Fins from ray-finned fishes do not contain muscles, yet fish can change the shape of their fins with high precision and speed, while producing large hydrodynamic forces without collapsing. This remarkable performance has been intriguing researchers for decades, but experiments have so far focused on homogenized properties, and models were developed only for small deformations and small rotations. Here we present fully instrumented micromechanical tests on individual rays from Rainbow trout in both morphing and flexural deflection mode and at large deflections. We then present a nonlinear mechanical model of the ray that captures the key structural elements controlling the mechanical behavior of rays under large deformations, which we successfully fit onto the experiments for property identification. We found that the flexural stiffness of the mineralized layers in the rays (hemitrichs) is 5-6 times lower than their axial stiffness, an advantageous combination to produce stiff morphing. In addition, the collagenous core region can be modeled with spring elements which are 3-4 orders of magnitude more compliant than the hemitrichs. This fibrillar structure provides negligible resistance to shearing from the initial position, but it prevents buckling and collapse of the structure at large deformations. These insights from the experiments and nonlinear models can serve as new guidelines for the design of efficient bioinspired stiff morphing materials and structures at large deformations. STATEMENT OF SIGNIFICANCE: Fins from ray-finned fishes do not contain muscles, yet fish can change the shape of their fins with high precision and speed, while producing large hydrodynamic forces without collapsing. Experiments have so far focused on homogenized properties, and models were developed only for small deformations and small rotations providing limited insight into the rich nonlinear mechanics of natural rays. We present micromechanical tests in both morphing and flexural deflection mode on individual rays, a nonlinear model of the ray that captures the mechanical behavior of rays under large deformations and combine microCT measurements to generate new insights into the nonlinear mechanics of rays. These insights can serve as new guidelines for the design of efficient bioinspired stiff morphing materials and structures at large deformations.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.actbio.2023.06.029 | DOI Listing |
Sensors (Basel)
January 2025
Wearable and Gait Assessment Research (WAGAR) Group, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia.
Introduction: Gait analysis is a vital tool in the assessment of human movement and has been widely used in clinical settings to identify potential abnormalities in individuals. However, there is a lack of consensus on the normative values for gait metrics in large populations. The primary objective of this study is to establish a normative database of spatiotemporal gait metrics across various age groups, contributing to a broader understanding of human gait dynamics.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Xi'an Institute of Space Radio Technology, Xi'an 710100, China.
The deformation monitoring of integrated truss structures (ITSs) is essential for ensuring the reliable performance of mounted equipment in complex space environments. Reconstruction methods based on local strain information have been proven effective, yet the identification faces significant challenges due to variable thermal-mechanical loads, interactions among structural components, and special boundary conditions. This paper proposes a deformation reconstruction strategy tailored for ITSs under combined thermal-mechanical load scenarios wherein deformations of both the primary truss structures and the attached panel systems are investigated.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Faculty of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China.
To address the challenges of missed detections caused by insufficient shape and texture features and blurred boundaries in existing detection methods, this paper introduces a novel moving vehicle detection approach for satellite videos. The proposed method leverages frame difference and convolution to effectively integrate spatiotemporal information. First, a frame difference module (FDM) is designed, combining frame difference and convolution.
View Article and Find Full Text PDFJ Clin Med
January 2025
"Carol Davila" University of Medicine and Pharmacy, 020021 Bucharest, Romania.
Neurofibromatosis is a genetic disorder arising de novo or with an autosomal dominant transmission that typically presents either at birth or in early childhood, manifesting through distinctive clinical features such as multiple café-au-lait spots, benign tumors in the skin, bone enlargement, and deformities. This literature review aims to resume the spectrum of maternal and fetal complications encountered in pregnant women with neurofibromatosis type 1 (NF1). Thorough research was conducted on databases such as Web of Science, PubMed, Science Direct, Google Scholar, and Wiley Online Library.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
School of Mechanical and Electrical Engineering, Hainan University, Haikou 570228, China.
The phononic crystals composed of soft materials have received extensive attention owing to the extraordinary behavior when undergoing large deformations, making it possible to provide tunable band gaps actively. However, the inverse designs of them mainly rely on the gradient-driven or gradient-free optimization schemes, which require sensitivity analysis or cause time-consuming, lacking intelligence and flexibility. To this end, a deep learning-based framework composed of a conditional variational autoencoder and multilayer perceptron is proposed to discover the mapping relation from the band gaps to the topology layout applied with prestress.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!