One of the most important phenomenon that occurs in sheet metal forming processes is the spring-back, which causes several geometrical alterations in the parts. The accurate prediction of springback after bending unloading is the key to the tool design, operation control, and precision estimate concerning the part geometry. This study investigated experimentally the effect of pretension in three rolling direction (0, 90, 45 degree) on the springback behavior of the yellow brass, sheet under V shape bending die. The pre-tension ranges from five different levels starting of 11% to 55% from the total strain in each rolling direction by regular increase of 11 %, then bent on a V-die 90 degree for the springback estimate. From experiment the

Heat treatment by solid solution method in the ?+? phase region was used at 970°C for Ti-5Al-2.5Fe alloy. The specimens cooled under different cooling media [water quenched (WQ), air cooled (AC) and furnace cooled (FC)], and subsequently aged at 550°C for 4 hours. Five specimens from each treatment were immersed in simulated body fluid SBF for a period of time (3 months). The dependence of corrosion rate on compositional variation in the phases resulted from various type of cooling rates are discussed based on immersion tests. The EDXA results show the precipitation of phosphate and calcium compounds on the alloy after 3 months of immersion in blood plasma solution forming a bone-like apatite, which enhanced the alloy biocompatibility ma

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m

In the modern world, wind turbine (WT) has become the largest source of renewable energy. The horizontal-axis wind turbine (HAWT) has higher efficiency than the vertical-axis wind turbine (VAWT). The blade pitch angle (BPA) of WT is controlled to increase output power generation over the rated wind speed. This paper proposes an accurate controller for BPA in a 500-kw HAWT. Three types of controllers have been applied and compared to find the best controller: PID controller (PIDC), fuzzy logic type-2 controller (T2FLC), and hybrid type-2 fuzzy-PID controller (T2FPIDC). This paper has been used Mamdani and Sugeno fuzzy inference systems (FIS) to find the best inference system for WT controllers. Furthermore, genetic algorithm (GA) and particl

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Hybrid bilayer heterojunction Zinc Phthalocyanine (ZnPc) thin-film P-type is considered as a donor active layer as well as the Zinc Oxide (ZnO) thin film n-type is considered as an acceptor with (Electron Transport Layer). In this study, using the technique of Q-switching Nd-YAG Pulsed Laser Deposition (PLD) under vacuum condition 10-3 torr on two ITO (Indium Tin Oxide) and (AL) electrodes and aluminum, is used to construct the hydride bilayer photovoltaic solar cell heterojunction (PVSC). The electrical properties of hybrid heterojunction Al/ZnPc/ZnO/ITO thin film are studied. The results show that the voltage of open circuit (V_oc=0.567V), a short circuit (I_sc=36 ?A), and the fill factor (FF) of 0.443. In addition, the conversion

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall