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Simscale ain't that bad!
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がはは 今まで個人的には SimScale しか存在を知らなかった物理演算シミュレーターのサイトを Grok で探せば幾つも紹介してくれるなんて、僕はもう幸せで死にそう(寝るって意味です) おやすみなさい。
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the second goes to the valeo.ai team for creating a simple transformer-based driving agent with SOTA performance on NAVSIM. it’s getting harder and harder to get into or even continue self-driving research because of closed source VLAs, word models. so kudos to the team for open sourcing code, models, and keeping it up-to-date by training on SimScale (an oral at this CVPR) already!
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CAD in Onshape. Simulations were done in Simscale, and Ansys.
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Modern engineering is already distributed across software, standards, notation, workflows, instruments, libraries, solvers, checklists, and teams. Closed-book exams pretend engineering is still an isolated skull activity. ANSYS, COMSOL, MATLAB, SimScale, SolidWorks, CATIA, KiCad, Altium, Revit, Fluent, Abaqus, OpenFOAM all of these encode enormous amounts of scientific and engineering labor.
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Replying to @yacineMTB
How accurate do you need it to be, is it just for fun visuals or actual data? OpenFOAM, Ansys Fluent, SimScale, Star CCM for accurate sims. OpenFOAM is free, text file setup. Fluent has free educational licenses up to some node count (not sure the current limits) on one CPU. SimScale has a free tier, all cloud based. CFD is OpenFOAM, FEA uses CODE_Aster. Salome has CFD using Code_Saturne but it is quite clunky. FreeCAD now has FEA and CFD implementation. They use OpenFOAM solvers. Your biggest problem will be solid meshing. It can be clunky using open source solvers. Ansys has really good meshing. Beyond that how good is your fluids? You’ll need to either run a RAS simulation which doesn’t look fancy, but gets you good data quick. Beyond that, if you want to see eddys you’ll need to run a LES sim with some sort of turbulence model such as k-ω, k-ε, SST, etc.
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SimScale [CVPR 2026 Oral] Learning to Drive via Real-World Simulation at Scale 🏗️ A scalable simulation pipepline that synthesizes diverse and high-fidelity reactive driving scenarios with pseudo-expert demonstrations. 🚀 An effective sim-real co-training strategy that improves robustness and generalization synergistically across various end-to-end planners. 🔬 A comprehensive recipe that reveals crucial insights into the underlying scaling properties of sim-real learning systems for end-to-end autonomy.
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🎉 Excited to share our recent work SimScale, which has been accepted to CVPR 2026 as Oral presentation! 🤖Can we improve policies via scaling synthetic experience? 😢End-to-end driving policies struggles on safety-critical & OOD scenarios that are rare in human logs. To tackle this, SimScale features: 🏗️ A scalable simulation pipeline synthesizes diverse, high-fidelity reactive driving scenarios upon existing logs. (See attached visualization as one synthetic data sample). 🚀 With pseudo-expert demonstrations, Sim-real co-training boosts LTF / DiffusionDrive / GTRS-Dense, up to 8.6 EPDMS on navhard, 2.9 on navtest. 🔬 Performance scales smoothly by adding simulation data alone, with no extra real-world data needed. Joint effort by @HCTian713, @francislee2020, @OpenDriveLab, @sephy_li
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Gambar 3 : A. Churazova (2025), Simscale
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Konteks 1: Matematik, Simulasi, Numerical analysis Ramai pelajar & pengkaji bila sebut converging & diverging ini yang terlintas terus dalam fikiran. Hal ni merujuk kepada mathematical behaviour. Gambar: Simscale
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今日の自己啓発パート2 初期温度を受け付けないDiscoveryに超ムカついたので、simscaleで過渡解析をやってみた 環境温度 約20℃ 基板温度 約20℃ cpu温度 -20℃ サンプル時間 1秒 解析実行時間 約12分 冷気の伝わり方、流れ方が見たいだけなのだよ でもだんだんやりたいことに近づいてる
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SimScale is selected as CVPR 2026 Oral 🎉🥳 Code, simulation data, and checkpoints have been fully open-sourced. 📷Home: opendrivelab.com/SimScale/ 📷Paper: arxiv.org/abs/2511.23369 📷Github: github.com/OpenDriveLab/SimS… If you find something useful, please give it a star⭐

1/n 🎉 SimScale: Learning to Drive via Real-World Simulation at Scale 🤖 An innovative real-world simulation pipeline and a real-sim co-training strategy that significantly boost the robustness and generalization of any end-to-end planner. 📈 For the first time, we reveal the scaling effect of simulation data in autonomous driving: with zero extra real-world data, simply scaling up simulation alone can keep improving model performance!
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飛行機界隈の方、SimScaleって使ってますか?もしかして学生無料だったりしますかねこれ
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🏗️ Every great building starts with understanding airflow. CFD is the tool that makes it possible — and this book makes CFD accessible to everyone in the built environment. 📖 𝘾𝙤𝙢𝙥𝙪𝙩𝙖𝙩𝙞𝙤𝙣𝙖𝙡 𝙁𝙡𝙪𝙞𝙙 𝘿𝙮𝙣𝙖𝙢𝙞𝙘𝙨 𝘼𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨 𝙞𝙣 𝙩𝙝𝙚 𝘽𝙪𝙞𝙡𝙩 𝙀𝙣𝙫𝙞𝙧𝙤𝙣𝙢𝙚𝙣𝙩 by 𝐃𝐫 𝐇𝐞𝐞 𝐉𝐨𝐨 𝐏𝐨𝐡 (NUS) — the complete practical guide from meshing to green building certification, backed by 30 years of real project experience. 💡 What's inside? 🌬️Full CFD workflow purpose-built for architects, engineers & urban planners 🏙️Real industry case studies: ventilation, urban microclimate, fire safety & hydrogen infrastructure 🌿 Vegetation, pollutant dispersion & urban heat island CFD modelling 🏅 Aligned with Green Mark, LEED, ASHRAE & AIJ certification criteria 🔮Future directions: digital twin CFD, BIM integration & AI-driven surrogate models Includes downloadable working example files & tutorial questions in every chapter. 🔥 30% OFF with code WSTWTR30 worldscientific.com/worldsci… 💬 Join the conversation: @ASHRAE @USGBC @WorldGBC @BRE_Group @CIBSE @ANSYSInc @SimScale @OpenFOAM @ArchDaily @ArupGroup @CTBUH @NUSingapore @UrbanLandInst #CFD #ComputationalFluidDynamics #BuiltEnvironment #GreenBuilding #SustainableDesign #LEED #UrbanMicroclimate #Ventilation #BIM #DigitalTwin #FireSafety #ThermalComfort #UrbanHeatIsland #IndoorAirQuality
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And to take me into the evening, computational fluid dynamics again - this time using SimScale & as I often do I get myself aligned using the trusty NACA 0012 airfoil. This got me out of many tight corners numerous times during my engineering PhD.
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