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The physics of snapping a twig

APR 16, 2021
By studying the mechanical properties of jujube branches, researchers learned how much to trust computer models when studying microstructures in the natural world.
The physics of snapping a twig internal name

The physics of snapping a twig lead image

Jujube is a common cash crop grown in China for its sweet fruit. Although often referred to as red dates, the jujube is not related to dates at all.

But Wang et al. were not after the delectable fruit. Instead, they studied the shear and compression mechanical properties of jujube branches, and the relationship between these properties and the microstructure of the branches. By testing the performance of different computer models for predicting a microstructure’s macro-mechanical properties, they quantified the accuracy of the models based on the different ways they were simplified.

First, they used computer tomography to scan and reconstruct a high-resolution model of the microstructure of the jujube branches. Then, they constructed a simplified version of the model by making the microstructure smoother and more regular.

Compared to the natural model, the transverse elastic modulus predicted by the simplified model was off by more than15% in some cases. The authors attribute this deviation to the assumption made in the simplified model that fibers grow perfectly parallel to the branch, while there exist some variations in reality. However, the longitudinal and transverse shear moduli predicted by the simplified model were not as affected by this assumption and were only off by roughly 4% and 2%, respectively.

The authors expect the effect of cell distribution on the transverse elastic modulus to be present in mechanical models across length scales. The findings can guide the use of simplified models when studying “the mechanical properties of plant stems, bones and even alveoli, and design bionic structures or porous materials,” said author Baoshuai Wang.

Source: “Evaluation of biomechanical properties of jujube branches and analysis of prediction accuracy based on multi-scale artificially simplified model,” by Baoshuai Wang, Xuyang Zhao, Huijie Peng, Hewei Meng, Lihong Wang, and Chengsong Li, AIP Advances (2021). The article can be accessed at https://doi.org/10.1063/5.0035110 .

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