Search

The displacement field and governing equation completely depend on the cross-section shape in the torsion of nano-bars. Due to the torsion of structure and warping of its cross-section, axial strain is created. A review of the literature demonstrates that the effect of the normal strain in the torsional analysis of nanostructures with non-circular cross-sections is ignored for the sake of simplicity and causes a computational error. While in the torsion of short nano-bars due to the great warping of the cross-section the normal strain appears and it shouldn't be ignored. Therefore, for the first time, the effect of normal strain based on the torsion of Timoshenko-Gere theory is considered in this research. In this theory, the twist rate of non-circular sections in the axial direction is not considered constant, unlike studies in the literature. The governing equation of torsional vibration is extracted using the Hamilton principle, and the nonlocal strain gradient theory is used to show the size-dependent effects. The fundamental frequency is calculated for the arbitrary cross-section shape by using Galerkin's method. The effect of parameters such as size effects, the thickness of nano-bar, mode number, and dimensions changes of cross-section versus natural frequency of nano-bar for both the Timoshenko-Gere and typical theories are investigated. Results indicate that neglecting normal strain due to warping the cross-section causes a significant error in the short nano-bars, especially at higher mode numbers. Also, a comparison is made between the obtained natural frequencies and those of the results reported in the literature. [ABSTRACT FROM AUTHOR]

In this study, the free torsional vibration of the nanorod with noncircular cross-section based on the nonlocal strain gradient theory is investigated. The rectangular cross-section has been selected. The governing partial equation of the torsional vibration of the noncircular nanorod is derived using Hamilton's principle. Using a Galerkin method, and by consideration of the rectangular shape function in series, the natural frequency of noncircular nanorod is obtained. The obtained results indicate the convergence of the nondimensional natural frequency of the nanorod by enhancement of the number of the rectangular shape function. Furthermore, the nondimensional natural frequency of the noncircular nanorod for different nondimensional nonlocal parameter and nondimensional material length scale parameter is studied. Eventually, the effects of both nonlocal parameter and material length scale parameter on the nondimensional natural frequency, which causes torsional stiffness softening and torsional stiffness hardening of the nanorod, is also illustrated. [ABSTRACT FROM AUTHOR]

In this paper the forced axial vibration of a nanobeam by deploying the nonlocal strain gradient theory exposed to a distributed moving force, is investigated. The assumed nanobeam in this paper is under the axial constant distributed load. The governing equations of the vibration of the nanobeam are obtained via the classic beam theory and the Hamilton principle. The determined partial differential equations are converted to differential equations by applying the assumed modes method. The dynamic axial displacement of the nanobeam along its length, is obtained by solving the differential equations via the convolution integral. The effect of length scale parameter, nonlocal parameter, velocity parameter, the constant distributed load and the excitation frequency on the maximum nondimensional dynamic axial displacement of the nanobeam are analyzed. Accordingly, the effect of these two parameters on the maximum nondimensional axial displacement of the nanobeam under the harmonic moving load is of significance importance. [ABSTRACT FROM AUTHOR]

Variational mode decomposition is a powerful signal processing technique that can adaptively decompose a multi-component signal into a number of modes, via solving an optimization problem. The optimal performance of this method in signal decomposition and avoiding of the mode mixing problem strictly relies on the true selection of decomposition parameters, that is, the number of extracted modes (K) and the mode frequency bandwidth control parameter (α). In the literature, the optimal values of these parameters are achieved by evaluating fault-related indices like kurtosis, but such an index is inefficient in judging the decomposition of healthy (without fault-related components), low-defective, and high-noise signals. In this research, a novel method called fine-tuned variational mode decomposition is proposed to determine the optimal values of decomposition parameters K and α, by judging the adaptive indices. In this proposed method, the optimal values of these parameters are obtained by minimizing the mean bandwidth of the extracted modes. In order to achieve these optimal values, the mean correlation coefficients between the adjacent modes and the energy loss coefficient between the original signal and the reconstructed signal, should not exceed of defined thresholds for optimal values. The proposed method is applied to the simulation signal and experimental ones collected from the automobile gearbox system. Comparing this method with those in the literature exhibits its higher effectiveness in the true decomposition of signals with different natures. It is also shown that using the proposed method for signal decomposition is able to correctly classify the healthy and defective states of the gearbox system alongside the principal component analysis method and support vector machine classifier. [ABSTRACT FROM AUTHOR]

Lower limb joint's torsional stiffness is directly related to the individual's performance and probability of injury when landing. There are various methods of calculating ankle, knee, and hip joint's torsional stiffness in which the reliability of the achieved values by them are highly controversial. The purpose of this research is to provide a new method of calculating lower limb joint's active torsional stiffness based on the body's four-degrees-of-freedom biomechanical model. For this purpose, a group of subjects performs single-leg landing protocol from the box. In this method, the biomechanical model's equations of motion are derived in the sagittal plane and are combined with a combinatorial optimization algorithm, which consists of genetic and simulated annealing. By the use of acquired data from the force plate and motion analysis system, combinatorial genetic algorithm–simulated annealing algorithm tries to minimize the differences between the model's ground reaction force (GRFModel) and the GRFExperimental for each subject and thereby the joint's torsional stiffness values are obtained. Results show that calculating lower limb joint's torsional stiffness using the proposed method has good ability in simulating the GRFExperimental in the model. Also, the obtained values by the proposed method have moderate to good reliability and desirable variability in the measurements. Comparing the obtained stiffness values with the values of three conventional computation method in the literature shows that those common methods' results have high computational errors, low reliability, and high variability in the measurement. Also, their ability to produce GRFModel similar to the GRFExperimental is weaker than the proposed method in single-leg landing protocol. [ABSTRACT FROM AUTHOR]

The vibration of the gold microbeam resonator considering the effects of the material length scale under the temperature effect is investigated in this article. The modified couple stress theory is utilized to show the material length scale effects. The effects of temperature considering the thermoelastic damping are taken into account based on Green-Naghdi thermoelasticity theory. The Green-Naghdi coupled thermoelasticity and modified couple stress governing equations for Euler-Bernoulli beam are derived based on Hamilton's principle. The Laplace method is utilized to solve the obtained equations. The inverse Laplace method as Talbot method is used to obtain the lateral deflection and temperature response of the microbeam in the time domain. The effects of the various parameters such as the nondimensional material length scale parameter, the thickness of the microbeam, and the initial temperature conditions, on the lateral deflection as well as temperature responses of the microbeam are studied to investigate the results. Raising the material length scale parameter and width to length ratio makes the lateral deflection of the beam decrease in the time domain. Increase in temperature shock and Poisson's ratio makes the lateral deflection increase, and both have a direct effect on the lateral deflection in the time domain, except that this increase is linear for temperature shock. The temperature of the microbeam decreases by an increase in Poisson's ratio and progressing in the axial direction. For the final observation, it should be noted that the couple stress has an inverse effect on the lateral deflection. [ABSTRACT FROM AUTHOR]

In this study, a new method to improve ride comfort, vehicle handling, and workspace was presented in multi-objective optimization using nonlinear asymmetrical dampers. The main aim of this research was to provide suitable passive suspension based on more efficiency and the low cost of the mentioned dampers. Using the model with five degrees of freedom, suspension system parameters were optimized under sinusoidal road excitation. The main functions of the suspension system were chosen as objective functions. In order to better illustrate the impact of each objective functions on the suspension parameters, at first two-objective and finally five-objective were considered in the optimization problem. The obtained results indicated that the optimized viscous coefficients for five-objective optimization lead to 3.58% increase in ride comfort, 0.74% in vehicle handling ability, and 2.20% in workspace changes for the average of forward and rear suspension. [ABSTRACT FROM AUTHOR]

Recently, providing a model in order to investigate human body vibrations and also finding a methodology to simulate the functionality of the central nervous system in muscle tuning while pre and post fatigue conditions during running has been discussed in numerous papers. In the current study, a 4 degree of freedom vibration model of human body and an objective function that mimics the functionality of the central nervous system with bounds for pre-fatigue and post fatigue conditions were considered. Firstly, it was shown that the optimization method used in the literature leads to inaccurate results. Then, in order to achieve more accurate results, the optimization problem was solved using Particle Swarm Optimization method. A comparison between the results of the current study with those in literature showed that our results are more consistent with the experiments. Our findings indicated that an increase in running time followed by an increase in fatigue leads to a significant decrease in the safe region and increase in vibration amplitude of lower body wobbling mass. Moreover, a parametric study was conducted to investigate the effects of mass distribution and variations in touchdown velocities on the area of the safe region for both pre and post fatigue conditions. High dependency of this area to the mass distribution and touchdown velocities of lower extremities was also indicated. The results of this study can be useful in the shoe design for running and similar activities. [ABSTRACT FROM AUTHOR]

Introduction: Body sensor network is a key technology that is used for supervising the physiological information from a long distance that enables physicians to predict and diagnose effectively the different conditions. These networks include small sensors with the ability of sensing where there are some limitations in calculating and energy. Methods: In the present research, a new compression method based on the analysis of principal components and wavelet transform is used to increase the coherence. In the present method, the first analysis of the main principles is to find the principal components of the data in order to increase the coherence for increasing the similarity between the data and compression rate. Then, according to the ability of wavelet transform, data are decomposed to different scales. In restoration process of data only special parts are restored and some parts of the data that include noise are omitted. By noise omission, the quality of the sent data increases and good compression could be obtained. Results: Pilates practices were executed among twelve patients with various dysfunctions. The results showed 0.7210, 0.8898, 0.6548, 0.6765, 0.6009, 0.7435, 0.7651, 0.7623, 0.7736, 0.8596, 0.8856 and 0.7102 compression ratios in proposed method and 0.8256, 0.9315, 0.9340, 0.9509, 0.8998, 0.9556, 0.9732, 0.9580, 0.8046, 0.9448, 0.9573 and 0.9440 compression ratios in previous method (Tseng algorithm). Conclusion: Comparing compression rates and prediction errors with the available results show the exactness of the proposed method. [ABSTRACT FROM AUTHOR]