Search

Vehicle traffic flow channelizing can significantly contribute to fewer collisions and smooth traffic flow in isolated signalized intersection design. Therefore, this study investigates the effect of changes in the number of right-turn lanes with splitter islands and left-turn storage bays for different volume approaches on intersection performance. This study aims to provide an accurate analysis to estimate the effect of such changes on signalized intersections, which can improve intersection performance. Furthermore, the delay parameter derived from HCM2016 and simulation was evaluated for different scenarios. For this purpose, simulation was performed using Synchro software. In this study, a symmetrical, 90-degree, undersaturated (volume per capacity lower than 1, V/C, Author(s): Omid Rahmani (corresponding author) [1]; Amir Saman Abdollahzadeh Nasiri [2]; Iman Aghayan [1] 1. Introduction The intersection capacity plays an important role in determining the traffic capacity of an [...]

In this study, dynamic response of functionally graded (FG) nanobeam under a moving load in a thermal environment has been investigated. By considering the size effect, nonlocal Euler–Bernoulli beam theory has been used to model a FG nanobeam. By applying Hamilton's principle, governing equations of motion and boundary conditions, have been derived. Analytical solution by using Laplace transform method has been achieved. Presented results have been verified by comparing with the results found in the literature, which this comparison shows good agreement between them. Influences of the nonlocal parameter, material distribution index, velocity of the moving load, and temperature changes on the response of the FG nanobeam have been investigated. The results show that increasing the nonlocal parameter and temperature changes leads to raising the dynamic deflection of the FG nanobeam. [ABSTRACT FROM AUTHOR]

This paper studied the free vibration behavior of coiled carbon nanotubes (CCNTs) using continuum mechanics methods and molecular dynamics (MD) simulations. Based on the continuum mechanics method, a new elasticity model called the nonlocal generalized Washizu beam (NGWB) was innovated by considering the effects of the curvature and cross-section thickness of nanotubes, as well as size-dependent effect. Then, the governing equations for the vibrational behavior of CCNTs were derived and solved using the numerical generalized differential quadrature method (GDQM). The free vibration behavior of CCNTs was also examined by performing the MD simulations to determine the calibrated values of the nonlocal parameter ( μ) that are applied in the NGWB elasticity model and to validate and evaluate the obtained results. Since the NGWB elasticity model considers the size-dependent effect on the vibrational behavior, obtained results from it well agrees with the MD simulation results in the present study. For CCNTs, there was a coupling between transverse, longitudinal, and torsional vibrations, which led to the beating phenomenon. The natural frequencies decreases by increasing the number of pitches ( n p) , aspect ratio (p / D) , and pitch angle (α ¯). The nonlocal parameter has a more significant effect on the frequencies of CCNTs with smaller geometrical parameters. In addition, the type of boundary conditions affects the calibrated values of the nonlocal parameter, frequency values, and arrangement of vibrating mode shapes of CCNTs. Results of the present study can be applied in the design and analysis of nano-electro-mechanical systems (NEMS), sensors, and nano-composite structures containing CCNTs. Also, the NGWB elasticity model might be useful in the statics and wave propagation studies of CCNTs, and other coiled and curved nano-structures. [ABSTRACT FROM AUTHOR]

In this study, a framework for statistical design of a brushless DC (BLDC) motor is proposed in order to maximise yield while keeping efficiency as high as possible and the non‐linear constraints, that is, limitations of flux density, current density and physical dimensions, satisfied. The proposed yield maximisation method has two major steps: polyhedral approximation of the constraint region and yield maximisation. By implementing the proposed method, the optimum design parameters, that is, embrace, thickness and length of magnet, are obtained with maximum immunity to variations in magnet dimensions. Also, highly accurate artificial neural network‐based models are used to estimate the objective function and constraints. It is also shown that by adjusting performance constraints (efficiency and flux density), different design goals can be achieved which help to choose the appropriate design according to the designer's goals. [ABSTRACT FROM AUTHOR]

Here, the authors present a new constrained multi‐objective optimization method for maximizing output power and efficiency of switched reluctance motor (SRM). The constraints play a significant role in this process. Artificial neural network‐based models are created to represent the SRM behaviour which is a difficult task. For this reason, a single neural network for each objective is built and the number of training data has been increased to reach a good accuracy. The authors propose a neural network‐based adjoint Lp metric technique to combine several objective functions and constraints with different weight factors to a single function which should be minimized. To apply the constraints, an adjoint term is added to the original Lp function including only objective functions. The flux densities of the magnetic materials are selected as the optimization constraints. When approaching as close as possible to the saturation level, the SRM has a better performance. Adding an adjoint term to the original Lp leads to better optimization results which were proved by comparing with a conventional optimization. Also, all obtained results were finally validated by the Ansoft Maxwell software. [ABSTRACT FROM AUTHOR]