Abstract :

Fluid Dynamics Engineering Systems That Govern Flow In Pipelines, Turbomachinery, Heat Exchangers, Aerodynamic Surfaces, And Hydraulic Networks Demand Rigorous Mathematical Modeling Coupled With Computational Optimization To Achieve Efficient, Reliable, And Cost-effective Designs. This Paper Presents A Mathematical And Computational Framework For Modeling Incompressible Viscous Fluid Flow Using The Continuity And Navier-Stokes Equations, And For Optimizing System Parameters Such As Pipe Diameter, Flow Velocity, Pressure Drop, And Pump Power Through Gradient-based And Metaheuristic Optimization Techniques. The Governing Partial Differential Equations Are Discretized Using The Finite Volume Method, And The Resulting Nonlinear Algebraic System Is Solved Iteratively Using The SIMPLE Algorithm. An Optimization Layer Is Formulated As A Constrained Nonlinear Programming Problem That Minimizes Total Energy Loss Subject To Continuity, Momentum, And Geometric Constraints, Solved Using Gradient Descent And Genetic Algorithm Approaches. Simulation Experiments On Representative Pipeline And Duct Configurations Demonstrate That The Proposed Computational Optimization Framework Reduces Pressure Drop By A Significant Margin And Improves Overall Energy Efficiency Compared To Baseline Non-optimized Designs, While Maintaining Solution Convergence Within An Acceptable Number Of Iterations. The Results Confirm That Combining Rigorous Mathematical Modeling With Computational Optimization Provides A Systematic, Reproducible, And Scalable Methodology For The Design And Analysis Of Modern Fluid Dynamics Engineering Systems.

Published:

31-11-2022

Issue:

Vol. 22 No. 11 (2022)

Page Nos:

29-37

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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