Development of a dynamic mathematical model for membrane bioelectrochemical reactors with different configurations

Li, Jian; He, Zhen

doi:10.1007/s11356-015-5611-3

Cited by 15 publications

(13 citation statements)

References 24 publications

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“…The model can predict the growth and loss of "cake" layer on the membrane reactor, to indicate the impact of biofouling on the system performance. The contribution of this model is to accurately model three MBERs with various configurations [80]. The versatility of the configuration application can cover many important properties in a MFC-MBR system, such as membrane fouling, nitrogen removal, cake formation and detaching based on various cross-flow rates through the membrane.…”

Section: Applications Of Ordinary Differential Equation Stereotypesmentioning

confidence: 99%

“…ODEs have advantages in terms of low computational load and relatively easy to be adjusted [19,73,80].…”

Section: Advantages and Limitationsmentioning

confidence: 99%

“…For example, biofouling formation and detachment strongly impacts electrochemical reaction on a cathode due to bacterial competition for oxygen [18,118]. To address this issue, the researchers adopted the increase rate of resistance in their model to describe the difficulty of water filtration through the membrane under biofouling [80,119]. Sensitivity analysis can also assist in parameter tuning for accelerated model construction.…”

Section: Sensitivity Analysis Of Model Parametersmentioning

confidence: 99%

“…Normally, RMSE below 20% is acceptable for the model validation, but acceptable level is difficult to be fixed due to variously actual cases [73,74,76,77,80,83]. For example, Yuan et al [77] constructed an engineering model to successfully predict the dynamic volume profile of feed and draw solution with RMSE smaller than 2.5%; although the RMSE for a MEC model was relatively high (13%-23.6%), the predicted output was still acceptable because the error came from overestimation of organics in the model, which was related to microbial degradation of organics in anode featured with relatively higher unstableness and delayed response of biological factors than other physical attributes.…”

Section: Model Validationmentioning

confidence: 99%

“…For example, Yuan et al [77] constructed an engineering model to successfully predict the dynamic volume profile of feed and draw solution with RMSE smaller than 2.5%; although the RMSE for a MEC model was relatively high (13%-23.6%), the predicted output was still acceptable because the error came from overestimation of organics in the model, which was related to microbial degradation of organics in anode featured with relatively higher unstableness and delayed response of biological factors than other physical attributes. There are also some cases with high RMSE or intrinsic limitations indicating that engineering models are not powerful enough to deal with specific outputs [49,63,76,80]. For example, a model was proposed to simulate the performance of a MBER with fluidized-bed system with granular activated carbon (GAC) as media [80].…”

Section: Model Validationmentioning

confidence: 99%

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A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects

et al. 2016

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Bioelectrochemical systems (BES) are promising technologies to convert organic compounds in wastewater to electrical energy through a series of complex physical-chemical, biological and electrochemical processes. Representative BES such as microbial fuel cells (MFCs) have been studied and advanced for energy recovery. Substantial experimental and modeling efforts have been made for investigating the processes involved in electricity generation toward the improvement of the BES performance for practical applications. However, there are many parameters that will potentially affect these processes, thereby making the optimization of system performance hard to be achieved. Mathematical models, including engineering models and statistical models, are powerful tools to help understand the interactions among the parameters in BES and perform optimization of BES configuration/operation. This review paper aims to introduce and discuss the recent developments of BES modeling from engineering and statistical aspects, including analysis on the model structure, description of application cases and sensitivity analysis of various parameters. It is expected to serves as a compass for integrating the engineering and statistical modeling strategies to improve model accuracy for BES development.

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Section: Applications Of Ordinary Differential Equation Stereotypesmentioning

confidence: 99%

“…ODEs have advantages in terms of low computational load and relatively easy to be adjusted [19,73,80].…”

Section: Advantages and Limitationsmentioning

confidence: 99%

Section: Sensitivity Analysis Of Model Parametersmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

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A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects

et al. 2016

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Reactors for Microbial Electrobiotechnology

Krieg

Madjarov

Rosa

et al. 2018

Bioelectrosynthesis

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From the first electromicrobial experiment to a sophisticated microbial electrochemical process - it all takes place in a reactor. Whereas the reactor design and materials used strongly influence the obtained results, there are no common platforms for MES reactors. This is a critical convention gap, as cross-comparison and benchmarking among MES as well as MES vs. conventional biotechnological processes is needed. Only knowledge driven engineering of MES reactors will pave the way to application and commercialization. In this chapter we first assess the requirements on reactors to be used for bioelectrochemical systems as well as potential losses caused by the reactor design. Subsequently, we compile the main types and designs of reactors used for MES so far, starting from simple H-cells to stirred tank reactors. We conclude with a discussion on the weaknesses and strengths of the existing types of reactors for bioelectrochemical systems that are scored on design criteria and draw conclusions for the future engineering of MES reactors.

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Manufacture and optimization of low-cost tubular ceramic supports for membrane filtration: application to algal solution concentration

Issaoui

Limousy

Lebeau

et al. 2017

Environ Sci Pollut Res

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Low-cost tubular macroporous supports for ceramic membranes were elaborated using the extrusion method, followed by curing, debinding, and sintering processes, from a powder mixture containing kaolin, starch, and sand. The obtained substrates were characterized using mercury intrusion porosimetry, water absorption test, water permeability, scanning electron microscopy, and three-point bending test to evaluate the effects of the additives on the relevant characteristics. According to experimental results, adding the starch ratio to the kaolin powder shows a notable impact on the membrane porosity and consequently on the water permeability of the tubular supports, whereas their mechanical strength decreased compared to those prepared from kaolin alone. It has been shown that the addition of an appropriate amount of starch to the ceramic paste leads to obtaining membrane supports with the desired porosity. Indeed, the water permeability increased significantly from 20 to 612 L h m bar for samples without and with 20 wt% of starch, respectively, as well as the open porosity, the apparent porosity, and the pore size distribution. The bending strength decreased slightly and reached about 4 MPa for samples with the highest starch amounts. On the other hand, the incorporation of sand in a mixture of kaolin + 10 wt% starch increased the mechanical strength and the water permeability. The samples containing 3 wt% of sand exhibited a bending strength four times higher than the supports without sand; the water permeability measured was about 221 L h m bar. These elaborated tubular supports for membrane are found to be suitable for solution concentration; they were applied for algal solution and are also easily cleaned by water.

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Development of a dynamic mathematical model for membrane bioelectrochemical reactors with different configurations

Cited by 15 publications

References 24 publications

A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects

A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects

Reactors for Microbial Electrobiotechnology

Manufacture and optimization of low-cost tubular ceramic supports for membrane filtration: application to algal solution concentration

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