歐姆龍G2R-2-SND 直流固態(tài)伺服電機(jī)

歐姆龍G2R-2-SND 直流固態(tài)伺服電機(jī)

Siemens & PhysicsX Collaborate to Build AI-based Deep Physics Simulation
西門子與PhysicsX合作打造基于AI的深度物理仿真

Siemens Digital Industries Software announced its ongoing collaboration with PhysicsX, a startup leveraging generative AI to enable breakthrough engineering in advanced industries. Together, they aim to create the next generation of AI-based deep physics simulation to accelerate performance prediction and optimization.

西門子數(shù)字工業(yè)軟件宣布與PhysicsX進(jìn)行持續(xù)合作，后者是一家利用生成式AI推動行業(yè)工程創(chuàng)新的初創(chuàng)公司。他們共同的目標(biāo)是創(chuàng)建下一代基于AI的深度物理仿真，以加速性能預(yù)測和優(yōu)化。

PhysicsX is building its latest pre-trained deep physics model for aerodynamics on high-fidelity simulation data generated with the Siemens Xcelerator portfolio.

PhysicsX正在使用西門子Xcelerator產(chǎn)品組合生成的高保真度仿真數(shù)據(jù)，構(gòu)建其的預(yù)訓(xùn)練深度物理模型，用于空氣動力學(xué)。

“AI represents a truly transformative opportunity for the simulation community, and we are exploring its potential at an accelerated rate,” said Jean-Claude Ercolanelli, senior vice president, Simulation and Test Solutions, Siemens Digital Industries Software. “To scale AI adoption, open collaboration is key and Siemens is delighted to see PhysicsX unveil to the world what it is working on–together, we’re exploring an AI-enhanced simulation industry that has the potential to change how products are ideated and engineered.”

“人工智能為仿真社區(qū)帶來了真正的變革性機(jī)遇，我們正在以加速的速率探索其潛力，”西門子數(shù)字工業(yè)軟件仿真和測試解決方案高級副總裁Jean-Claude Ercolanelli表示。“要擴(kuò)大AI的應(yīng)用，開放合作至關(guān)重要。西門子很高興看到PhysicsX向世界展示其研究成果。我們正在共同探索一個AI增強(qiáng)的仿真行業(yè)，這有可能改變產(chǎn)品構(gòu)思和工程的方式。”

“We are delighted to take our collaboration with Siemens to the next level, working together on fundamental technology to improve the way engineering is practiced,” said Robin Tuluie, founder and chairman of PhysicsX.

“我們很高興將與西門子的合作提升到一個新的水平，共同致力于改善工程實踐方式的基礎(chǔ)技術(shù)，”PhysicsX的創(chuàng)始人兼董事長Robin Tuluie表示。

“The basis for successful AI deployment into engineering hinges on highest-quality synthetic data, robust integrations between Computer Aided Engineering (CAE) and AI [Artificial Intelligence] and building on the trust customers have in our respective technologies. We are thrilled to be building into the opportunity space together with Siemens with the release of our latest Large Geometry Model (LGM) for aerodynamics, LGM-Aero, trained on high-fidelity data generated with Siemens Xcelerator portfolio tools. We are also delighted to be releasing Ai.rplane, an open-access reference application showcasing the power of LGM-Aero to design innovative aero solutions.”

“成功將AI部署到工程中的基礎(chǔ)在于質(zhì)量的合成數(shù)據(jù)、計算機(jī)輔助工程（CAE）與AI之間的強(qiáng)大集成，以及建立在客戶對我們各自技術(shù)信任之上。我們很高興能與西門子共同抓住這個機(jī)會，發(fā)布我們的用于空氣動力學(xué)的大幾何模型（LGM-Aero），該模型使用西門子Xcelerator產(chǎn)品組合工具生成的高保真數(shù)據(jù)進(jìn)行訓(xùn)練。我們還很高興發(fā)布Ai.rplane，這是一個開放訪問的參考應(yīng)用，展示了LGM-Aero在設(shè)計創(chuàng)新空氣動力學(xué)解決方案方面的強(qiáng)大能力。”

Large Geometry Model (LGM) release
Much of the promise of AI in industrial applications starts with the dramatic acceleration that AI can bring to simulation. PhysicsX’s LGM-Aero is trained on a corpus of more than 25 million geometries and associated physics simulation. The training data contains tens of billions of mesh elements and tens of thousands of Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) simulations using high-quality Simcenter STAR-CCM+ software and Simcenter Nastran software. It allows users to fine-tune deep learning models for their own applications with as little as a few tens of simulations.

大幾何模型（LGM）發(fā)布
AI在工業(yè)應(yīng)用中的許多承諾始于AI能夠為仿真帶來的顯著加速。PhysicsX的LGM-Aero是在超過2500萬個幾何體及其相關(guān)的物理仿真數(shù)據(jù)集上訓(xùn)練的。訓(xùn)練數(shù)據(jù)包含數(shù)千億個網(wǎng)格元素和數(shù)萬個使用高質(zhì)量Simcenter STAR-CCM+軟件和Simcenter Nastran軟件進(jìn)行的計算流體動力學(xué)（CFD）和有限元分析（FEA）仿真。它允許用戶為自己的應(yīng)用微調(diào)深度學(xué)習(xí)模型，只需數(shù)十次仿真即可。