Miguel Gomez

Boats and waves. This is a very easy way to simulate the effect to different waves on the durability of floating structures. https://lnkd.in/gE6x_2VM

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You are a Mechanical Engineer who took some Machine Learning courses. How can you combine those two now, or more specifically, how can you apply ML to CAE problems? Here is what I would do if I started again: 1. Read the book "Approaching ML problems in CFD and CAE applications" by Justin Hodges, PhD. It will allow you to make the connection between ML and CAE, shifting your mindset about many aspects you have learned in generic ML bootcamps and giving you tons of ideas. You can order the book here: https://geni.us/JaXp 2. Learn about CAE-specific model architectures. There is hundreds of them, but in the beginning you only need to understand the main concepts of how people approach 3D data processing. I recommend reading about Graph Neural Networks (here is a great Medium resource https://lnkd.in/eQm2qniT by Rayan Kanfar) and Occupancy Networks (https://lnkd.in/ePPuWWRs). 3. Get familiar with a 3D data processing library, I recommend PyVista. Don't spend too much time learning it from tutorials, start building things straight away and then find information in the documentation as you progress. After that, build, build and build. The more you build and the more you fail the better. You could try re-creating a project you found online or, if you feel ready, build something of your own. Have you seen the SimJEB dataset? I hope it will give you some ideas: https://simjeb.github.io/ And if you think "I don't even know how 3D data is saved in a computer", here is a super simple explanation of how 3D meshes work.

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Ever tried to design parts from a 3D scan? Either work with super heavy stl conversion or spend a lot of time create a clean model. I never knew how powerful STL to SubD conversion was until I tried this out in Ansys Discovery! What a powerful tool for working with faceted data! #ansys #stl #3dprinting https://lnkd.in/gHQQuv8V

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💻 CoolSim's "occasional use" pricing model ensures you only pay for what you need, when you need it. Access advanced CFD modeling software and high-performance HPC clusters without breaking the bank. Optimize your data center with CoolSim's cost-effective and flexible solution. Visit https://lnkd.in/eK5B9EFz to learn more. #coolsim #coolsimsoftware #datacenter #data #software #innovation #technology #CFD #appliedmathmodelling

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This is a great read and bodes well for the future of any industry leveraging CFD in their innovation. #CFD #HPC #Innovation

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Great blog post on blood flow modeling and validation by a true expert in the field. I put together some youtube videos on this topic using older Ansys tools, but Ertan Taskin is showing we can get very good results in Ansys Discovery! Much easier to use and lower cost compared to any other solutions on the market! #ansys #biomed #CFD #bloodflow

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The best part of working with Ansys is the vast suite to tools to solve different problems. I did a full 2 way FSI of stress on a boat due to waves close to 20 years ago and it was tough! This is the easy button... and the right approach.

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Learn how aerospace and defense organizations use MathWorks tools for digital transformation to create digital twins, a digital thread, and DevSecOps pipelines that work with interconnected digital infrastructures #modelbaseddesign #MATLAB https://spr.ly/6047gAR69

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Creo Parametric 11 offers great improvements in creating model-based definition annotations on cylindrical features. When creating a new annotation or adding additional semantic references on hole and shaft features, the second half cylinder is automatically highlighted and selected by Creo as the annotation reference. This streamlines the MBD annotation workflow.

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Conference Paper Spotlight: Fully Coupled CFD Simulations for Micro Gas Turbine (MGT) Engines Explore how fully coupled simulations of the KJ66 MGT engine improve 3D numerical accuracy by integrating the compressor, turbine, and exhaust into a single model. Learn about RANS, NLH, and LES methods, and how they provide insights into turbine efficiency, fuel combustion, and inter-component interactions. Read the full paper: https://ow.ly/gb2J50TQ6OZ #turbomachinery #computationalfluiddynamics #FidelityCFD

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Hope this article is useful to the structural mechanics engineers with an interest in scripting!

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🚀 Engineers, ready to speed up your simulations? Join our webinar on July 17th to learn how to create AI-based reduced order models using Simulink. Discover how to integrate AI models for system-level simulations and optimize C code for HIL tests. Don't miss out! Register now 🔗 #AI #Engineering #Simulink #Webinar https://spr.ly/6048g5BIE

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Is cutting and pasting from NASA's CEA code causing your pointing finger to become a workplace injury? Does having to repeat the same thermo-chemical equilibrium calculations over again after a slight propellant change give you nightmares? Want to calculate the optimum mixture ratio for a dual-fuel system, but don't have the time to perform the calculations to minimize NOx? Then give Cequel and pyrho a try. Cequel performs all of CEA's calculations as a dynamic Excel spreadsheet function, allowing for fast parametric studies or supplying problem specific parameters without cutting and pasting. Need Isp, ratio of specific heats, C* or the mass fraction of CO2? Multiple parameters can be returned with one function call. Once your spreadsheet is set up how you want to solve the problem, it can be easily updated for future problems. Pyrho is a python library that provides the same functionality to both python and MatLab scripts. By encoding your analysis according to how you want to solve the problem, when a change happens, just tweak the input parameters to re-perform the calculations. A tri-propellant mixture parameter plot is included as an example. For more information and to request a free 30 day demo, please visit www.praqsys.com.

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Accelerate your CFD simulations with Ansys Fluent 2024 R2 and AMD! Learn about the integration of AMD Instinct MI200 and MI300 acceleration, drastically reducing simulation times. https://bit.ly/3TRfDM5

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Join Jeff Baxter, Cameron Krivitsky and Kyle Gallaher for a deep dive into how Ansys STK, ModelCenter and the Systems Architect Model (SAM) revolutionize digital engineering and MBSE practices. Discover how these powerful tools can significantly reduce design time and optimize tradeoffs through a satellite imaging demo. #digitaltransformation #DigitalEngineering #MBSE

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Join Jeff Baxter, Cameron Krivitsky and Kyle Gallaher for a deep dive into how Ansys STK, ModelCenter and the Systems Architect Model (SAM) revolutionize digital engineering and MBSE practices. Discover how these powerful tools can significantly reduce design time and optimize tradeoffs through a satellite imaging demo. #digitaltransformation #DigitalEngineering #MBSE

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Ansys 2024 R2: Boost Digital Engineering with Ansys Minerva, Ansys ModelCenter, and Ansys STK Integration https://bit.ly/3SF4Xzz

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For safety-critical aerospace applications of AI/ML, safety-assurance must be an integral part of the design process and not an afterthought. A huge shoutout to the team - Naresh Iyer, Dan Prince, Michael Durling, Liang Tang, Mike Meiners, Baoluo Meng, Ph.D., Nikita Visnevski, and others - for collaborating with an open mind and combining their domain expertise to lay the foundation for an Overarching Properties-based framework for the Safety Assurance of AI. Many thanks to Srini Mandalapu, George Romanski, Trung Pham, the Federal Aviation Administration, and Michael Holloway for their invaluable support in this endeavor. ✈️🚀🛰️

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