A Review of Modeling Bioelectrochemical Systems: Engineering and Statistical Aspects

Abstract

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.

Resource recovery from low strength wastewater in a bioelectrochemical desalination process

“…CCD is one of the modules in RSM to obtain the points of each factor according to their levels [39]. RSM is instrumental in modeling, designing experiments, and establishing the relationship between several independent variables (factors) and the dependent variable [32,45]. RSM helps in predicting the best performance conditions for desirable responses while reducing the number of experimental trials required to evaluate the interaction between multiple factors.…”

“…It is also important to note that though experiments can satisfactorily determine the influence of various factors on the performance characteristics of a bioelectrochemcial system, limitations on the factors of cost and time required to perform the experiments are inevitable. To overcome this limitation, several studies focused on developing mathematical models for estimating the performance of microbial fuel cells and other membrane fuel cells [25][26][27][28][29][30][31][32][33].…”

Computational investigation of the flow field contribution to improve electricity generation in granular activated carbon-assisted microbial fuel cells

“…Comparing to other MFC models that usually integrate conventional Monod and Butler-Volmer equations [13], the multi-order Butler-Volmer equation is expected to provide a simple but realistic simulation. It is assumed that the addition of GAC can provide enough surface area for microbial adhesion and also change the flow pattern of the substrate and microbes within the bulk liquid.…”

Mathematical modeling based evaluation and simulation of boron removal in bioelectrochemical systems

“…Owing to the multiple processes of microbiology, chemistry and electrochemistry, the parameters in BES are dynamically linked (Luo et al, 2016), and most BES models that focused on the fate of solute did not deal with non-dissociable compounds (Harnisch et al, 2009;Picioreanu et al, 2010;Ping et al, 2015b). Therefore, it is essential to develop BES models for evaluation of the boron removal process and prediction of the performance affected by operational factors.…”