Model and data synthesis of the tire-road system (long-term forecast) taking into account polymorphic uncertainty (B04)

在TP B04中，开发了多物理多场问题的时间均匀化方法，以TP A01中详细的物理3D轮胎-道路模型以及可用于长期预测的简化模型（2D参考路面截面，神经网络）为基础，获得轮胎-道路系统的长期模型。简化后的模型为多态不确定性建模环境下的不确定性分析提供了快速的确定性解决方案。为此，考虑了实验数据（材料数据）和传感器技术数据（测量），并与模型的仿真结果进行了综合。

In TP B04, temporal homogenization methods for multi-physical multi-field problems are developed in order to obtain a long-term model of the tire-road system based on the detailed, physical 3D tire-road model from TP A01 as well as reduced models (2D reference cross-section of the road, neural networks) that can be used for long-term predictions. The reduced models provide the fast deterministic solution for uncertainty analyzes in the context of polymorphic uncertainty modeling. For this purpose, data from experiment (material data) and sensor technology (measurement) are considered and synthesized with the simulation results of the model.