(1) The family of k-ε turbulence models still remains among the most popular turbulence models for industrial applications.
(2) Most known and recognized among this family of turbulence models is the Jones-Launder k-ε turbulence model.
(3) The model supplies the flow equations with two additional partial differential turbulence equations. One for the turbulence kinetic energy and the other for its dissipation for the modeling of the entire turbulent flow field.
(4) The model is in this sense closed (i.e. no flow parameters are specified a priori besides calibration constants).
The following SlideShare from "AllAboutCFD" is a concise yet informative and communicated summary on the application of the k-ε model.
It is based on "AllAboutCFD" post: "Understanding The k-ε Turbulence Model" - https://lnkd.in/eBRieUQU#turbulence#fluidmechanics#fluidynamics#aerodinamics#engineering
I guess that modern CFD solvers like (Fluent, OpenFOAM and CFX) Are using Launder-sharma model because it provides a high performance and accuracy and because it is the up to date model (1974) while Jones-Launder k-epsilon model was in (1972).
I want to take a snapshot of this video and ask AI "please explain me about curl using this figure" 🤔
So this time, Google Gemini answered :
Okay, let's delve into the concept of curl, using this intriguing figure as our guide. Now, imagine you're observing a flowing river. You might notice leaves or twigs swirling and rotating as they're carried along by the current. This rotation within the fluid is what we're interested in when we talk about curl.
In essence, curl is a mathematical operator that quantifies the local rotation of a vector field. In the context of fluid dynamics, this vector field often represents the velocity of the fluid at different points. The curl at a specific point tells us how much the fluid is rotating around that point.
Now, let's connect this to the image you've provided. The black shape represents an airfoil, similar to the cross-section of an airplane wing. The red color variations depict the curl of the fluid velocity field around the airfoil. The deeper the red, the higher the curl, indicating stronger rotation.
You can visualize this as tiny whirlpools or vortices forming in the fluid as it flows over the airfoil. These vortices are a direct manifestation of the curl. The color intensity in the figure gives us a sense of how vigorously these vortices are spinning.
The curl is a fundamental concept in fluid dynamics, helping us understand phenomena like lift, drag, and turbulence. It's a powerful tool for analyzing and predicting the behavior of fluids in various scenarios.
Do you have any specific questions about curl or how it relates to this particular image? I'm here to help you grasp this concept in a way that's clear and intuitive.
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What do you think?
📈 We build scalable B2B marketing & sales systems for agencies, service providers and consultants | 🚀 Mechanical Engineer | 🧠 AI in Marketing
⚡Large eddy simulation of a pitching airfoil undergoing deep dynamic stall⚡
Representation of the flow field developed around a pitching airfoil under deep dynamic stall. This video shows how the large-scale Leading Edge Vortex is formed during pitch-up motion and it gets shed due to a Trailing Edge Vortex formed prior the maximum pitch angle is reached.
📝 Case simulated with the LES-solver Hydro3D and published in Journal of Fluids Engineering: https://lnkd.in/dQdwx2sv
🎬 Video Source: https://lnkd.in/dHHMGT8#cfd#simulation#engineering
⚡Large eddy simulation of a pitching airfoil undergoing deep dynamic stall⚡
Representation of the flow field developed around a pitching airfoil under deep dynamic stall. This video shows how the large-scale Leading Edge Vortex is formed during pitch-up motion and it gets shed due to a Trailing Edge Vortex formed prior the maximum pitch angle is reached.
📝 Case simulated with the LES-solver Hydro3D and published in Journal of Fluids Engineering: https://lnkd.in/dQdwx2sv
🎬 Video Source: https://lnkd.in/dHHMGT8#cfd#simulation#engineering
⚡Large eddy simulation of a pitching airfoil undergoing deep dynamic stall⚡
Representation of the flow field developed around a pitching airfoil under a deep dynamic stall.
This video shows how a large-scale Leading Edge Vortex is formed during pitch-up motion and shed due to a Trailing Edge Vortex formed before the maximum pitch angle is reached.
📝 Case simulated with the LES-solver Hydro3D and published in Journal of Fluids Engineering: https://lnkd.in/e3ys4QuK#cfd#simulation#engineering#aerodynamics
"Excited to share my recent project on modeling and simulating a bubbling fluidized bed reactor"
I delved into the complex dynamics of gas-solid interactions within this reactor, gaining valuable insights into its performance and optimization. This project allowed me to apply my skills in Modelling,research and CFD techniques.
Key findings include visualization of hydrodynamics and heat transfer in Fluidized bed reactor and to can make sure that there is fairly turbulent flow and investigate bubbling formation. This project open new horizons about multiphase flow and how can we model it obtaining interaction effects between phases and new models that can handle this phenomena.
Tip : make video on 0.5X 😅
#CFD#ANSYS#FluidizedBedReactor#ChemicalEngineering#Simulation#Modeling#MechanicalEngineering
⚡Large eddy simulation of a pitching airfoil undergoing deep dynamic stall⚡
Representation of the flow field developed around a pitching airfoil under a deep dynamic stall. This video shows how the large-scale Leading Edge Vortex is formed during pitch-up motion, and it gets shed due to a Trailing Edge Vortex formed prior to the maximum pitch angle being reached.
📝 Case simulated with the LES-solver Hydro3D and published in Journal of Fluids Engineering: https://lnkd.in/dQdwx2sv
🎬 Video Source: https://lnkd.in/dHHMGT8#cfd#engineering#simulation
🌊 In turbulent flows, the synergy between eddy viscosity (Vt)) and vortex behavior is crucial.💡
Eddy viscosity, a key component of turbulence modeling, characterizes momentum transport by resolved turbulent eddies. It is the key to capture complicated mixing phenomena at sub-grid scales, refining our understanding beyond the boundaries of the Navier-Stokes equations. 💨
Meanwhile, vortices, those captivating swirls in fluid motion, hold enormous effect on aerodynamics—shaping lift (L ), drag (D), and flow stability. Their relationship with eddy viscosity is complex; turbulent eddies contribute to viscosity, while vortex dynamics shape the flow field's energy distribution and dissipation rates.
Advanced turbulence models analyze vortex generation, evolution, and interaction. This comprehensive approach enables computational fluid dynamics to forecast and optimize engineering solutions with unparalleled precision and efficiency. 📈🔍
#EngineeringInsights#Aerodynamic#Fluid Dynamics #Turbulence#Engineering 🚀
Using Computational Fluid Dynamics (CFD) in ship design offers several key benefits that enhance performance and efficiency.
At 21 Knots Group, our expert and experienced team utilizes #CFD to simulate and analyze fluid flow around ship hulls, enabling precise predictions of hydrodynamic performance. This advanced modeling helps in optimizing hull shapes to reduce resistance, improve fuel efficiency, and ensure stability in various marine conditions.
CFD also aids in the assessment of #propeller performance and the interaction between hull and propeller, leading to better propulsion systems. By leveraging CFD, the marine industry can achieve significant cost savings and performance improvements.
For more information, contact us to discover how our solutions can benefit your ship design projects.
📧 info@21-knots.com
📞 +91 99676 13005
#21KnotsGroup#ShipDesign#CFD#MarineEngineering#FluidDynamics#Hydrodynamics#HullOptimization#FuelEfficiency#PropulsionSystems#MarineTechnology#PerformanceImprovement
Discover the underwater magic of computational fluid dynamics (CFD) 🌊
Our Insights article reveals 13 enchanting examples of how CFD can be used to make ship propulsion more efficient – from identifying propeller or thruster issues to improving waterjet performance.
See a sneak peek of 5 examples below and click here to find out more 👉 https://wartsi.ly/40opmdj#CFD#maritime#shipdesign#efficiency#propulsion#EEXI#CII#EnergoFlow#EnergoProFin
Wind is not a steady thing.
CFD-steady solutions deliver mean properties, such as mean velocity and mean pressure. Even though they have many engineering applications, wind pressures manifest high-frequency peaks that steady or low-resolution simulations are unable to predict. Besides, low-fidelity simulations fail to indicate susceptibility to resonance and other turbulence phenomena that affect structures.
Experienced wind engineers use high-fidelity simulations - large eddy simulations (LES) - to compose wind loads for structural projects.
#AeroSim#DigitalWindTunnel#Structures#WindLoad#Aerodynamics
🚢 Hydrodynamics of Ship Propellers
I am excited to share some insights from my recent project focused on the hydrodynamics of ship propellers. I have conducted an in-depth comparison between 4-bladed and 5-bladed propellers to assess wake regions and tip vortices using the innovative Lattice Boltzmann Method (LBM) for CFD analysis.
🔍 Key Findings
simulations revealed that the 4-bladed propeller is more prone to cavitation due to significantly larger wake formation at the tip compared to the 5-bladed propeller. The intense tip vortices in the 4-bladed propeller can lead to erosion and impingement on the blade tips, potentially reducing the lifespan and efficiency of the propeller.
🌊 Why LBM?
The Lattice Boltzmann Method (LBM) is a computational fluid dynamics (CFD) technique that differs fundamentally from traditional methods based on the Navier-Stokes equations.
LBM is based on the mesoscopic particle interactions rather than directly solving macroscopic fluid flow equations. The fluid domain is represented by a grid , where each node contains a distribution of particles moving in discrete directions with discrete velocities operates in two main steps:
Collision Step: Particles at each lattice node collide and redistribute their velocities according to specific rules.
Streaming Step: Particles move to neighboring nodes along their respective directions.
Understanding tip vortices is crucial for designing more durable and efficient ship propellers, ultimately enhancing performance and reducing maintenance costs.
#Hydrodynamics#ShipPropellers#CFD#LatticeBoltzmannMethod#MarineEngineering#Innovation
Ph.D. Student at College of Computing, UM6P | Turbulence Modeling | Computational Fluid Dynamics | Wind Farm Turbulence
9moI guess that modern CFD solvers like (Fluent, OpenFOAM and CFX) Are using Launder-sharma model because it provides a high performance and accuracy and because it is the up to date model (1974) while Jones-Launder k-epsilon model was in (1972).