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CFD and Optimization Study of Frictional Pressure Drop Through Bends
Suman Debnath1, Anirban Banik2, Tarun Kanti Bandyopadhyay3
1Department of Mathematics, NIT, Agartala, Tripura (W), Jirania, 799046, India.
Recent Patents on Biotechnology
|August 21, 2018
Summary
Optimizing fluid flow in pipe bends is crucial for bioengineering applications. Genetic Algorithm (GA) effectively minimizes frictional pressure drop in non-Newtonian fluid flow through bends, validated by CFD simulations.
Area of Science:
- Fluid Dynamics
- Computational Science
Background:
- Non-Newtonian pseudoplastic liquid flow in pipe bends presents complex challenges compared to straight pipes.
- Bends are critical in bioengineering, biotechnology, and biomedical fields, including biofluid studies and medical equipment design.
Purpose of the Study:
- To estimate the loss coefficient and frictional pressure drop of Newtonian and non-Newtonian fluid flow through pipe bends.
- To optimize frictional pressure drop using Genetic Algorithm (GA) and Gene Expression Programming (GEP).
Main Methods:
- Utilized commercial CFD software (Fluent 6.3) for flow simulations.
- Employed the Laminar Non-Newtonian Power Law model for Sodium Carboxy Methyl Cellulose (SCMC) solutions.
- Developed generalized input-output correlations using Gene Expression Programming (GEP) in MATLAB.
Main Results:
- The GA model accurately predicted and optimized pressure drop.
- Minimum pressure drop was achieved under optimal conditions: 133.16° bend angle, 0.2 Kg/m³ concentration, and 0.53 m/s velocity.
- Investigated the influence of flow rate, bend angle, and fluid behavior on static pressure and pressure drop.
Conclusions:
- The developed GA model demonstrates strong agreement with CFD results.
- The software-predicted data can aid in solving industrial problems and designing equipment for fluid flow applications.
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