As the population continues to grow, so too does the waste stream. At the same time, government regulations regarding the removal of nutrients (typically nitrogen and phosphorus) from treated wastewater that is discharged back into the environment grow ever more stringent. This confluence leaves many treatment facilities facing significant capital costs as they look to expand capacity and upgrade treatment processes. Optimization of the treatment process — making relatively small modifications to equipment and operating strategies rather than expanding the physical structure of a plant — can help facilities meet these standards and increase capacity without unnecessary capital investment.
Full-plant simulation models are powerful tools for evaluating, sizing, and optimizing wastewater treatment facilities. These simulators incorporate the latest advances in technical knowledge and can reliably predict performance if properly calibrated. Full-plant simulators do have limitations, however, most notably in their ability to simulate accurately the performance of clarifiers, which play a significant role in the wastewater treatment process.
Clarifiers, also known as settling and sedimentation tanks, provide separation of solid materials from the liquid stream through particle settling. Clarifiers are commonly used in two places in most municipal wastewater treatment plants:
1)Wastewater first enters primary clarification, where influent solids settle to the bottom of the tank and are typically pumped to the solids-handling process. Meanwhile, fats, oils, and greases rise to the top and are skimmed off and removed.
2)The wastewater then undergoes secondary treatment, during which micro-organisms consume much of the soluble and particulate organic pollutant material such as sugars, remaining fats, and organic short-chain carbon molecules. These organisms then bind together, or flocculate, becoming heavier and separating from the treated wastewater by gravity sedimentation in secondary clarifiers.
Secondary clarifier performance is vital for efficient wastewater treatment because it is often the final barrier to organic and solid material removal. Poor performance will lead to effluent quality violations and a gradual decrease in process capacity.
Clarifier performance depends on several interrelated factors. Hydrodynamics, turbulence, flocculation (ability of suspended solids to coagulate), the settling properties of the floc, and solids rheology (solids flow characteristics) all have an impact, as do atmospheric conditions, tank geometry, internal features, and loading conditions. Current full-plant simulators normally use one-dimensional clarifier models that cannot account for all these processes and factors and, therefore, do not offer an accurate simulation of clarifier performance. However, 2D and 3D computational fluid dynamics (CFD) can and do provide accurate simulation.
CFD is an advanced technique that can be used in clarifier design, troubleshooting, and optimization. It uses mathematical methods — and millions of calculations — to analyze systems that involve fluid motion, mass transfer, heat transfer, and their associated phenomena. The primary limitation of 2D and 3D CFD modeling is that its computational time is very demanding. Additionally, the biological reactions within — and outside — the clarifiers are normally not included in the model. This is an important facet of treatment process optimization that must be performed using a full-plant model.
2Dc CFD clarifier model
One of the state-of-the-art tools in CFD clarifier modeling is the 2Dc model, developed at the University of New Orleans under the supervision of Professor J. Alex McCorquodale, Ph.D. He is the North American pioneer in CFD modeling of clarifiers, and has more than 35 years of experience in development, testing, and application of these types of models.
The 2Dc model capitalizes on the exponential increase in the speed and memory of computers and the advancement in our understanding of the physical processes in clarifiers to offer users unprecedented insight. We can now accurately model crucial performance measures such as discrete, zone, and compression settling; flocculation; non-Newtonian flow; and floatable particles; in addition to variable internal tank options including skirts and baffles.
Users can quickly and cost-effectively model any number of different combinations of physical geometries (retrofits with baffles, modification to inlet conditions, et cetera) and hydrodynamics within a clarifier, simulating a full spectrum of possible loading and atmospheric conditions and comparing the results against current and potential effluent standards. These simulations readily identify needed improvements to existing clarifier infrastructure and operating strategies, ensuring improved reliability in meeting stringent effluent requirements and reducing operational and capital costs through optimization of existing facilities.
Calibrating a CFD model
As with any model, CFD must be used cautiously and with a good understanding of the processes and factors that affect clarifier performance. Model calibration and verification is crucial to model accuracy and the credibility of the model output.
The data needed for calibration and validation of a secondary clarifier CFD model includes the following:
- tank geometry and internal details;
- solids-settling properties (zone, discrete, and compression rates);
- flocculation parameters;
- mixed liquor suspended solids;
- effluent flow rate;
- secondary clarifier effluent suspended solids concentration;
- return activated sludge suspended solids concentration;
- sludge blanket depth and solids profile; and
- return activated sludge flow rate.
Sampling to acquire this data is best performed at typical operating conditions and during a simulated wet-weather event (stressed conditions), during which units are taken offline until the desired level of “stress” on the system is reached. Operating performance is then continuously monitored until performance reaches a determined “failure” point, such as high effluent total suspended solids (TSS) or high sludge blanket level, at which point the stress testing is ended.
A properly calibrated CFD model provides valuable results in just a few days, rather than the weeks it often takes to construct physical models. The 2Dc model produces clear visual representations of fluid flow, including animations and movies, as well as graphical representations of important elements of clarifier performance. These graphics illustrate the effect of increased flow of wastewater through the facility and the effect of proposed changes to clarifier infrastructure or operating strategies, simulating the corresponding suspended solids concentrations, velocity vectors, and sludge blanket depth, as well as many other parameters indicative of clarifier performance. With repeated simulations, the proper physical and operational modifications necessary to achieve the desired quality of effluent becomes clear.
Achieving optimized treatment
Wastewater treatment operation will only grow more complex over time. Plant capacities will continue to increase, regulations will continue to tighten, and more challenging contaminants will be identified in the waste stream. Fortunately, our understanding of how to be most efficient and effective in the treatment of wastewater will also continue to advance.
Treatment plant owners and operators already have powerful tools at hand to understand the effects of treatment process decisions on the quality of their treated effluent. By combining CFD, such as the 2Dc model, with sophisticated full-plant modeling software, we can achieve effluent quality that meets increasingly stringent standards and benefits both public health and the environment at optimum economic conditions.
Alonso Griborio, Ph.D., P.E., is a process engineer and Paul Pitt, Ph.D., P.E., is director of wastewater technology for Hazen and Sawyer. They can be contacted at email@example.com and firstname.lastname@example.org, respectively.