PMID- 30758301
OWN - NLM
STAT- MEDLINE
DCOM- 20190523
LR  - 20201215
IS  - 1477-8920 (Print)
IS  - 1477-8920 (Linking)
VI  - 17
IP  - 1
DP  - 2019 Feb
TI  - Modification of the Thomas model for predicting unsymmetrical breakthrough curves 
      using an adaptive neural-based fuzzy inference system.
PG  - 25-36
LID - 10.2166/wh.2019.210 [doi]
AB  - The Thomas equation is a popular model that has been widely used to predict 
      breakthrough curves (BTCs) when describing the dynamic adsorption of different 
      pollutants in a fixed-bed column system. However, BTCs commonly exhibit 
      unsymmetrical patterns that cannot be predicted using empirical equations such as 
      the Thomas model. Fortunately, adaptive neural-based fuzzy inference systems 
      (ANFISs) can be used to model complex patterns found in adsorption processes in a 
      fixed-bed column system. Consequently, a new hybrid model merging Thomas and an 
      ANFIS was introduced to estimate the performance of BTCs, which were obtained for 
      Cd(II) ion adsorption on ostrich bone ash-supported nanoscale zero-valent iron 
      (nZVI). The results obtained showed that the fair performance of the Thomas model 
      (NRMSE = 27.6% and E(f) = 64.6%) improved to excellent (NRMSE = 3.8% and E(f) = 
      93.8%) due to the unique strength of ANFISs in nonlinear modeling. The 
      sensitivity analysis indicated that the initial solution pH was a more 
      significant input variable influencing the hybrid model than the other 
      operational factors. This approach proves the potential of this hybrid method to 
      predict BTCs for the dynamic adsorption of Cd(II) ions by ostrich bone 
      ash-supported nZVI particles.
FAU - Amiri, Mohammad Javad
AU  - Amiri MJ
AD  - Department of Water Engineering, College of Agriculture, Fasa University, 
      74617-81189 Fasa, Iran E-mail: mj_amiri@fasau.ac.ir.
FAU - Khozaei, Maryam
AU  - Khozaei M
AD  - Department of Water Engineering, College of Agriculture, Shiraz University, 
      Shiraz 71365, Iran.
FAU - Gil, Antonio
AU  - Gil A
AD  - Department of Sciences, Public University of Navarra, Campus of Arrosadia, 31006 
      Pamplona, Spain.
LA  - eng
PT  - Journal Article
PL  - England
TA  - J Water Health
JT  - Journal of water and health
JID - 101185420
RN  - 0 (Ions)
RN  - 0 (Water Pollutants, Chemical)
RN  - E1UOL152H7 (Iron)
SB  - IM
MH  - Adsorption
MH  - Fuzzy Logic
MH  - Ions
MH  - Iron
MH  - *Models, Chemical
MH  - Water Pollutants, Chemical/*analysis
EDAT- 2019/02/14 06:00
MHDA- 2019/05/24 06:00
CRDT- 2019/02/14 06:00
PHST- 2019/02/14 06:00 [entrez]
PHST- 2019/02/14 06:00 [pubmed]
PHST- 2019/05/24 06:00 [medline]
AID - 10.2166/wh.2019.210 [doi]
PST - ppublish
SO  - J Water Health. 2019 Feb;17(1):25-36. doi: 10.2166/wh.2019.210.