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TechTalk: Breaking Boundaries with Altair physicsAI
I recently joined Jim Green on an episode of the AMD TechTalk podcast to discuss how Altair is transforming product and system innovation with its design and simulation platform, Altair® HyperWorks®. We made the podcast so that product developers of all skill levels can discover how Altair's AI-powered engineering…
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Configuring GPU for PhysicsAI model training
Configuring GPU for PhysicsAI model training Hello PhysicsAI users, As you are already aware that the GPU can be leveraged for model training in PhysicsAI, however, there are a few important points which should be considered to make sure that the GPU gets utilized by PhysicsAI for the same. First consideration : required…
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5 Frequently Asked Questions about Altair’s AI-Powered Engineering Solutions
1: Can the AI for engineering applications run on my laptop, or do I need cloud access? AI-powered engineering solutions can run on a laptop, though for intensive tasks such as computational fluid dynamics (CFD), using high-performance computing (HPC) in the cloud is more efficient. But yes, Altair's physicsAI, romAI, the…
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AIを活用した車室内空調の快適性向上
概要 本記事では、3DCFDのAcuSolveを用いた熱流体解析とromAIによる低次元化により、車室内の温度を高速に予測する手法を紹介します。 本記事はUrvi Mehtaによる投稿 Improving Passenger Thermal Comfort using AI を和訳したものです。 はじめに…
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Improving Passenger Thermal Comfort using AI
Introduction In the modern technological landscape, digital twin technology is revolutionizing the way we interact with physical objects and systems. A digital twin is a computerized model of an object or system that covers its entire lifecycle, utilizing real-time data for constant updates. This article demonstrates the…
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CAE Connectors Extension now available for AI Studio
So you've run a simulation or two, but what do you now do with the data you've produced? Of course, Altair has a number of tools available to plot and post-process this data to help accelerate engineering, such as HyperView and HyperGraph. However, many users still utilise tools such as Excel in their workflows to perform…
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Multidisciplinary Optimization: Enhancing Efficiency and Performance with Artificial Intelligence (AI)
Organizations commonly incorporate virtual modeling into product development cycles to reduce costly reliance on physical prototyping and expedite time-to-market. With mainstream accessibility to simulation technology, virtual prototyping has become standard practice along with high-performance computing (HPC). Broad…
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Harnessing Test Data in Model-Based Development through AI: Discovering the Path to Efficiency and Accuracy
In the rapidly evolving landscape of artificial intelligence (AI), companies are witnessing a shift away from costly, time-consuming activities like prototyping and testing. Instead, they are turning to simulation to optimize processes and meet requirements through the adoption of virtual models. The aim is to design and…
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Beyond Simulation: Creating & Deploying Digital Twins Starting From Finite Element Analysis
Traditional simulation plays a pivotal role in the design of products, offering numerous benefits that streamline the design process, reduce costs, and enhance product quality. This technology, encompassing a range of computational tools and methods, allows designers and engineers to model, analyze, and predict the…
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Altair is the Home of Engineering with Artificial Intelligence
For decades, HyperWorks has helped make better products faster. Recent AI embedded workflows put 21st century technology in the hands of everyday users. HyperWorks simulation software’s broad range of applications has made it a standard in many engineering industries, from automotive to high technology electronics. Recent…
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5 Reasons to Attend Altair's Data Science Day 2023
Unlocking the Future: Top 5 Reasons to Attend Altair Data Science Day | November 2, 2023 In a world where data is king, data scientists are the knights in shining armor, and the demand for these knights is on the rise. The Altair Data Science Day on November 2, 2023, is your ticket to explore the world of data science,…
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romAI & nFX : ドライブトレインCFDシミュレーションにおけるAIの活用
本記事はSpiros-Foivos Malliosによる投稿 romAI & nFX: Leveraging AI on Drivetrain CFD Simulations を和訳したものです。 概要 この記事では、nanoFluidXRのオイル流動シミュレーションのデータをスマートに利用し、運転中のギアボックスの熱挙動を効率的に予測するために、romAITMがどのように役立つかを説明します。熱問題を解決するために、ギアボックスの回転数とオイルの充填量からギアとオイルの熱伝達率(HTC)を推定する動的非線形低次元化モデル(ROM)を作成します。 序論と問題提起 実運用のシナリオでは、ドライブトレインは次のようなさまざまな条件で動作します：…
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romAI & nFX: Leveraging AI on Drivetrain CFD Simulations
Abstract In this article we discuss how romAITM can help to efficiently predict the thermal behavior of gearboxes during operations smartly reusing data from nanoFluidXR oil flow simulations. To solve the thermal problem, a dynamic non-linear Reduced Order Model (ROM) is generated to estimate the Gear-Oil heat transfer…
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HyperWorks 2023 Comes with Exciting New Updates for physicsAI
The newest version of HyperWorks builds upon the first release of Altair’s physicsAI tech. Learning from your existing simulation data has gotten easier. HyperWorks 2022.3 contained the first release of the new exciting physicsAI technology that streamlines the process of training machine learning models from historical…
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13 Frequently Asked Questions About Altair physicsAI
Altair physicsAI has brought advanced geometric deep learning to everyday CAE users. Get to know these basic facts before you get started. HyperWorks 2022.3 contained the first release of our new physicsAI technology for fast physics predictions using historical simulation data. Since then, we have been hard at work…
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Altair physicsAI の概要
本記事はEamon Whalenによるブログ A sneak peek at physicsAI from Altair を和訳したものです。 本日は、高速物理予測を行うための新しいツールである Altair physicsAI を少しだけ紹介したいと思います。physicalAI は過去のシミュレーション データから学習し、形状と工学性能の関係を抽出します。トレーニングが完了すると、physicsAI モデルは、ソルバーよりも 10倍から100倍の速度でアニメーション化されたコンターを出力します。 実験計画法 (DOE)や設計変数を必要とする他の機械学習ツールとは異なり、physicsAI…
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Part Classification Workflows Now Available in HyperWorks 2022.3
Automatic part recognition saves time. HyperWorks brings machine learning-powered shapeAI technology to every user. I remember being taught in my fist finite element class that the finite element method consists of three steps: pre-processing, solving, and post-processing. The class focused on the math of solving and, to a…
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Sobol Sequence: not just another sampling method
Designs of Experiments (DOE) is a branch of statistics that creates systematic sampling patterns that are used to determine cause and effect relationships between inputs and outputs. DOE is a powerful data collection and analysis tool that can be used in a variety of experimental situations. Design of Experiments is…
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Application Of romAI for Stress and Load Prediction From Strains
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…
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Fine tuning signalAI in Compose
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…
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Introducing DesignAI
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.…
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Using shapeAI to find mirrored parts
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…
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Curve-Prediction using Machine Learning
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…
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A sneak peek at physicsAI from Altair
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…
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Utilizing the power of gradients in predictive modelling
This post is about gradients. Gradients are the partial derivatives of some scalar response, with respect to the design variables. For instance; how much does the tip displacement (response) of a wing change as a function of the thicknesses (design variables) of the wing ribs. Knowing this is extremely useful in…