Concevoir l'avenir

Exploration des derniers cas d'utilisation en ingénierie numérique, des tendances du secteur et des innovations de la plateforme Rescale.

Nouveautés en ingénierie numérique

Tous les blogs

  • HiLiftAeroML Open Dataset Accelerates AI Physics Model Adoption

    HiLiftAeroML Open Dataset Accelerates AI Physics Model Adoption

    Develop aerodynamic AI Physics models with HiLiftAeroML, an open-source dataset now available natively within Rescale AI Physics. Built from surface-based simulation data across four geometries and multiple angles of attack, it gives engineers a practical starting point for training AI surrogate models without first assembling and building their own dataset.

    Read More

  • Agentic Multi-Disciplinary Design Exploration with Ansys CFX and Mechanical

    Agentic Multi-Disciplinary Design Exploration with Ansys CFX and Mechanical

    Connect CFD insight to downstream engineering decisions with an agentic Ansys CFX and Mechanical workflow on Rescale. The workflow combines the power of agentic engineering with deterministic simulation across multiple disciplines, analyzing a completed CFX design study, identifying key parameters and data gaps, kicking off follow-on studies, and then brings CFX pressure loads into Mechanical…

    Read More

  • Coreweave Multi-node Workload Support

    Coreweave Multi-node Workload Support

    Rescale has now extended its job submission environment to support multi-node MPI and Kubernetes-based workloads running on CoreWeave Cloud, bringing enterprise-grade HPC capabilities to a cloud infrastructure option that offers meaningfully lower cost for large-scale simulation. The capability has been validated end-to-end across multi-node configurations, with stability confirmed through scale testing and initial production use…

    Read More

  • Simulation Guide Agent: Expert Guidance for Every Engineer, Tailored to Any Workflow

    Simulation Guide Agent: Expert Guidance for Every Engineer, Tailored to Any Workflow

    Make simulation expertise easier to access across your organization. Rescale’s Simulation Guide Agent uses trusted technical documentation, user guides, templates, and team best practices to help users ask better questions, interpret results, select an appropriate workflow, configure jobs correctly, and verify recommendations before taking action, all within the existing simulation workflow on Rescale.

    Read More

  • Agent Foundations: The Building Blocks of Agentic Engineering Success

    Agent Foundations: The Building Blocks of Agentic Engineering Success

    Rescale’s purpose-built platform agents embed agentic actions into existing workflows, creating a trusted path towards end-to-end agentic engineering processes.

    Read More

  • Predictive Maintenance Digital Twins: Connect Simulation, Python, and Machine Learning

    Predictive Maintenance Digital Twins: Connect Simulation, Python, and Machine Learning

    Build digital twin workflows that connect simulation and machine learning in one engineering process. Rescale helps teams move beyond isolated analyses by linking physics-based simulation, custom code, and data-driven models so digital twin initiatives can become more practical, repeatable, and useful in day-to-day engineering work.

    Read More

  • Multi-stage Simulation Workflows for Computational Chemistry

    Multi-stage Simulation Workflows for Computational Chemistry

    Run multi-stage computational chemistry workflows without manual handoffs between steps. Rescale helps research teams connect simulation stages, compute environments, and downstream analysis so complex studies move forward in a more repeatable, scalable workflow instead of depending on ad hoc scripts and one-off operational effort.

    Read More

  • Automated CAD-to-CFD Design Loops with Data Lake Integration

    Automated CAD-to-CFD Design Loops with Data Lake Integration

    Shorten the loop between design changes and aerodynamic insight. Rescale can connect updated CAD inputs, CFD workflows, and engineering data pipelines so new designs automatically trigger analysis, feed results into a shared data foundation, and return faster feedback to the teams shaping the product.

    Read More

  • Parametric Optimization via Local AI Inference

    Parametric Optimization via Local AI Inference

    Explore more design options faster with local AI Physics inference. Rescale’s inference tooling lets engineers connect geometry, surrogate models, and outputs in a lightweight design workflow so they can run parametric studies and optimization loops directly on their own device (e.g. local workstation) without needing inference servers or HPC clusters.

    Read More

  • File Sharing Across Multi-Step Simulation Workflows

    File Sharing Across Multi-Step Simulation Workflows

    Move files across multi-step workflows without manual hand-offs or separate storage setup. Rescale Workflows can now use cloud storage to pass files directly between job and workstation steps, helping engineering teams keep preprocessing, solve, and post-processing stages connected inside one reusable workflow.

    Read More

  • Compute Economics: How Engineering Teams Spend Smarter on Rescale
    ,

    Compute Economics: How Engineering Teams Spend Smarter on Rescale

    Rescale’s novel cost controls help engineering and IT leaders reduce computing spending while preserving the benefits of cloud–all without changing the way engineering teams work.

    Read More

  • Agent-Accelerated Computational Chemistry

    Agent-Accelerated Computational Chemistry

    Accelerate computational chemistry workflows with agentic support for molecular dynamics simulation on Rescale. Agents help researchers analyze results, propose next steps, configure new simulations, and critique outcomes with scientific context preserved, connecting HPC execution, scientific analysis, historical knowledge, and job setup into one guided workflow that keeps the researcher in control.

    Read More

  • AI Physics for Automotive Crash and Structural FEA Simulations

    AI Physics for Automotive Crash and Structural FEA Simulations

    Build surrogate models for crash and structural simulation with Rescale’s integrated AI Physics workflow for transient FEA data. The updated crash use case brings GeoTransolver support for transient behavior, solver-specific metadata extraction, and training-ready formatting into one reusable pipeline—helping engineers move toward faster crash insight with less manual setup.

    Read More

  • Evaluation Framework for Engineering Agents

    Evaluation Framework for Engineering Agents

    Deploy engineering agents with confidence with Rescale’s agent evaluation approach, anchored by the Rescale Agent Fidelity Toolkit (RAFT). Rescale RAFT combines response scoring, tool-use validation, ground-truth checks, and continuous monitoring to systematically verify that agents deliver relevant answers and take correct actions, providing the quality discipline that production agentic engineering demands.

    Read More

  • Rescale Interlink: Open-Source Data Transfer and Job Management

    Rescale Interlink: Open-Source Data Transfer and Job Management

    Move simulation data between your desktop and the cloud faster with Rescale Interlink, an open-source hybrid CLI and GUI tool for managing files and jobs on Rescale. FIPS 140-3 compliant and available on Windows, Mac, and Linux, Interlink delivers multithreaded parallel transfers, a visual file browser, auto-download of completed job results, and full job submission,…

    Read More

  • Agent-Driven Simulation Troubleshooting

    Agent-Driven Simulation Troubleshooting

    Resolve simulation failures in minutes, not hours. Rescale’s Job Troubleshooting Agent analyzes solver logs, pinpoints the failure, explains what went wrong in plain language, and recommends corrective actions, all within the Rescale Assistant. Engineers review and approve fixes before resubmission, keeping human judgment in the loop while eliminating the manual overhead of failure diagnosis.

    Read More

  • Simulation Monitoring Automation

    Simulation Monitoring Automation

    Detect diverging and stalled simulations in real time, before they waste hours of compute. The Simulation Monitor automation runs alongside iterative solver jobs on Rescale, providing a live dashboard with residual plots, tabular data switching, and automated CSV exports without requiring an interactive workstation. It supports Ansys Fluent, STAR-CCM+, and CFX today, with a plugin-based…

    Read More

  • How Rescale Data Connectors Harness Historical Engineering Datasets to Unlock Simulation Breakthroughs

    How Rescale Data Connectors Harness Historical Engineering Datasets to Unlock Simulation Breakthroughs

    Connect, find, and use external engineering data more easily on Rescale. Engineering data rarely lives in one place. Simulation inputs, reference documents, program files, and supporting context often sit across cloud object stores, SharePoint libraries, and other enterprise systems. That fragmentation slows teams down, especially when engineers need to find the right file quickly, attach…

    Read More

  • Open-source AI Datasets for AI Physics Model Training

    Open-source AI Datasets for AI Physics Model Training

    Start training surrogate models faster with open-source AI Datasets now available in Rescale AI Physics. Engineers can now train models directly from the DrivAerML dataset, a subset of the high-fidelity open-source public dataset for automotive aerodynamics based on 500 parametrically morphed variants. Providing a great way to get started with AI Physics without having to…

    Read More

  • Q2 News | Agentic Digital Engineering, Platform Highlights and More

    Q2 News | Agentic Digital Engineering, Platform Highlights and More

    Engineering teams can now put AI-first engineering into practice on Rescale — with new capabilities across agentic digital engineering, AI physics, and compute economics that streamline routine workflows, operationalize AI-assisted product development, and make smarter tradeoffs between speed, throughput, and cost.

    Read More