COMPUTATIONAL FLUID DYNAMICS

EXPLORE THE DYNAMICS OF FLUIDS WITH COMPUTATIONAL FLUID DYNAMICS (CFD)
WHERE ENGINEERING MEETS PRECISION SIMULATION
Decoding Fluid Behaviour with Algorithms

UNDERSTANDING CFD: DECODING FLUID BEHAVIOUR WITH ALGORITHMS

Computational Fluid Dynamics (CFD) is a branch of fluid mechanics that utilizes numerical methods and algorithms to analyze and solve problems involving fluid flow. It’s a powerful tool for engineers and scientists to simulate and understand the behaviour of fluids in various scenarios without relying solely on costly and time-consuming experimental tests.

Analysis Type

multiphase

Multi Phase and Multi Species

Multi-phase refers to simulations involving multiple phases of matter to account for interactions between liquids, solids and gases.

For accurate simulations of Industrial applications, such as liquid-gas, solid-liquid, or even more complex scenarios like free surface flows (e.g., air-water interfaces). Similarly, “multi-species” simulations involve the modeling of multiple chemical species or components within a fluid mixture. Phase Interaction Models: ANSYS Computational Fluid Dynamics provides various models to simulate interactions between different phases, such as Volume of Fluid (VOF), Eulerian-Eulerian, Eulerian-Lagrangian, etc. These models describe how phases interact, mix, and exchange mass, momentum, and energy. Species Transport Models: For multi-species simulations, ANSYS CFD offers different approaches to model species transport, including species mass transport equations, mixture fraction models, and more complex models like the species transport model with turbulent chemistry.
Computational Fluid Dynamics simulations are used to predict and prevent overheating, thermal stress, and component failure in electronic devices, mechanical systems, vehicles, industrial processes, and energy systems. It involves dissipating heat effectively, maintaining optimal operating temperatures, and ensuring thermal equilibrium to enhance performance and longevity. Conjugate Heat Transfer (CHT) refers to the analysis of heat transfer phenomena where both fluid flow and solid conduction are considered simultaneously. This is crucial in systems like electronic cooling where heat generated by solid components must be dissipated efficiently through both fluid and solid materials, engine cooling systems, and industrial processes where understanding the interaction between fluid flow and heat transfer in solid materials is crucial for optimizing thermal performance.

Internal Aerodynamics focuses on airflow within ducts, pipes, engines, and HVAC systems. Computational Fluid Dynamics simulations are used to analyze aerodynamic performance, drag reduction, and airflow optimization in these applications.

It is common in aerodynamics, ventilation systems, and low-speed fluid dynamics applications. Computational Fluid Dynamics is used to study airflow patterns, pressure distributions, and lift/drag forces in subsonic flow regimes. Transonic Flow occurs when fluid flow transitions from subsonic to supersonic speeds, typically around the speed of sound. It is relevant in aerodynamics, turbo machinery, and aircraft design. CFD simulations help analyze shock waves, flow separation, and aerodynamic performance in transonic conditions.

Supersonic Flow refers to fluid flow where the flow velocity exceeds the speed of sound. It is encountered in high-speed aerodynamics, propulsion systems, and aerospace applications. Computational Fluid Dynamics simulations are used to study phenomena such as shock waves, compressibility effects, and supersonic flow behavior.

To study the generation, propagation, and control of noise and vibrations in aerospace and mechanical systems. It is applicable in aerospace, automotive, and industrial settings where reducing noise and controlling vibrations are critical for performance and comfort.

Computational Fluid Dynamics simulations are used to analyze thermal behavior, optimize cooling strategies, and improve the overall efficiency and safety of battery systems in electric vehicles, energy storage systems, and portable electronics.

In computational fluid dynamics (CFD), FSI simulations involve modeling the coupled behavior of fluids and structures to analyze how fluid forces affect the deformation and response of solid objects. It is important in applications such as aircraft wings, wind turbines, and biomedical devices where understanding how fluid forces affect structural behavior is essential for design optimization and performance prediction.

Hydraulic systems utilize fluid (typically oil or water) to transmit power and control mechanical motion. Computational Fluid Dynamics simulations are employed to model fluid flow in hydraulic circuits, analyze pressure distributions, optimize component designs and ensure efficient energy transfer and system performance.

Pumps and turbines are essential components in fluid power systems, industrial processes, and energy generation. Simulation of fluid flow through pumps (centrifugal, positive displacement) and turbines (gas, steam, hydraulic) helps to analyze performance characteristics (flow rates, pressures, and efficiencies), optimize designs for maximum efficiency, and troubleshoot issues like cavitation and flow separation.

Valves play a crucial role in regulating fluid flow, pressure, and direction in hydraulic and fluid control systems. Computational Fluid Dynamics simulations help in designing and optimizing valve geometries, analyzing flow characteristics (such as pressure drops, and flow velocities), predicting valve performance under different operating conditions, and improving control system responsiveness and stability.

CFD simulations are used to model combustion processes in engines (internal combustion engines, gas turbines), furnaces, boilers, and industrial reactors. These simulations help optimize combustion efficiency, analyze flame characteristics, predict temperature distributions, and improve fuel consumption and emissions performance. Computational Fluid Dynamics is also utilized to model complex chemical reactions occurring in reactive flows, such as combustion, pyrolysis, gasification, and chemical reactions in reactors and industrial processes. It allows engineers and researchers to predict reaction kinetics, species concentrations, and product distributions, aiding in the design and optimization of chemical processes and reactors.

Computational Fluid Dynamics simulations are used to model the flow of molten polymer, predict temperature distributions, optimize cooling strategies, and analyze material behavior during shaping and solidification. This helps in designing efficient molds, reducing cycle times, minimizing defects, and improving the mechanical properties of polymer products.

It involves developing custom functions, user-defined features, and tailored simulation methodologies to enhance the capabilities and flexibility of CFD simulations for specific applications or industries.

Applications

combustion
Combustion Stability
Combustion stability is a paramount concern as it can lead to engine component erosion. Use Ansys to ensure stable and efficient combustion, preventing damage to engine components.
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Aerodynamics
Ansys simulation empowers you to enhance automotive & aerospace exteriors by minimizing drag, decreasing weight, and enhancing fuel efficiency and range.
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gasturbines
Gas Turbines
Ansys gas turbine simulation solutions empower you to conceptualize and enhance the design of next generation gas turbines.
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gasliquid
Gas Liquid Systems
Discover how Ansys' multiphysics simulation allows you to effectively upscale gas-liquid process equipment for enhanced yield and efficiency optimization.
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mixing
Mixing
Ansys fluid mixing simulation tools aid in modeling the process of mixing and blending one or more fluid-like materials.
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batterysimulation
Battery Simulation
Ansys empowers you to enhance battery designs by balancing safety, performance, size, cost, and reliability, positioning you as a market leader. The multiphysics battery simulation solution facilitates the integration of interdisciplinary expertise across various scales.
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