The vibration of nanobeam resting on elastic foundation using modified couple stress theory

In this paper, the vibration of nanobeams resting on the Winkler foundation is proposed using the modified couple stress theory. Hamilton’s principle is utilized to construct the governing equations. The size effect of the nanobeam cannot be captured by using classical Euler-Bernoulli beam theory, but the modified couple stress theory model can capture it because it includes material length scale parameter that a newly developed model has. Once the material length scale parameter is assumed to be zero, the classical Euler-Bernoulli beam theory equation is obtained. Multiple scale method is employed to obtain the result. Simply supported boundary condition is used to study natural frequencies. The influence of material length scale parameter and the Winkler elastic foundation parameter on the fundamental frequencies of the nanobeam is investigated and tabulated. Also, in the present study, Poisson’s ratio is taken as constant. Nanobeam resting on the Winkler foundation which is simply supported is analyzed to illustrate the size effects on the free vibration. Numerical results for the simply supported nanobeam indicate that the first fundamental frequency calculated by the presented model is higher than the classical one. Moreover, it is obtained that the size influence is more substantial for higher vibration modes. The results indicate that the significant importance of the size influences the analysis of nanobeams. The vibration of nanobeam exhibits a hardening spring behavior, and the newly developed models are the beams stiffer than according to the classical beam theory. Modified couple stress theory tends to be more helpful in describing the size-dependent mechanical properties of nanoelectromechanical systems (NEMS)

Nonlinear Vibration of a Nanobeam on a Pasternak Elastic Foundation Based on Non-Local Euler-Bernoulli Beam Theory

In this study, the non-local Euler-Bernoulli beam theory was employed in the nonlinear free and forced vibration analysis of a nanobeam resting on an elastic foundation of the Pasternak type. The analysis considered the effects of the small-scale of the nanobeam on the frequency. By utilizing Hamilton’s principle, the nonlinear equations of motion, including stretching of the neutral axis, are derived. Forcing and damping effects are considered in the analysis. The linear part of the problem is solved by using the first equation of the perturbation series to obtain the natural frequencies. The multiple scale method, a perturbation technique, is applied in order to obtain the approximate closed solution of the nonlinear governing equation. The effects of the various non-local parameters, Winkler and Pasternak parameters, as well as effects of the simple-simple and clamped-clamped boundary conditions on the vibrations, are determined and presented numerically and graphically. The non-local parameter alters the frequency of the nanobeam. Frequency-response curves are drawn

Genetic programming approach to predict torque and brake specific fuel consumption of a gasoline engine

This study presents genetic programming (GP) based model to predict the torque and brake specific fuel consumption a gasoline engine in terms of spark advance, throttle position and engine speed. The objective of this study is to develop an alternative robust formulations based on experimental data and to verify the use of GP for generating the formulations for gasoline engine torque and brake specific fuel consumption. Experimental studies were completed to obtain training and testing data. Of all 81 data sets, the training and testing sets consisted of randomly selected 63 and 18 sets, respectively. Considerable good performance was achieved in predicting gasoline engine torque and brake specific fuel consumption by using GP. The performance of accuracies of proposed GP models are quite satisfactory (R2 = 0.9878 for gasoline engine torque and R2 = 0.9744 for gasoline engine brake specific fuel consumption). The prediction of proposed GP models were compared to those of the neural network modeling, and strictly good agreement was observed between the two predictions. The proposed GP formulation is quite accurate, fast and practical.Gasoline engine Torque Brake specific fuel consumption Genetic programming Explicit solution Modeling engine

Prediction of torque and specific fuel consumption of a gasoline engine by using artificial neural networks

This study presents an artificial neural network (ANN) model to predict the torque and brake specific fuel consumption of a gasoline engine. An explicit ANN based formulation is developed to predict torque and brake specific fuel consumption of a gasoline engine in terms of spark advance, throttle position and engine speed. The proposed ANN model is based on experimental results. Experimental studies were completed to obtain training and testing data. Of all 81 data sets, the training and testing sets consisted of randomly selected 63 and 18 sets, respectively. An ANN model based on a back-propagation learning algorithm for the engine was developed. The performance and an accuracy of the proposed ANN model are found satisfactory. This study demonstrates that ANN is very efficient for predicting the engine torque and brake specific fuel consumption. Moreover, the proposed ANN model is presented in explicit form as a mathematical function.Gasoline engine Torque Brake specific fuel consumption Neural networks Explicit solution

Magnetic field effect on nonlinear vibration of nonlocal nanobeam embedded in nonlinear elastic foundation

The history of modern humanity is developing towards making the technological equipment used as small as possible to facilitate human life. From this perspective, it is expected that electromechanical systems should be reduced to a size suitable for the requirements of the era. Therefore, dimensionless motion analysis of beams on the devices such as electronics, optics, etc., is of great significance. In this study, the linear and nonlinear vibration of nanobeams, which are frequently used in nanostructures, are focused on. Scenarios have been created about the vibration of nanobeams on the magnetic field and elastic foundation. In addition to these, the boundary conditions (BC) of nanobeams having clamped-clamped and simple-simple support situations are investigated. Nonlinear and linear natural frequencies of nanobeams are found, and the results are presented in tables and graphs. When the results are examined, decreases the vibration amplitudes with the increase of magnetic field and the elastic foundation coefficient. Higher frequency values and correction terms were obtained in clamped-clamped support conditions due to the structure's stiffening

Formulation of effects of atropine, pralidoxime and magnesium sulfate on cardiac tissue levels of nitric oxide, malondialdehyde and glutathione in organophosphate poisoning using artificial neural network

Anticholinesterase poisoning is an important health problem in our country, and a complete understanding of its underlying mechanisms is essential for the emergency physician. So, this study focused on two purposes. First one was aimed to investigate the biochemical analysis to determine the tissue levels of malondialdehyde (MDA), glutathione and nitric oxide (NO). Secondly, it was planned to model and formulate the effects of some drugs on cardiac tissues levels of NO, MDA and glutathione in acute organophosphate poisoning in rats by the application of neural network based on experimental results. It has been planned to determine whether artificial neural network (ANN) is appropriate tool to analyze and formulate it. As a result, it has been considered that ANN can be effectively used to model NO, MDA and glutathione level. The performances of ANN formulation versus target experimental values are found to be quite high. It is concluded that, proposed NN models are also presented as simple explicit mathematical functions for further use by researchers. Crown Copyright © 2009