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1
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A Study on Optimization of Planetary Gear Trains

100%
Hüseyin Filiz İ., Olguner S., Evyapan E.
Acta Physica Polonica A
|
2017
|
vol. 132
|
issue 3
728-733
EN
This study presents optimization of planetary gear train in a specific configuration. General characteristics of planetary gear trains are discussed briefly. A compound configuration for planetary gear train is selected and an optimization study is performed for this configuration. For the given input power, motor speed and overall gear ratio, modules, facewidths, teeth numbers of gears are found, satisfying the condition of minimum kinetic energy of the gear trains. In optimization, the objective is set to minimization of kinetic energy. Allowable bending stress and allowable contact stress are considered as design constraints. Minimum teeth number for a given pressure angle, center distance, recommendation on the facewidth, limitations on teeth ratios are considered as geometrical and kinematical constraints. The Matlab® Optimtool optimization toolbox is used. Results for certain operating conditions are obtained and tabulated.
2
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Solving Generalized Semi-Infinite Programming Problems with a Trust Region Method

100%
Tezel Özturan A.
Acta Physica Polonica A
|
2015
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vol. 128
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issue 2B
B-93-B-96
EN
In this paper, a trust region method for generalized semi-infinite programming problems is presented. The method is based on [O. Yi-gui, "A filter trust region method for solving semi-infinite programming problems", J. Appl. Math. Comput. 29, 311 (2009)]. We transformed the method from standard to generalized semi-infinite programming problems. The semismooth reformulation of the Karush-Kuhn-Tucker conditions using nonlinear complementarity functions is used. Under some standard regularity condition from semi-infinite programming, the method is convergent globally and superlinearly. Numerical examples from generalized semi-infinite programming illustrate the performance of the proposed method.
3
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Research and Parameter Optimization of the Pattern Recognition Algorithm for the Eye Tracking Infrared Sensor

63%
Murawski K., Różanowski K., Krej M.
Acta Physica Polonica A
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2013
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vol. 124
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issue 3
513-516
EN
The paper presents the process and results of tests of the pattern recognition algorithm. The algorithm has been developed for the sensor to track the activity of the eyes. The study was conducted on a group of ten people. The group was selected, so that it was possible to determine the influence of gender, age, eye color, contact lenses and glasses on the result of the algorithm. The object of the study was also to optimize the pattern recognition algorithm in terms of CPU utilization. For this purpose the duration of the algorithm steps were measured as a function of the allocation of tasks to multiple processor cores.
4
Content available remote

SVD Augmented Gradient Optimization

63%
Pazdanowski M.
Acta Physica Polonica A
|
2015
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vol. 128
|
issue 2B
B-213-B-214
EN
Solution time of nonlinear constrained optimization problem depends on the number of constraints, decision variables and conditioning of decision variables space. While the numbers of constraints and decision variables are external to the optimization procedure itself, one may try to affect the conditioning of the decision variables space within the self contained optimization module. This will directly affect the ratio of convergence of an iterative, gradient based optimization routine. Another opportunity for speedup of the solution process in case of quadratic objective function lies in the chance to eliminate the decision variables least affecting the objective function, and thus decrease the optimization problem size. Elimination of decision variables is based on the singular value decomposition of the objective function. Singular values showing up as a result of such procedure indicate that certain linear combinations of original decision variables do not affect the objective function, and thus may be eliminated from further deliberations. Also if near singular values are encountered as well, even deeper reduction of the optimization problem size is still possible, but at a cost in terms of final solution quality. An idea how to improve the conditioning of decision variables space, and limit the number of decision variables in case of quadratic objective function using singular value decomposition is presented in this paper. Results of computer tests performed during minimization of quadratic objective function and subject to quadratic constraints are enclosed and discussed.
5
Content available remote

The Idea of the Selection of PZT-Beam Interaction Forces in Active Vibration Protection Problem

51%
Brański A., Borkowski M., Szela S.
Acta Physica Polonica A
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2010
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vol. 118
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issue 1
17-22
EN
The paper concerns an active vibration protection (p-reduction) of the structure. This problem corresponds to the active vibration reduction (a-reduction). The quantity and effectivness of the a-/p- reduction, measured with reduction and effectiveness coefficient respectively, depends on, inter alia, the PZT distribution on the structure subdomains with the largest curvatures (quasi optimal distribution) are considered. The aim of this paper is to determine such interacting forces PZT-structure, assuming QO distribution of PZTs, which maximize the effectiveness of p-reduction. The beam clamped at one end, vibrating separately with first three modes, is chosen as the research object. The interacting forces are searched requiring that the shear force and bending moment at the clamped side are equal to zero. The total p-reduction is achieved for separate modes. Assuming the QO distribution of the PZTs, the best p-effectiveness is achieved. The validation of theoretical considerations is confirmed numerically.
6
Content available remote

Solution of a Class of Optimization Problems Based on Hyperbolic Penalty Dynamic Framework

51%
Evirgen F.
Acta Physica Polonica A
|
2017
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vol. 132
|
issue 3
1062-1065
EN
In this study, a gradient-based dynamic system is constructed in order to solve a certain class of optimization problems. For this purpose, the hyperbolic penalty function is used. Firstly, the constrained optimization problem is replaced with an equivalent unconstrained optimization problem via the hyperbolic penalty function. Thereafter, the nonlinear dynamic model is defined by using the derivative of the unconstrained optimization problem with respect to decision variables. To solve the resulting differential system, a steepest descent search technique is used. Finally, some numerical examples are presented for illustrating the performance of the nonlinear hyperbolic penalty dynamic system.
7
Content available remote

Conformable Fractional Gradient Based Dynamic System for Constrained Optimization Problem

51%
Evirgen F.
Acta Physica Polonica A
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2017
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vol. 132
|
issue 3
1066-1069
EN
A conformable fractional gradient based dynamic system with a steepest descent direction is proposed in this paper for a class of nonlinear programming problems. The solutions of the dynamic system, modelled with the conformable fractional derivative are investigated to obtain the minimizing point of the optimization problem. For this purpose, we use a step variational iteration method, adapted to use a conformable integral definition. Numerical simulations and comparisons show that the conformable fractional gradient based dynamic system is both feasible and efficient for a certain class of equality constrained optimization problems. Furthermore, the step variational iteration method, combined with the conformable integral definition, is a reliable tool for solving a system of fractional differential equations.
8
Content available remote

Design and Thinning of Linear and Planar Antenna Arrays Using a Binary Teaching Learning Optimizer

51%
Recioui A.
Acta Physica Polonica A
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2016
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vol. 130
|
issue 1
7-8
EN
In this paper, a binary variant of the teaching learning optimization technique is used to the design and thinning of linear and planar arrays. The purpose of the optimization task is to enhance the ratio directivity/sidelobe level which turns out to be having two conflicting parameters. The binary variant of the teaching learning optimization technique searches the way of exciting some selected elements. The array thinning problem requires some elements to be excited with the others having no current in them. This is a binary (ON-OFF) problem that requires an optimization technique that can handle the binary variables. The teaching learning optimization has been proposed initially to handle real valued variables. The results show good agreement between the desired and calculated radiation patterns with reduction in resource usage in terms of power consumption.
9
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Content available

Application of Genetic Algorithm for Extraction of the Parameters from Powder EPR Spectra

45%
Spałek T., Pietrzyk P., Sojka Z.
Acta Physica Polonica A
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2005
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vol. 108
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issue 1
95-102
EN
The application of the stochastic genetic algorithm in tandem with the deterministic Powell method to automated extraction of the magnetic parameters from powder EPR spectra was described. The efficiency and robustness of such hybrid approach were investigated as a function of the uncertainty range of the parameters, using simulated data sets. The discussed results demonstrate superior performance of the hybrid genetic algorithm in fitting of complex spectra in comparison to the common Monte Carlo method joint with the Powell refinement.
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