A space for miscellaneous discussions.
Introduction: A digital twin is a computerized model of an object or a system that covers its entire lifecycle. It utilizes real-time data for constant updates, and integrates simulation, machine learning, and reasoning algorithms to support decision-making. Sensors are used on physical objects to gather data on crucial…
Optimize model performance in Compose signalAI by hyperparameter tuning In the previous article, we had discussed about how the end-to-end modelling process looks like in Compose “signalAI director” and also learnt about the algorithms available within the director. Picking up from where we have left, in today’s blog we…
Recently, Altair has introduced DesignAI, an application that combines physics-based simulations and machine learning to identify high potential designs early in the development cycle. DesignAI integrates all aspects of Altair's vision for computational science: simulation, data analytics, and high performance computing.…
Have you seen the new “AI/ML” group on the “Assembly” ribbon in HyperMesh? These tools are powered by shapeAI, a technology which allows us to interpret geometry and mesh into a format on which we can use machine learning. Match lets you find or group components by similarity. In this blog you can see an example of how…
ラテン超方格、Hammersleyの変数の数の目安が(n+1)(n+2)/2なのはなぜですか？ ヘルプには以下の記述があり、目的関数が2次多項式と仮定されている。 (N+1)(N+2)/2 runs are needed to fit a second order polynomial, 目的関数が設計変数の2次式で近似されると仮定すると変数がn個の場合、係数の数は f(x1, x2, …, xn)=a1x1^2+a2x1^2+…+anxn^2←xi^2の係数はn個 +b12x1x2+b13x1x3+…+bn-1nxn-1xn←xixjの係数はnC2個 +c1x1+c2x2+…+cnxn←xiの係数はn個 +定数←定数は1個…
OptiStruct can calculate and output design sensitivities for structural optimization problems. Prerequisite: Create a shape or sizing optimization .fem deck for OptiStruct. Sensitivity analysis is a technique to understand how certain responses in a design optimization problem are influenced by changing the values of the…
Hi Altair Community! This is the first time (hopefully out of many) that I am posting a blog post, so bear with me in my attempt to start a discussion regarding my use of Altair Tools. I was recently in a discussion with a client who was looking at predict stress-strain curves for their materials, specifically to reduce…
Today I’d like to give a sneak peek at Altair physicsAI: a new tool for making fast physics predictions. physicsAI learns from your historical simulation data, extracting the relationships between shape and engineering performance. Once trained, physicsAI models output fully animated contours at speeds 10x-100x faster than…
At Future.Industry 2023, we’ll explore the latest megatrends impacting our world. From electrification and the data-driven enterprise to AI-driven simulation and semiconductors, you’ll learn how the convergence of simulation, high-performance computing (HPC), and AI can unlock the full potential of your technology…
With computational software expertise of more than 35 years, Altair has grown to service customers across multiple domains. Altair One is a grand commencement of Altair's own convergence onto a single platform serving engineers and admins to create, compute, and collaborate. Until now, Altair One has been synonymous with…
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Hi Everyone, While this roundup arrives a bit later than planned, we wanted to ensure that we captured the key highlights and achievements from September. Lets dive in. 📢Altair RISE Updates As you know our RISE Program(Recognition for Innovation, Solutions & Expertise) officially launched in August. This exclusive…
Hi Everyone, Sorry for the delay in posting our community highlights and achievements for October and November. There has been a lot of going on, but we didn't want to overlook the great content and contributions for these months. So without further ado, let's jump right in. 📣 Important Announcement - Altair Support is…