基于CSDI扩散模型的连续FRP降解曲线的概率模型和预测
Yuan Yue1,2, Ming-Li Zhou3, Hui Shen3
1School of Civil Engineering and Architecture, Henan University, Kaifeng 475004, China.
Polymers
|March 14, 2026
概括
本研究引入了使用CSDI扩散模型进行持续纤维增强聚合物 (FRP) 耐久性预测的新概率框架. 它可以从有限的数据准确地预测退化曲线,提高结构可靠性评估.
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 数据科学数据科学数据科学
背景情况:
- 传统的纤维增强聚合物 (FRP) 耐久性预测使用离散回归,忽视时间数据模式和不确定性.
- 现有的方法在稀少的实验数据中扎,限制了准确的长期性能预测.
研究的目的:
- 为持续FRP降解曲线重建开发一种新的概率框架.
- 使用有限的数据,使FRP结构的准确长期预测和生命周期可靠性评估成为可能.
主要方法:
- 使用CSDI扩散模型重建连续FRP降解曲线.
- 制定了长期预测作为序列生成的条件归算任务.
- 采用多因素数据库来评估框架的性能.
主要成果:
- 实现了高预测准确度 (RMSE = 0.332,R2 = 0.86),数据缺失率为30%.
- 证明了强大的概率校准 (CRPS = 0.170),使得可靠的风险信封生成.
- 展示了对FRP性能演变的持续序列生成的范式转变.
结论:
- 基于CSDI的框架为FRP生命周期可靠性评估在小样本限制下提供了可靠的工具.
- 这种概率方法增强了对FRP降解中的时间连贯性和随机不确定性的理解.
- 能够从稀疏的实验观测中生成物理一致的性能轨迹.
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