作者: Matthew Collette , Kaihua Zhang
DOI: 10.1016/J.MARSTRUC.2021.102943
关键词: Structural engineering 、 Tension (physics) 、 Work (physics) 、 Experimental data 、 Strain gauge 、 System capacity 、 Structural degradation 、 Computer science 、 Structural system 、 Measure (data warehouse)
摘要: Abstract Few experimental data sets exist in the literature to support development and evaluation of digital twins predicting structural degradation. The is especially sparse for system tests where multiple failures occur interact. In this work, a laboratory-level experiment conducted mimic many properties larger more complex marine structures with redundant load paths, failure interaction, component-to-system level integration. experiment, such are reflected by hexagon tension specimen four propagating fatigue cracks tested under displacement-controlled loading. applied loading cycles corresponding crack lengths recorded as major time-varying degradation, resisting force at maximum extension used capacity. A novel computer vision method measure length. Strain gauges also monitor structure’s status. presented analyzed paper. resulting can be evaluate performance different twin updating approaches.