...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mechanical systems and signal processing >A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements
【24h】

A fast Bayesian inference scheme for identification of local structural properties of layered composites based on wave and finite element-assisted metamodeling strategy and ultrasound measurements

机译：一种快速贝叶斯推理方案，用于识别基于波和有限元辅助元义策略和超声测量的分层复合材料局部结构性能

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Reliable verification and evaluation of the mechanical properties of a layered composite ensemble are critical for industrially relevant applications, however it still remains an open engineering challenge. In this study, a fast Bayesian inference scheme based on multi-frequency single shot measurements of wave propagation characteristics is developed to overcome the limitations of ill-conditioning and non-uniqueness associated with the conventional approaches. A Transitional Markov chain Monte Carlo (TMCMC) algorithm is employed for the sampling process. A Wave and Finite Element (WFE)-assisted metamodeling scheme in lieu of expensive-to-evaluate explicit FE analysis is proposed to cope with the high computational cost involved in TMCMC sampling. For this, the Kriging predictor providing a surrogate mapping between the probability spaces of the model predictions for the wave characteristics and the mechanical properties in the likelihood evaluations is established based on the training outputs computed using a WFE forward solver, coupling periodic structure theory to conventional FE. The valuable uncertainty information of the prediction variance introduced by the use of a surrogate model is also properly taken into account when estimating the parameters' posterior probability distribution by TMCMC. A numerical study as well as an experimental study are conducted to verify the computational efficiency and accuracy of the proposed methodology. Results show that the TMCMC algorithm in conjunction with the WFE forward solver-aided metamodeling can sample the posterior Probability Density Function (PDF) of the updated parameters at a very reasonable cost. This approach is capable of quantifying the uncertainties of recovered independent characteristics for each layer of the composite structure under investigation through fast and inexpensive experimental measurements on localized portions of the structure.
机译：可靠的验证和评估层叠综合集合的机械性能对工业相关的应用至关重要，但它仍然是开放的工程挑战。在本研究中，基于多频单拍摄测量的波传播特性的快速贝叶斯推理方案是开发的，以克服与传统方法相关的不良调节和非唯一性的局限性。用于采样过程采用过渡性马尔可夫链蒙特卡罗（TMCMC）算法。提出了一种波浪和有限元（WFE） - 拟合元素的元素调节方案，代替昂贵至评价FE分析，以应对TMCMC采样中涉及的高计算成本。为此，基于使用WFE向前求解器，耦合周期性结构理论到传统的训练输出，建立在波特性的模型预测的概率空间之间提供代理映射的替代空间和似然评估中的概率评估。 FE。当通过TMCMC估算参数的后验概率分布时，还可以正确考虑通过使用代理模型引入的预测方差的有价值的不确定性信息。进行了数值研究以及实验研究，以验证所提出的方法的计算效率和准确性。结果表明，TMCMC算法与WFE前进求解器辅助元素结合可以以非常合理的成本对更新参数的后验概率密度函数（PDF）进行采样。这种方法能够通过对结构的局部部分的快速和廉价的实验测量来定量正在调查的复合结构层的回收独立特性的不确定性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号