A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater

Turkdogan-Aydınol, F. Ilter; Yetilmezsoy, Kaan

doi:10.1016/j.jhazmat.2010.06.054

Cited by 130 publications

(85 citation statements)

References 70 publications

(122 reference statements)

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“…The measured data collected from Khaldiya residential area were arbitrarily classified into different fuzzy set categories with respective minimum and maximum values of model variables. Then, different scalar ranges of both triangular and trapezoidal membership functions were tested until the satisfactory outputs were obtained with respect to the set of rules used in the FIS, as similarly conducted in previous studies (Mitra et al, 1998;Turkdogan-Aydinol and Yetilmezsoy, 2010;Yetilmezsoy et al, 2012;Yetilmezsoy, 2012). Results of the preliminary analysis indicated that trapezoidal shaped membership functions with ten levels for the input variables and fifteen levels for the output variable demonstrated the optimum prediction performance in estimation of PM levels at the studied area.…”

Section: Selection Of Membership Functionsmentioning

confidence: 90%

“…For comparative purpose, the measured data were evaluated by a multiple regression software package (DataFit® V8.1.69, Copyright© 1995, Oakdale Engineering, PA, RC167), containing 298 two-dimensional (2D) and 242 three-dimensional (3D) non-linear regression models. The regression analysis was performed based on the Levenberg-Marquardt method with double precision, as similarly done in several studies of the first author (Yetilmezsoy, 2007;Yetilmezsoy and Saral, 2007;Yetilmezsoy and Sapci-Zengin, 2009;Yetilmezsoy and Sakar, 2008;Turkdogan-Aydinol and Yetilmezsoy, 2010;Yetilmezsoy, 2011;Yetilmezsoy, 2012).…”

Section: Multiple Regression-based Modelmentioning

confidence: 99%

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A Prognostic Approach Based on Fuzzy-Logic Methodology to Forecast PM10 Levels in Khaldiya Residential Area, Kuwait

Yetilmezsoy

Abdul‐Wahab

2012

Aerosol Air Qual. Res.

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A prognostic approach is proposed based on a fuzzy-logic model to estimate suspended dust concentrations, related to PM 10 , in a specific residential area in Kuwait with high traffic and industrial influences. Seven input variables, including four important meteorological parameters (wind speed, wind direction, relative humidity and solar radiation) and the ambient concentrations of three gaseous pollutants (methane, carbon monoxide and ozone) were fuzzified using a sytem with a graphical user interface (GUI) and an artificial intelligence-based approach. Trapezoidal membership functions with ten and fifteen levels were employed for the fuzzy subsets of each model variable. A Mamdani-type fuzzy inference system (FIS) was developed to introduce a total of 146 rules in the IF-THEN format. The product (prod) and the centre of gravity (centroid) methods were performed as the inference operator and defuzzification methods, respectively, for the proposed FIS. The results obtained using uzzy-logic were compared with the outputs of an exponential regression model. The predictive performances of the models were compared based on various descriptive statistical indicators, and the proposed method was tested against additional observed data. The prognostic model presented in this work produced very small deviations from the actual results, and showed better predictive performance than the other model with regard to forecasting PM 10 levels, with a very high determination coefficient of over 0.99.

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Section: Selection Of Membership Functionsmentioning

confidence: 90%

Section: Multiple Regression-based Modelmentioning

confidence: 99%

A Prognostic Approach Based on Fuzzy-Logic Methodology to Forecast PM10 Levels in Khaldiya Residential Area, Kuwait

Yetilmezsoy

Abdul‐Wahab

2012

Aerosol Air Qual. Res.

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“…The efficiency of UASB reactors is regulated by a large number of factors including wastewater characteristics, acclimatization of seed sludge, pH, nutrients, presence of toxic compounds, loading rate, upflow velocity ( up ), hydraulic retention time (HRT), liquid mixing, and reactor design that affect the growth of sludge bed [16,[67][68][69].…”

Section: Effect Of Different Parameters On the Efficiency Of Uasb Reamentioning

confidence: 99%

Review of Upflow Anaerobic Sludge Blanket Reactor Technology: Effect of Different Parameters and Developments for Domestic Wastewater Treatment

Daud

Rizvi

Akram

et al. 2018

Journal of Chemistry

103

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The upflow anaerobic sludge blanket (UASB) reactor has been recognized as an important wastewater treatment technology among anaerobic treatment methods. The objective of this study was to perform literature review on the treatment of domestic sewage using the UASB reactor as the core component and identifying future areas of research. The merits of anaerobic and aerobic bioreactors are highlighted and other sewage treatment technologies are compared with UASB on the basis of performance, resource recovery potential, and cost. The comparison supports UASB as a suitable option on the basis of performance, green energy generation, minimal space requirement, and low capital, operation, and maintenance costs. The main process parameters such as temperature, hydraulic retention time (HRT), organic loading rate (OLR), pH, granulation, and mixing and their effects on the performance of UASB reactor and hydrogen production are presented for achieving optimal results. Feasible posttreatment steps are also identified for effective discharge and/or reuse of treated water.

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“…The general form of the models used in this study is expressed as Eq.1 [26][27][28][29][30]. The output variable y, written as a function of k, has input variables (x 1 , x 2 , …, x k ) and a random error term ε that is In this study, the evaluation, feasibility and efficiency of biogas production from anaerobic digestion of PSPW within an upflow anaerobic sludge blanket (UASB) reactor was conducted.…”

Section: Model Descriptionmentioning

confidence: 99%

Modelling Biogas Fermentation from Anaerobic Digestion: Potato Starch Processing Wastewater Treated Within an Up flow Anaerobic Sludge Blanket

Antwi¹,

Li²,

Shi³

et al. 2017

J Bioremediat Biodegrad

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IntroductionPotato is one of the most valuable food crop grown in many countries [1]. It has been reported that, a considerable proportion of the potato cultivated globally consumed through starch processing which subsequently generates tons of wastewater that goes to pollute water bodies [1][2][3]. Wastewater of raw potato processed into starch are classified as complex wastewater [4,5], and its concentration of chemical oxygen demand (COD), total suspended solid (TSS) and volatile suspended solid of (VSS) can yield concentrations of 50000, 9700 and 9500 mg/L, respectively [6]. Arhoun et al. argued that recovering valuable resource such as bioenergy (biogas) from such wastewater to supplement energy needs will be beneficial to humans and society at large [6,7]. Anaerobic digestion has severally been reported as a successful bioprocess treating various organic wastewaters and subsequently generating biogas [7][8][9][10][11][12]. However, the biological mechanism of anaerobic digestion is not well understood due to the complexity of the bacterial community structure and bioconversion [13]. Hu et al. asserted that process modeling is a good tool for predicting and describing the performance of biological processes [13]. Other reports also confirmed that process modeling based on previously acquired data is one technical route to enhancing the performance of anaerobic processes. These process models are often developed [14,15]. Nonetheless, modeling of anaerobic digestion is quite challenging and tough because performance of anaerobic systems is complex and varies considerably with influent characteristics and operational conditions [16].Some predictive models have been developed in the past decades for biogas estimation during anaerobic treatment processes. For instance, a regression analysis model for estimating biogas generated in a landfill leachate treatment process was developed by Akaya et al. AbstractHerein, a modeling approach to predict biogas yield within a mesophilic (35 ± 1°C) upflow anaerobic sludge blanket (UASB) reactor treating potato starch processing wastewater (PSPW) for pollutant removal was conducted. HRTs and seven anaerobic process-related parameters viz; chemical oxygen demand (COD), ammonium (NH 4 + ), alkalinity, total Kjeldahl Nitrogen, total phosphorus, volatile fatty acids (VFAs) and pH with average concentration of 4028.91, 110.09, 4944.67, 510.47, 45.20, 534.44 mg/L and 7.09, respectively, were used as input variables (x) to develop stochastic models for predicting biogas yield from the anaerobic digestion of PSPW. Based on the prediction accuracy of the models, it was established that, prediction of biogas yield from the UASB with the combination of COD, NH 4 + and HRT, or COD, NH 4 + , HRT and VFAs as input variables proved more efficient as opposed to HRT, alkalinity, total Kjeldahl Nitrogen, total phosphorus and pH. Highest coefficient of determination (R 2 ) observed was 97.29%, suggesting the efficiency of the models in making predictions. The developed models efficiencies co...

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A fuzzy-logic-based model to predict biogas and methane production rates in a pilot-scale mesophilic UASB reactor treating molasses wastewater

Cited by 130 publications

References 70 publications

A Prognostic Approach Based on Fuzzy-Logic Methodology to Forecast PM10 Levels in Khaldiya Residential Area, Kuwait

A Prognostic Approach Based on Fuzzy-Logic Methodology to Forecast PM10 Levels in Khaldiya Residential Area, Kuwait

Review of Upflow Anaerobic Sludge Blanket Reactor Technology: Effect of Different Parameters and Developments for Domestic Wastewater Treatment

Modelling Biogas Fermentation from Anaerobic Digestion: Potato Starch Processing Wastewater Treated Within an Up flow Anaerobic Sludge Blanket

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