New TCAE 24.03 Release

We're happy to announce the release of the latest version of TCAE simulation software - Version 24.03! 

TCAE continues to be the go-to solution for engineers seeking powerful, user-friendly, and cost-efficient simulation software that can tackle complex engineering challenges with ease.

To introduce you to the exciting features of the new TCAE 24.03, we invite you to join our upcoming webinar. Here are the details:

Title: TCAE 24.03 Introduction

Date: Thu, Apr 11, 2024 

Time: 3:00 PM CEST

Duration: Approximately 1 hour

Agenda:

Overview of TCAE Version 24.03. Live demonstration showcasing the user-friendly interface, advanced features, and fast solvers 

Q&A Session: 

Ask your questions, and our experts will provide answers. Feel free to send your questions in advance to info@cfdsupport.com.

Speakers:

🎤 Lubos Pirkl, Co-Founder at CFD Support 

🛠️ Radek Máca, Head Engineer at CFD Support

Registration: 

Secure your spot now by registering at https://attendee.gotowebinar.com/register/6791084528975214686

Even if you can't attend the live event, register anyway to receive the recording for future viewing at your convenience.

More Information: 

Visit our website to learn more about TCAE and its capabilities: https://www.cfdsupport.com/tcae.html. Explore our publishable benchmarks and real project-based case studies, all of which are transparent and freely downloadable.

With TCAE, you not only gain access to cutting-edge simulation technology but also become a valued member of our community. Benefit from our ongoing support, training resources, and valuable insights to elevate your engineering projects.

Don't miss this opportunity to discover how TCAE Version 24.03 can empower you to overcome your engineering challenges and achieve your design goals.

We look forward to welcoming you to the webinar!

As always. We're one email away!

Best Regards, 

CFD SUPPORT Team

Airfoil Acoustic Benchmark NACA 0012

We are thrilled to announce the launch of our newest engineering simulation benchmark Airfoil Acoustic Benchmark NACA 0012, showcasing the capabilities of our cutting-edge simulation software, TCAE. This benchmark, centered around the NACA 0012 airfoil, delves into the realm of Computational Aero-Acoustics (CAA) and highlights the smooth usability and advanced features of TCAE software.

Access the Airfoil Acoustic Benchmark NACA 0012 case study: To learn more about this benchmark and dive into the details of our study, please visit our website. You'll find comprehensive documentation, detailed results, and insights into the fascinating world of CAA.

Experience the flowing air and vortices around the NACA0012 airfoil firsthand by watching our accompanying YouTube video: https://youtu.be/6mKSCT1-wK4

This video offers a glimpse into the intricate dynamics captured in our simulations including the sound reconstruction!

Join Our Webinar on March 5, 2024: We invite you to join our upcoming webinar where we'll delve deeper into the methodology, results, and implications of this benchmark study. Register now to secure your spot and engage with our team of experts:  https://attendee.gotowebinar.com/register/6369598840280329815

Download the project and run it for yourself: For those eager to explore the project firsthand, the entire benchmark project is available for download on our website. Simply visit our website to access the files and replicate the study in your own environment. 

https://www.cfdsupport.com/naca-0012-acoustic-benchmark.html​​

Thank you for your continued support and interest in our engineering simulation endeavors. We are excited to share this milestone with you and look forward to your participation in our upcoming webinar.

Stay tuned for more exciting updates on the horizon. Together, we'll shape the future of simulation.

As always. We're one email away!

Best Regards, 

CFD SUPPORT Team

🔓 Open Source CAE Tools! 🌐🔧

If you're passionate about the world of computer-aided engineering (CAE) and scientific computing, you're in for a treat! 🤓

At CFDSUPPORT, we've created a dynamic list of the most influential open-source software packages in the CAE domain. 📦✨

Our list is a treasure trove of open-source gems, meticulously updated to keep you in the loop about the latest advancements and innovations in this ever-evolving field. 💡🚀

But here's the exciting part – we're not just sharing our discoveries; we want to hear from you too! If you know of any remarkable open-source software that's not on our list, drop us a line, and we'll add it pronto. 📣💬

🌟 Explore the World of Open Source CAE Software:

https://www.cfdsupport.com/cae-open-source-software.html

Join us in the open-source CAE revolution. Let's collaborate, innovate, and empower each other with the knowledge and tools to shape the future of engineering. Together, we'll build a stronger CAE community! 🤝🌍

🌀💻 Centrifugal Pump simulation with Cutting-Edge CFD & FEA + FSI Simulations by TCAE! 🚀

In numerous industries, centrifugal pumps are the heartbeat 💓, and enhancing their efficiency leads to major cost savings 💸. Dive into the world of Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Fluid-Structure Interaction (FSI) simulations to elevate your pump's performance. 🌊🔧

Our CFD simulations shed light on the inner workings of fluid flow, spotting recirculation zones, and forecasting the pump's head, flow rate, and efficiency 📊. FEA steps in to ensure your pump's structural soundness, braving operational stresses and strains 💪. The magic happens when FSI simulations merge CFD and FEA insights, offering a holistic view of your pump’s behavior, balancing both fluid dynamics and structural integrity 🤝.

🌟 TCAE's all-encompassing CFD, FEA, and FSI services are your key to a more efficient, energy-saving centrifugal pump design. These simulations are not just about performance enhancement; they're about smart savings and extending your pump's lifespan! 💡💚

Summing up, TCAE's arsenal of CFD, FEA, and FSI simulations are your secret weapon 🛠️ in mastering centrifugal pump design and operation. Ready to boost efficiency and save big? 💰🌱

📖 Full Case Study (Download Available): https://www.cfdsupport.com/centrifugal-pump-cfd-fea-fsi-simulation.html

🎬 YouTube Video: https://youtu.be/FJaT1aiDXSE

#Pump #CFDSimulation #FEAAnalysis #FSISimulation #EnergySavings #TCAE #IndustrialInnovation #EngineeringExcellence #Optimization 🌍🔧📈

AI for CAE

The question isn’t “if” but “how soon”

CAE, or Computer-Aided Engineering (CFD, FEA, FSI, and optimization), is a field that utilizes computer software and tools to deliver the design, analysis, and optimization of engineering systems and components. This field plays a crucial role in industries such as automotive, aerospace, manufacturing, and civil engineering, enabling engineers to make informed decisions and improve the efficiency and reliability of their designs.

With recent developments, seeing how AI (Artificial Intelligence – here I mean rather Machine Learning but only calling it AI to make things easier) is disrupting field by field, everything seems that AI will disrupt the CAE field too. In my humble opinion, it’s just a matter of time and the only question is when (and how exactly) it happens rather than if it happens.

We’re just somewhere at the beginning and it’s even very difficult to say what is going on at the moment – not a mention that it’s impossible to predict what will happen in the future. However, there are a couple of things that we CAN say. 

The thing is, the usual CAE workflow involves a bunch of easy manual tasks and decisions based on data. And AI seems to be perfect for lending a hand with all of that.

https://www.cfdsupport.com/ai-for-cae.html

Francis Turbine CFD & FEA + FSI benchmark 

TCAE  – the ultimate simulation software for engineers and researchers! A comprehensive simulation environment, based on open source, offers a wide range of analysis capabilities, including CFD, FEA, FSI, and modal analysis.

The following study focuses on the analysis of a Francis turbine, one of the most widely used hydro turbines in the world. This complex analysis takes you step-by-step through the entire simulation process, from preprocessing to advanced CFD & FEA simulations. The study also includes FSI and modal analysis, providing a complete understanding of the turbine's behavior under various operating conditions.

TCAE was used for this analysis, offering users a robust simulation environment with a user-friendly interface. With TCAE, engineers and researchers can easily simulate complex systems and processes, gaining valuable insights into their behavior.

The Francis turbine CFD & FEA + FSI benchmark presented in this study is a validation of a real existing turbine, providing accurate results that can be used for further optimization and improvement. Whether you're working in the energy industry or researching new technologies, TCAE is the perfect simulation software for your needs.

Full Case Study (download available):

https://www.cfdsupport.com/francis-turbine-cfd-fea-fsi-simulation.html

PDF report:

https://www.cfdsupport.com/download/TCFD-CFDSUPPORT-Francis-Turbine-Benchmark.pdf

Centrifugal fan design & simulation, an overview of complex virtual prototyping of centrifugal fans using Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Fluid-Structure Interaction (FSI). These technologies offer engineers a comprehensive toolset to design, optimize, and analyze the performance, structural integrity, and reliability of centrifugal fans.

With the use of CFD, engineers can simulate and analyze the fluid flow inside the fan, allowing them to optimize the geometry, blade angles, and other design parameters for maximum efficiency and performance. Additionally, FEA can be used to analyze the structural integrity of the fan, ensuring it can withstand the forces and stresses generated by the fluid flow. FSI combines the analysis of fluid flow and structural response, allowing engineers to understand how the fan structure will deform under the influence of fluid forces.

The combination of these technologies enables engineers to simulate and optimize a variety of scenarios, including different operating conditions, such as varying fan speeds, flow rates, and fluid properties. This allows engineers to refine the design of the fan before building a physical prototype, reducing development costs and improving the overall performance and reliability of the fan.

In this overview, we will explore the benefits of using CFD, FEA, and FSI to design and optimize centrifugal fans. We will also cover the basic principles of each technology and how they can be used in combination to simulate and analyze the performance and structural integrity of centrifugal fans. So, let's dive in and explore the world of virtual prototyping of centrifugal fans using CFD, FEA, and FSI!

Full Case Study & Download: 

https://www.cfdsupport.com/centrifugal-fan-design-and-simulation.html

PDF:

https://www.cfdsupport.com/download/TCAE-CFDSUPPORT-Centrifugal-Fan-Design-and-Simulation.pdf

Our team at CFDSUPPORT believes that success in engineering projects is the result of a combination of focus, skills, experience, patience, and dedication, rather than quick actions in a rush. To ensure accuracy, CFDSUPPORT regularly tracks and compares CFD results with real-world physical measurements. An example of our commitment to accuracy is the Centrifugal Compressor Benchmark project. This project was a collaboration between CFDSUPPORT and compressor manufacturer CZ a.s. The goal of the benchmark validation was to assess the accuracy of the TCFD software and compare its simulation results with actual compressor measurement data. By continuously striving for accuracy, CFDSUPPORT and its partners are able to deliver more reliable and trustworthy results for their clients.

https://www.cfdsupport.com/centrifugal-compressor-cfd-benchmark.html

#Simulation #CAE #CFD #FSI #CAA #Optimization #HPC #engineering #turbomachinery

The combination of fluid dynamics and machine learning has become an area of increasing interest in recent years, as researchers look for ways to use machine learning techniques to improve our understanding of fluid dynamics and make better predictions about fluid behavior.

One way that machine learning can be applied to fluid dynamics is through the use of data-driven models. These models are trained using large datasets of fluid flow data and can be used to make predictions about future fluid behavior. For example, a data-driven model could be used to predict the flow of air around an airplane wing or the movement of water in a river.

Another area where machine learning can be applied to fluid dynamics is in the optimization of fluid systems. By using machine learning algorithms to analyze fluid flow data, researchers can identify areas where fluid flow can be improved and develop optimized designs for fluid systems.

Overall, the combination of fluid dynamics and machine learning has the potential to revolutionize many scientific and engineering fields, providing new insights into fluid behavior and enabling the development of more efficient and effective fluid systems.

A forum category to discuss and exchange information, ideas, and knowledge related to the context of ML/AI applied in engineering simulations.

The goal of this category is to serve as a community of users, developers, and experts who interact and collaborate on various aspects of the software, such as usage, development, bug fixing, and feature requests. Joining this discussion group is a great way to learn from others and stay updated on the latest developments in data analysis, and ML/AI in engineering simulations.

A forum category for hardware related to CAE (Computer-Aided Engineering) simulations for users, developers, and experts to discuss and exchange information, ideas, and knowledge about hardware components and systems that are suitable for CAE simulations.

A forum category to discuss and exchange information, ideas, and knowledge related to the context of open-source CAE (Computer-Aided Engineering) software.

The goal of this category is to serve as a community of users, developers, and experts who interact and collaborate on various aspects of the software, such as usage, development, bug fixing, and feature requests. Joining this discussion group is a great way to learn from others and stay updated on the latest developments in the field of open-source CAE software tools.

This category is focused on providing a public discussion, and guidance exclusively for the RWIND simulation environment. Specifically, the theory and strategies related to CFD methods.

RWIND is a software tool for simulating wind loads on buildings and other structures. It is a comprehensive tool that can be used to analyze the wind loads on a wide range of structures, including buildings, bridges, towers, and other structures. RWIND software also provides a user-friendly interface that allows users to easily input building geometry and wind data, as well as create and edit wind load cases. The results of the wind load calculations can be viewed and analyzed in various formats, including detailed reports, graphs, and 3D visualizations. It is used by engineers and designers to predict wind loads on a structure and check if it is designed to withstand those loads. It's a widely used tool by consultants and contractors for the design and construction of wind-sensitive structures like bridges, skyscrapers, towers, and more.

This category aims to enable discussion and support and enhance the users' knowledge and skills in using RWIND.

This category is dedicated to Optimization in Engineering Simulations. We discuss here optimization methods, tools, and case studies. 

CFD (Computational Fluid Dynamics), FEA (Finite Element Analysis), and FSI (Fluid-Structure Interaction) simulations are used to analyze and predict the behavior of fluid flow, heat transfer, and structural mechanics in various engineering applications. Optimization is the process of finding the best solution to a problem by adjusting various input parameters. Optimization can be applied to CFD, FEA, and FSI simulations to improve the accuracy and efficiency of the simulation results. For example, optimization algorithms can be used to adjust mesh size, boundary conditions, and material properties to improve the accuracy of the simulation results, or to minimize the computational cost of the simulation.

Parametric optimization is a specific type of optimization in which the input parameters of a CFD, FEA, or FSI simulation are varied systematically to find the optimal solution. In parametric optimization, a set of input parameters is defined as the design variables, and a set of performance criteria is defined as the objective function. The optimization algorithm then searches for the combination of input parameters that minimizes or maximizes the objective function.

For example, in a CFD simulation of fluid flow through a pipe, the design variables might include the pipe diameter and the roughness of the pipe walls, while the objective function might be the pressure drop across the pipe. The optimization algorithm would then search for the combination of pipe diameter and roughness that minimizes the pressure drop.

Similarly, in an FEA simulation of a structure, the design variables might include the material properties and dimensions of the structure, while the objective function might be the stress or deflection of the structure. The optimization algorithm would then search for the combination of material properties and dimensions that minimizes the stress or deflection.

In an FSI simulation, the design variables are the parameters that affect the fluid and structure behavior, the objective function can be the displacement of the structure or pressure of the fluid.

Parametric optimization can be a powerful tool for designing and optimizing engineering systems, as it allows engineers to quickly and efficiently explore the design space and find the best solutions to their problems.