CHAPTER 7
Introduction
This chapter describes the aerobic attached-growth models available in GPS-X. These models are used in the Trickling Filter Model, Rotating Biological Contactor (RBC) Model, Submerged Biological Contactor (SBC) Model , Simple Biological Aerated Filter (BAF) Model/Advanced Biological Aerated Filter (BAF) Model, Passively Aerated biofilm system, Hybrid System, Membrane-Aerated Bioreactor (MABR) – Hollow Fibre/Membrane-Aerated Bioreactor (MABR) – Flat Sheet and Aerobic granular sludge reactor objects. The biofilm model is also used in the Denitrification Filter object in the Tertiary Treatment process model group and the High-Rate Primary Filter/High-Rate Biological Filter objects in the Primary Treatment process model group.
The major difference between the attached growth models and the suspended-growth models described in CHAPTER 6 is the inclusion of the diffusion process in the biofilm. Although diffusion occurs in suspended-growth systems (substrate and oxygen must diffuse into the activated sludge floc), it is usually neglected since the biological reactions are the rate limiting steps; however, in attached-growth processes, both diffusion and biological reactions must be considered, increasing the complexity of the models.
The trickling filter, RBC, SBC and hybrid processes are similar. They all provide biofilm biological treatment, with excess biofilm sloughing separated in a clarifier object. The SBC and BAFs are flooded processes, with mechanical supplemental aeration.
The BAF process differs from the other processes in that it:
· is a combined biological and solids separation process; and,
· has a mechanical process for controlling excess biomass growth and captured solids (i.e. backwash)
The advanced BAF model is a combination of an attached-growth model, and a filtration model. The filtration model is described in the Empiric Models section of CHAPTER 8.
Trickling Filter Model
Introduction
The trickling filter model is available in all the libraries, using the same biological reactions found in the suspended-growth models in the appropriate library. The model can predict the extent of carbon and nitrogen removal (by uptake or oxidation) and denitrification, and phosphorus uptake and release. This model incorporates the growth kinetics and transport processes for the corresponding state variables. The profiles of the various components through the biofilm are modelled so that different environments (aerobic, anoxic and anaerobic) can exist within the biofilm.
To reduce the complexity of the model, some assumptions are necessary. The limitations of this model concern the hydraulics of the trickling filter and the biofilm itself. The model assumes that the flow rate and solids loading to the filter can always be processed; that is, clogging and head losses through the filter are not modelled. Also the maximum thickness of the biofilm is not calculated, rather the user specifies it. This assumption was made because there are little or no data available for calibration/verification of the maximum film thickness calculations. It is assumed that there is equal flow distribution over the entire surface area of the trickling filter and the media inside the trickling filter. The effect of the rotation speed of the rotary distributor is neglected.
The dimensions of the trickling filter model are larger than the suspended-growth models since the state variables are now modelled through the film as well as down through the trickling filter. The suspended-growth models only considered the state variables along the reactor (1-dimensional). The additional dimension in the biofilm has some impact on the simulation speed; therefore, more time is required when using this model. Improvements to the speed of this model have been made by integrating the state variables with different frequencies. For example, the particulate components were found to change more slowly than the soluble components since they are diffusing through the biofilm. Therefore, the integration of the soluble components was handled differently from the particulate components (see Figure 7‑3).
Conceptual Model
The trickling filter is divided into ‘n’ horizontal sections (default is six sections) each representing a cross-section of the trickling filter at a different depth. The transfer of the state variables between each of these horizontal sections through the liquid film is through liquid flow. The biofilm in each of these horizontal sections is modelled as a number of layers (default is one layer for the liquid film on top of five layers for the biofilm). The transfer of soluble state variables between each of these layers is by diffusion only. Particulate variables have a certain physical volume associated with them and can be displaced into the neighbouring layer by growth processes.
Each layer of the biofilm is modelled as a CSTR with the same biological reactions as the suspended-growth biological model (See Appendix A for the mantis model). Attachment and detachment coefficients are used to provide for a means of transfer of particulate components between the biofilm surface and the liquid film. This conceptualization is shown in Figure 7‑1. The concentration of each particulate state variable is converted to volume based on the dry material content of biofilm and the density of biofilm (both user inputs). When the volume of each layer is filled (based on maximum biofilm thickness and number of biofilm layers) the next layer begins to fill. When the film thickness approaches the specified maximum, increasing detachment of biofilm will occur.
Figure 7‑1 - Conceptual Diagram of the Tricking Filter Model
Mathematical Model
The mathematical equations used within each layer of the biofilm are provided in the corresponding Model matrix (for example, see Appendix A for the mantis model). The equation used for the diffusion of the state variables from the bulk liquid into the biofilm is provided below. The diffusion through the biofilm is described by Fick's second law and supplemented with biological reactions:
Equation 7‑1
where:
Aa = surface area of biofilm through which transport is occurring (m2)
δL = thickness of attached liquid layer (m)
S jL = substrate conc. in liquid film horizontal section (mg/L)
t = time (days)
SjBLi = substrate concentration at biofilm liquid interface section j (mg/L)
S o = saturated liquid-film substrate concentration (mg/L)
Q L = volumetric flow rate of attached liquid layer (L/d)
KM = mass transfer coefficient from liquid to biofilm (m/d)
KML = oxygen transfer coefficient from air to liquid film (m/d)
Equation 7‑2
where:
A = surface area of attached microorganisms (m 2)
D S = state variable diffusion coefficient (m2/d)
Q B = volumetric flow rate of attached biofilm layer (L/d)
R s = substrate utilization rate (mg/L/d)
S = state variable concentration in layer (mg/L)
SjB = state variable concentration in attached biofilm layer j (mg/L)
y = thickness of biofilm layer (m)
dL = attached biofilm thickness in layer (m)
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user would encounter when using this model. The examples and discussion below pertain to the mantis model in the CN library.
Physical
These menu items are found under the Parameters sub-menu item Physical and contain both real physical dimensions to describe the actual trickling filter being modelled, as well as model dimensions which allow the user to specify how the physical system will be modelled. There are two items under the heading Speed, which allow the user to optimize the simulation speed of this model by changing the frequency of integration for the soluble components.
As seen in Figure 7‑2, the real dimensions of the trickling filter require inputs such as: the filter bed depth, filter bed surface and specific surface of media. Together, these three parameters will provide an estimation of the total biofilm surface area in the model. The liquid retention time in filter refers to the retention time of the liquid flowing past the biofilm, the maximum attached liquid film thicknessrefers to the liquid film which is not moving past the biofilm due to friction (no-slip layer) and the maximum biofilm thickness will be reached only with infinite sloughing. The density of biofilm and dry material content of biofilmare used to convert the concentration of each state variable to a volume measurement.
Figure 7‑2 - Physical Dimensions of the Tricking Filter
The model dimensions are fixed, that is, the number of layers in the biofilm is six (one liquid layer and five biofilm layers). Also, the number of horizontal and vertical sections in the model is fixed at six and one respectively.
The next two items in this form, under the heading Speed, concern the integration of the soluble state variables. Since these variables are diffusing through the biofilm, and consequently change rapidly when compared to the particulate state variables, which are changing only due to their growth rates, they tend to dominate the numerical solver. To increase the speed of simulation, the soluble states can be integrated less frequently without loss of accuracy. When the variables are scheduled to be integrated their derivatives are calculated from equations (Equation 7‑1) and (Equation 7‑2) shown above. Otherwise, the derivatives are set to zero. There are two variables used to specify how frequently the soluble states are integrated and the duration for integration or how long the states are integrated for each period: the soluble integration period and soluble integration length. These concepts are shown in Figure 7‑3 with the results on ammonia shown in Figure 7‑4.
Figure 7‑3 - Integration of Soluble Components
Figure 7‑4 – Integration
Transport
The parameters shown in Figure 7‑5 are used for the transport model (diffusion) of the various components through the biofilm. Since there are insufficient data in the literature concerning the diffusion of various components through a biofilm, the values used for the diffusion through water are reduced by a constant fraction, shown as reduction in diffusion in biofilm. The default diffusion coefficients shown for water are used for the diffusion of components from the liquid layer to the first layer (outside) of the biofilm. The detachment rate and attachment rate are used for calculating the sloughing rate and particulate components attachment to the biofilm, respectively.
Figure 7‑5 - Mass Transport Parameters
The physical dimensions of the tricking filter show more physical components associated with oxygen. The oxygen mass transfer coefficient is calculated from the physical conditions within the filter (thickness of biofilm and diffusion rate of oxygen) and is affected by temperature and the saturated dissolved oxygen concentration. These values are either input in the general data entry area or specifically set for each object as shown in Figure 7‑6.
Figure 7‑6 - Physical Dimensions of the Trickling Filter
Stoichiometric and Kinetic Parameters
The parameters shown in these menus refer to the biological reactions that are described in CHAPTER 6.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. Figure 7‑7 shows the variables available for display for the trickling filter.
Trickling Filter Variables
This includes the biofilm thickness for each horizontal section from the top to the bottom of the filter.
Biofilm Profiles
This provides all the state variables plus the suspended solids composite variable for each horizontal section of the trickling filter (i.e. six profiles for six horizontal sections). The first layer in the profile is the liquid film, followed by the biofilm layers (i.e. liquid and maximum of five biofilm layers).
Figure 7‑7 - Tricking Filter Output Variables
Liquid Film Concentrations
This provides the liquid film state variables for each horizontal section of the trickling filter, from top (section 1) to bottom (section 6).
2D Variables
This is used for plotting both the filter horizontal sections and biofilm layers variables using the 3D bar chart or grayscale outputs. Examples are shown in Figure 7‑8. From left to right are the liquid layer and five biofilm layers. In the 3D bar chart, the top of the filter is located in the foreground, and the bottom of the filter in the background. In the greyscale graph, the six horizontal trickling filter horizontal sections are shown from top to bottom (i.e. top layer of the filter is shown at the top of the graph).
Figure 7‑8 - 2D Variables
Rotating Biological Contactor (RBC) Model
Introduction
The rotating biological contractor (RBC) model is available in all the libraries, using the same biological reactions found in the suspended-growth models in the appropriate library. The model can predict the extent of carbon and nitrogen removal (by uptake or oxidation) and denitrification, as well as phosphorus uptake and release. This model incorporates the growth kinetics and transport processes for the corresponding state variables. The profiles of the various components through the biofilm are modelled so that different environments (aerobic, anoxic and anaerobic) can exist within the biofilm.
To reduce the complexity of the model, some assumptions are necessary. The limitations of this model concern the hydraulics of the rotating biological contactor and the biofilm itself. The model assumes that the flow rate and solids loading to the RBC can always be processed; that is, clogging and head loss are not modelled. Also the maximum thickness of the biofilm is not calculated; rather it is specified by the user. This assumption was primarily made because there are little or no data available for calibration/verification of the maximum film thickness calculations. The effect of the rotation speed and direction of the RBC and its impact on media sloughing and aeration requirements is neglected.
Similar to the trickling filter model, the RBC is more complex than the suspended-growth models since the state variables are modelled through the biofilm as well as through various RBC stages.
Conceptual Model
The rotating biological contactor is divided into ‘n’ stages (default is 1 stage) each representing a baffled RBC system. The transfer of the state variables between each of these stages is through the liquid flow. The biofilm in each stage is modelled as a number of layers (default is one layer as the liquid film on top of five layers as the biofilm). The transfer of soluble state variables between each of these layers is by diffusion only. Particulate variables have a certain physical volume associated with them and can be displaced into the neighbouring layer by growth processes. Each layer of the biofilm is modelled as a CSTR with the same biological reactions as the suspended-growth biological model (See Appendix A for the mantis model). Attachment and detachment coefficients are used to provide for a means of transfer of particulate components between the biofilm surface and the liquid film.
This conceptualization is shown in Figure 7‑9. The concentration of each particulate state variable is converted to volume based on the dry material content of biofilm and its density, both input by the user. When the volume of each biofilm layer is filled (based on maximum biofilm thickness and number of biofilm layers) the next layer begins to fill. When the biofilm thickness starts to approach the specified maximum, increasing detachment of biofilm will occur.
Figure 7‑9 – Conceptual Diagram of the RBC Model
Mathematical Model
The mathematical equations used within each layer of the biofilm are provided in the corresponding Model matrix (For example, see Appendix A for the mantis model). The equation used for the diffusion of the state variables from the bulk liquid into the biofilm is provided in the trickling filter section.
Model Parameters
The mathematical equations used within each layer of the biofilm are provided in the corresponding Model matrix (For example, see Appendix A for the mantis model). The equation used for the diffusion of the state variables from the bulk liquid into the biofilm is provided in the trickling filter section.
Physical
These menu items are found under the Parameters sub-menu item Physical and contain both real physical dimensions to describe the actual rotating biological contactor modelled, as well as model dimensions which allow the user to specify how the physical system will be modelled. There are two items under the heading Speed, which allow the user to optimize the simulation speed of this model by changing the frequency of integration for the soluble components. As seen in Figure 7‑10, the real dimensions of the rotating biological contactor require inputs such as the rbc liquid volume, the rbc media volume and the specific surface area of media. Together, these three parameters provide an estimation of the total biofilm surface area in the model. The submerged fraction of the biofilm refers to the percent of the RBC submerged at any given time, the maximum attached liquid film thickness refers to the liquid film which is considered to be associated with the biofilm due to friction (no-slip layer), and the maximum biofilm thickness will be reached only with infinite sloughing. The density of biofilm and dry material content of biofilm are used to convert the concentration of each state variable to a volume measurement. The model dimensions include the number of RBC tanks in series or stages. The model assumes each tank or stage is of equal size. If the stages are of unequal size (different media density and/or parallel feeding), the user should tie individual RBC objects together to simulate the process.
Figure 7‑10 - Physical Dimensions of the RBC
The next two items in this form, under the heading Speed, concern the integration of the soluble components. Since these components are diffusing through the biofilm, and consequently change rapidly when compared to the particulate components, which are changing only due to their growth rates, they tend to dominate the numerical solver. To increase the speed of simulation, it was found that these components can be integrated less frequently without loss of accuracy. When the soluble variables are scheduled to be integrated, their derivatives are calculated from equations (Equation 7‑1) and (Equation 7‑2). Otherwise, the derivatives are set to zero. There are two variables which are used to specify how frequently the states are integrated: the soluble integration period, and the duration for integration or how long the states are integrated for each period (soluble integration length). These concepts are shown in Figure 7‑3, with the results for ammonia shown in Figure 7‑4.
Figure 7‑11 shows more physical components associated with oxygen solubility. The oxygen mass transfer coefficient is calculated from the physical conditions within the filter (thickness of biofilm and diffusion rate of oxygen) and is affected by temperature and the saturated dissolved oxygen concentration. These values are either input in the general data entry area or specifically set for each object.
Figure 7‑11 – Physical Dimensions of the RBC (More…)
Mass Transport
The parameters shown in Figure 7‑5 are used by the RBC for the transport model (diffusion) of the various components through the biofilm. Since there are insufficient data in the literature concerning the diffusion of various components through a biofilm, the values used for the diffusion through water are reduced by a constant fraction, shown as reduction in diffusion in biofilm. The default diffusion coefficients shown for water are used for the diffusion of components from the liquid layer to the first layer (outside) of the biofilm. The rate of detachment and attachment is used for calculating the sloughing rate and particulate components attachment to the biofilm.
Stoichiometric and Kinetic Parameters
The parameters shown in these menus refer to the biological reactions that are described in CHAPTER 6.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. These are accessed through the object’s Output Variables menu item.
· RBC Variables(see Trickling Filter Variables section in this chapter)
· Liquid Concentrations (see Liquid Film Concentrations section in this chapter)
· 2D Variables (see 2D Variablessection in this chapter)
Submerged Biological Contactor (SBC) Model
Introduction
The submerged biological contactor (SBC) model is a modification of the RBC model for units that are air driven or are provided with supplemental aeration. Units with supplemental aeration tend to be more submerged than conventional RBCs (conventional RBCs are generally 40 percent submerged) providing additional contact of the media with the influent, since the unit is not dependent on ambient air for oxygen.
The SBC model discussed herein is available in all the libraries, using the same biological reactions found in the suspended-growth models in the appropriate library. The model can predict the extent of carbon and nitrogen removal (by uptake or oxidation) and denitrification, as well as phosphorus uptake and release (in the carbon-nitrogen-phosphorus library). This model incorporates the growth kinetics and transport processes for the corresponding state variables. The profiles of the various components through the biofilm are modelled so that different environments (aerobic, anoxic and anaerobic) can exist within the biofilm.
To reduce the complexity of the model, some assumptions are necessary. The limitations of this model concern the hydraulics of the submerged biological contactor and the biofilm itself. The model assumes that the flow rate and solids loading to the SBC can always be processed; that is, clogging and head loss is not modelled. The maximum thickness of the biofilm is not calculated; rather it is specified by the user. This assumption was made because there are little or no data available for calibration/verification of the maximum film thickness calculations. It is assumed that there is equal flow distribution over the entire surface area of the SBC and the media inside the SBC. The effect of the rotation speed or direction of the SBC and its impact on media sloughing is neglected. The oxygen diffused into the biofilm when the media is in the air is neglected, since the SBC media is generally submerged more than 80 percent of the time; therefore, the SBC is modelled as completely submerged.
Similar to the trickling filter model and the RBC, the SBC is more complex than the suspended-growth models since the state variables are now modelled through the film and through various SBC stages (or shafts).
Conceptual Model
The submerged biological contactor is divided into a number of stages (default is 2 stages) each representing a baffled SBC shaft. The transfer of the state variables between each of these stages is through the liquid flow. The biofilm in each stage is modelled as a number of layers (default is one layer as the liquid film on top of five layers as the biofilm). The transfer of soluble state variables between each of these layers is by diffusion. Particulate variables have a certain physical volume associated with them and can be displaced into the neighbouring layer by growth processes. Each layer of the biofilm is modelled as a CSTR with the same biological reactions as the suspended-growth biological model (See Appendix A for the mantis model). Attachment and detachment coefficients are used to provide for a means of transfer of particulate components between the biofilm surface and the liquid film.
For the SBC the process is the same as the RBC (conceptually shown in Figure 7‑9). The concentration of each particulate state variable is converted to volume based on the dry material content of biofilm and its density input by the user. When the volume of each layer is filled (based on maximum biofilm thickness and number of biofilm layers) the next layer begins to fill. When the film thickness starts to approach the specified maximum, increasing detachment of biofilm will occur.
Mathematical Model
The mathematical equations used within each layer of the biofilm are provided in the corresponding Model matrix (for example, see Appendix A for the mantis model). The equation used for the diffusion of the state variables from the bulk liquid into the biofilm is provided in the trickling filter section.
Model Parameters
This section of the chapter discusses the model parameters and inputs that the user will encounter using this model, in particular those different from the other fixed film models. The example and discussion below pertains to the mantis model in the Carbon - Nitrogen(CN) library.
Physical
These menu items are found under Parameters > Physical, and contain both real physical dimensions to describe the actual submerged biological contactor being modelled, and model dimensions which allow the user to specify how the physical system will be modelled. there are two items under the heading Speed, which allow the user to optimize the simulation speed of this model by changing the frequency of integration for the soluble components.
As seen in Figure 7‑12, the real dimensions of the submerged biological contactor require inputs such as:
1. tanks in series
2. volume set up method
3. SBC liquid volume in tanks
4. SBC media volume in tanks
5. SBC total volume
6. SBC total media volume
7. volume fractions
8. Specific surface of media (which will provide an estimation of the total biofilm surface area in the model.)
Based on the volume set up method (input 2), the user either specifies the individual volumes per tank (inputs 3 and 4), or the volume fractions based on the total volumes (inputs 5, 6 and 7). The latter two items are used to convert the concentration of each state variable to a volume measurement. Model dimensions include the number of SBC tanks in series or stages.
Figure 7‑12 – Physical Dimension of the SBC
Biofilm characteristics include:
1. Maximum attached liquid film thickness, which refers to the liquid film that is considered to be associated with the biofilm due to friction (no-slip layer).
2. Maximum biofilm thickness, which will be reached with infinite sloughing
3. Density of biofilm
4. Dry material content of biofilm
The next two items in this form under the heading Speed, concern the integration of the soluble components. Since these components are diffusing through the biofilm, and consequently change rapidly when compared to the particulate components, which are changing only due to their growth rates, they dominate the numerical solver. To increase the speed of simulation, it was found that these components could be integrated less frequently without loss of accuracy. When the soluble variables are scheduled to be integrated their derivatives are calculated as normal. Otherwise, the derivatives are set to zero. There are two variables which are used to specify how frequently the states are integrated (Soluble integration period) and the duration for integration or how long the states are integrated for each period (Soluble integration length). These concepts are shown in Figure 7‑3, with the results for ammonia shown in Figure 7‑4.
The oxygen mass transfer coefficient is calculated from the physical conditions within the filter (thickness of biofilm and diffusion rate of oxygen) and is affected by temperature and the saturated dissolved oxygen concentration. These values are input in the general data entry area or specifically set for each object as shown in Figure 7‑13.
Figure 7‑13 - Physical Dimensions of the SBC (More...)
Operational
The operational parameters are similar to the activated sludge model. Like the activated sludge model, the aeration method can be chosen as either “Enter KLa” or “Enter Airflow”. No mechanical method is provided since this method is not appropriate for the SBC.
Mass Transport
The parameters shown in Figure 7‑5 are used by the SBC for the transport model (diffusion) of the various components through the biofilm. Since there are insufficient data in the literature concerning the diffusion of various components through a biofilm, the values used for the diffusion through water are reduced by a constant fraction, shown as reduction in diffusion in biofilm. The default diffusion coefficients shown for water are used for the diffusion of components from the liquid layer to the first layer (outside) of the biofilm. The rate of detachment and attachment is used for calculating the sloughing rate and particulate components attachment to the biofilm.
Stoichiometric and Kinetic Parameters
The parameters shown in these menus refer to the biological reactions that are described in CHAPTER 6.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. They are the same as the trickling filter. These are accessed through the following subheadings:
· SBC Variables(see Trickling Filter Variables section in this chapter)
· Liquid Concentrations (see Liquid Film Concentrations section in this chapter)
· 2D Variables (see 2D Variablessection in this chapter)
Simple Biological Aerated Filter (BAF) Model
Conceptual Model
The simple BAF model combines the 1-D biofilm model used in the trickling filter with an aeration model and simple solids-separation model. It is similar in construct to the denitrification filter, with the addition of aeration. The Simple BAF model is designed to be a less sophisticated, but easier-to-use alternative to the advanced BAF model. The Simple BAF model will solve to steady-state using the GPS-X steady-state solver (whereas the Advanced BAF model cannot, and requires a dynamic simulation to come to equilibrium).
The simple BAF uses a series of horizontal layers (6 by default) to represent plug-flow through media. The filter is fed from the bottom and effluent is taken from the top.
Figure 7‑14 - Simple BAF Model Configuration
Oxygen solubility is calculated separately for each layer, allowing for depth effects to be reflected in oxygen saturation concentration.
Hydraulics
Influent flow enters the unit through the lower-left connection point, and exits from the upper right-hand connection point. Solids that are periodically backwashed from the unit are converted to a continuous flow that exits from the lower-right connection point.
Physical Parameters
The physical parameters menu for the Simple BAF model contains parameters for the description of the unit, including the characteristics of the media. Figure 7‑15 shows the physical parameters menu. The definitions of the various biofilm parameters (e.g. maximum biofilm thickness, etc.) are identical to those described in the section on the Trickling Filter model. The default parameter values for the media characteristics are set for typical BAF media.
Figure 7‑15 - Simple BAF Model Operational Parameters Menu
Operational Parameters
The operational parameters menu contains settings for the aeration and backwashing of the filter.
The solids capture fraction is used to determine the mass of solids captured on the filter. These solids are then removed via the
The backwash flow rate and backwash duration per 24-hr period are used (along with the calculated captured solids) to calculate a mass flow of backwashed solids. The backwashed flow is converted from an intermittent event to a continuous flow of equivalent mass solids. This allows for the model to be solved using the steady-state solver.
Details of the aeration setup can be found in the More... button under in the Aeration Setup section. (Figure 7‑16)
Figure 7‑16 - Simple BAF Model Operational Parameters Menu (More...)
The remaining menus are equivalent to those found in the Trickling Filter Model.
Advanced Biological Aerated Filter (BAF) Model
The advanced biological aerated filter (BAF) model is a robust, mechanistically-based model. It uses the same biological reactions found in the suspended-growth models discussed in CHAPTER 6.
Conceptual Model
The advanced BAF model consists of four major components: Hydraulics and Filter Operation, Filtration, Biological Reactions, and a Biofilm. They are described in the following sections.
Figure 7‑17 - Advanced BAF Model Configuration
Hydraulics and Filter Operation
The model needs to be able to describe the complex operation of the bio filter stages each consisting of one or more units in different operating modes.
In the simplest implementation (number of units is 1); the model simulates the behavior of a single BAF unit. This unit can be in filtration, standby, backwash, or flush mode. In filtration, standby and flush mode, the filter is represented hydraulically as a tank consisting of a certain number of horizontal sections (6 in the default case). The actual filtration bed is preceded by a mixed tank without filter material to describe the dilution effects of the volume of water under the filter bed. A similar mixed tank is added to account for the liquid on top of the filter media. In backwash mode the horizontal sections of the filter are combined and converted to one mixed tank. The model assumes that during backwash the filter media is ideally mixed.
The influent loading to the filter determines if the filter is in filtration, standby, backwash, or flush mode. In filtration and flushed modes, flow is entering the filter through the input stream and coming out through the output stream. In standby mode, there is no flow through the filter. In backwash mode, flow is entering the filter through the backwash input stream and coming out through the backwash output stream.
A complex bio filter plant could be represented by the proper number of individual filter units placed on the drawing board to describe the changing conditions in the plant and forecast effluent quality. Due to the level of complexity within one filter unit and the typical number of units in the plant this approach is not feasible even with substantial computing capacity. Since the difference between individual units operating in the same mode is not drastic, a simplified operation mode provides a good approximation of operating and effluent conditions with substantially less overhead.
For this purpose the hydraulics of the filter (which now can be thought of as a series of units) is described in three different ways. A certain fraction of the total number of units is in filtration mode, i.e. layered with influent flowing through them. Another fraction is in standby mode, with light aeration and no influent loading. A third fraction is in backwash mode. The sum of the three fractions adds up to the total number of units. At times any one of these fractions may be completely missing, i.e. the number of units in backwash or standby mode can be zero. In GPS-X, the individual fractions are specified in two ways:
1. As constants – This allows a simple run when the number of units in standby does not change. When a particular backwash criterion is reached, a certain number (user-specified) of units in a filtration mode are backwashed. This mode can be used if an actual operation of a filter plant is recorded and has to be replayed in GPS-X. The number of units can be read in through the GPS-X input file facility, and the original loading conditions recreated.
2. As volume fractions which vary according to a target load on the filter component – This way the ration of the operating filter volume, and the standby volume changes continuously according to changes in influent load. This operation mimics a "constant loading" operational policy, although the loading is completely constant on the filter volume because the limitation created by the individual bio filter unit volumes are ignored.
During the simulation when volume fractions in different operating modes change, the model correctly keeps track of mass balances by recalculating the mass of all model components currently in that element. As an example consider the event of one standby unit coming on-line due to increasing load on the filter. The other elements in the filter, which have been in operation, may contain much higher active biomass than one, which has been on standby for a period of time. When the standby component comes on-line, a volume weighted average biomass concentration is calculated for the new, increased filter volume for all horizontal sections and all biofilm layers, and integration continues using the new conditions.
Filtration Component
The modified Iwasaki equation (Horner et al., 1986) was used to calculate the filtration rate, while head loss is calculated according to the Kozeny equation. In the filtration mode, the number of horizontal sections is determined by the plug flow characteristics of the BAF bed (6 by default). This component of the model is used in predicting solids capture, effluent suspended solids and other constituents and backwash quality. In backwash mode, the backwashed fraction of the bed is treated as an ideally mixed tank; biofilm layers are retained.
The filtration element of the model is available without the biological reactions in the current sand-filter model in GPS-X described in One-Dimensional Model section of CHAPTER 9.
Biological Reactions Component
The BAF models use the same biological reactions found in the suspended-growth models in the appropriate library. The mantis model has been successfully used in several biofilm configurations by Hydromantis/Hatch and is able to predict ammonia and BOD profiles in the reactor and in the biofilm. For more specific information on biological models, please consult CHAPTER 6.
Biofilm Component
The existing biofilm model in GPS-X is based on Spengel and Dzombak (1992). This model was adapted to the simple and advanced BAF configurations. The model handles soluble material diffusion, biofilm growth, and particulate attachment and detachment. Details are described in the
Trickling Filter Model section of this chapter.
Mathematical Model
The mathematical equations used within each layer of the biofilm are provided in the corresponding Model matrix (see Appendix A for the mantis model). The equations used for the diffusion of the state variables from the bulk liquid into the biofilm are provided in the
Trickling Filter Model section of this chapter. The equations used for the filtration component are provided in the One-Dimensional Model section of CHAPTER 9.
Model Parameters
This section discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
The physical parameters are found under the Input Parameters sub-menu item Physical. It contains physical dimensions to describe the actual BAF being modelled and model dimensions, which allow the user to specify how the physical system will be modelled. There are three items under the heading Speed, which allow the user to optimize the simulation speed of this model.
As seen in Figure 7‑18, the unit dimensions of the BAF require inputs such as the single filter bed surface area, the total filter bed depth from support, the media fill (empty bed depth) (the difference between the last 2 inputs giving the water height above the media), and the water height below support. The number of units makes the simplified multiple units operation possible.
The next section of this form, media, includes inputs to characterize the media being used in the filter: Specific surface of media together with the filter bed depth and surface area provides an estimation of the total biofilm surface area in the model; Equivalent particle diameter, where multi-media filters can be described; Clean bed porosity (void space); and ultimate bulk biofilm volume, the maximum space the biofilm can take up before completely clogging the filter.
The next two items under the Biofilm heading, density of biofilm and dry material content of biofilm, are used to convert the concentration of each state variable to a volume measurement. The Model Dimensions section includes the number of sections in filter; the model assumes each horizontal section is of equal size.
Figure 7‑18 shows physical components associated with oxygen solubility and model speed. The oxygen mass transfer coefficient is calculated from the physical conditions within the filter (thickness of biofilm and diffusion rate of oxygen) and is affected by the liquid and air temperatures, and the oxygen fraction in air (See 0). These values are input in the general data entry area or specifically set for each object as shown in this screen. The first two items under the heading Speedconcern the integration of the soluble components, which is described in the
Trickling Filter Model section of this chapter. The third item, calculate DO in liquid, is used to improve the speed of simulation if the BAF installation maintains a relatively high level of DO in the liquid (close to saturation). By setting this parameter to OFF, a constant DO level is maintained in the liquid and integration of the DO state variable is bypassed, thereby speeding up the simulation. The constant DO level can be adjusted in the initial conditions form (Process Data > Initialization > initial concentrations).
Figure 7‑18 - Advanced BAF Physical Parameters
Operational
In the first part of the Operationalmenu item, aeration constants are available similar to all aerated biological units. Specific to the advanced BAF model is the ability to specify a different KLa (or air flow, if the aeration method is set to diffused) for each of the filter operational states (active, standby, flushed, or backwashed). These parameters are shown in Figure 7‑19
Figure 7‑19 - BAF Operational Parameters
The entry under the Cycles heading, backwash operation, is used to set up the method by which a backwash operation will be initiated when operating the filter(s). The backwash operationcan be time-based, head loss-based, effluent quality based, or manual. The filter can be operated in single unit mode (the whole volume will be in filter, backwash, standby or flushed mode), or multiple unit operation. In multiple unit operation (if the number of units is greater than one), the number of units in filter mode can be specified, and the remaining units are in standby mode. The number of simultaneously backwashed unitswill be taken out of the filtration mode and replaced with standby units when a backwash operation is initiated if the constant filter loading rate controller is on. The target loading rate on the filter fraction can be specified and thus the volume of filter in filtration mode will vary to maintain the target loading rate.
This form contains further information about the backwash operation. Backwash can be initiated after a certain period (i.e. every 24 hours), or after a maximum allowable head loss is achieved (i.e. 1 m), or when the effluent solids reach a threshold level (i.e. 10 g/m3). This last mode may be useful for optimizing plant performance in the mathematical model. In manual mode, the operation of the BAF has to be done through a Control window (or file input), which needs to be set up with all the operational variables.
Further model parameters are included in the mass transport, stoichiometric, kinetic and filtration menu items in the BAF model. These forms are described in the
Trickling Filter Model section of this chapter and in the Sand Filtration Models section developed in CHAPTER 9.
Figure 7‑20 - More Advanced BAF Operational Parameters
Output Variables – Hydraulics
Here, hydraulic information can be accessed and displayed for each of the horizontal filter sections (6 by default). It includes dilution rate and headloss-related variables: Reynolds number, friction factor, and headloss in each horizontal filter section for both clean and dirty filter beds.
2D BAF
The solids capture rate during filtration can be displayed for each of the horizontal filter sections. The other variables (O2 partial pressure, pore size, biofilm thickness, deposit concentration, bulk deposit volume) can be displayed on 3D graphs. The x-axis has the six horizontal filter sections, the y-axis has the five biofilm layers and liquid phase, and the z-axis displays the variable value.
Filter Segment
The state variables and the solids composite variable can be displayed on 3D graphs. The x-axis has the six horizontal filter sections, the y-axis has the five biofilm layers and liquid phase, and the z-axis displays the variable value.
Liquid Film Concentration in Filter Part
In this form, the state variables and unattached solids composite variable values in the liquid phase can be selected for display for each of the horizontal filter sections. The values displayed are only valid for the BAF units in filtration mode.
Variables in Backwashed Segment
In this form, the state variables can be selected for display for each of the biofilm layers. The values displayed are only valid for the units in backwash mode, and represent the average of all horizontal filter sections. In filtration mode, the filter is treated as a completely mixed tank.
Passively Aerated biofilm system
The passively aerated biofilm (PAB) system allows users to model a biofilm-based process with natural air ventilation for air supply.
Figure 7‑21 - Passively Aerated Biofilm System Model Configuration
Biological Component
The passively aerated biofilm system uses the same biological reactions found in the suspended-growth models. For more specific information on biological models, please consult CHAPTER 6.
Biofilm Component
The existing biofilm model in GPS-X is based on Spengel and Dzombak (1992). This model was adapted to the hybrid-system. The model handles soluble material diffusion, biofilm growth, and particulate attachment and detachment. Details are described in the
Trickling Filter Model section of this chapter.
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
The physical parameters are found under the Parameters sub-menu item Physical. It contains physical dimensions to describe the passively aerated biofilm system, and model dimensions which allow the user to specify how the physical system will be modelled.
The passively aerated biofilm system requires inputs such as the tower dimensions, biofilm parameters, and the oxygen mass transfer coefficient.
Mass Transport Menu
The mass transport menu of the PAB object contains parameters relevant to the transport of components to, from, and within the layers of the biofilm. The menu is shown below:
Figure 7‑22 - PAB mass transport menu.
These parameters are similar to those used in other biofilm objects:
attachment rate – a rate constant used to determine the mass flow of solids from the bulk liquid to the outermost biofilm layer
detachment rate – a rate constant used to determine the mass flow of solids from the outermost biofilm layer to the bulk liquid
internal solids exchange rate – a parameter used to determine the mass flow of solids between internal layers in the biofilm
Initialization
In addition to the standard initial volume input, the PAB-system requires the reactor portion filled by media (media or empty bed fill), which can be input in the Initial Volume sub-menu form.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that
Aerobic granular sludge reactor
A new model is developed to simulate the Aerobic Granular Sludge Reactor. The two- phase solid-liquid model considers the growth of granular biomass in the reactor. In comparison to models based on fixed granular surface area, the model with growth of new granular biomass and associated surface area allows the user to study the evolution of granular sludge during start-up period of the reactor.
Hybrid System
The Hybrid-System model in GPS-X is based on a combination of the standard plug flow tank configuration with suspended growth biomass, and the GPS-X biofilm model representing fixed film growth on the media inserted into the tank. Any type of media will be represented in the model as long as the specific surface area is set correctly. Thus the model is able to represent commercial systems such as MBBR, Ringlace, Captor, Bionet and other types of hybrid systems, whether they contain sludge recycle or not.
Figure 7‑23 - IFAS/MBBR Model Configuration
Biological Component
The hybrid-system uses the same biological reactions found in the suspended-growth models. For more specific information on biological models, please consult CHAPTER 6.
Biofilm Component
The existing biofilm model in GPS-X is based on Spengel and Dzombak (1992). This model was adapted to the hybrid-system. The model handles soluble material diffusion, biofilm growth, and particulate attachment and detachment. Details are described in the
Trickling Filter Model section of this chapter.
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
The physical parameters are found under the Parameters sub-menu item Physical. It contains physical dimensions to describe the hybrid-system, and model dimensions which allow the user to specify how the physical system will be modelled.
The hybrid-system requires inputs such as the specific surface of media, the water displaced by media, and the specific density of media.
Operational
In the Operational form, aeration constants are available similar to all aerated biological units. Specific to the hybrid-system is the ability to specify two additional recycle streams. These streams are internal recycle with carrier(if internal recycle carries carrier with it) and flow from tank # with carrier (if the carrier can flow from one cell to the next one).
Further model parameters are included in the mass transport, stoichiometric and kinetic menu items in the hybrid-system model. (See
Trickling Filter Model section in this chapter)
Initialization
In addition to the standard initial volume input, the hybrid-system requires the reactor portion filled by media (media or empty bed fill), which can be input in the Initial Volume sub-menu form.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. These are accessed through the object's output variables menu item.
Denitrification Filter
The denitrification filter objects are found in the “Tertiary Treatment” group of objects, rather than in the “Attached Growth” group, as the other biofilm objects.
The denitrification filter model is similar to the trickling filter model in hydraulic structure. There are, however, a few fundamental differences:
1. The filter is assumed to be entirely flooded. There is no empty void space between media, as in the trickling filter model.
2. The trickling filter model is assumed to be downflow, whereas there are two different denitrification filter models: Upflow and Downflow, as shown in Figure 7‑24.
Figure 7‑24 - Upflow and Downflow Denitrification Filter Objects
Biological Component
The denitrification filter model uses the same biological reactions found in the suspended-growth models. For more specific information on biological models, please consult CHAPTER 6.
Biofilm Component
The existing biofilm model in GPS-X is based on Spengel and Dzombak (1992). This model was adapted for use in the attached-growth objects such as the trickling filter and denitrification filters. The model handles soluble material diffusion, biofilm growth, and particulate attachment and detachment. Details are described in the
Trickling Filter Model section of this chapter.
Filtration Component
The filtration of solids is modeled as a simple capture of the particulate state variables from the effluent layer of the denitrification filter (bottom layer in the downflow filter and top layer in the upflow filter). Users specify a capture fraction, and all solids captured are removed through the backwash connection stream. Backwashing (and its associated removal of solids) is modeled as a continuous process flow.
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
The physical parameters are found under the Parameters sub-menu item Physical. It contains physical dimensions to describe the denitrification filter, and model dimensions which allow the user to specify how the physical system will be modelled.
The denitrification filter requires inputs such as the specific surface of media and the porosity of media.
Operational
The operational menu contains three parameters that define the removal of solids via backwash. The solids capture fraction defines the fraction of particulate state variables (on a concentration basis) that is removed from the effluent stream. The parameters backwash duration during 24-hr period and backwash flow are used to determine the total amount of flow leaving through the backwash connection point per day. The backwash concentration is calculated as the total amount of captured solids divided by the daily backwash flow rate.
Other Menus
Further model parameters are included in the mass transport, stoichiometric and kinetic menu items in the denitrification filter model. These forms are described in the
Trickling Filter Model section of this chapter.
Initialization
The initialization menu of the denitrification filter object is the same as for the trickling filter object, and contains the initial concentrations of the state variables in each layer of the filter.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. These are accessed through the object's output variables menu item.
Membrane-Aerated Bioreactor (MABR) – Hollow Fibre
The Membrane-Aerated (MABR) object is found in the Attached Growth section of the Unit Process Table.
Figure 7‑25 – Membrane Aerated Bioreactor – Hollow Fibre Model Configuration
The MABR object uses a structure similar to the Hybrid object, in that it is a suspended growth reactor with media supporting biofilm growth. Unlike the Hybrid object, the media can only be fixed (as opposed to floating), and the aeration of the biofilm is done from the membrane surface itself (as opposed to via the bulk liquid), effectively aerating the biofilm from the inside out. Regular diffused aeration of the bulk liquid is also available in this object.
Figure 7‑26 shows the structure of the MABR biofilm model. At the left, the media surface area supports the growth of biofilm. The biofilm is modelled as 5 homogeneous layers, followed by an interface with the bulk liquid. Soluble components from the bulk liquid can diffuse into (and out of) the outermost biofilm layer (the one in contact with the liquid). The MABR membrane surface allows for the diffusion of oxygen through the membrane and into the innermost biofilm layer.
Figure 7‑26 - MABR biofilm structure, showing diffusion of soluble components
As the with the other biofilm models in GPS-X, each of the biofilm layers is modelled as a completely-mixed reactor. All aspects of solids transfer (internal solids exchange, attachment and detachment at the liquid/biofilm interface) are all modelled similar to the hybrid model.
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
The physical parameters are found under the Parameters sub-menu item Physical. It contains physical dimensions of the MABR unit, and details of the media surface area and biofilm properties.
The total amount of surface area available for growing biofilm is equal to the number of cassettes multiplied by the modules per cassette, cords per module and media length. The surface area per length of media is determined from the media outside diameter and the thickness of the biofilm. Therefore, the surface area per length of media increases with increasing media diameter and biofilm thickness.
Figure 7‑27 - MABR Physical Parameters Menu
Operational
The operational menu contains parameters that define the operation of the membrane aeration, conventional bulk liquid aeration and hydraulic settings (e.g. internal mixed-liquor recycle flow) of the MABR unit.
The first section of the menu, “Inner Biofilm Aeration” contains settings for specifying the mass transfer of oxygen from the membrane to the innermost biofilm layer. There are three options available for specifying oxygen transfer:
1) setting the mass transfer coefficient, kLa, in units of 1/d
2) setting the mass transfer of oxygen directly, in kg/d
3) using the pressure difference equation, which specifies the oxygen transfer through the length of the membrane using inlet and outlet pressure and oxygen fraction
The pressure-difference oxygen transfer model is described by Côté (1989), and is shown below:
Equation 7-4
where,
J = oxygen flux, mol/m2-sec
K = mass transfer coefficient, m2/sec
pin = partial pressure of oxygen at inlet, Pa
pout = partial pressure of oxygen at outlet, Pa
H = Henry’s Law constant, Pa-m3/mol
CL = oxygen concentration in liquid, mol/m3
The operational menu for selecting the method for specifying oxygen transfer is shown below.
Figure 7‑28 - MABR Operational Menu
Note that the kLa and pressure difference options incorporate the oxygen saturation term into the overall mass transfer, meaning that as the dissolved oxygen in the liquid (or biofilm, in this case) comes closer to saturation, the oxygen transfer decreases. This is not the case for the direct oxygen mass transfer setting. The amount of oxygen (in mass-per-unit-time terms) will be transferred, regardless of oxygen saturation. The user is should note that this can possibly result in the oxygen concentration in the innermost biofilm layers being above saturation.
The default setting for oxygen transfer specification is the pressure difference model.
Mass Transport Menu
The mass transport menu of the MABR object contains parameters relevant to the transport of components to, from, and within the layers of the biofilm. The menu is shown below:
Figure 7‑29 - MABR Operational Menu
These parameters are similar to those used in other biofilm objects:
attachment rate – a rate constant used to determine the mass flow of solids from the bulk liquid to the outermost biofilm layer
detachment rate – a rate constant used to determine the mass flow of solids from the outermost biofilm layer to the bulk liquid
anoxic shear reduction factor – a parameter which reduces the amount of detachment in tanks with no aeration, to simulate the calmer conditions present without diffused aeration
internal solids exchange rate – a parameter used to determine the mass flow of solids between internal layers in the biofilm
For details on how the attachment/detachment and solids exchange rates are calculated, please see the details of the trickling filter model.
The Mass Transport menu also contains further constants for the diffusion of soluble components through the biofilm. These are accessed by clicking on the MORE… button at the bottom of the menu. The menu that pops up contains diffusion constants for each of the soluble components as well as the biofilm reduction factor. The reduction in diffusion constant for each soluble component is treated differently in the MABR model than it is in the other biofilm models in GPS-X. In the other models, there is one biofilm reduction factor that is applied to all the soluble components (default = 0.5). In the MABR model, each soluble component has its own biofilm reduction factor, which can be different from each other. In general, the default values for the different soluble components are 0.2 for organic components, and 0.8 for inorganic components, as per Stewart (2003).
Other Menus
Further model parameters are included in the stoichiometric and kinetic menu items. These forms are described in the
Trickling Filter Model section of this chapter.
Initialization
The initialization menu of the MABR object is the same as for other biofilm objects, and contains the initial concentrations of the state variables in each layer of the biofilm.
Output Variables
In addition to the standard effluent parameters, there are a number of fixed film specific variables that can be displayed. These are accessed through the object's Output Variables menu item.
The MABR Performance Variables menu contains several display unique state variables that illustrate the mass transfer and concentrations of various elements throughout the biofilm. The menu is shown below.
Figure 7‑30 - MABR Performance Variables Menu
The 1-D Rates section contains output variables such as nitrification rate and oxygen transfer rate, calculated in various ways. The Ammonia Fate section summarizes the transformation of ammonia in the reactors of the MABR unit (e.g. how much is removed biologically, how much diffuses into the biofilm, and how much remains in the bulk liquid).
The 1-D Masses and 1-D Mass Flows summarize the distribution and fate of the heterotrophic, ammonia-oxidizing, and nitrite-oxidizing biomass in the bulk liquid and the biofilm. The 2-D Concentrations section contains 2-dimensional array variables of the various soluble and particulate components in the biofilm. These variables are intended to be displayed on a “3D Bar Graph” type, and appear as shown below:
Figure 7‑31 - MABR Performance Variables Menu
In these diagrams, the orientation of the media, bulk liquid and the biofilm layers is shown below:
Figure 7‑32 - MABR Performance Variables Menu
Membrane-Aerated Bioreactor (MABR) – Flat Sheet
Another MABR model uses flat-sheet membranes for aeration and biofilm growth. It is found in the Attached Growth section of the Unit Process Table.
Figure 7‑33 – Membrane Aerated Bioreactor – Flat Sheet Model Configuration
Figure 7‑34 shows the structure of the Flat Sheet MABR model, compared to the Hollow Fibre MABR, the Flat Sheet MABR contains an air spacer in between membranes, oxygen passes through the self-respiring membrane envelope to the mixed liquor side of the MABR surface helps to grow and sustain the biofilm of autotrophic organisms capable of using chemical energy to synthesize their own food from inorganic substances (i.e. ammonia).
Figure 7‑34 - Flat Sheet MABR biofilm structure, showing diffusion of soluble components
Model Parameters
This section of the chapter discusses the various model parameters and inputs that the user will encounter when using this model.
Physical
Similar to the hollow fibre MABR unit, the physical parameters are found under the Parameters sub menu item Physical. It contains physical dimensions of the MABR unit, and details of the media surface area and biofilm properties.
The total amount of surface area available for growing biofilm is equal to the number of spirals multiplied by the area per spiral.
Figure 7‑35 - Flat Sheet MABR Physical Parameter Menu
Operational
The operational menu contains parameters that define the operation of the membrane aeration, conventional bulk liquid aeration and hydraulic settings (e.g. internal mixed-liquor recycle flow) of the MABR unit.
The first section of the menu, “Inner Biofilm Aeration” contains settings for specifying the oxygen membrane diffusion mass transfer coefficient.
Figure 7‑36 - Flat Sheet MABR Operational Menu
Other Menus
The rest of the menus of the Flat Sheet MABR object are the same as the Hollow Fibre MABR Object.
High-Rate Primary Filter
Filtration performance can be affected by environmental and operational factors. The high-rate primary filter model is a data-driven model for up-flow filtration that relates concentration-based removal efficiency to solids loading per unit area, backwash fraction and temperature. This object is found under found in the Primary Treatment section of the Unit Process Table.
Figure 7‑37 - High-Rate Primary Filter Model Configuration
Introduction
The data driven model was created using data from a 2-metre-deep filter, thus the average removal efficiency term is specific to that depth. If the depth of filter bed is changed the model calculates a removal efficiency for that depth (REA, DF) using a filter coefficient (λ) calculated from the average removal efficiency for a 2m deep filter:
Equation 7‑3
The backwashing coefficient, temperature coefficient and solids loading per filter area coefficient can be adjusted to calibrate the sensitivity of the filter to the respective parameters. The max removal efficiency of filter and min removal efficiency of filter bound the removal efficiency equation.
The removal efficiency (RE) calculated by the data-driven model is concentration-based. Thus, the effluent solids concentration (Xo) is calculated as:
Equation 7‑4
The volume per backwash as a fraction of filter volume and backwash frequency are used to calculate a continuous backwash flow. The effluent flow is calculated as the difference between the influent flow and the backwash flow. A simple mass balance on the solids across the filter is used to determine the solids concentration in the backwash stream.
The range of data used to train the high-rate primary filter model is shown below. Caution should be taken when applying the model to predict filter performance with inputs that fall outside one or more of these ranges.
Table 7‑1 - The range of data used to train the high-rate filter model.
|
Parameter |
Range |
|
Backwash fraction |
Valid between 0.059-0.67 |
|
Temperature |
Valid between 10.7-28.3 |
|
Loading per filter area |
Valid between 7.93-357
|
Physical
The physical menus for the high-rate primary filter object are shown in the figure below.
Figure 7‑38 - Physical menu for the high-rate primary filter.
Operational
The operational menus for the high-rate primary filter object are shown in the figure below.
Figure 7‑39 - Operational menu for the high-rate primary filter.
High-Rate Biological Filter
The high-rate biological filter model is a stacked up-flow filter model with a non-aerated zone followed by an aerated zone. The model was developed by integrating the high-rate primary filter model with a biological filter model. This object is found under found in the Attached Growth section of the Unit Process Table.
Figure 7‑40 - High-Rate Biological Filter Model Configuration
The sequential calculation scheme is outlined below.
1. Use the high-rate primary filter model to calculate the solids removal efficiency in the non-aerated zone of the filter
2. Use the effluent of the anoxic zone as the influent of the aerobic zone, and use a modified version of the simple biological aerated filter to model the aerobic zone
a. Further solids capture is performed
b. Biological reactions remove organics (particulate and soluble)
c. Calibration parameters include maximum biofilm thickness, specific surface area, etc.
Physical
The physical input menu for the high-rate biological filter object is shown in the figure below.
Figure 7‑41 - Physical menu for high-rate biological filter.
Operational
The major difference between the high-rate biological filter and the simple BAF model is the presence of the non-aerated zone. The two zone depths can be specified independently in the input menu. Additionally, a filter coefficient can be specified. This is used to calculate the overall removal efficiency in the filter using the depth of the anoxic zone and a corrected depth of the aerobic zone (corrected due to the reduced solids removal performance with aeration). The operational input menu for the high-rate biological filter object is shown in the figure below.
Figure 7‑42 - Operational menu for high-rate biological filter.
The backwashing and solids removal in the unaerated zone are calculated in the same manner as the high-rate primary filter. In the aerobic zone the solids removal is either calculated using the filter coefficient (specified on the physical menu) or the solids capture in the aerobic zone parameter. A simple mass balance on the solids across the filter is used to determine the solids concentration in the backwash stream.
The aeration can be specified either by entering
a KLa, airflow per unit area, or the DO setpoint in the
effluent.