Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/155043
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dc.contributor.authorBurcham, Daniel C.en_US
dc.contributor.authorAu, Siu-Kuien_US
dc.date.accessioned2022-02-03T06:29:05Z-
dc.date.available2022-02-03T06:29:05Z-
dc.date.issued2022-
dc.identifier.citationBurcham, D. C. & Au, S. (2022). Identifying modal properties of trees with Bayesian inference. Agricultural and Forest Meteorology, 316, 108804-. https://dx.doi.org/10.1016/j.agrformet.2021.108804en_US
dc.identifier.issn0168-1923en_US
dc.identifier.urihttps://hdl.handle.net/10356/155043-
dc.description.abstractIn forested landscapes, the presence of trees enhances turbulent airflow governing the exchange of momentum, heat, and gas between the atmosphere and biosphere, especially when horizontal motion dominates near-surface winds, and tree vibration is a prominent feature of the dynamic interaction between wind and trees. The vibration characteristics of trees reflect their underlying mechanical properties (i.e., mass, stiffness, damping) and govern their response to dynamic loads. Despite numerous investigations of tree vibration, there have been few studies examining methodological improvements for identifying and characterizing variability in the modal properties of trees during ambient wind excitation. In the engineering disciplines, however, there are several techniques commonly used to estimate the modal properties of a structure from its ambient vibration, often called ‘operational modal analysis’ (OMA). Operating in the frequency domain, this study examined the use of Bayesian OMA for identifying several important modal properties, including frequencies, damping ratios, and partial mode shapes, as well as their identification uncertainty. Using the ambient vibration recorded on a mature Hopea odorata Roxb. (Dipterocarpaceae) tree over a one-week period, the identified modal properties and associated uncertainties were physically reasonable and consistent with previous measurements for trees, and the identification uncertainty was much greater for damping ratio than frequency, which can be explained theoretically. Beyond the consistency with existing measurements, the analysis also yielded new insight about the vibration behavior of large trees. The modal properties varied considerably over consecutive one-hour intervals, and the changes were likely related to differences in wind excitation during each period, suggesting the existence of amplitude dependence in the modal properties of trees. Over the same periods, there were consistently two close modes (i.e., with similar frequencies), oriented approximately orthogonal to one another, near the tree’s fundamental frequency. With additional evaluation and refinement, the techniques can be used for OMA of trees in different settings.en_US
dc.description.sponsorshipNanyang Technological Universityen_US
dc.language.isoenen_US
dc.relationSUG/4 (C120032000)en_US
dc.relation.ispartofAgricultural and Forest Meteorologyen_US
dc.rights© 2022 Elsevier B.V. All rights reserved. This paper was published in Agricultural and Forest Meteorology and is made available with permission of Elsevier B.V.en_US
dc.subjectEngineering::Civil engineeringen_US
dc.titleIdentifying modal properties of trees with Bayesian inferenceen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Civil and Environmental Engineeringen_US
dc.identifier.doi10.1016/j.agrformet.2021.108804-
dc.description.versionAccepted versionen_US
dc.identifier.volume316en_US
dc.identifier.spage108804en_US
dc.subject.keywordsAmbient Modal Identificationen_US
dc.subject.keywordsBAYOMAen_US
dc.subject.keywordsBiomechanicsen_US
dc.subject.keywordsOperational Modal Analysisen_US
dc.subject.keywordsTree Swayen_US
dc.description.acknowledgementThe second author was supported by grant SUG/4 (C120032000) from the Nanyang Technological University, Singapore.en_US
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item.grantfulltextembargo_20240501-
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