Predicting Vehicle Frame Structural Stress Using AI Big Data Models｜Knowledge Studio

 Software used : Knowledge Studio

【 Background 】

      In the process of lightweight motorcycle frame design, ensuring sufficient structural strength, stiffness, and durability is crucial. Traditionally, designers had to rely on trial-and-error, validating frame designs through experiments or by building complex computational models. However, these methods consume significant time, resources, and manpower, and they also limit how extensively different design options can be explored.
      In recent years, with the rapid development of artificial intelligence (AI) and big data technologies, AI-driven data analytics can learn from large datasets and extract patterns to enable fast and accurate predictions. Therefore, the industry hopes to apply this technology to motorcycle frame design to improve design efficiency and performance.

 

【 Results 】

• Richin used Altair AI big data analytics software Knowledge Studio and trained an AI model with the customer’s historical frame structural data to perform prediction.

• It is confirmed that by inputting different frame structures and member thicknesses,  Knowledge Studio AI models can quickly predict the stress distribution of each region, helping designers optimize the structural layout. 

• By comparing with traditional CAE analysis results, it is verified that the Knowledge Studio AI model can successfully predict accurate structural stress and deformation.

• This approach enables faster and more accurate structural analysis and design optimization, thereby improving frame performance and safety while shortening time-to-market.

【 Technical Features 】

Direct prediction of stress and deformation: 
        Knowledge Studio allows users to import parameters into the AI model and directly predict structural stress and deformation. This means designers no longer need to rely solely on traditional experiments or complex model analyses, but can quickly obtain accurate results through an AI model.
 

Automatic selection of the best AI model: 

        Knowledge Studio allows users to import parameters into the AI model and directly predict structural stress and deformation. This means designers no longer need to rely solely on traditional experiments or complex model analyses, but can quickly obtain accurate results through an AI model.

Visualized plots and charts: 

       Knowledge Studio provides various visualization plots to help users better understand the data. For example, histograms can present the sensitivity of analysis parameters and help identify key parameters; correlation matrices can reveal relationships among parameters and help users discover potential patterns and dependencies.

AI model export and conversion:
        Knowledge Studio also provides the capability to convert AI models into C code, Python, and other program code formats. This allows users to easily integrate trained AI models into other applications or systems, enabling broader and more flexible deployment.