Abstract:Residence time distribution (RTD) of liquid phase in a two‐compartment (packed‐bed/packed‐bed or packed‐bed/packing‐free) bioreactor for wastewater treatment was evaluated via a complex liquid flow structure. RTD in packed‐bed compartments was modelled using a modified axial dispersion‐exchange model with a liquid stream which bypasses the dynamic liquid region. The liquid in the dynamic region is dispersed in axial and transverse directions, whereas the stagnant region exchanges mass with the dynamic region, … Show more
“…From this value, the average residence time remains constant. Similar behavior was observed when evaluating the effect of the number of transfer units for the case of a packed-bed bioreactor operated with horizontal flow [5,12]. Figure 5e shows the influence of the average residence time of the packed-free compartment (s 1 ) on the residence time distribution function E(t).…”
Section: Sensitivity Analysis Of the Parameterssupporting
confidence: 55%
“…The mass balance for the system gives the governing equations for the tracer concentration in the mixture model with a mass exchange between dynamic and stagnant zones (packed-free) [19] and PDE model (packed-bed) which can be divided into dynamic and stagnant regions [6,12,20]:…”
Section: Bioreactor Transport and Inhibition Modelmentioning
confidence: 99%
“…where Q is the flow rate, and S is the cross section of the bed, e is the porosity of the bed and b d is the fraction of the reactor void volume in the dynamic zone or dynamic saturation), D d is the axial dispersion coefficient in the dynamic phase, k ma is the overall mass transfer coefficient at the interface dynamic-stagnant phase and u is the dynamic liquid fraction, Equations 3 and 4 are solved using the following initial and boundary conditions, which includes Danckwerts' conditions [6,12]:…”
Section: Bioreactor Transport and Inhibition Modelmentioning
confidence: 99%
“…Recently the hydrodynamics of a two-compartment bioreactor was described using a phenomenological model able to represent the mass exchange between active and stagnant zones, bypass and axial dispersion of the liquid [12]. This bioreactor has some similarity with the rector presented in this study; however, it is a two-compartment packing-free/packed-bed bioreactor instead of a packedbed/packing-free bioreactor.…”
Souring of oil fields during secondary oil recovery by water injection occurs mainly due to the action of sulfate-reducing bacteria (SRB) adhered to the rock surface in the vicinity of injection wells. Upflow packed-bed bioreactors have been used in petroleum microbiology because of its similarity to the oil field near the injection wells or production. However, these reactors do not realistically describe the regions near the injection wells, which are characterized by the presence of a saturated zone and a void region close to the well. In this study, the hydrodynamics of the two-compartment packing-free/packed-bed pilot bioreactor that mimics an oil reservoir was studied. The packed-free compartment was modeled using a continuous stirred tank model with mass exchange between active and stagnant zones, whereas the packed-bed compartment was modeled using a piston-dispersion-exchange model. The proposed model adequately represents the hydrodynamic of the packed-free/packed-bed bioreactor while the simulations provide important information about the characteristics of the residence time distribution (RTD) curves for different sets of model parameters. Simulations were performed to represent the control of the sulfate-reducing bacteria activity in the bioreactor with the use of molybdate in different scenarios. The simulations show that increased amounts of molybdate cause an effective inhibition of the souring sulfate-reducing bacteria activity.
“…From this value, the average residence time remains constant. Similar behavior was observed when evaluating the effect of the number of transfer units for the case of a packed-bed bioreactor operated with horizontal flow [5,12]. Figure 5e shows the influence of the average residence time of the packed-free compartment (s 1 ) on the residence time distribution function E(t).…”
Section: Sensitivity Analysis Of the Parameterssupporting
confidence: 55%
“…The mass balance for the system gives the governing equations for the tracer concentration in the mixture model with a mass exchange between dynamic and stagnant zones (packed-free) [19] and PDE model (packed-bed) which can be divided into dynamic and stagnant regions [6,12,20]:…”
Section: Bioreactor Transport and Inhibition Modelmentioning
confidence: 99%
“…where Q is the flow rate, and S is the cross section of the bed, e is the porosity of the bed and b d is the fraction of the reactor void volume in the dynamic zone or dynamic saturation), D d is the axial dispersion coefficient in the dynamic phase, k ma is the overall mass transfer coefficient at the interface dynamic-stagnant phase and u is the dynamic liquid fraction, Equations 3 and 4 are solved using the following initial and boundary conditions, which includes Danckwerts' conditions [6,12]:…”
Section: Bioreactor Transport and Inhibition Modelmentioning
confidence: 99%
“…Recently the hydrodynamics of a two-compartment bioreactor was described using a phenomenological model able to represent the mass exchange between active and stagnant zones, bypass and axial dispersion of the liquid [12]. This bioreactor has some similarity with the rector presented in this study; however, it is a two-compartment packing-free/packed-bed bioreactor instead of a packedbed/packing-free bioreactor.…”
Souring of oil fields during secondary oil recovery by water injection occurs mainly due to the action of sulfate-reducing bacteria (SRB) adhered to the rock surface in the vicinity of injection wells. Upflow packed-bed bioreactors have been used in petroleum microbiology because of its similarity to the oil field near the injection wells or production. However, these reactors do not realistically describe the regions near the injection wells, which are characterized by the presence of a saturated zone and a void region close to the well. In this study, the hydrodynamics of the two-compartment packing-free/packed-bed pilot bioreactor that mimics an oil reservoir was studied. The packed-free compartment was modeled using a continuous stirred tank model with mass exchange between active and stagnant zones, whereas the packed-bed compartment was modeled using a piston-dispersion-exchange model. The proposed model adequately represents the hydrodynamic of the packed-free/packed-bed bioreactor while the simulations provide important information about the characteristics of the residence time distribution (RTD) curves for different sets of model parameters. Simulations were performed to represent the control of the sulfate-reducing bacteria activity in the bioreactor with the use of molybdate in different scenarios. The simulations show that increased amounts of molybdate cause an effective inhibition of the souring sulfate-reducing bacteria activity.
“…The TF system has numerous advantages in wastewater treatment compared to suspended growth systems, such as low space and operational requirements, cost effectiveness, being environmentally friendly, resistance to toxins and shock loads, operational compliance, increased retention time, enhanced biodegradation rate, and reduced sludge production due to a slower microbial growth rate. Moreover, TF systems also have the ability to regulate reaction rates according to the demand [17,18]. Furthermore, their large air-water interface can remove CO 2 , H 2 , N 2 , and other gases.…”
The aim of the present study is to assess the wastewater treatment efficiency of a low-cost pilot-scale trickling filter (TF) system under a prevailing temperature range of 12 °C–38 °C. Operational data (both influent and effluent) for 330 days were collected from the pilot-scale TF for various physicochemical and biological parameters. Average percentage reductions were observed in the ranges of 52–72, 51–73, 61–81, and 74–89% for BOD5, COD, TDS, and TSS, respectively, for the whole year except the winter season, where a 74–88% reduction was observed only for TSS, whilst BOD5, COD, and TDS demonstrated reductions in the ranges of 13–50, 13–49, and 23–61%, respectively. Furthermore, reductions of about 43–55% and 57–86% in fecal coliform count were observed after the 1st and 6th day of treatment, respectively, throughout study period. Moreover, the pilot-scale TF model was based on zero-order kinetics calibrated at 20 °C using experimental BOD5 data obtained in the month of October to calculate the k20 value, which was further validated to determine the kt value for each BOD5 experimental setup. The model resulted in more accurate measurements of the pilot-scale TF and could help to improve its ability to handle different types of wastewater in the future.
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