Membranes for industrial microfiltration and ultrafiltration

Cassano, Alfredo; Basile, Angelo

doi:10.1533/9780857093790.5.647

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…In the palm oil industry, the membrane bioreactor system is one of the widely used wastewater treatment technologies for palm oil mill effluent (POME). Membrane technology is preferable due to its simple operation, lesser weight, fewer space requirements, and high efficiency [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Improved Artificial Neural Network Training Based on Response Surface Methodology for Membrane Flux Prediction

Ibrahim

Wahab

2022

Membranes

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This paper presents an improved artificial neural network (ANN) training using response surface methodology (RSM) optimization for membrane flux prediction. The improved ANN utilizes the design of experiment (DoE) technique to determine the neural network parameters. The technique has the advantage of training performance, with a reduced training time and number of repetitions in achieving good model prediction for the permeate flux of palm oil mill effluent. The conventional training process is performed by the trial-and-error method, which is time consuming. In this work, Levenberg–Marquardt (lm) and gradient descent with momentum (gdm) training functions are used, the feed-forward neural network (FFNN) structure is applied to predict the permeate flux, and airflow and transmembrane pressure are the input variables. The network parameters include the number of neurons, the learning rate, the momentum, the epoch, and the training functions. To realize the effectiveness of the DoE strategy, central composite design is incorporated into neural network methodology to achieve both good model accuracy and improved training performance. The simulation results show an improvement of more than 50% of training performance, with less repetition of the training process for the RSM-based FFNN (FFNN-RSM) compared with the conventional-based FFNN (FFNN-lm and FFNN-gdm). In addition, a good accuracy of the models is achieved, with a smaller generalization error.

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Section: Introductionmentioning

confidence: 99%

Improved Artificial Neural Network Training Based on Response Surface Methodology for Membrane Flux Prediction

Ibrahim

Wahab

2022

Membranes

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“…HF polymer membranes are most often prepared from natural and synthetic polymers by the solution method using the phase inversion process [1]. The main advantage of HF membranes is the higher packing density of the membrane in the module (from 3000 to 20,000 m 2 /m 3 ) compared to flat or tubular membranes [2][3][4], which significantly reduces the size of the separation devices. Phase inversion is a phase separation process where a polymer is transferred from a solution or melted state to a solid state in a controlled manner.…”

Section: Introductionmentioning

confidence: 99%

Express Method of Preparation of Hollow Fiber Membrane Samples for Spinning Solution Optimization: Polysulfone as Example

et al. 2021

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This article describes a new technique for the preparation of hollow fiber (HF) membrane samples using an automatic manipulator unit. The manipulator uses a syringe needle to form a HF of a given geometry. The needle in automatic mode is sequentially immersed, first into the polymer solution and then into the coagulation bath. The possibility of using a manipulator to obtain HF samples was studied on the known polysulfone (PSf)/N-methylpyrrolidone (NMP)/pore-forming additive system. A series of HF membrane samples were made within 29 h from twelve 1 mL PSf casting solutions. This was 15 times faster than obtaining samples of HF membranes at the multifunctional research laboratory facility. From the point of view of the consumption of the components of the casting solution, the use of the manipulator was 30 times more economical, and the consumption of water for precipitation and washing was 8000 times less. The developed method made it possible to study samples of HF by scanning electron microscopy (SEM), ultrafiltration, and evaluate its mechanical properties without spinning the membranes. Using the new technique, the optimal composition of the casting solution for the wet spinning of HF PSf membranes was selected during two weeks. Thus, the manipulator makes it possible to significantly reduce the time of the new membrane preparation, reduce the volume of used polymer, and thus makes it promising to study expensive or new membrane materials.

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“…UF can effectively remove pathogenic microorganisms and pathogenic viruses such as Giardia and bacteria in water (Laîné et al, 2000). UF has been widely used in pharmaceutical applications, biotechnology, and sugar refining (Cassano and Basile, 2011) and in the fields of water treatment, such as drinking water production (Chang et al, 2017;Wu et al, 2016) seawater desalination (Anis et al, 2019;Badruzzaman et al, 2019;Voutchkov, 2010;Jamaly et al, 2014), and water reuse (Warsinger et al, 2018). In our knowledge, UF pilot plant was used by Cordier et al for the first time in hatchery for oyster production.…”

Section: Introductionmentioning

confidence: 99%

Ultrafiltration to secure shellfish industrial activities: Culture of microalgae and oyster fertilization

Eljaddi

Ragueneau²,

Clémence

et al. 2021

Aquacultural Engineering

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Membranes for industrial microfiltration and ultrafiltration

Cited by 12 publications

References 28 publications

Improved Artificial Neural Network Training Based on Response Surface Methodology for Membrane Flux Prediction

Improved Artificial Neural Network Training Based on Response Surface Methodology for Membrane Flux Prediction

Express Method of Preparation of Hollow Fiber Membrane Samples for Spinning Solution Optimization: Polysulfone as Example

Ultrafiltration to secure shellfish industrial activities: Culture of microalgae and oyster fertilization

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