Bentley Systems推出AI工程工具 钢材用量优化降低40%
分类科技
地点全球
来源CP
发布时间2026/05/20 11:54
详情描述
Bentley Systems近日宣布对其工程软件套件进行升级,通过集成人工智能技术,旨在实现复杂结构工作流的自动化。此次更新引入了模型上下文协议(Model Context Protocol),使AI代理能够执行具备可验证性的结构工程任务,以满足基础设施建设中对结构完整性的严苛要求。
该技术的核心应用集中在结构分析工具STAAD上。通过将AI与STAAD的工程引擎直接连接,工程师能够利用自然语言指令,自动完成板墙网格划分等高技能且重复性高的工作。这一流程旨在将工程师从繁琐的计算任务中解放出来,使其能够专注于高层级的判断与决策。
在实际生产模型的测试中,该AI优化方案展现了显著的工程效益。通过对多种几何形状和材料进行快速分析,AI驱动的优化设计成功将钢材用量减少了40%。该系统还建立了一个协作反馈循环,通过工程师的专业知识不断提升AI的执行效率,在确保结构安全的前提下,提升了基础设施建设的成本效益与可持续性。
📋 简要摘要 ▸
Bentley Systems通过集成AI技术升级其工程软件套件,利用Model Context Protocol实现复杂结构工作流的自动化。核心工具STAAD现可通过自然语言指令完成板墙网格划分等高难度任务。在生产模型测试中,该AI优化方案成功将钢材用量减少40%,显著提升了基础设施建设的成本效益与可持续性。
📋 完整原文 ▸
[来源: CP] [分类提示: NEWS]
标题: Bentley Systems Launches AI-Powered Engineering Tools to Revolutionize Global Infrastructure
Bentley Systems is redefining the future of civil engineering by integrating high-precision Artificial Intelligence (AI) into its industry-standard software suite. By utilizing the Model Context Protocol (MCP), Bentley is moving beyond simple text generation to provide engineers with AI agents capable of executing complex, verifiable structural workflows.
This shift addresses the critical need for absolute accuracy in infrastructure, where “plausible” AI outputs are insufficient and structural integrity is paramount.
The core of this advancement centers on STAAD, Bentley’s renowned structural analysis tool. By connecting AI directly to STAAD’s validated engineering engines, the software can now automate high-skill, repetitive tasks such as slab-wall meshing through simple natural language prompts. This collaboration allows human engineers to move away from tedious calculations and focus on high-level judgment and intuition.
The benefits of this AI integration are already yielding significant real-world results. In recent production model tests, AI-driven optimization successfully reduced steel weight by 40% by rapidly analyzing various geometries and materials—a feat that translates to massive cost savings and improved sustainability.
Furthermore, the system operates within a collaborative feedback loop, where the engineer’s expertise makes the AI more effective while ensuring