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Ansys 2025 R2 Enables Next-Level Productivity by Leveraging AI, Smart Automation, and Broader On-Demand Capabilities
SynopsysSynopsys(US:SNPS) Prnewswire·2025-07-29 13:00

Core Insights - Ansys, now part of Synopsys, announced the release of 2025 R2, featuring AI-powered capabilities that enhance simulation speed and accessibility [2][3] - The new version includes improved solvers, streamlined workflows, and expanded Python compatibility, enabling better engineering agility and cloud computing [2][3] AI-Driven Enhancements - Ansys Engineering Copilot is introduced as a virtual assistant that provides AI-driven assistance within Ansys products, enhancing user experience and access to resources [4][5] - The integration of Microsoft Azure AI Foundry with AnsysGPT allows for automatic creation, validation, and optimization of simulations, reducing manual effort and human error [5][6] Data Management and Automation - The latest release simplifies data handling and management, boosting efficiency and collaboration across enterprises [7][11] - Enhanced model-based systems engineering (MBSE) capabilities ensure digital continuity and cross-team collaboration [7] Python Compatibility and Customization - Expanded Python compatibility allows for customized automation, accelerating workflows and improving data management [9] - Companies like Danfoss Drives utilize Ansys simulation to validate complex designs, optimizing performance and reducing energy consumption [9][10] Cloud-Based Simulation - Cloud technology and high-performance computing (HPC) capabilities enable faster, scalable simulations, allowing for more design possibilities [15] - Ansys Cloud Burst Compute™ provides on-demand HPC capabilities across multiple products, streamlining setup and eliminating the need for extensive IT support [20] Advanced Computational Tools - Ansys continues to enhance its core technology to solve complex design challenges, enabling faster results and unlocking new product development opportunities [12][14] - New features in Ansys Mechanical improve performance on large transient models and enhance meshing capabilities for complex systems [16]