Computational Fluid Dynamics (CFD) modeling to optimize design of biological treatment reactor-...

COMPUTATIONAL FLUID DYNAMICS (CFD) MODELING TO OPTIMIZE DESIGN OF BIOLOGICAL

TREATMENT REACTOR

Robert B. Stallings, P.E. Ryan Edison

Earth Tech, Inc. 196 Baker Avenue

Concord, MA 01742 ABSTRACT The City of Newport, Rhode Island is located on an island at the mouth of Narragansett Bay in the southeastern part of the state. The Newport Wastewater Treatment Facility (WWTF) is a secondary treatment facility utilizing the conventional activated sludge process to provide removal of pollutants. As part of an on-going Capital Improvement Program the City is having the existing Aeration tanks retrofitted with membrane style fine-pore diffusers to replace the existing mechanical aerators. Computational Fluid Dynamics (CFD) was used to analyze the flow characteristics of the four (4) aeration tanks at the Newport, RI WWTP after the existing mechanical mixing and aeration system is removed. Conditions with and without influent target baffles were modeled. The Capital Improvement Plan entails the replacement of the mechanical aerators with a fine bubble diffused aeration system. The initial design included inflow and outflow structures, combined with two mechanical mixers in each tank. After the removal of these mixers, the overall flow distribution pattern within each tank is important to assess. The CFD analysis looks at the relative flow pattern through the tank under both unbaffled and baffled conditions. INTRODUCTION AND BACKGROUND The Newport WWTF receives flow from a combined sewer system. The WWTF was designed to discharge monthly average flows of 10.7 million gallons per day (mgd) to Narragansett Bay. The WWTF peak design flow is 30.0 mgd. The WWTF treats flow from the City of Newport, Town of Middletown, and United States Navy. The WWTF utilizes the following unit processes to provide treatment:

• A headworks with two (2) aerated grit chambers, and two (2) comminutors.

• Six (6) rectangular primary clarifiers with a total effective surface are of 15,360 square feet.

• A primary effluent lift station utilizing three (3) screw pumps 72-inches in diameter, each

rated to deliver 10,400 gallons per minute (gpm) at a total dynamic head (TDH) of 11 feet.

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Copyright ©2002 Water Environment Federation. All Rights Reserved.

• Four (4) aeration tanks with a total volume of 2.3 million gallons.

• Four (4) secondary clarifiers each 90 feet diameter with a sidewater depth of 12 feet.

• Two (2) chlorine contact tanks.

• An effluent pump station utilizing three (3) screw pumps 72-inches in diameter.

• Raw sludge is mechanically thickened, and disposed of by a private contractor.

The WWTF must meet secondary treatment standards. Table 1 shows current effluent discharge permit requirements. AERATION SYSTEM DESIGN The four existing Aeration Tanks are arranged to operate in the conventional activated sludge, plug-flow configuration. The tanks are not configured to operate in the step-feed, or contact-stabilization modes. Each aeration tank is 50 feet width, 100 feet length, with a sidewater depth of 15 to 16 feet. Prior to the upgrade each aeration tank contained two (2) mechanical aerators. Each mechanical aerator was 60 horsepower. After the upgrade is completed fine pore diffused aeration will be utilized. Table 2 shows a summary of the design criteria for the upgraded secondary treatment system. Flow enters each tank through a 2.5 foot by 2.5 foot sluice gate. The invert of this sluice gate is located approximately 10.5 feet above the bottom of the tank and is located along either the right or left-hand side of the front wall. The outflow weir is located directly inline with this inlet gate and has an invert approximately 15.2 feet above the bottom. This asymmetric construction is the principle concern for causing poor mixing and short-circuiting within the tank under the new aeration conditions (i.e. fine pore diffusers). DESCRIPTION OF CFD MODELING Computational Fluid Dynamics involves the use of a computer to investigate the dynamic behavior of liquids and gases. The abbreviation, CFD, is commonly used in reference to computer programs for determining fluid motion in three-dimensions. CFD programs are designed to produce simulations of fluid flows influenced by a wide variety of physical processes (e.g., heat conduction, solidification, cavitation, and surface tension). Because these programs are based on the fundamental laws of mass, momentum, and energy conservation, they are applicable to almost any type of flow process. For this reason CFD programs are referred to as “general purpose” solvers.

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The roots of CFD, in the United States, may be traced back to original developments at the Los Alamos National Laboratory (LANL) beginning in the early 1960s. Many basic numerical techniques originated there for the solution of compressible and incompressible flow problems. Of particular interest are techniques for describing the behavior of free surface flows, a technique for solving both compressible and incompressible flow problems with a single solution method, and emerging types of grid and geometry models. Widespread commercial use did not begin until the early 1980’s when CFD analysis was adopted by the aerospace industry for solving external flow problems (aerodynamics) and for designing fuel control systems (sloshing). Today, CFD is used extensively by hydraulic engineers, bio-medical engineers, automotive engineers, metal casters and inkjet designers to solve difficult flow problems. CFD involves the solution of the governing equations for fluid flow (Navier-Stokes) at thousands of discrete points within a computational grid. All of the computations presented were done using a fixed (Eulerian) grid of rectangular control volumes because these are efficient to generate and they possess many other desirable properties (e.g., increased accuracy, smaller demands on memory, and simpler numerical approximations). Next, a special technique called the Fractional-Area-Volume-Obstacle-Representation (FAVOR) method was used to define general geometric regions within the rectangular grid. This method uses partial control volumes to provide the advantages of a body-fitted grid but retains the construction simplicity of ordinary rectangular grids. The method also allows for the calculation of flow through “porous” media.

In this study, the Volume-of-Fluid (VOF) technique was used to track the motion of fluid through the grid. The method consists of three elements: a VOF function for defining fluid regions, a special advection method that maintains a sharp definition of fluid surfaces as they move and deform within the computational grid, and the application of normal and tangential stress boundary conditions at the fluid surfaces. The VOF method is capable of modeling extremely complex fluid behaviors involving any number of independent free fluid surfaces. The VOF method also allows for the breakup and coalescence of fluid surfaces. The computational mesh of the Newport Aeration Tank CFD model was constructed consisting of approximately 75,000 control volumes (100 in the direction of flow, 15 in the vertical direction and 50 laterally). The control volumes were sized uniformly. A number of these control volumes were occupied by solid mass for the modeling to simulate the influence of having columns supporting the mechanical aerator platforms located within the flow stream. The FAVOR method was used to “build” the aeration tank within the computational mesh. Actual dimensional data of the aeration tanks (as provided from record drawings) were used to construct the computational model. The VOF method was used to define the initial fluid configuration. In all cases, the mesh was “filled” with water and all flow speeds were set to zero. The flow in the model domain was controlled by boundary conditions set upstream (fluid velocity and density set at the inlet gate), downstream (fluid velocity set at the effluent weirs), and at the fluid free surface (atmospheric pressure and zero shear). Additionally, a no-slip condition was specified at solid boundaries within the model domain. These same boundary conditions were used for all of the calculations made.

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The movement of marker particles through the aeration tank were calculated, and the results used to estimate the detention time provided by the baseline condition (without inlet baffles) and for alternative condition (with an inlet baffle). Comparing the detention time provided by this enhancement provided a way to evaluate the effectiveness of the upgrade scheme with the baffle. The CFD analysis was performed using Tank 3. The other tanks are hydraulically similar, with flow inlets positioned directly opposite of the flow outlets. The modeled inflow was 11.25 MGD (or 17.4 cfs) per basin. This represents the peak hydraulic flow condition which is equally divided between the four basins (where 30 mgd of primary effluent and 15 mgd of return activated sludge are flowing through the system). This flow was distributed uniformly across the inlet as a set velocity boundary condition. The outlet velocity was determined using model results under “steady-state” conditions. One foot cells were used for the model computations. After the development of baseline (or steady state) runs, massless particles were released at the inlet and tracked throughout the fluid field. These particle runs provided visual information on the behavior of each condition and also gave approximations of travel times (the time at which released particles begin exiting the tank via the outlet weir). The CFD model showed stark contrast in the relative performance between the unbaffled, and baffled conditions. In the unbaffled condition, a strong current develops and heads directly across the tank to the outlet weir. Particle runs show a minimum particle travel time of approximately 1.3 minutes for the unbaffled case. Figure 1 shows a velocity distribution plot for the unbaffled condition. The colored mass is an area of constant velocity of 0.7 feet per second (fps). The maximum particle velocity through the tank is approximately 1.28 fps without the baffle. Figure 2 shows a plot of the flow streamlines for the particles with the maximum velocity. The baffle in front of the inlet gate significantly reduced the current, and dramatically increased the minimum estimated particle travel time through the reactor. The minimum particle travel time is increased to 10.5 minutes by installation of a solid baffle directly in front of the inlet sluice gate. Figure 3 shows a velocity distribution for the baffled condition. The colored mass is an area of constant velocity of 0.2 fps. The maximum particle velocity through the tank is reduced by the baffle. Figure 4 shows a plot of the flow streamlines for the particles with the maximum velocity.

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CONCLUSIONS In summary, the CFD modeling demonstrated the following:

• The relative flow characteristics of the unbaffled case indicate the presence of a strong current shooting directly across the tank. This current is broken up and distributed laterally across the tank when the baffle is added.

• There is an almost eight (8) fold increase in the minimum particle travel time between the

baffled and unbaffled conditions.

• Adding the baffle should improve the overall treatment efficiency within the biological treatment reactor. The baffle should be included to optimize performance of the fine-pore aeration system design.

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Figure 1 Newport, Rhode Island

Aeration System CFD Modeling Unbaffled Aeration Tank No. 3 – Velocity Distribution

Note: Constant Surface of Velocity in the x-direction (colored by speed, 0.7 fps) Computational Grid Showing Velocity in the x-direction (colored by speed, 0.0 to 0.7 fps)

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Aeration System CFD Modeling Unbaffled Aeration Tank No. 3 – Flow Streamlines

Note: Streamlines (placed at inflow location) Computational Grid Showing Velocity in the x-direction (colored by speed, 0.0 to 0.7 fps)

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Aeration System CFD Modeling Baffled Aeration Tank No. 3 – Velocity Distribution

Note: Constant Surface of Velocity in the x-direction (colored by speed, 0.2 fps) Computational Grid Showing Velocity in the x-direction (colored by speed, 0.0 to 0.2 fps)

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Aeration System CFD Modeling Baffled Aeration Tank No. 3 – Flow Streamlines

Note: Streamlines (placed at inflow location)

Computational Grid Showing Velocity in the x-direction (colored by speed, 0.0 to 0.2 fps)

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TABLE 1 NEWPORT, RHODE ISLAND

WWTF EFFLUENT DISCHARGE PERMIT LIMITS

Parameter

Monthly Average

Weekly Average

Daily Maximum

Flow (MGD) 10.7 -- 19.7 Biochemical Oxygen Demand (mg/L) 30 45 50 Total Suspended Solids (mg/L) 30 45 50 Settleable Solids (ml/l) 0.1 -- 0.3 Fecal Coliform Bacteria (#/100 ml) 200 400 400 Chlorine Residual (mg/L) 0.59 -- 0.86 Toxicity testing (% survival-LC50) 100 -- -- pH -- -- 6 to 9.0

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TABLE 2 NEWPORT, RI

SECONDARY TREATMENT SYSTEM DESIGN CRITERIA

Parameter Design Criteria Design Average Flow 10.7 mgd Design Peak Instantaneous Flow 30.0 mgd Influent Biochemical Oxygen Demand (BOD5) Load 20,800#/day Influent Total Suspended Solids (TSS) Load 22,000#/day Primary Effluent BOD5 Loading 12,480#/day Total Aeration Volume 2.3 mg Aeration Tank Detention Time 5.2 hrs. BOD5 Loading 40 lbs/day/1,000 cf Mixed Liquor Concentration 1,800 mg/L Minimum Wastewater Temperature 10°C Maximum Wastewater Temperature 22°C Sludge Yield 0.75 #TSS/#BOD5 removed Mean Cell Residence Time 4 days Food to Micro-organism (F/M) Ratio 0.36 Design Waste Activated Sludge Quantity 8,691#/day Peak Actual Oxygen Requirement (AOR) 1,067#/hr Type of Diffuser Fine Pore Diffuser Material EPDM Rubber Alpha Factor 0.60 Beta Factor 0.98 Minimum Dissolved Oxygen Concentration 2.0 mg/L Diffuser Submergence 13.94 ft Minimum Standard Oxygen Transfer Efficiency 27.5% Estimated Actual Oxygen Transfer Efficiency 13.0% Total Design Peak Air Flow 7,820 scfm Type of Aeration Blower Centrifugal Number of Blowers 3+1 standby Design Maximum Inlet Air Temperature 95 F Design Inlet Air Relative Humidity 90% Blower Capacity Each Unit 2,900 icfm Estimated Blower Operating Pressure 8.0 psig Secondary Clarifier Type Circular Number of Secondary Clarifiers 4 each Diameter Each 90 ft. Sidewater Depth Each 12 ft. Average Hydraulic Loading 420 gpd/sf Instantaneous Peak Hydraulic Loading 1,179 gpd/sf Average Return Sludge Flow 10.7 mgd Peak Return Sludge Flow (2 pumps at maximum) 15.3 mgd Average Secondary Clarifier Solids Loading 12.6#/day/sf Peak Secondary Clarifier Solids Loading 26.7#/day/sf

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