Performance, evaluation, and modelling of an integrated petroleum refinery wastewater treatment system using multi-layer perceptron neural networks

Mokhtari, Habib A.; Mirbagheri, Seyed Ahmad; Dehkordi, Nazli Rafei

doi:10.5004/dwt.2021.26616

Cited by 9 publications

(4 citation statements)

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“…NNs discover the relation between empirical data and their hidden rule by processing them and transferring their learning to the network. Each NN consists of several nodes called neurons, and the connection weights, which connect the nods 48–52 …”

Section: Methodsmentioning

confidence: 99%

“…Each NN consists of several nodes called neurons, and the connection weights, which connect the nods. [48][49][50][51][52] Input data are multiplied by their corresponding weights, and their sum has entered the neurons. Each neuron has a transmission function from which the input value passes and the neuron's output are determined.…”

Section: Modeling Artificial Neural Networkmentioning

confidence: 99%

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Optimization of an artificial neural network topology using response surface methodology for microbial fuel cell power prediction

Malekmohammadi

Mirbagheri

2022

Biotechnology Progress

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Microbial fuel cells (MFCs) are among the newest bioelectrical devices that have attracted significant attention because they convert biodegradable organic matter to electricity. MFC design can be improved by understanding and predicting the performance of MFC under different conditions and substrate concentrations. However, few mathematical models have been investigated due to problems caused by the high sensitivity of MFC systems. In this research, a multilayer neural network (NN) was used to predict the generated power of a cell with three inputs (concentration, time, and resistance). Response surface methodology with factors including the number of first layer neurons, number of second layer neurons, training epochs, validation check, and training percentage was used to obtain the optimum structure of the network, and mean squared error (MSE). NN had the minimum MSE when the Number of neurons in the first and second hidden layers, the training epochs, validation check, training percentage were 28, 20, 1000, 100, and 70, respectively. This builtnetwork had an excellent ability to predict, and R 2 was 98%. According to the results, increasing COD concentration increases generated power and system utilization time. In addition, reducing the external resistance up to 100 Ω can lead to more power obtained.

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Section: Methodsmentioning

confidence: 99%

Section: Modeling Artificial Neural Networkmentioning

confidence: 99%

Optimization of an artificial neural network topology using response surface methodology for microbial fuel cell power prediction

Malekmohammadi

Mirbagheri

2022

Biotechnology Progress

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“…This integrated process might be a good option for the treatment of PRWW with high ammonia concentrations. On the other hand, Mokhtari et al [208] have also reported the application of an innovative method of a biological process coupled with a sand filter column for the treatment of Iranian PRWW as a hybrid process. It is a simple integrated process where the sand filter column is used in the last part of the treatment process.…”

Section: Integrated Treatment Processes (Itp)mentioning

confidence: 99%

Recent Advancements in the Treatment of Petroleum Refinery Wastewater

Lawan,

Kumar,

Rashid

et al. 2023

Water

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The treatment of petroleum refinery wastewater (PRWW) is of great interest in industrial wastewater management. This wastewater contains a diverse concentration of contaminants such as oil and grease, petroleum hydrocarbons, phenols, ammonia, and sulfides, as well as other organic and inorganic composites. Refinery wastewater treatment has been attempted through various processes, including physical, biological, chemical, and hybrid methods, which combine two or more techniques. This review aims to summarize current research studies involved in the treatment of petroleum refinery wastewater using conventional, advanced, and integrated treatment techniques. Furthermore, it critically highlights the efficiencies and major limitations of each technique and the prospects for improvements. Several conventional treatment techniques (basically, the physicochemical and biological processes) are discussed. In this context, advanced oxidation processes (AoPs), especially electrochemical oxidation and photocatalysis, as well as integrated/hybrid processes are found to be effective in removing the recalcitrant fraction of organic pollutants through their various inherent mechanisms. These techniques could effectively remove COD and phenol concentrations with an average removal efficiency exceeding 90%. Hence, the review also presents an elaborate discussion of the photocatalytic process as one of the advanced techniques and highlights some basic concepts to optimize the degradation efficiency of photocatalysts. Finally, a brief recommendation for research prospects is also presented.

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“…The use of the ozonation process also enhanced the permeate flux of the membrane by up to 96% and improved pollutant removal efficiency by up to 77%. Mokhtari, et al (2021) have also reported the application of an innovative method of biological process coupled with a sand filter column for the treatment of Iranian petroleum refinery wastewater as a hybrid process. It is a simple integrated process where the sand filter column was used in the last part of the treatment process.…”

Section: Integrated Treatment Processes (Itp)mentioning

confidence: 99%

Recent Advancement in the Treatment of Petroleum Refinery Wastewater

Lawan,

Kumar,

Rashid

et al. 2023

Preprint

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The treatment of petroleum refinery wastewater (PRWW) is of great interest in the field of industrial wastewater management. The wastewater contains a diverse concentration of contaminants such as oil and grease, petroleum hydrocarbons, phenol, ammonia, sulfides, as well as other organic and inorganic composites etc. The treatment of refinery wastewater has been treated through various processes including; physical, biological, chemical or hybrid methods which combine two or more techniques. Hence, the objective of this review is to summarize the recent research studies applied in the treatment of petroleum refinery wastewater using conventional, advanced as well as integrated treatment techniques. Furthermore, critically highlight the efficiencies and major limitations of each technique as well as prospects for improvement. Several conventional treatment techniques (basically, the physicochemical and biological processes) were discussed. In this context, advanced oxidation processes (AoPs) especially electrochemical oxidation and photocatalysis as well as the integrated/hybrid processes are found effective to remove the recalcitrant fraction of organic pollutants because of their various inherent mechanisms. These techniques could effectively remove COD and phenols concentration with an average removal efficiency exceeding 90%. Hence, the review also presented an elaborate discussion of the photocatalytic process as one of the advanced techniques and highlighted some basic concepts to optimize the degradation efficiency of a photocatalyst. Finally, a brief recommendation for research prospects is also presented.

show abstract

Performance, evaluation, and modelling of an integrated petroleum refinery wastewater treatment system using multi-layer perceptron neural networks

Cited by 9 publications

References 0 publications

Optimization of an artificial neural network topology using response surface methodology for microbial fuel cell power prediction

Optimization of an artificial neural network topology using response surface methodology for microbial fuel cell power prediction

Recent Advancements in the Treatment of Petroleum Refinery Wastewater

Recent Advancement in the Treatment of Petroleum Refinery Wastewater

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