Methodological advances in predicting flow-induced dynamics of plants using mechanical-engineering theory

Emmanuel De Langre 1, *
Abstract : The modeling of fluid-structure interactions, such as flow-induced vibrations, is a well-developed field of mechanical engineering. Many methods exist, and it seems natural to apply them to model the behavior of plants, and potentially other cantilever-like biological structures, under flow. Overcoming this disciplinary divide, and the application of such models to biological systems, will significantly advance our understanding of ecological patterns and processes and improve our predictive capabilities. Nonetheless, several methodological issues must first be addressed, which I describe here using two practical examples that have strong similarities: one from agricultural sciences and the other from nuclear engineering. Very similar issues arise in both: individual and collective behavior, small and large space and time scales, porous modeling, standard and extreme events, trade-off between the surface of exchange and individual or collective risk of damage, variability, hostile environments and, in some aspects, evolution. The conclusion is that, although similar issues do exist, which need to be exploited in some detail, there is a significant gap that requires new developments. It is obvious that living plants grow in and adapt to their environment, which certainly makes plant biomechanics fundamentally distinct from classical mechanical engineering. Moreover, the selection processes in biology and in human engineering are truly different, making the issue of safety different as well. A thorough understanding of these similarities and differences is needed to work efficiently in the application of a mechanistic approach to ecology.
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Article dans une revue
Journal of Experimental Biology, Cambridge University Press, 2012, 215 (march), pp.914-921. 〈10.1242/​jeb.058933〉
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Emmanuel De Langre. Methodological advances in predicting flow-induced dynamics of plants using mechanical-engineering theory. Journal of Experimental Biology, Cambridge University Press, 2012, 215 (march), pp.914-921. 〈10.1242/​jeb.058933〉. 〈hal-01025500〉

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