinakis A.S., Domestic wastewater management in Greece: greenhouse gas emissions estimation at country scale, Journal of Cleaner Production 188 (2018) 851-859.
18
Kyung D., Kim M., Chang J., Lee W., Estimation of greenhouse gas emissions from a hybrid wastewater treatment plant, Journal of Cleaner Production 95 (2015) 117-123.
19
Law Y., Ye L., Pan Y., Yuan Z., Nitrous oxide emissions from wastewater treatment processes, Philosophical Transactions of the Royal Society B: Biological Sciences 367 (2012) 1265-1277.
20
Lexmond M.J., and Zeeman G., Potential of controlled anaerobic wastewater treatment in order to reduce the global emissions of methane and carbon dioxide." In Non-CO2 Greenhouse Gases: Why and How to Control?, First Ed., Springer, Netherlands; (1994).
21
Ma Z.Y., Feng P., Gao Q.X., Lu Y.N., Liu J.R., Li W.T., CH4 emissions and reduction potential in wastewater treatment in China, Advances in Climate Change Research 6 (2015) 216-224.
22
Ministry of Agriculture, Statistics and Information, http://maj.ir/index.aspx?lang=2&sub=0/; 2017.
23
Ministry of Energy, Iran's Energy balance sheet of 2015. http://pep.moe.gov.ir/; 2017.
24
Ministry of Industry, Mine and Trade, Statistics and Information, http://en.mimt.gov.ir/web_directory/13625-Case-Reports.html/; 2017.
25
Ministry of Petroleum, Statistics and Information, http://www.mop.ir/; 2017.
26
Mo W., and Zhang Q., Energy–nutrients–water nexus: integrated resource recovery in municipal wastewater treatment plants, Journal of Environmental Management 127 (2013) 255-267.
27
Molinos-Senante M., Hernández-Sancho F., Mocholí-Arce M., Sala-Garrido R., Economic and environmental performance of wastewater treatment plants: Potential reductions in greenhouse gases emissions, Resource and Energy Economics 38 (2014) 125-140.
28
Ren W.X., Geng Y., Xue B., Fujita T., Ma Z.X., Jiang P., Pursuing co-benefits in China’s old industrial base: A case of Shenyang, Urban Climate 1 (2012) 55-64.
29
Rodríguez-Caballero A., Aymerich I., Poch M., Pijuan M., Evaluation of process conditions triggering emissions of green-house gases from a biological wastewater treatment system, Science of the Total Environment 493 (2014) 384-391.
30
Saghafi S., Mehrdadi N., Bid Hendy G.N., Rad H.A., Estimating the electrical energy in different processes for Nasir Abad industrial wastewater treatment plant with emphasis on COD removal, Journal of Environmental Studies 42 (2016) 4-6.
31
Saghafi S., Mehrdadi N., Bid Hendy G.N., Rad H.A., Estimating the electrical energy in different processes for Nasir Abad industrial wastewater treatment plant with emphasis on COD removal, Journal of Environmental Studies 42 (2016) 4-6.
32
Shahabadi M.B., Yerushalmi L., Haghighat F., Impact of process design on greenhouse gas (GHG) generation by wastewater treatment plants, Water Research 43 (2009) 2679-2687.
33
Solomon S., Qin D., Manning M., Chen Z., Marquis M., Averyt K.B., Tignor M., Miller H.L., Intergovernmental panel on climate change climate change: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, USA; (2007).
34
Strategic planning and supervising deputy of the president, Environmental Regulations Reports on Reuse of Returned Waters and Sewages- Journal No. 535, Iran, (2010).
35
Sweetapple C., Fu G., Butler D., Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment, Water Research 62 (2014) 249-259.
36
Yerushalmi L., Ashrafi O., Haghighat F., Reductions in greenhouse gas (GHG) generation and energy consumption in wastewater treatment plants, Water Science and Technology 67 (2013) 1159-1164.
37
Yoshida H., Mønster J., Scheutz C., Plant-integrated measurement of greenhouse gas emissions from a municipal wastewater treatment plant, Water Research 61 (2014) 108-118.
38
ORIGINAL_ARTICLE
Integrating the process of Ni (II) ions removal from aqueous solution and cooling of a photovoltaic module by 1.7 MHz ultrasound waves
In this study, Ni+2 removal from aqueous solution was investigated by concurrent usage of Fe3O4 nanoparticles and a high frequency ultrasound (1.7 MHz). In addition to Ni+2 removal, presence of the high frequency ultrasound led to being cooled photovoltaic (PV) module. Studied variables were pH and adsorbent dose (AD). Results indicated that the Ni+2 removal efficiency increased with an increase in the pH ranging from 2 to 9. Furthermore, the Ni+2 removal efficiency boosted by an increase in the AD. However, no significant enhancement in Ni+2 removal efficiency was observed at the AD above 9 g. Generally, the maximum Ni+2 removal efficiency was about 79 % for contact time of 50 min at pH=9 and AD=9 g in the presence of ultrasound. At the efficient condition (pH=9, AD=9 g and contact time=50 min), using ultrasound showed 16-20 % enhancement in Ni+2 removal efficiency compared to no ultrasound usage. From heat transfer view, it was observed that propagation of 1.7 MHz ultrasound into nanofluid significantly has cooled the photovoltaic (PV) module. Moreover, an increase in concentration of nanofluid (AD) showed a positive effect on reduction of heat from the PV module surface and maximum generated power. Obtained data demonstrated that agitating nanofluid by 1.7 MHz ultrasound decreased temperature of the PV module up to 15.5 % compared to no cooling system.
https://arww.razi.ac.ir/article_1421_5e8a1cd09646baafe6b7bd029706cd97.pdf
2020-06-30
70
76
10.22126/arww.2020.5091.1160
Adsorption
Ultrasound
Fe3O4
Bentonite
Nanoparticles
Sono-separator
Zakie
Rostami
z_rostami@hotmail.com
1
Department of Chemical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
Masoud
Rahimi
masoudrahimi@yahoo.com
2
Department of Chemical Engineering, Faculty of Petroleum and Chemical Engineering, Razi University, Kermanshah, Iran.
LEAD_AUTHOR
Neda
Azimi
neda_azimi1988@yahoo.com
3
Department of Chemical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
An W., Wu J., Zhu T., Zhu Q., Experimental investigation of a concentrating PV/T collector with Cu9S5 nanofluid spectral splitting filter, Applied Energy 184 (2016) 197–206.
1
Al-Waeli A.H.A., Sopian K., Chaichan M.T., Kazem H.A., Hasan H.A., Al-Shamani A.N., An experimental investigation of SiC nanofluid as a base-fluid for a photovoltaic thermal PV/T system, Energy Conversion and Management 142 (2017) 547–558.
2
Asfaram A., Ghaedi M., Hajati S., Goudarzi A., Bazrafshan A.A., Simultaneous ultrasonic-assisted ternary adsorption of dyes onto copper-doped zinc sulfide nanoparticles loaded on activated carbon: Optimization by response surface methodology, Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 145 (2015) 203-212.
3
Belova D.A., Lakshtanov L.Z., Carneiro J.F., Stipp S.L.S., Nickel adsorption on chalk and calcite, Journal of Contaminant Hydrology 170 (2014) 1–9.
4
Chow T.T., Hand J.W., Strachan P.A., Building-integrated PV and thermal applications in a subtropical hotel building, Applied Thermal Engineering 23 (2003) 2035–2049.
5
Es-sahbany H., Berradi M., Nkhili S., Hsissou R., Allaoui M., Loutfi M., Bassir D., Belfaquir M., Youbi M.S., Removal of heavy metals (nickel) contained in wastewater-models by the adsorption technique on natural clay, Materials Today: Proceedings 13 (2019) 866–875.
6
Fu F., and Wang Q., Removal of heavy metal ions from wastewaters: a review, Journal of Environmental Management 92 (2011) 407-418.
7
Ghadiri M., Sardarabadi M., Pasandideh-fard M., Moghadam A.J., Experimental investigation of a PVT system performance using nano Ferrofluids, Energy Conversion and Management 103 (2015) 468–476.
8
Hamdaoui O., Naffrechoux E., Adsorption kinetics of 4-chlorophenol onto granular activated carbon in the presence of high frequency ultrasonic, Ultrasonic Sonochemestry 16 (2009) 15-22.
9
Hussien H.A., Noman A.H., Abdulmunem A.R., Indoor investigation for improving the hybrid photovoltaic/thermal system performance using nanofluid (Al2O3-water), Engineering and Technology Journal 33 (2015) 889–901.
10
Kalogirou S.A., Tripanagnostopoulos Y., Hybrid PV/T solar systems for domestic hot water and electricity production, Energy Conversion and Management 47 (2006) 3368–82.
11
Karami N., Rahimi M., Heat transfer enhancement in a hybrid microchannel-photovoltaic cell using Boehmite nanofluid, International Communications in Heat and Mass Transfer 55 (2014) 45-52.
12
Karami N., and Rahimi M., Heat transfer enhancement in a PV module using Boehmite nanofluid, Energy Convers Manage 86 (2014) 275–285.
13
Khanjari Y., Pourfayaz F., Kasaeian A.B., Numerical investigation on using of nanofluid in a water-cooled photovoltaic thermal system, Energy Convers Manage 122 (2016) 263–78.
14
Ji J., Lu X., Xu Z., Effect of ultrasonic on adsorption of Geniposide on polymeric resin, Ultrasonic Sonochemestry 13 (2006) 463–470.
15
Liao B., Sun W.Y., Guo N., Ding S.L., Su S. J., Equilibriums and kinetics studies for adsorption of Ni (II) ion on chitosan and its triethylenetetramine derivative, Colloids and Surfaces A: Physicochemical and Engineering Aspects 501 (2016) 32-41.
16
Malamis S., and Katsou E., A review on zinc and nickel adsorption on natural and modified zeolite, bentonite and vermiculite: Examination of process parameters, kinetics and isotherms, Journal of Hazardous Materials 252 (2013) 428-461.
17
Menkah E.S., Dzade N.Y., Tia R., Adei E., Leeuw N.H.,. Hydrazine adsorption on perfect and defective fcc nickel (100), (110) and (111) surfaces: A dispersion corrected DFT-D2 study, Applied Surface Science 480 (2019) 1014–1024.
18
Mousavi S.A., Almasi A., Navazeshkha F., Falahi F., Biosorption of lead from aqueous solutions by algae biomass: optimization and modeling, Desalination and Water Treatment 148 (2019) 229–237.
19
Nayeri D., Mousavi S.A., Mehrabi A., Oxytetracycline removal from aqueous solutions using activated carbon prepared from corn stalks, Journal of Applied Research in Water and Wastewater 6 (2019) 67-72.
20
Parvizian F., Rahimi M., Azimi N., Macro- and micromixing studies on a high frequency continuous tubular sono-container, Chemical Engineering Processing 57–58 (2012) 8–15.
21
Radwan A., Ahmed M., Ookawara S., Performance enhancement of concentrated photovoltaic systems using a microchannel heat sink with nanofluids, Energy Convers Manage 119 (2016) 289–303.
22
Rahimi M., Azimi N., Parvizian F., Using microparticles to enhance micromixing in a high frequency continuous flow sono-container, Chemical Engineering Processing 70 (2013) 250-258.
23
Sayadi M.H., and Rezaei M.R., Impact of land use on the distribution of toxic metals in surface soils in Birjand city, Proceedings of the International Academy of Ecology and Environmental Sciences 4 (2014) 18-29.
24
Siahkamari L., Rahimi M., Azimi N., Banibayat M., Experimental investigation on using a novel phase change material (PCM) in micro structure photovoltaic cooling system, International Communications in Heat and Mass Transfer 100 (2019) 60-66.
25
Suresh A.K., Khurana S., Nandan G., Dwivedi G., Kumar S., Role on nanofluids in cooling solar photovoltaic cell to enhance overall efficiency, Materials Today: Proceedings 5 (2018) 20614–20620.
26
Wang J., Xu L., Cheng C., Meng Y., Li A., Preparation of new chelating fiber with waste PET as adsorbent for fast removal of Cu2+ and Ni2+ from water: kinetic and equilibrium adsorption studies, Chemical Engineering Journal 193 (2012) 31-38.
27
ORIGINAL_ARTICLE
Modeling and optimization study by response surface methodology on magnesium ions removal from hard water through a biosorbent
Hazelnut shell was used as a green adsorbent and environment-friendly for magnesium ions (Mg2+) adsorption from hard water solution in batch system. The characterization of the biosorbent was entirely evaluated using SEM, XRD and FT-IR analyses. Design of experiments (DOE) decreased the number of non-significant experiments, which resulted in reducing the time and cost of studies. Response surface methodology (RSM) was applied to dynamic assessment of the adsorption process. The effects of variables (pH, adsorbent dosage, Mg2+ concentration, time) and their interactions were investigated by central composite face design (CCFD). In addition, the numerical optimization was also analyzed. The results demonstrated that maximum efficiency, 56.21 %, and adsorbent capacity, 5.729 mg/g, occurred at initial concentration of 200 mg/L, adsorbent dosage of 1 g and pH 10 in duration of 59.816 min which were in good agreement with experimental results. In order to validate of the dynamic model, artificial neural network (ANN) was employed. Although RSM had a superior capability in developing of the model in comparison with ANN, it was acceptable to forecast the magnesium ions removal by both RSM and ANN approaches. Finally, the studies of the adsorption isotherms, kinetic models, reusability tests of the adsorbent and comparison with walnut shell were also done.
https://arww.razi.ac.ir/article_1422_f082bd03de1144eea800e60a729a5823.pdf
2020-06-30
77
89
10.22126/arww.2020.4897.1155
Hard water
Response Surface Methodology (RSM)
Optimization
Biosorbent
Magnesium ions removal
Abedin
Raziani
abedin.raziani@gmail.com
1
Department of Chemical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
AUTHOR
Akbar
Mohammadidoust
mohammadidoust@gmail.com
2
Department of Chemical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
LEAD_AUTHOR
Aghav R.M., Kumar S., Mukherjee S.N., Artificial neural network modeling of phenol and resorcinol from water environment using some carbonaceous adsorbents, Journal of Hazardous Material 188 (2011) 67-77.
1
Aksu Z., and Akpinar D., Competitive biosorption of phenol and chromium (VI) from binary mixtures onto dried anaerobic activated sludge, Biochemical Engineering Journal 7 (2001) 183-193.
2
Al-Senani G.M., and Al-Fawzan F.F., Adsorption study of heavy metal ions from aqueous solution by nanoparticle of wild herbs, Egyptian Journal of Aquatic Research 44 (2018) 187-94.
3
Babel S., and Kurniawan T.A., Cr (VI) removal from synthetic wastewater using coconut shell charcoal and commercial activated carbon modified with oxidizing agents and/or chitosan, Chemosphere 54 (2004) 951-967.
4
Banat FA., Albashir B., Alasheh S., Hayajneh O., Adsorption of phenol by bentonite, Environmental Pollution 107 (2000) 391-398.
5
Bingol D, Hercan M, Elevli S., Kilic E., Comparison of the results of response surface methodology and artificial neural network for the biosorption of lead using black cumin, Bioresource Technology 112 (2012) 111-115.
6
Cardoso V.D.A., Souza AGD., Sartoratto P.P.C., Nunes L.M., The ionic exchange of cobalt, nickel and copper (II) in alkaline and acid-layered titanates, Colloids and Surfaces A: Physicochemical and Engineering Aspects 248 (2004) 145-149.
7
Castro L., Blazquez M.L., Gonzalez F., Munoz J.A., Balester A., Heavy metal adsorption using biogenic iron compounds, Hydrometalurgy 179 (2018) 44-51.
8
Cimino G., Passerini A., Toscano G., Removal of toxic cations and Cr (VI) from aqueous solution by hazelnut shell, Water Research 34 (2000) 2955-2962.
9
Desai K.M., Survase S.A., Survase PS., Saudagar P.S., LeLe S.S., Singhal R.S., Comparison of artificial neural network (ANN) and response surface methodology (RSM) in fermentation media optimization: case study of fermentative production of scleroglucan, Biochemical Engineering Journal 41(2008) 266-273.
10
Eccles H., Treatment of metal-contaminated wastes: why select a biological process? Trends Biotechnololgy 17(1999) 462-465.
11
Esalah J.O., Weber M.E., Vera J.H., Removal of lead, cadmium and zinc from aqueous solutions by precipitation with sodium Di-(n-Octyl) phosphinate, Canadian Journal of Chemical Engineering 78 (2000) 948-954.
12
Ferreira L.S., Rodrigues M.S., Carvalho J.C.M.D., Lodi A., Finocchio E., Perego P., et al. Adsorption of Ni+2, Zn+2 and Pb+2 onto dry biomass of Arthrospira (Spirulina) platensis and Chlorella vulgaris, I. single metal systems, Chemical Engineering Journal 173 (2011) 326-333.
13
Freundlich H.M.F., Over the adsorption in solution, Journal of Physical Chemistry 57 (1906) 385–471.
14
Geyikci F., Kilic E., Coruh S., Elevli S., Modeling of lead adsorption from industrial sludge leachate on red mud by using RSM and ANN, Chemical Engineering Journal 183 (2012) 53-59.
15
Harington J., The desirability function, India Quality Control, 21 (1965) 494-498.
16
Hasan S.H., Srivastava P., Talat M., Biosorption of Pb (II) from water using biomass of aeromonas hydrophila: central composite design for optimization of process variables, Journal of Hazardous Material 168 (2009) 1155-1162.
17
Hong M., Yu L.Y., Wang Y., Zhang J., Chen Z., Dong L., Zan Q., Li R., Heavy metal adsorption with zeolites: the role of hierarchical pore architecture, Chemical Engineering Journal 359 (2019) 363-372.
18
Inspectorate D.W., Water hardness, Northern Ireland Environment Agency, 1999.
19
Kasiri M.B., Aleboyeh H., Aleboyeh A., Heterogeneous photo-fenton process with response surface methodology and artificial neural networks, Environmental Science and Technology 42 (2008) 7970-7975.
20
Khayet M., Cojocaru C., Essalhi M., Artificial neural network modeling and response surface methodology of desalination by reverse osmosis, Journal of Membrane Science 368 (2011) 202-214.
21
Kumar N.S., Subbaiah M.V., Reddy A.S., Krishnaiah A., Biosorption of phenolic compounds from aqueous solutions onto chitosanabrus precatorius blended beads, Journal of Chemical Technology and Biotechnology 84 (2009) 972-981.
22
Kyzas G.Z., Bomis G., Kosheleva R.I., Efthimiadou E.K., Favvas E.P., Kostoglou M., Mitropoulos A.C., Nanobubbles effect on heavy metal ions adsorption by activated carbon, Chemical Engineering Journal 356 (2019) 91-97.
23
Langmuir I., The constitution and fundamental properties of solids and liquids. Part I. solids, Journal of the American Chemical Society 38 (1916) 2221–2295.
24
Low K.S., Lee C.K., Leo A.C., Removal of metals from electroplating wastes using banana pith, Bioresource Technology 51(1995) 227-31.
25
Marshal W.E., and Johns M.M., Agricultural by-products as metal adsorbents: sorption properties and resistance to mechanical abrasion, Journal of Chemical Technology and Biotechnology 66 (1996) 192-198.
26
Mohammadidoust A., Rahimi M., Feyzi M., Effects of solvent addition and ultrasound waves on viscosity reduction of residue fuel oil, Chemical Engineering and Processing: Process Intensification 95 (2015) 353-361.
27
Mohammadidoust A., Rahimi M., Feyzi M., An optimization study by response surface methodology (RSM) on viscosity reduction of residue fuel oil exposed ultrasonic waves and solvent injection, Iranian Journal of Chemical Engineering 13 (2016a) 3-19.
28
Mohammadidoust A., Rahimi M., Feyzi M., Prediction and optimization of the effects of combining ultrasonic waves and solvent on the viscosity of residue fuel oil by ANN and ANFIS, Physical Chemistry Research 4 (2016b) 333-53.
29
Monser L., and Adhoum N., Modified activated carbon for the removal of copper, zinc, chromium and cyanide from wastewater, Separation and Purification Technology 26 (2002) 137-146.
30
Montgomery D.C., Design and analysis of experiments, seventh ed. John Wiley&Sons, NewYork, 2008.
31
Ni B.J., Huang Q.S., Wang C., Ni T.Y., Sun J., Wei W., Competitive adsorption of heavy metals in aqueous solution onto biochar derived from anaerobicaly digested sluge, Chemosphere 219 (2019) 351-357.
32
Ngah W.S.W., and Hanafiah M.A.K.M., Removal of heavy metal ions from wastewater by chemically modified plant wastes as adsorbents: a review, Bioresource Technology 99 (2008) 3935-3948.
33
Ogata F., Ueta E., Kawasaki N., Characteristics of a novel adsorbent Fe-Mg-type hydrotalcite and its adsorption capability of As (III) and Cr (VI) from aqueous solution, Journal of Industrial and Engineering Chemistry 59 (2018) 56-63.
34
Pamukoglu M.Y., Kargi F., Removal of copper (II) ions from aqueous medium by biosorption onto powdered waste sluge, Process Biochemistry 41 (2006) 1047-1054.
35
Pavan F.A., Mazzocato A.C., Jacques R.A., Dias S.L.P., Ponkan peel: a potential biosorbent for removal of Pb (II) ions from aqueous solution, Biochemical Engineering Journal 40 (2008) 357-362.
36
Pedersen A.J., Characterization and electrolytic treatment of wood combustion fly ash for the removal of cadmium, Biomass & Bioenergy 25 (2003) 447-458.
37
Prakash N., Manikandan S.A., Govindarajan L., Vijayagopal V., Prediction of biosorption efficiency for the removal of copper (II) using artificial neural networks, Journal of Hazardous Materials 152 (2008) 1268-1275.
38
Preetha B., and Viruthagiri T., Application of response surface methodology for the biosorption of copper using rhizopus arrhizus, Journal of Hazardous Materials 143 (2007) 506-510.
39
Ranjan D., Mishra D., Hasan S.H., Bioadsorption of arsenic: an artificial neural networks and response surface methodology approach, Industrial and Engineering Chemistry Research 50 (2011) 9852-9863.
40
Rostami K., Joodaki M.R., Some studies of cadmium adsorption using aspergillus niger, penicillium austurianum, employing an airlift fermenter, Chemical Engineering Journal 89 (2002) 239-252.
41
Saber S., Amani-Ghadim A.R., Mirzajani V., Removal of Cr (II) from polluted solutions by electrocoagulation: modeling of experimental results using artificial neural network, Journal of Hazardous Material 171 (2009) 484-490.
42
Shihani N., Kumbhar B.K., Kulshreshtha M., Modeling of extrusion process using response surface methodology and artificial neural networks, Journal of Engineering Science and Technology 1 (2006) 31-40.
43
Shojaeimehr T., Rahimpour F., Khadivi M.A., Sadeghi M., A modeling study by response surface methodology (RSM) and artificial neural network (ANN) on Cu2+ adsorption optimization using light expended clay aggregate (LECA), Journal of Industrial and Engineering Chemistry 20 (2014) 870-880.
44
Singh K.P., Gupta S., Singh A.K., Sinha S., Experimental design and response surface methodology for optimization of Rhodamine B removal from water by magnetic nanocomposite, Chemical Engineering Journal 165 (2010) 151-160.
45
Sud D., Mahajan G., Kaur M.P., Agricultural waste material as potential adsorbent for sequestering heavy metal ions from aqueous solutions: A review, Bioresource Technology 99 (2008) 6017-6027.
46
Tchobanoglous G., and Burton F.L., Wastewater engineering: Treatment and reuse, Metcalf & Eddy, Inc., 4th ed. McGraw-Hill. New York; 2003.
47
Turan N.G., Mesci B., Ozgonenel O., Artificial neural network (ANN) approach for modeling Zn (II) adsorption from leachate using a new biosorbent, Chemical Engineering Journal 173 (2011) 98-105.
48
Tyusenkov A.S., and Cherepashkin S.E., Scale inhibitor for boiler water systems, Russian Journal of Applied Chemistry 87 (2014) 1240-1245.
49
Wu Y., Qiu X., Cao S., Chen J., Shi X., Du Y., Deng H., Adsorption of natural composite sandwich-like nanofibrous mats for heavy metals in aquatic environment, Journal of Colloid and Interface Science 539 (2019) 533-544.
50
Xu D., Tan X., Chen C., Wang X., Removal of Pb (II) from aqueous solution by oxidized multiwaled carbon nanotubes, Journal of Hazardous Materials 154 (2008) 407-416.
51
Zhang Z., Li M., Chen W., Zhu S., Liu N., Zhu L., Immobilization of lead and cadmium from aqueous solution and contaminated sediment using nano-hydroxyapatite, Environmental Pollution 158 (2010) 514-519.
52
ORIGINAL_ARTICLE
Removal of heavy metals from synthetic wastewater using silica aerogel- activated carbon composite by adsorption method
In this study, removal of heavy metals from synthetic wastewater has been investigated using silica aerogel-activated carbon composite. The synthesized adsorbent was characterized by FE-SEM, FTIR and BET techniques. The effect of amine functional groups embedded on the surface of silica aerogel-activated carbon 0.5 wt. % composite, optimal initial pH of removal of ions, impact of initial concentration of the solution containing heavy metal ions, adsorbent amount and contact time on removal percentage of ions were investigated. The results showed the optimal pH of 8, optimal adsorbent amount of 0.3 g for the removal of cadmium ion and 0.06 g for the removal of lead ion and optimal contact time of 80 min for cadmium and 60 min for lead ions. Adsorption data were investigated using Langmuir and Freundlich isotherms and maximum adsorption capability for cadmium and lead was obtained at 38.16 and 175.44 mg/g adsorbent, respectively.
https://arww.razi.ac.ir/article_1471_5557c9781a085a66720f198cf8a4349f.pdf
2020-06-30
90
96
10.22126/arww.2020.3512.1093
Heavy metals
Silica aerogel-activated carbon
Sol-gel
Adsorption
Amine functional group
Mohammad Hesam
Falsafi
hesamfalsafi7@gmail.com
1
Transport Phenomena Research Center, Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran.
AUTHOR
Mohsen
Moghaddas
mhsmgh7@gmail.com
2
Department of Water Resource Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran.
AUTHOR
Jafarsadegh
Moghaddas
jafar.moghaddas@sut.ac.ir
3
Transport Phenomena Research Center, Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran.
LEAD_AUTHOR
Ahmadpour A., Zabihi M., Bastami T.R., Tahmasbi M., Ayati A., Rapid removal of mercury ion (II) from aqueous solution by chemically activated eggplant hull adsorbent, Journal of Applied Research in Water and Wastewater 6 (2016) 236–240.
1
Bargozin H., Amirkhani L., Moghaddas J., Ahadian M., Synthesis and application of silica aerogel-MWCNT nanocomposites for adsorption of organic pollutants, Scientia Iranica 17 (2010) 122-132.
2
Bayramoglu G., Gursel I., Tunali Y., Arica M.Y., Biosorption of phenol and 2-chlorophenol by Funalia trogii pellets, Bioresource Technology 100 (2009) 2685-2691.
3
Begag R., Rhine W.E., Dong W., Aerogel sorbents, https://patents. google.com/patent/US9931612B2/en; (2018).
4
Eisapour Chanani M., Bahramifar N., Younesi H., Synthesis of Fe3O4@silica core–shellparticles and their application for removal of copper ions from water, Journal of Applied Research in Water and Wastewater 4 (2015) 176-182.
5
Chen A., Xin X., Xu J., Bian Y., Bian Z., Cadmium ion adsorption by amine-modified activated carbon, Water Science and Technology 75 (2017) 1675-1683.
6
Chiron N., Guilet R., Deydier E., Adsorption of Cu (II) and Pb (II) onto a grafted silica: isotherms and kinetic models, Water Research 37 (2003) 3079-3086.
7
Dąbrowski A., Adsorption — from theory to practice, Advances in Colloid and Interface Science 93 (2001) 135-224.
8
Dada A., Olalekan A., Olatunya A., Dada O., Langmuir, Freundlich, Temkin and Dubinin–Radushkevich isotherms studies of equilibrium sorption of Zn2+ unto phosphoric acid modified rice husk, IOSR Journal of Applied Chemistry (IOSR-JAC) 3 (2012) 38-45.
9
Ebisike K., Okoronkwo A.E., Alaneme K.K., Adsorption of Cd (II) on chitosan–silica hybrid aerogel from aqueous solution, Environmental Technology & Innovation 14 (2019) 3-20.
10
Faghihian H., Nourmoradi H., Shokouhi M., Performance of silica aerogels modified with amino functional groups in PB (II) and CD (II) removal from aqueous solutions, Polish Journal of Chemical Technology 14 (2012) 50-56.
11
Fariba T., Mina H., Shiva M., Nanocomposite silica aerogel activated carbon: preparation, characterization and application to remove lead (ii) from aqueous solutions, Journal of the Chinese Chemical Society 59 (2012) 1578-1583.
12
Givianrad M.H., Rabani M., Saber-Tehrani M., Aberoomand-Azar P., Hosseini Sabzevari M., Preparation and characterization of nanocomposite, silica aerogel, activated carbon and its adsorption properties for Cd (II) ions from aqueous solution, Journal of Saudi Chemical Society 17 (2013) 329-335.
13
Guo S., Dan Z., Duan N., Chen G., Gao W., Zhao W., Zn (II), Pb (II), and Cd (II) adsorption from aqueous solution by magnetic silica gel: preparation, characterization, and adsorption, Environmental Science and Pollution Research 25 (2018) 30938-30948.
14
Hamadi N.K., Chen X. D., Farid M.M., Lu M.G., Adsorption kinetics for the removal of chromium (VI) from aqueous solution by adsorbents derived from used tyres and sawdust, Chemical Engineering Journal 84 (2001) 95-105.
15
Huang, Y.-D., Gao, X.-D., Gu, Z.-Y., & Li, X.-M., Amino-terminated SiO2 aerogel towards highly-effective lead (II) adsorbent via the ambient drying process, Journal of Non-Crystalline Solids 443 (2016) 39-46.
16
Karnib M., Kabbani A., Holail H., Olama Z., Heavy metals removal using activated carbon, silica and silica activated carbon composite, Energy Procedia 50 (2014) 113-120.
17
Khanahmadzadeh S., Khorshidi N., Rabbani M., Khezri B., Removal of phenol in aqueous solutions by silica aerogel-activated carbon nano composite, Journal of Applied Environmental and Biological Sciences 2 (2012) 281-286.
18
Mohammadi A., and Moghaddas J., Synthesis, adsorption and regeneration of nanoporous silica aerogel and silica aerogel-activated carbon composites, Chemical Engineering Research and Design 94 (2015) 475-484.
19
Naghizadeh A., Comparison between activated carbon and multiwall carbon nanotubes in the removal of cadmium (II) and chromium (VI) from water solutions, Journal of Water Supply: Research and Technology-Aqua 64 (2015) 64-73.
20
Nah H.-Y., Parale V. G., Lee K.-Y., Choi H., Kim T., Lim C.-H., Park H.-H., Silylation of sodium silicate-based silica aerogel using trimethylethoxysilane as alternative surface modification agent, Journal of Sol-Gel Science and Technology 87 (2018) 319-330.
21
Pouretedal H., and Kazemi M., Characterization of modified silica aerogel using sodium silicate precursor and its application as adsorbent of Cu2+, Cd2+, and Pb2+ ions, International Journal of Industrial Chemistry 3 (2012) 3-20.
22
Roque-Malherbe R.M., Adsorption and diffusion in nanoporous materials: CRC press, Taylor & Francis Group; (2018).
23
Soleimani Dorcheh A., and Abbasi M.H., Silica aerogel; synthesis, properties and characterization, Journal of Materials Processing Technology 199 (2008) 10-26.
24
Štandeker S., Veronovski A., Novak Z., Knez Ž., Silica aerogels modified with mercapto functional groups used for Cu (II) and Hg (II) removal from aqueous solutions, Desalination 269 (2011) 223-230.
25
Wu J., and Yu H.-Q., Biosorption of 2, 4-dichlorophenol by immobilized white-rot fungus Phanerochaete chrysosporium from aqueous solutions, Bioresource Technology 98 (2007) 253-259.
26
Yang C.h., Statistical mechanical study on the Freundlich isotherm equation, Journal of Colloid and Interface Science 208 (1998) 379-387.
27
ORIGINAL_ARTICLE
Oily wastewater treatment using modified microfiltration membrane
new polyethersulfone (PES) microfiltration (MF) membrane was fabricated via phase inversion method using a melamine-modified zirconium-based metal-organic framework (MOF). The wettability and permeability of the membrane were measured using water contact angle and pure water flux (PWF), respectively. By introducing the MOF additive (0.1 wt. %) to the membrane matrix, the performance of the membrane in the separation of the oil-water mixture (different oil concentrations of 300 and 500 mg/L) was enhanced. The flux recovery ratio (FRR) of the modified membrane was significantly increased to 90.76 % compared to that in the bare membrane (20.41 %). Furthermore, the antifouling property was considerably improved.
https://arww.razi.ac.ir/article_1603_60fc10e7cd45fc0d5b2d8c8ddf3b2310.pdf
2020-06-30
97
101
10.22126/arww.2020.1603
Oily wastewater
Membrane
Microfiltration
MOF
Mahya
Samari
sirus.zeinaddini1@gmail.com
1
Environmental Research Center (ERC), Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran.
AUTHOR
Sirus
Zinadini
sirus.zeinaddini@gmail.com
2
Environmental Research Center (ERC), Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran.
LEAD_AUTHOR
Ali Akbar
Zinatizadeh
zinatizadeh@gmail.com
3
Environmental Research Center (ERC), Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran.
AUTHOR
Mohammad
Jafarzadeh
sirus.zeinaddini2@gmail.com
4
Department of Organic Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran.
AUTHOR
Foad
Gholami
sirus.zeinaddini3@gmail.com
5
Environmental Research Center (ERC), Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran.
AUTHOR
Chu Z., Feng Y., Seeger S., Oil/water separation with selective superantiwetting/superwetting surface materials, Angewandte Chemie International Edition 54 (2015) 2328-2338.
1
Dechnik J., Gascon J., Doonan C.J., Janiak C., Sumby C.J., Mixed‐matrix membranes, Angewandte Chemie International Edition 56 (2017) 9292-9310.
2
Denny Jr M.S., Moreton J.C., Benz L., Cohen S.M., Metal–organic frameworks for membrane-based separations, Nature Reviews Material 1 (2016) 16078.
3
Dietzel P.D., Besikiotis V., Blom R., Application of metal–organic frameworks with coordinatively unsaturated metal sites in storage and separation of methane and carbon dioxide, Journal of Materials Chemistry 19 (2009) 7362-7370.
4
Furukawa H., Cordova K.E., O’Keeffe M., Yaghi O.M., The chemistry and applications of metal-organic frameworks, Science 341 (2013) 1-12.
5
Kleindienst S., Paul J.H., Joye S.B., Using dispersants after oil spills: impacts on the composition and activity of microbial communities, Nature Reviews Microbiology 13 (2015) 388.
6
Kumar P., Bansal V., Kim K.H., Kwon E.E., Metal-organic frameworks (MOFs) as futuristic options for wastewater treatment, Journal of Industrial and Engineering Chemistry 62 (2018) 130-145.
7
Lahann J., Environmental nanotechnology: Nanomaterials clean up, Nature Nanotechnology 3 (2008) 320.
8
Lee W., Goh P., Lau W., Ong C., Ismail A., Antifouling zwitterion embedded forward osmosis thin film composite membrane for highly concentrated oily wastewater treatment, Separation and Purification Technology 214 (2019) 40-50.
9
Ma Q., Cheng H., Fane A.G., Wang R., Zhang H., Recent development of advanced materials with special wettability for selective oil/water separation, Small 12 (2016) 2186-2202.
10
Maroofi S.M., Mahmoodi N.M., Zeolitic imidazolate framework-polyvinylpyrrolidone-polyethersulfone composites membranes: From synthesis to the detailed pollutant removal from wastewater using cross flow system, Colloids and Surfaces A: Physicochemical and Engineering Aspects 572 (2019) 211-220.
11
Miao R., Wang L., Zhu M., Deng D., Li S., Wang J., Lv Y., Effect of hydration forces on protein fouling of ultrafiltration membranes: the role of protein charge, hydrated ion species, and membrane hydrophilicity, Environmental Science & Technology 51 (2016) 167-174.
12
Ren Y., Li T., Zhang W., Wang S., Shi M., Shan C., Hua M., MIL-PVDF blend ultrafiltration membranes with ultrahigh MOF loading for simultaneous adsorption and catalytic oxidation of methylene blue, Journal of Hazardous Materials 365 (2019) 312-321.
13
Rice E.W., Baird R.B., Eaton A.D., Clesceri L.S., Standard methods for the examination of water and wastewater (Vol. 10): American Public Health Association Washington, DC (2012).
14
Rowsell J.L., and Yaghi O.M., Metal–organic frameworks: a new class of porous materials, Microporous and Mesoporous Materials 73 (2004) 3-14.
15
Sadeghi S., Jafarzadeh M., Abbasi A.R., Daasbjerg K., Incorporation of CuO NPs into modified UiO-66-NH2 metal–organic frameworks (MOFs) with melamine for catalytic C–O coupling in the Ullmann condensation, New Journal of Chemistry 41 (2017) 12014-12027.
16
Schrope M., Oil spill: Deep wounds, Nature News 472 (2011) 152-154.
17
Shi Y., Huang J., Zeng G., Cheng W., Hu J., Shi, L., Yi K., Evaluation of self-cleaning performance of the modified g-C3N4 and GO based PVDF membrane toward oil-in-water separation under visible-light, Chemosphere 230 (2019) 40-50.
18
Wang W., Zhu L., Shan B., Xie C., Liu C., Cui F., Li G., Preparation and characterization of SLS-CNT/PES ultrafiltration membrane with antifouling and antibacterial properties, Journal of Membrane Science 548 (2018) 459-469.
19
Wang Y.X., Li, Y.J., Yang H., Xu Z.L., Super-wetting, photoactive TiO2 coating on amino-silane modified PAN nanofiber membranes for high efficient oil-water emulsion separation application, Journal of Membrane Science 580 (2019) 40-48.
20
Wang Y., Wang B., Wang Q., Di J., Miao S., Yu J., Amino-functionalized porous nanofibrous membranes for simultaneous removal of oil and heavy-metal ions from wastewater, ACS Applied Materials & interfaces 11 (2018) 1672-1679.
21
Zhu Y., Wang D., Jiang L., Jin J., Recent progress in developing advanced membranes for emulsified oil/water separation, NPG Asia Materials 6 (2014) 1-11.
22