Stochastic convergence analysis of recursive successive over-relaxation algorithm in adaptive filtering

A stochastic convergence analysis of the parameter vector estimation obtained by the recursive successive over-relaxation (RSOR) algorithm is performed in mean sense and mean-square sense. Also, excess of mean-square error and misadjustment analysis of the RSOR algorithm is presented. These results are verified by ensemble-averaged computer simulations. Furthermore, the performance of the RSOR algorithm is examined using a system identification example and compared with other widely used adaptive algorithms. Computer simulations show that the RSOR algorithm has better convergence rate than the widely used gradient-based algorithms and gives comparable results obtained by the recursive least-squares RLS algorithm.     

Performance of a Tied-Arch Reinforced Concrete Railway Bridge: Rating, Safety Assessment, and Bond Length Evaluation

This study presents investigations regarding visual inspection, dynamic testing, and finite-element modeling of an approximately 80-year old reinforced concrete tied-arch railway bridge that is still in service in Turkey. Investigations were conducted as part of a systematic periodic inspection along Ankara-Zonguldak railway line. The bridge is subject to heavy freight trains with increasing axle loads. Field tests such as material tests and dynamic tests were used to calibrate the finite-element model of the bridge. Detailed information regarding testing and model updating procedure is given. Based on test results, computer model was refined. The calibrated model of the bridge structure was then used for structural assessment and evaluation. Despite sufficient overall safety, local details were found to be problematic. Due to insufficient bond length in hanger-to-arch connection, a strengthening scheme using steel channel sections was proposed.     

Extraction of caffeine from tea stalk and fiber wastes using supercritical carbon dioxide

The purpose of this study was to investigate obtaining of caffeine from tea plant wastes by supercritical carbon dioxide extraction. Experiments were carried out with tea stalk and fiber wastes of Turkish tea plants that has no economical value. Stalk and fiber wastes were supplied from tea factories. These wastes were ground, sieved and dried at 105 °C temperature in an oven. Parameters affecting caffeine leaching from tea wastes were determined to be, extraction time, extraction temperature, carbon dioxide flow rate, process pressure and particle size. The maximum yield of caffeine from tea stalk wastes and fiber wastes were 14.9 mg/g tea stalk and 19.2 mg/g tea fiber, respectively. The yield increase had been recorded as 61.9% and 65.5%, respectively, in comparison with the chloroform extraction of tea stalk and fiber wastes.     

Water-soluble poly(4-styrenesulfonic acid-co-maleic acid) stabilized ruthenium(0) and palladium(0) nanoclusters as highly active catalysts in hydrogen generation from the hydrolysis of ammonia–borane

Water-soluble poly(4-styrenesulfonic acid-co-maleic acid), PSSA-co-MA, stabilized ruthenium(0) and palladium(0) nanoclusters were for the first time prepared in situ from the reduction of ruthenium(III) chloride and potassium tetrachloropalladate(II), respectively, by ammonia–borane during its hydrolysis at room temperature. PSSA-co-MA stabilized ruthenium(0) and palladium(0) nanoclusters having average particle size of 1.9 ± 0.5 and 3.5 ± 1.6 nm, respectively, were isolated from the reaction solution and characterized by TEM and UV–visible electronic absorption spectroscopy. PSSA-co-MA stabilized ruthenium(0) and palladium(0) nanoclusters are highly active catalysts for hydrogen generation from the hydrolysis of ammonia–borane at low temperature. PSSA-co-MA stabilized ruthenium(0) and palladium(0) nanoclusters provide 51,720 and 8720 turnovers, respectively, in the hydrogen generation from the hydrolysis of ammonia–borane at 25 °C before deactivation. Catalytic hydrolysis of ammonia–borane is first order with respect to the catalyst concentration, but zero order with respect to the substrate concentration in the case of both ruthenium(0) and palladium(0) nanoclusters. Activation energies for the hydrolysis of ammonia–borane in the presence of PSSA-co-MA stabilized ruthenium(0) or palladium(0) nanoclusters (54 ± 2 kJ mol⁻¹ and 44 ± 2 kJ mol⁻¹, respectively) are smaller than most of the values reported for the same reaction in the presence of other catalyst systems.     

Efficiency of an Otto engine under alternative power optimizations

The proper optimization criterion to be chosen for the optimum design of the heat engines may differ depending on their purposes and working conditions. In this study, a comparative performance analysis is carried out for a reversible Otto cycle based on three alternative performance criteria namely maximum power (mp), maximum power density (mpd) and maximum efficient power (mep). The power density criterion is defined as the power per minimum specific volume in the cycle and the efficient power criterion is defined as multiplication of the power by the efficiency of the Otto cycle. Maximizing the efficient power gives a compromise between power and efficiency. Three different objective functions are defined and maximization of these functions is carried out under different design parameters of the Otto engine. The variations of power, power density and efficient power outputs are derived and presented with respect to the thermal efficiency of the cycle for various temperature ratios. It has been found that the design parameters at mep conditions lead to more efficient engines than that at the mp condition and the mep criterion may have a significant power advantage compared with mpd criterion. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

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.     

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.