Optimum design of n continuous stirred-tank bioreactors in series for fermentation processes based on simultaneous substrate and product inhibition

Optimization of the continuous fermentation process is important for increasing efficiency and decreasing cost, especially for complicated biochemical processes described by substrate and product inhibition. The optimum design (minimum volume) of CSTRs in series assuming substrate and product inhibition was determined in this study. The effect of operating parameters on the optimum design was investigated. The optimum substrate concentration in the feed to the first reactor was determined for N reactors in series. The nonlinear, constrained optimization problem was solved using the MATLAB function “fmincon”. It was found that the optimum design is more beneficial at high substrate conversion and at a medium level of feed substrate concentration. The best number of reactors is two to three for optimum arrangements and two for equal-size arrangements. The presence of biomass in the feed to the first reactor reduces the reactor volume, while the presence of product in the feed slightly increases the required total volume. The percentage reduction in the total volume using the optimum design compared to equal-volume design (R%) was determined as a function of substrate conversion and substrate concentration in the feed to the first reactor. The obtained R% values agree with experimental data available in the literature for ethanol fermentation

Acrylonitrile process enhancement through waste minimization: Effect of reaction conditions and degree of backmixing

Waste minimization in reactor design is an effective approach for pollution control, when compared to the traditional practice of the end-of-pipe treatment. Reactor degree of backmixing and operating conditions are important factors that determine the performance of chemical process, including environmental impact. For the purpose of waste minimization, two modeling methods were used for simulating the performance of the acrylonitrile production reactor, based on the ammoxidation of propylene. The effect of residence time, temperature, degree of backmixing on the steadystate propylene conversion, and production of waste were determined. The tanks-in-series model and the axial dispersion model were used to account for the degree of backmixing. The two main by-products in the acrylonitrile process are acetonitrile and hydrogen cyanide, which are both highly toxic waste. Extensive reactor backmixing reduces propylene conversion, especially at high temperature and residence time. Minimum acetonitrile production is favored by low residence time, high to moderate temperature, and no backmixing. Minimum hydrogen cyanide production is favored by low residence time, low temperature, and no backmixing. At 450 °C, the percentage of increase in the selectivity of acrylonitrile, with respect to hydrogen cyanide at plug-flow reactor conditions, as compared to a continuous stirred tank reactor, is 87.1, 74.3, 50.9, 30.4, and 12.4% at a residence time of 1, 2, 4, 6, and 8 s, respectively. The reactor degree of backmixing and operating conditions are important factors that affect the environmental friendliness of the acrylonitrile production process

Single-and multi-objective optimization of a dual-chamber microbial fuel cell operating in continuous-flow mode at steady state

Microbial fuel cells (MFCs) are a promising technology for bioenergy generation and wastewater treatment. Various parameters affect the performance of dual-chamber MFCs, such as substrate flow rate and concentration. Performance can be assessed by power density (PD), current density (CD) production, or substrate removal efficiency (SRE). In this study, a mathematical model-based optimization was used to optimize the performance of an MFC using single-and multi-objective optimization (MOO) methods. Matlab's fmincon and fminimax functions were used to solve the nonlinear constrained equations for the single-and multi-objective optimization, respectively. The fminimax method minimizes the worst-case of the two conflicting objective functions. The single-objective optimization revealed that the maximum PD, CD, and SRE were 2.04 W/m2, 11.08 A/m2, and 73.6%, respectively. The substrate concentration and flow rate significantly impacted the performance of the MFC. Pareto-optimal solutions were generated using the weighted sum method for maximizing the two conflicting objectives of PD and CD in addition to PD and SRE simultaneously. The fminimax method for maximizing PD and CD showed that the compromise solution was to operate the MFC at maximum PD conditions. The model-based optimization proved to be a fast and low-cost optimization method for MFCs and it provided a better understanding of the factors affecting an MFC's performance. The MOO provided Pareto-optimal solutions with multiple choices for practical applications depending on the purpose of using the MFCs

Applications of Matlab optimization capabilities in the design of N-continuous stirred tank bioreactors connected in series

The optimal design (variable volume) of continuous stirred tank reactors (CSTR's), in series, performing biological conversion of organic materials, was derived. The optimal design was based on the minimum overall reactor volume required for a certain degree of substrate conversion, and the number of reactors. In this study, it was assumed that cell growth kinetics follows the Contois model with endogenous decay. This unstructured kinetic model has been used by many researchers to describe biodegradation of organic materials, especially in the food industries and industrial wastewater treatment. The optimization problem was formulated as a nonlinear constrained mathematical programming problem, and solved using the Matlab function "fmincon". The effect of operating parameters such as; substrate concentration in the feed to the first reactor, substrate conversion, and number of CSTR's in series for the optimum design was investigated. Using the optimum design is beneficial only at high substrate conversion. The substrate concentration in the feed to the first reactor has little effect on the total required reactor volume. Up to 5 CSTRs in series were used in this study.qscienc

Bioelectrochemical production of hydrogen in an innovative pressure-retarded osmosis/microbial electrolysis cell system: experiments and modeling

Background While microbial electrolysis cells (MECs) can simultaneously produce bioelectrochemical hydrogen and treat wastewater, they consume considerable energy to overcome the unfavorable thermodynamics, which is not sustainable and economically feasible in practical applications. This study presents a proof-of-concept system in which hydrogen can be produced in an MEC powered by theoretically predicated energy from pressure-retarded osmosis (PRO). The system consists of a PRO unit that extracts high-quality water and generates electricity from water osmosis, and an MEC for organic removal and hydrogen production. The feasibility of the system was demonstrated using simulated PRO performance (in terms of energy production and effluent quality) and experimental MEC results (e.g., hydrogen production and organic removal). Results The PRO and MEC models were proven to be valid. The model predicted that the PRO unit could produce 485 mL of clean water and 579 J of energy with 600 mL of draw solution (0.8 M of NaCl). The amount of the predicated energy was applied to the MEC by a power supply, which drove the MEC to remove 93.7 % of the organic compounds and produce 32.8 mL of H2 experimentally. Increasing the PRO influent volume and draw concentration could produce more energy for the MEC operation, and correspondingly increase the MEC hydraulic retention time (HRT) and total hydrogen production. The models predicted that at an external voltage of 0.9 V, the MEC energy consumption reached the maximum PRO energy production. With a higher external voltage, the MEC energy consumption would exceed the PRO energy production, leading to negative effects on both organic removal and hydrogen production. Conclusions The PRO-MEC system holds great promise in addressing water-energy nexus through organic removal, hydrogen production, and water recovery: (1) the PRO unit can reduce the volume of wastewater and extract clean water; (2) the PRO effluents can be further treated by the MEC; and (3) the osmotic energy harvested from the PRO unit can be applied to the MEC for sustainable bioelectrochemical hydrogen production.NPRP grant # 6-289-2-125 from the Qatar National Research Fund (a member of Qatar Foundation)

Variance-based global sensitivity analysis of a multi-population, single-chamber microbial fuel cell operating in continuous flow mode at steady state

Microbial fuel cells (MFCs) are environmentally friendly devices which are used to convert chemical energy in organic wastes to electrical energy. MFCs have a strong non-linearity that requires a very sophisticated controlling system. Consequently, this makes optimization and performance study of MFCs a difficult process. For better estimation of the constants used for optimization of MFCs, global sensitivity analysis is performed. The global sensitivity method based on Sobol’s indices coupled with Monte Carlo simulations was applied on multi-population, single-chamber MFC operating in a continuous flow at steady state for the first time. In this paper, first-order and total-order sensitivity indices were used to visualize the impacts associated with six main parameters resulted from the maximization of power density using Matlab. Such parameters are maximum anodophilic-specific growth rate, half-rate constant of anodophilics, curve steepness factor, mediator half-rate constant, number of electrons transferred per mole mediator and decay rate constant of anodophilic bacteria. The results showed that the curve steepness factor has almost no impact on the power density of MFC. While all other studied, factors are sensitive parameters that impact the power density of MFC. It is worth mentioning that maximum anodophilic growth rate and the number of electrons transferred per mole of mediator are the most sensitive parameters that affecting the power density production having total indices of 0.74 and 0.624, respectively. While the half-rate constant of anodophilics, mediator half-rate constant and decay rate constant of anodophilics have almost similar impact by having total-order indices of 0.127, 0.144 and 0.192, respectively. The findings herein are critical in understanding and further model improvement of microbial fuel cells as the most impacting parameters on MFC power density can be optimized further to reduce uncertainty associated with the experimental parameters in the model

Enhancing organic contaminant degradation through integrating advanced oxidation processes with microbial electrochemical systems

Microbial electrochemical systems (MES) are studied to degrade organic contaminants with a lower energy demand, but degradation of recalcitrant compounds tends to be challenging. To enhance contaminant degradation in MES, advanced oxidation processes (AOPs) are synergistically linked to create cooperative processes such as bio-electro-Fenton (BEF) and enhanced bioanodes. BEF can achieve a high contaminant degradation efficiency with a low energy consumption due to the ability for energy recovery from the anodic organic wastes. Modifying a bioanode with catalytic oxidation materials, e.g., photocatalyst and MnO2, will achieve organic removal via the cooperation of catalysis and biodegradation. This paper has provided a concise review on the integration of AOPs with MES and identified and discussed the challenges such as deeper understanding of the electron transfer mechanisms, development of low-cost membrane, and the synergetic effects between functional materials and bacteria that are important to develop AOP-MES treatment systems. 2023 The AuthorsThis paper was made possible by NPRP grant # [ NPRP13S-0109-200029 ] from the Qatar National Research Fund (a member of Qatar Foundation). K. Y. would like to thank the support from Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis. The findings achieved herein are solely the responsibility of the authors.Scopu