scholarly journals Observation and analysis of diving beetle movements while swimming

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Debo Qi ◽  
Chengchun Zhang ◽  
Jingwei He ◽  
Yongli Yue ◽  
Jing Wang ◽  
...  
Keyword(s):  
Swimming Speed ◽  
High Speed ◽  
Kinematic Model ◽  
Movement Pattern ◽  
Unmanned Vehicles ◽  
Power Stroke ◽  
Cross Sectional ◽  
Motion Data ◽  
The Cross ◽  
Diving Beetle

AbstractThe fast swimming speed, flexible cornering, and high propulsion efficiency of diving beetles are primarily achieved by their two powerful hind legs. Unlike other aquatic organisms, such as turtle, jellyfish, fish and frog et al., the diving beetle could complete retreating motion without turning around, and the turning radius is small for this kind of propulsion mode. However, most bionic vehicles have not contained these advantages, the study about this propulsion method is useful for the design of bionic robots. In this paper, the swimming videos of the diving beetle, including forwarding, turning and retreating, were captured by two synchronized high-speed cameras, and were analyzed via SIMI Motion. The analysis results revealed that the swimming speed initially increased quickly to a maximum at 60% of the power stroke, and then decreased. During the power stroke, the diving beetle stretched its tibias and tarsi, the bristles on both sides of which were shaped like paddles, to maximize the cross-sectional areas against the water to achieve the maximum thrust. During the recovery stroke, the diving beetle rotated its tarsi and folded the bristles to minimize the cross-sectional areas to reduce the drag force. For one turning motion (turn right about 90 degrees), it takes only one motion cycle for the diving beetle to complete it. During the retreating motion, the average acceleration was close to 9.8 m/s2 in the first 25 ms. Finally, based on the diving beetle's hind-leg movement pattern, a kinematic model was constructed, and according to this model and the motion data of the joint angles, the motion trajectories of the hind legs were obtained by using MATLAB. Since the advantages of this propulsion method, it may become a new bionic propulsion method, and the motion data and kinematic model of the hind legs will be helpful in the design of bionic underwater unmanned vehicles.

scholarly journals Vehicle-Bridge Coupling Vibration Analysis for Simply Supported Girders of High-Speed Railway Bridges Based on the Cross-Sectional Decentralized Centre of Mass and Shear

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Chen Daihai ◽  
Zhou Shuai ◽  
Xu Shizhan ◽  
Li Zheng ◽  
Fang Yilin
Keyword(s):  
Dynamic Response ◽  
High Speed ◽  
Influence Factors ◽  
Centre Of Mass ◽  
Cross Sectional ◽  
High Speed Railway ◽  
Coupling Vibration ◽  
Offset Distance ◽  
Spatial Beam ◽  
The Cross

Taking the simply supported box girder bridge of high-speed railway as an example, the effect of cross-sectional decentralized centre of mass and shear on the spatial beam element stiffness matrix was theoretically derived. Based on the vehicle-bridge coupling vibration analysis method of the railway bridge, an analysis program of vehicle-bridge coupling vibration for the high-speed railway was compiled, and its reliability was verified through an example analysis. On this basis, considering the cross-sectional decentralized centre of mass and shear, the influence factors of vehicle-bridge coupling vibration response were studied, which included the offset distance of the beam section’s mass and shear centre, offset distance of track centreline, vehicle weight, and vehicle speed. The results show that the additional items of the spatial beam element stiffness matrix are generated by the torsion effect when the cross-sectional decentralized centre of mass and shear is considered, and it will affect the lateral and vertical stiffness of the element. The cross-sectional decentralized centre of mass and shear has a significant effect on the lateral dynamic response of the bridge’s mid-span, but the influence on the vertical response of the bridge and the dynamic response of the car body is small. The main influence factors of the lateral dynamic response of the bridge are the vertical offset distance of the beam section’s centre of mass and shear, the lateral offset distance of the track centreline, and the vehicle weight.

scholarly journals High-Speed Ice Friction Experiments under Lab Conditions: On the Influence of Speed and Normal Force

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Matthias Scherge ◽  
Roman Böttcher ◽  
Mike Richter ◽  
Udo Gurgel
Keyword(s):  
Coefficient Of Friction ◽  
High Speed ◽  
Aerodynamic Drag ◽  
Limiting Factors ◽  
Maximum Speed ◽  
Cross Sectional ◽  
Sliding Speed ◽  
Ice Friction ◽  
Wide Range ◽  
The Cross

Using a high-speed tribometer, coefficients of friction for bobsled runners were measured over a wide range of loads and speeds. Between 2.8 m/s and 28 m/s (equal to 10 km/h and 100 km/h), the measured coefficients of friction showed a linear decrease with increasing speed. The experiments revealed ultra-low friction coefficients of less than 0.01 after exceeding a sliding speed of about 20 m/s. At maximum speed of 28 m/s, the average coefficient of friction was 0.007. The experiments help to bridge the gap between numerous low-speed friction tests by other groups and tests performed with bobsleds on real tracks. It was shown that the friction data obtained by other groups and our measurements can be approximated by a single master curve. This curve exhibits the largest decrease in friction up to a sliding speed of about 3 m/s. The further increase in speed generates only a small decrease in friction. In addition, friction decreases with increasing load. The decrease stops when ice wear becomes effective. The load point of constant friction depends on the cross-sectional radius of the runner. The larger the radius is, the higher the load is, before the ice shows signs of fracture. It turned out that besides aerodynamic drag (not considered in this work), ice friction is one of the main speed-limiting factors. In terms of runner geometry, a flat contact of runner and ice ensures the lowest friction. The rocker radius of the runner is of greater importance for a low coefficient of friction than the cross-sectional radius.

Biomechanics of Frog Swimming: II. Mechanics of the Limb-Beat Cycle in Hymenochirus Boettgeri

1988 ◽  
Vol 138 (1) ◽  
pp. 413-429 ◽  
Author(s):  
JULIANNA M. GAL ◽  
R. W. BLAKE
Keyword(s):  
High Speed ◽  
Preceding Paper ◽  
Movement Pattern ◽  
Circular Cylinders ◽  
Power Stroke ◽  
Hymenochirus Boettgeri ◽  
Force Components ◽  
The Right ◽  
Hindlimb Kinematics ◽  
Flexion And Extension

The hindlimb kinematics of Hymenochirus boettgeri (Tornier) were investigated using high-speed ciné films. The movement pattern was stereotypic, flexion and extension of the metatarsal-phalangeals and feet always lagging behind flexion and extension of the femora and tibiofibulae. The right hindlimb was modelled as a series of linked circular cylinders and a flat plate. A blade-element approach was used to calculate the quasi-steady drag-based and accelerative force components parallel to the direction of motion, based on the hindlimb kinematics of sequence 1 (see preceding paper). Positive thrust is generated primarily during the initial stages of extension (power stroke) because of unsteady (added mass) effects. Negative thrust occurs over the latter half of extension, despite the continued acceleration of the animal. Hindlimb interaction is thought to provide propulsive thrust for the latter half of the extension phase. It is suggested that a jet and/or reflective effect may be involved.

On the cross-sectional shape of the cellulose crystallites in the tunicate Halocynthia papillosa

1990 ◽  
Vol 48 (3) ◽  
pp. 566-567
Author(s):  
J.-F. Revol ◽  
Y. Van Daele ◽  
F. Gaill
Keyword(s):  
Contrast Imaging ◽  
Animal Kingdom ◽  
Bright Field ◽  
Field Mode ◽  
Cross Sectional ◽  
Ultrathin Sections ◽  
The Cross ◽  
Sectional Shape ◽  
Valonia Ventricosa ◽  
C Nmr

The only form of cellulose which could unequivocally be ascribed to the animal kingdom is the tunicin that occurs in the tests of the tunicates. Recently, high-resolution solid-state l3C NMR revealed that tunicin belongs to the Iβ form of cellulose as opposed to the Iα form found in Valonia and bacterial celluloses. The high perfection of the tunicin crystallites led us to study its crosssectional shape and to compare it with the shape of those in Valonia ventricosa (V.v.), the goal being to relate the cross-section of cellulose crystallites with the two allomorphs Iα and Iβ.In the present work the source of tunicin was the test of the ascidian Halocvnthia papillosa (H.p.). Diffraction contrast imaging in the bright field mode was applied on ultrathin sections of the V.v. cell wall and H.p. test with cellulose crystallites perpendicular to the plane of the sections. The electron microscope, a Philips 400T, was operated at 120 kV in a low intensity beam condition.

A Technique for Measuring the Cross-Sectional Axes of the Longissimus Dorsi Muscle and Fat Depth in Lambs1,2

1960 ◽  
Vol 19 (3) ◽  
pp. 803-809
Author(s):  
D. J. Matthews ◽  
R. A. Merkel ◽  
J. D. Wheat ◽  
R. F. Cox
Keyword(s):  
Longissimus Dorsi ◽  
Cross Sectional ◽  
Longissimus Dorsi Muscle ◽  
Dorsi Muscle ◽  
The Cross

Automated Diagonal Slice and View Solution for 3D Device Structure Analysis

2018 ◽  
Author(s):  
Sang Hoon Lee ◽  
Jeff Blackwood ◽  
Stacey Stone ◽  
Michael Schmidt ◽  
Mark Williamson ◽  
...  
Keyword(s):  
Cross Section ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Image Data ◽  
Planar Surface ◽  
Device Structure ◽  
Cross Sectional ◽  
Device Structures ◽  
The Cross ◽  
Planar Analysis

Abstract The cross-sectional and planar analysis of current generation 3D device structures can be analyzed using a single Focused Ion Beam (FIB) mill. This is achieved using a diagonal milling technique that exposes a multilayer planar surface as well as the cross-section. this provides image data allowing for an efficient method to monitor the fabrication process and find device design errors. This process saves tremendous sample-to-data time, decreasing it from days to hours while still providing precise defect and structure data.

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