Sharif Digital Repository

An efficient hybrid modal-molecular dynamics method is developed for the vibration analysis of large scale nanostructures. Using the reduced order method, presented in this paper, linear and nonlinear vibrations of a suspended graphene nanoribbon (GNR) carrying an electric current in a harmonic magnetic field are investigated. The resonance frequencies as well as the nonlinear vibration response obtained by the present technique and direct molecular dynamic simulations are in very good agreement. Also, the obtained results illustrate the hardening behavior of nonlinear vibrations which is diminished by stretching the GNR  

The search for higher ship speeds and better propulsive performance has resulted in many performance enhancement techniques. One technique is to introduce an air film along the bottom of the hull to reduce skin friction drag. The air film system opens many possibilities for using designs with larger payloads such as barges and tankers, as well as catamarans with larger deck space which otherwise are not attractive because of their higher propulsion power. Although reducing hull drag by air injection was proposed in the beginning of this century, it still remains to be fully exploited. In this thesis, two models are used to do the experiments. The first one was a simple catamaran model and... 

The resonance frequencies of cantilever carbon nanocones (CNCs) up to 4 nm in height are determined using molecular dynamics simulation based on adaptive intermolecular reactive empirical bond order potential. The frequency content of the free vibrations of CNCs under a lateral initial excitation at the tip is analyzed using fast Fourier transformation, and the resonance frequencies are obtained. The results are reported for various samples to investigate the dependency of the resonance frequency to the geometrical parameters and temperature of CNCs  

Air cavity ship concept has received some interest due to its potential on viscous resistance reduction for high speed craft. Air-cavity ships (ACS) are advanced marine vehicles that use air injection at the wetted hull surfaces to improve a vessel's hydrodynamic characteristics. Air is supplied through nozzles under a profiled bottom to generate an air cavity beneath such a ship, so that a steady air layer separates a part of the bottom from contact with water, consequently reducing hydrodynamic resistance. Resistance tests were conducted with two forms: first of which was planning catamaran hull form, and second one was an alternative form with an air cavity injection under its bottom... 

In this study, a new antibacklash gear mechanism design comprising three pinions and a rack is introduced. This mechanism offers several advantages compared to conventional antibacklash mechanisms, such as lower transmission error as well as lower required preload. Nonlinear dynamic modeling of this mechanism is developed to acquire insight into its dynamic behavior. It is observed that the amount of preload required to diminish the backlash depends on the applied input torque and nature of periodic mesh stiffness. Then, an attempt is made to obtain an approximate relation to find the minimum requiring preload to preserve the system's antibacklash property and reduce friction and wear on the... 

In this investigation, the multi-objective selection and optimization of a gantry machine tool is achieved by analytic hierarchy process, multi-objective genetic algorithm, and Pareto-Edgeworth-Grierson-multi-criteria decision-making method. The objectives include maximum static deformation, the first four natural frequencies, mass, and fabrication cost of the gantry. Further structural optimization of the best configuration was accomplished using multi-objective genetic algorithm to improve all objectives except cost. The result of sensitivity analysis reveals the major contribution of columns of gantry with respect to the crossbeam's contribution. After determining the most effective... 

Deep Neural networks (DNNs) are getting deeper and larger which intensify the data movement and compute demands. Prior work focuses on reducing data movements and computation through exploiting sparsity and similarity. However, none of them exploit input similarity and only focus on sparsity and weight similarity. Synergistically analysing the similarity and sparsity of inputs and weights, we show that memory accesses and computations can be reduced by 5.7× and 4.1×, more than what can be decreased by exploiting only sparsity, and 3.9× and 2.1×, more than what can be decreased by exploiting only weight similarity. We propose a new data-aware compression approach, called DANA, to effectively...