Assessment of groundwater corrosivity in Hamedan Province, Iran using an adaptive neuro-fuzzy inference system (ANFIS)

다국어 초록 (Multilingual Abstract)

The Langelier Saturation Index (LSI) and Puckorius Scaling Index (PSI) were used to study the incrustation/corrosion potential of groundwaters in Hamedan Province, Iran. The LSI and PSI indices correlated strongly with total dissolved solids (TDS) (mgL^(–1)), pH and HCO^-_3(mmolL^(–1)) as revealed by determination coefficients of 0.90 and 0.99 for LSI and PSI, respectively. Subsequently, a trained adaptive neuro-fuzzy inference system (ANFIS) was deployed to predict the corrosion behavior of water in unsampled or partially sampled locations using available total dissolved solids (TDS), pH and HCO^-_3 as input data. Excellent agreement between the ANFIS simulations and the indices determined using conventional LSI and PSI techniques confirms that modeling using the ANFIS approach will allow water corrosion potential to be determined reliably and inexpensively using only TDS, pH, and HCO^-_3 data.

참고문헌 (Reference)

1 Rabbani, D., "Study for determination of industrial water corrosivity in KashsnFajre Sepahan galvanizing mills during 2005-2006 Iran" 11 : 131-134, 2008

2 Agatemor, C., "Studies of corrosion tendency ofdrinking water in the distribution system at the University ofBenin" 28 : 379-384, 2008

3 Eaton, A.D., "Standard methods for the examination ofwater and wastewater" ADHA, AWWA, and WPCF, WashingtonDC 1368-, 2005

4 Log, T., "Scale and corrosion control with combineddolomite/calcite filter" 46 : 41-47, 2004

5 Jalili, S., "Predictionof lead corrosion behavior using Feed-Forward artificialneural network" 5 : 669-676, 2008

6 Jianping, C.A.I., "Phenomenologicalmodeling of atmospheric corrosion using an artificial neuralnetwork" 41 : 2001-2030, 1999

7 Withers, A., "Options for recarbonation, remineralisation anddisinfection for desalination plants" 179 : 11-24, 2005

8 Cottis, R.A., "Neural network methods for corrosion datareduction" 20 : 169-178, 1999

9 Lloyd, J.W, "Natural inorganic chemistry inrelation to groundwater" Clarendon Press 296-, 1985

10 Denai, M.A., "Modeling and controlof non-linear systems using soft computing techniques" 7 : 728-738, 2007

11 Pakshir, M., "Limitations of corrosion and scaling indexes in industrialsystems" 51 : 60-66, 2004

12 Shahmansori, M, "Leaking of microelementdue to internal corrosion" 8 : 30-34, 2004

13 Schock, M.R., "Internal corrosion and deposition control" McGraw-Hill,New York 1-17, 1999

14 Change, L.-C., "Intelligent control for modelingof real-time reservoir operation" 15 : 1621-1634, 2001

15 Dietrich, A.M., "Health and aesthetic impacts of copper corrosionon drinking water" 49 : 55-62, 2004

16 Tsoukalas, L.H, "Fuzzy and neural approachesin engineering" Wiley-Interscience, New York 587-, 1997

17 Hajrasuliha, S., "Estimation ofchloride ion concentration in saline soils from measurement ofelectrical conductivity of saturated soil extracts" 49 : 117-127, 1991

18 Kim, D.H., "Development and implementation of a corrosion control algorithmbased on calcium carbonate precipitation potential (CCPP)in drinking water" 57 : 531-539, 2008

19 Trasatti, S.P, "Crevice corrosion, a neural networkapproach" 31 : 105-112, 1996

20 Silverman D.C, "Corrosion prediction frompolarization scans using an artifical neural network integratedwith an expert system" 47 : 734-745, 1992

21 Melidis, P., "Corrosion control by indirect method" 213 : 152-158, 2007

22 Roberge, P.R., "Corrosion Engineering: Principles and Practice" McGraw-Hill 754-, 2008

23 Zare Abyaneh, H., "Chloride estimation in groundwaterfrom electrical conductivity measurement" 11 : 110-114, 2005

24 Bassam, A., "Artificial neural network forthe evaluation of CO2 corrosion in a pipeline steel" 13 : 773-780, 2008

25 Guneri, A.F., "An approach basedon ANFIS input selection and modeling for supplier selectionproblem" 2011

26 Jang, J.-S.R., "ANFIS: adaptive-network-based fuzzy inferencesystem" 23 : 665-685, 1993