Investigation of microstructure and wear behaviors of al matrix composites reinforced by carbon nanotube

In this study, the effect of CNT amount in Al-CNT composites produced by adding carbon nanotube (CNT) to 7075 Al alloy in various amounts on microstructure and wear behaviors of aluminum matrix composites was investigated. CNT was added to 7075 Al alloy powder at five different amounts. The powders were mechanically milled for 2 hours. Mechanical milled powders were cold pressed and then pre-shaped by hot pressing. Pre-shaped samples were sintered for 1 hour under 10^?6 millibar in 580°C. Microstructure examinations, hardness measurements, and wear tests were carried out. The results show that CNT's in the microstructure were agglomerated as nanotube amount increases and there was no uniform distribution. The highest hardness value was obtained in AMC reinforced with 1% CNT while it is seen that hardness of the composite decreases and weight loss increases as CNT amount increases.     

Dexterous workspace optimization of an asymmetric six-degree of freedom Stewart–Gough platform type manipulator

In this paper, an asymmetric Generalized Stewart–Gough Platform (GSP) type parallel manipulator is designed by considering the type synthesis approach. The asymmetric six-Degree Of Freedom (DOF) manipulator optimized in this paper is selected among the GSPs classified under the name of 6D. The dexterous workspace optimization of Asymmetric parallel Manipulator with tEn Different Linear Actuator Lengths (AMEDLAL) subject to kinematics and geometric constraints is performed by using the Particle Swarm Optimization (PSO). The condition number and Minimum Singular Value (MSV) of homogenized Jacobian matrix are employed to obtain the dexterous workspace of AMEDLAL. Finally, the six-DOF AMEDLAL is also compared with the optimized Traditional Stewart–Gough Platform Manipulator (TSPM) considering the volume of the dexterous workspace in order to demonstrate its kinematic performance. Comparisons show that the manipulator proposed in this study illustrates better kinematic performance than TSPM.     

Computation of approximate optimal policies in a partially observed inventory model with rain checks

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite-dimensional states that are conditional distributions of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It then uses an appropriate functional basis to represent the state. Considering the speed and stability of computations, we choose truncated Chebyshev polynomials as the basis. We use Fast Fourier Transforms along with an appropriate discretization of inventory levels to speed up the computations. These main ideas are blended to obtain an iterative algorithm to solve a partially observed inventory model with rain checks. In this model, the inventory manager (IM) does not know the inventory level when it is positive. Otherwise, the IM fully observes it. This model provides a context to illustrate our methodology, which applies to other such models. Although this model has been studied mathematically in the literature, the use of our algorithm provides a numerical approximation of the optimal order quantities. These are compared to the orders released under a base mean-stock policy, where the IM replaces the unobserved inventory level with its mean and applies the well-known base stock policy. We show numerically that the optimal order quantity is very close to the base mean-stock order quantity, when the variance of the inventory distribution is small. When the mean of the inventory distribution is large, the optimal order quantity is more than the base mean-stock quantity, and it is the other way around when the mean is small or negative. These insights are explained via uncertainty and information effects and their interplay. We expect this interplay to show up in other partially observed inventory models.     

Synthesis and characterization of poly(N-(2-(thiophen-3-yl)methylcarbonyloxyethyl)maleimide) and its spectroelectrochemical properties

A new monomer; N-(2-(thiophen-3-yl)methylcarbonyloxyethyl) maleimide (NMT) was synthesized. The chemical structure of the monomer was characterized by Nuclear Magnetic Resonance (¹H-NMR) and Fourier Transform Infrared (FTIR) Spectroscopy. Electrochemical polymerization of NMT was performed in acetonitrile (AN)/borontrifloride ethylether (BFEE) solvent mixture (1:1, v/v) where tetrabutylammonium tetrafluoroborate (TBAFB) was utilized as the supporting electrolyte. The resulting conducting polymer was characterized by Fourier Transform Infrared (FTIR) Spectroscopy, thermal analyses and Scanning Electron Microscopy (SEM). Electrical conductivity was measured by the four-probe technique. The spectroelectrochemical behavior and switching ability of P(NMT) film were investigated by UV–Vis spectrophotometry. P(NMT) revealed color changes between yellow and blue in the reduced and oxidized states respectively.     

Optimization of Multireservoir Systems by Genetic Algorithm

Application of optimization techniques for determining the optimal operating policy of reservoirs is a major issue in water resources planning and management. As an optimization Genetic Algorithm, ruled by evolution techniques, have become popular in diversified fields of science. The main aim of this study is to explore the efficiency and effectiveness of genetic algorithm in optimization of multi-reservoirs. A computer code has been constructed for this purpose and verified by means of a reference problem with a known global optimum. Three reservoirs in the Colorado River Storage Project were optimized for maximization of energy production. Besides, a real-time approach utilizing a blend of online and a posteriori data was proposed. The results obtained were compared to the real operational data and genetic algorithm was found to be effective and can be utilized as an alternative technique to other traditional optimization techniques.     

Effect of injection timing on the exhaust emissions of a diesel engine using diesel–methanol blends

Environmental concerns and limited resource of petroleum fuels have caused interests in the development of alternative fuels for internal combustion (IC) engines. For diesel engines, alcohols are receiving increasing attention because they are oxygenated and renewable fuels. Therefore, in this study, the effect of injection timing on the exhaust emissions of a single cylinder, naturally aspirated, four-stroke, direct injection diesel engine has been experimentally investigated by using methanol-blended diesel fuel from 0% to 15% with an increment of 5%. The tests were conducted for three different injection timings (15°, 20° and 25 °CA BTDC) at four different engine loads (5 Nm, 10 Nm, 15 Nm, 20 Nm) at 2200 rpm. The experimental test results showed that Bsfc, NO_x and CO₂ emissions increased as BTE, smoke opacity, CO and UHC emissions decreased with increasing amount of methanol in the fuel mixture. When compared the results to those of original injection timing, NO_x and CO₂ emissions decreased, smoke opacity, UHC and CO emissions increased for the retarded injection timing (15 °CA BTDC). On the other hand, with the advanced injection timing (25 °CA BTDC), decreasing smoke opacity, UHC and CO emissions diminished, and NO_x and CO₂ emissions boosted at all test conditions. In terms of Bsfc and BTE, retarded and advanced injection timings gave negative results for all fuel blends in all engine loads.     

Process control at the sealing line during sheet metal hydroforming

Sheet metal hydroforming is a deep drawing process that uses a pressure medium for load transmission. The process is mainly influenced by the control of the blank holder force and the fluid pressure. This report describes investigations of a newly developed process-control system. Process variables can be controlled by the sealing state of the tool. The detection is performed by a CCD-camera system that allows the continuous recording of occurring leakages. Different control strategies can be used to control the multiple process parameters. This paper describes the performance and the limits of the aforementioned technology.     

Parasitic compensation in CCI-based circuits for reduced power consumption

In this paper, the compensation advantage of the first-generation current conveyor (CCI) over the second-generation current conveyor (CCII) in tunable circuits is shown. For this purpose, a new floating frequency dependent negative resistor (FDNR) simulator using three CCIs is presented and employed in a third-order high-pass filter. The compensation feature of the CCI is shown for the proposed high-pass filter. As a second example, the presented compensation method is tested in a second-order band-pass filter constructed with two CCIs. Applying the proposed compensation technique, the CCI-based circuits can operate in lower biasing currents, which result in lower power consumption.