Tank Filling System CFD Analysis - ANSYS Fluent Simulation

Project Overview

This computational fluid dynamics investigation examines tank filling operations between two interconnected reservoirs using ANSYS Fluent software. The simulation focuses on two-phase flow dynamics involving air and water phases within tanks of equal height, representing common industrial applications in chemical processing operations.

Industrial Applications

Tank filling systems play crucial roles in chemical industry operations where component separation, mixture processing, and pure substance extraction are essential. These systems require careful analysis of two-phase interactions to optimize performance and ensure operational safety during fluid transfer processes.

Multiphase Flow Analysis

The simulation employs the Volume of Fluid (VOF) methodology to investigate the complex interactions between water and air phases during the filling process, providing insights into interface dynamics and pressure equilibration mechanisms.

System Configuration and Geometric Design

Reservoir Specifications

The computational domain consists of two identical rectangular reservoirs, each measuring 1.25 meters in width by 2.5 meters in height. This configuration enables analysis of fluid transfer between tanks of equal capacity under gravitational influence.

Two-Dimensional Model Development

The geometric configuration was developed using ANSYS Design Modeler software, incorporating realistic tank dimensions and interconnecting pathways to simulate industrial filling operations. The design facilitates investigation of hydrostatic pressure effects and air-water interface behavior during the filling process.

Computational Grid Configuration

Structured Mesh Implementation

The computational grid was generated using ANSYS Meshing software with a structured mesh topology containing 32,510 computational cells. The structured mesh approach provides enhanced accuracy for capturing the regular geometric features and ensures efficient computational performance for the transient simulation.

Grid Quality Optimization

The mesh density and distribution are optimized to accurately resolve the air-water interface movement and capture the pressure-driven flow phenomena throughout the filling process.

CFD Simulation Configuration

Fundamental Modeling Assumptions

The simulation utilizes a pressure-based solver approach appropriate for incompressible flow conditions. The analysis is conducted in transient mode to capture the temporal evolution of the filling process and interface dynamics. Gravitational acceleration of -9.81 m/s² is applied along the negative y-axis to drive the filling phenomenon and establish hydrostatic pressure gradients.

Multiphase Flow Modeling

The Volume of Fluid model governs the two-phase flow field with air designated as the primary phase and water as the secondary phase. Sharp interface modeling ensures accurate tracking of the air-water boundary throughout the filling operation. The implicit formulation provides robust solution stability for gravitational flow applications with significant density differences between phases.

Turbulence Modeling

The realizable k-epsilon turbulence model with standard wall functions is employed to capture turbulent flow effects that may develop during the filling process. This approach provides accurate representation of turbulent mixing and energy dissipation while maintaining computational efficiency.

Material Properties

Air properties are defined with density of 1.225 kg/m³ and dynamic viscosity of 1.7894×10⁻⁵ Pa·s, representing standard atmospheric conditions. Water properties utilize density of 998.2 kg/m³ and dynamic viscosity of 0.001003 Pa·s, corresponding to water at standard temperature conditions.

Boundary Condition Specifications

The tank walls are configured as stationary wall boundaries with no-slip conditions to accurately represent the physical constraints. Inlet and outlet vents are specified as pressure boundaries with zero gauge pressure, allowing atmospheric pressure communication and air circulation during the filling process. The pressure profile multiplier is set to unity for standard atmospheric conditions.

Numerical Solution Methods

The pressure-velocity coupling employs the COUPLED algorithm for enhanced convergence in multiphase applications. Pressure discretization utilizes the PRESTO scheme, optimized for complex geometries with density variations. Momentum equations are solved using second-order spatial discretization for improved accuracy, while volume fraction transport employs the compressive scheme to maintain sharp interface definition. Turbulent kinetic energy and dissipation rate equations utilize first-order upwind discretization for numerical stability.

Domain Initialization and Patching

Standard initialization is applied throughout the computational domain with subsequent patching operations to establish initial water distribution. The water phase is patched with unity volume fraction in designated surface-body zones to represent the initial filling configuration.

Temporal Solution Configuration

The simulation employs a fixed time step size of 0.001 seconds with maximum of 20 iterations per time step to ensure convergence. The total simulation spans 10,000 time steps, providing comprehensive coverage of the filling process dynamics and pressure equilibration.

Results and Flow Analysis

Filling Process Characterization

The simulation generates comprehensive two-dimensional contour visualizations depicting volume fraction distribution, pressure fields, velocity magnitude, and turbulent kinetic energy throughout the filling evolution. These results provide detailed insight into the complex multiphase flow phenomena occurring during tank filling operations.

Interface Dynamics and Air Movement

The volume fraction contours demonstrate the upward movement of the air phase as water fluid advances toward the tank containing air. This behavior illustrates the fundamental principle of fluid displacement and interface tracking accuracy of the VOF model throughout the filling process.

Hydrostatic Pressure Equilibration

The pressure field analysis reveals the establishment of hydrostatic pressure equilibrium at equal heights within both tanks after several seconds of simulation time. This phenomenon demonstrates adherence to fundamental fluid statics principles and validates the simulation’s physical accuracy.

Engineering Insights

The velocity and turbulent kinetic energy distributions provide valuable information about flow patterns, mixing characteristics, and energy dissipation during the filling process. These results enable optimization of tank filling operations and assessment of system efficiency in industrial applications.

Temporal Evolution Analysis

The animated results demonstrate the progressive nature of the filling process, showing how the air-water interface evolves over time and how pressure gradients develop to drive the fluid transfer between reservoirs.