Optimal Design of Water Treatment Contact Tanks
Abstract
:1. Introduction
2. Computational and Optimization Models
2.1. Flow Model
2.2. Conservative Tracer Model
2.3. Computational Domain and Boundary Conditions
2.4. Optimization Model
2.5. Simulation-Optimization Procedure
3. Results
3.1. Baffle without Slots
3.2. Finite Width Slot Baffle Population
3.3. Full Width Slot Baffle Population
3.4. Optimal Baffle Geometry
4. Discussion
5. Conclusions
- The multidimensional design concept introduced is important in the overall design of the contact tanks since it provides a platform to include multiple design criteria that would contribute to the overall performance of contact tank design beyond a one-dimensional approach of baffle geometry design to improve mixing.
- The appropriate development of the optimization algorithm is important since a multitude of optimization solution strategies exist in the literature for the solution of multi-dimensional optimization problems, such as multi-objective approaches. The strategy recommended in this study, which is the use of a single objective function approach, performed well for the problem considered in this case without artificial controls on the final selection.
- Simulation-optimization techniques have been previously used in the literature. The recommended CFD analysis combined with PGA assisted genetic algorithm approach provided a preferable and efficient computational platform for the application considered in this case and may be adopted in future studies.
- The optimum contact tank design achieved that would satisfy the four design objectives in a smart manner, and using a single objective function, yielded a new contact tank baffle design that was not reported in the earlier literature. This indicates that the multidimensional analysis concept developed in this study is an important concept which may be adopted in future studies.
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Boundary Conditions Used | |||
---|---|---|---|---|
Inlet Region | Outlet Region | Atmosphere Boundary | Wall Regions | |
U | mapped | inletOutlet | symmetryPlane | noSlip |
p | mapped | inletOutlet | symmetryPlane | zeroGradient |
k | mapped | inletOutlet | symmetryPlane | kqRWallFunction |
ε | mapped | inletOutlet | symmetryPlane | epsilonWallFunction |
nut | mapped | inletOutlet | symmetryPlane | nutkWallFunction |
Parameters | Cases Considered | |||
---|---|---|---|---|
Baffle 1 | Baffle 2 | Baffle 3 | Options | |
Number of Slots | 1, 2, 3, 4 | 1, 2, 3, 4 | 1, 2, 3, 4 | PGA Elim. 1, 2, 4 |
Finite Slot (w-mm) | 100, 110, 120, 160 | 100, 110, 120, 160 | 100, 110, 120, 160 | Random |
Finite Slot (h-mm) | 10, 12, 14, 16 | 10, 12, 14, 16 | 10, 12, 14, 16 | Random |
Full Slot (h-mm) | 10, 12, 14, 16 | 10, 12, 14, 16 | 10, 12, 14, 16 | Random |
Space between slots (mm) | 40, 42, 44, 46 | 40, 42, 44, 46 | 40, 42, 44, 46 | Random Sym. |
Parameters | PGA Parameters |
---|---|
Value | |
Population Size | 60 |
Crossover Ratio | 0.8 |
New Member Generation Ratio | 0.3 |
Elitism Ratio | Best Member |
Mutation Ratio | 0.2 |
Maximum generation for each Subdomain | 40 |
Slot Number | Optimal Slot Geometry |
---|---|
(w, h) (mm) | |
Slot 1 | (230, 12) |
Slot 2 | (230, 16) |
Slot 3 | (230, 14) |
Slot 4 | (230, 14) |
Slot 5 | (230, 16) |
Slot 6 | (230, 12) |
Slot 7 | (230, 12) |
Slot 8 | (230, 16) |
Slot 9 | (230, 14) |
Spacing between slots | (39, 38) |
Distance from base to first slot | (45) |
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Aral, M.M. Optimal Design of Water Treatment Contact Tanks. Water 2022, 14, 973. https://doi.org/10.3390/w14060973
Aral MM. Optimal Design of Water Treatment Contact Tanks. Water. 2022; 14(6):973. https://doi.org/10.3390/w14060973
Chicago/Turabian StyleAral, Mustafa M. 2022. "Optimal Design of Water Treatment Contact Tanks" Water 14, no. 6: 973. https://doi.org/10.3390/w14060973