A low-frequency multi-mode ultrasonic Lamb wave method suitable for character- izing the thickness, the density and the elastic constants of the ultra-thin transversely isotropic laminate composite is presented. The &...A low-frequency multi-mode ultrasonic Lamb wave method suitable for character- izing the thickness, the density and the elastic constants of the ultra-thin transversely isotropic laminate composite is presented. The 'ultra-thin' here means that the thickness of the plate is much less than the wavelength of the ultrasonic wave so that the echoes from the front and back faces of the plate can't be separated in the time domain. The dispersion equations for the low frequency ultrasonic Lamb waves with the propagation directions parallel and vertical to the fiber direction are derived. In conjunction with the least square algorithm method, the secant algorithm is used to estimate the parameters of the ultra-thin fiber-reinforced composite layer. The evaluation errors and the sensitivity of the method to different paramters of the thin composite are analyzed. The technique has been used to characterize the ultra-thin grass fiber reinforced PES composite with thickness down to ten percents of the ultrasonic wavelength. It is observed that the agreement between the nominal and the estimation values is reasonably good.展开更多
Soft robotic crawlers have limited payload capacity and crawling speed.This study proposes a high-performance inchworm-like modular robotic crawler based on fluidic prestressed composite(FPC)actuators.The FPC actuator...Soft robotic crawlers have limited payload capacity and crawling speed.This study proposes a high-performance inchworm-like modular robotic crawler based on fluidic prestressed composite(FPC)actuators.The FPC actuator is precurved and a pneumatic source is used to flatten it,requiring no energy cost to maintain the equilibrium curved shape.Pressurizing and depressurizing the actuators generate alternating stretching and bending motions of the actuators,achieving the crawling motion of the robotic crawler.Multi-modal locomotion(crawling,turning,and pipe climbing)is achieved by modular reconfiguration and gait design.An analytical kinematic model is proposed to characterize the quasi-static curvature and step size of a single-module crawler.Multiple configurations of robotic crawlers are fabricated to demonstrate the crawling ability of the proposed design.A set of systematic experiments are set up and conducted to understand how crawler responses vary as a function of FPC prestrains,input pressures,and actuation frequencies.As per the experiments,the maximum carrying load ratio(carrying load divided by robot weight)is found to be 22.32,and the highest crawling velocity is 3.02 body length(BL)per second(392 mm/s).Multi-modal capabilities are demonstrated by reconfiguring three soft crawlers,including a matrix crawler robot crawling in amphibious environments,and an inching crawler turning at an angular velocity of 2/s,as well as earthworm-like crawling robots climbing a 20 inclination slope and pipe.展开更多
The traditional stochastic homogenization method can obtain homogenized solutions of elliptic problems with stationary random coefficients.However,many random composite materials in scientific and engineering computin...The traditional stochastic homogenization method can obtain homogenized solutions of elliptic problems with stationary random coefficients.However,many random composite materials in scientific and engineering computing do not satisfy the stationary assumption.To overcome the difficulty,we propose a normalizing field flow induced two-stage stochastic homogenization method to efficiently solve the random elliptic problem with non-stationary coefficients.By applying the two-stage stochastic homogenization method,the original elliptic equation with random and fast oscillatory coefficients is approximated as an equivalent elliptic equation,where the equivalent coefficients are obtained by solving a set of cell problems.Without the stationary assumption,the number of cell problems is large and the corresponding computational cost is high.To improve the efficiency,we apply the normalizing field flow model to learn a reference Gaussian field for the random equivalent coefficients based on a small amount of data,which is obtained by solving the cell problems with the finite element method.Numerical results demonstrate that the newly proposed method is efficient and accurate in tackling high dimensional partial differential equations in composite materials with complex random microstructures.展开更多
基金the National Natural Science Foundation of China (No. 69631020) and theOffice of Naval Research of America (00014-93-1-0340).
文摘A low-frequency multi-mode ultrasonic Lamb wave method suitable for character- izing the thickness, the density and the elastic constants of the ultra-thin transversely isotropic laminate composite is presented. The 'ultra-thin' here means that the thickness of the plate is much less than the wavelength of the ultrasonic wave so that the echoes from the front and back faces of the plate can't be separated in the time domain. The dispersion equations for the low frequency ultrasonic Lamb waves with the propagation directions parallel and vertical to the fiber direction are derived. In conjunction with the least square algorithm method, the secant algorithm is used to estimate the parameters of the ultra-thin fiber-reinforced composite layer. The evaluation errors and the sensitivity of the method to different paramters of the thin composite are analyzed. The technique has been used to characterize the ultra-thin grass fiber reinforced PES composite with thickness down to ten percents of the ultrasonic wavelength. It is observed that the agreement between the nominal and the estimation values is reasonably good.
基金supported by the National Natural Science Foundation of China under Grant No.62203174the Guangzhou Municipal Science and Technology Project under Grant No.202201010179.
文摘Soft robotic crawlers have limited payload capacity and crawling speed.This study proposes a high-performance inchworm-like modular robotic crawler based on fluidic prestressed composite(FPC)actuators.The FPC actuator is precurved and a pneumatic source is used to flatten it,requiring no energy cost to maintain the equilibrium curved shape.Pressurizing and depressurizing the actuators generate alternating stretching and bending motions of the actuators,achieving the crawling motion of the robotic crawler.Multi-modal locomotion(crawling,turning,and pipe climbing)is achieved by modular reconfiguration and gait design.An analytical kinematic model is proposed to characterize the quasi-static curvature and step size of a single-module crawler.Multiple configurations of robotic crawlers are fabricated to demonstrate the crawling ability of the proposed design.A set of systematic experiments are set up and conducted to understand how crawler responses vary as a function of FPC prestrains,input pressures,and actuation frequencies.As per the experiments,the maximum carrying load ratio(carrying load divided by robot weight)is found to be 22.32,and the highest crawling velocity is 3.02 body length(BL)per second(392 mm/s).Multi-modal capabilities are demonstrated by reconfiguring three soft crawlers,including a matrix crawler robot crawling in amphibious environments,and an inching crawler turning at an angular velocity of 2/s,as well as earthworm-like crawling robots climbing a 20 inclination slope and pipe.
基金supported by the National Natural Science Foundation of China grant(12131002,51739007,12271409)Strategic Priority Research Program of the Chinese Academy of Sciences(XDC06030101)+2 种基金the National Key R&D Program of China with the grant(2020YFA-0713603)Natural Science Foundation of Shanghai grant(21ZR1465800)the Interdisciplinary Project in Ocean Research of Tongji University and the Fundamental Research Funds for the Central Universities..
文摘The traditional stochastic homogenization method can obtain homogenized solutions of elliptic problems with stationary random coefficients.However,many random composite materials in scientific and engineering computing do not satisfy the stationary assumption.To overcome the difficulty,we propose a normalizing field flow induced two-stage stochastic homogenization method to efficiently solve the random elliptic problem with non-stationary coefficients.By applying the two-stage stochastic homogenization method,the original elliptic equation with random and fast oscillatory coefficients is approximated as an equivalent elliptic equation,where the equivalent coefficients are obtained by solving a set of cell problems.Without the stationary assumption,the number of cell problems is large and the corresponding computational cost is high.To improve the efficiency,we apply the normalizing field flow model to learn a reference Gaussian field for the random equivalent coefficients based on a small amount of data,which is obtained by solving the cell problems with the finite element method.Numerical results demonstrate that the newly proposed method is efficient and accurate in tackling high dimensional partial differential equations in composite materials with complex random microstructures.
