ERX特刊征稿|聚焦桥梁结构健康监测的物理信息学习方法

27 11月 2023 gabriels

特刊详情

客座编辑

  • Filippo Ubertini,意大利佩鲁贾大学
  • Simon Laflamme,美国爱荷华州立大学
  • Enrique Garcìa-Macìas,西班牙格拉纳达大学

主题范围

Recent advances in artificial intelligence (AI) and machine learning have opened vast possibilities for the development of next-generation structural health monitoring (SHM) systems. In their broadest sense, the increasingly frequent implementation of AI algorithms is empowering unprecedented methods to link monitoring signals to decision-making. Particularly promising are physics-based AI applications, enabling the injection of engineering knowledge and the outcomes of field inspections into the decision-making process. Such applications may become particularly ground-breaking for the condition-based maintenance of bridge structures, which represent key assets in the built infrastructure stock with critical socio-economic values related to the management of their accelerated degradation. The aim of this Focus Issue is to generate discussions on most recent research advances in physics-informed learning methods for bridge SHM. Topics of interest include, but are not limited to:

  • Deep learning
  • Supervised/unsupervised machine learning
  • Bayesian methods
  • Surrogate modelling
  • Model selection methods for damage identification
  • Intelligent signal processing
  • Data fusion
  • Data mining
  • Long-term big data processing and management
  • Internet of things for structural health monitoring of bridges
  • Field SHM applications to real bridges
  • Transfer learning

 

投稿流程

特刊文章与ERX期刊常规文章遵循相同的审稿流程和内容标准,并采用同样的投稿模式。

有关准备文章及投稿的详细信息,可以参阅IOPscience页面的作者指南。

作者可登入期刊主页进行在线投稿,先选择“文章类型”,然后在“选择特刊”的下拉框中选择“Focus Issue on Physics-Informed Learning Methods for Bridge Structural Health Monitoring”。

投稿截止日期:2023年12月31日。


期刊介绍

Engineering Research Express

  • 2022年影响因子:1.7  Citescore: 1.9
  • Engineering Research Express(ERX,《工程研究快讯》)是一本涵盖工程科学所有领域的多学科期刊,致力于发表新的实验和理论研究。ERX对文章长度的具有灵活性并采用快速同行评审政策。发表范围涵盖:电气工程(包括控制工程、量子工程、电子工程、光学工程、电力工程、机器人和半导体工程)、 机械工程(包括航空工程、汽车工程、材料工程和真空工程)、土木工程(包括环境工程、水利工程、海洋和地理工程、结构工程)、化学工程(包括生物工程、食品科学、化学合成和精炼,以及微加工)等方面。