CRRC needed an industrial large-model environment and a faster approach to aerodynamic simulation so it could carry out the state-owned-enterprise 'AI plus industry' mandate without the time and compute overhead of traditional simulation tools.
Reported impact
CRRC gained a reusable industrial-AI service layer and a dramatic reduction in aerodynamic-simulation cycle time, improving both general AI adoption and a high-value engineering workload.
CRRC used Baidu AI Cloud to build two connected industrial-AI layers. First, Baidu delivered a one-stop enterprise large-model solution adapted to CRRC's domestic GPU environment, dedicated container cloud and MaaS interfaces. That gave CRRC access to language, image, computer-vision and multimodal model services for tasks such as agent development, visual analysis, quality inspection and design support. Second, the two sides created the 'Zhuolun Fengchi' aerodynamic-simulation large model for high-speed train development. Instead of treating simulation as a purely numerical batch job, the new design combines a data-driven simulation model, an efficient compute framework and application tools so engineers can change shapes and get feedback almost immediately. The platform therefore serves both general industrial-AI use cases and one deeply vertical engineering workload, giving CRRC a shared industrial model layer plus a breakthrough application in train aerodynamics.
Industrial users access language, vision and multimodal services through the MaaS platform, while train-shape data is sent through the aerodynamic large model to generate near-real-time simulation results for design iteration.
Baidu adapted the model suite to CRRC's domestic GPU, dedicated container cloud and MaaS service interfaces (original: 针对中国中车MaaS平台的国产GPU、专属容器云、服务接口，进行了模型的深度适配工作).
The aerodynamic-simulation large model cut runtime from 24 hours to 10 seconds on a single machine (original: 仿真时间从天级别缩短到了秒级别（从过去的24小时缩短至如今的10秒，单机运行）).
The platform gives CRRC language, image, CV and multimodal model capabilities for industrial tasks (original: 满足用户NLP自然语言处理、智能体开发、图文设计、CV行为分析、质量检验等一系列AI需求).
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