This paper presents the use of a modified optimization artificial immune network and differential evolution algorithm (opt-aiNet-DE) to solve the optimal power flow problem. The problem was formulated as a non-linear optimization problem where the control variables were the real power produced at each generator, the voltage magnitude at each voltage controlled bus, the transformer tap settings of voltage regulating transformers and the configurations of shunt reactive compensation devices. The optimal settings of the control variables were determined using the proposed algorithm with the inequality constraints being handled using a penalty parameterless constraint handling method. Two case studies were considered in order to show the effectiveness of the proposed technique. The first case study aimed at minimizing the cost of power generation and the second case study aimed at improving the voltage profile of the whole system. The modified opt-aiNet-DE algorithm was tested on the IEEE 30 bus system and the results compared with other heuristic methods.
In this paper, a multi objective approach is presented for automatic modular fixture planning. The presented system first generates all feasible fixture plans and then sequentially eliminates them by applying the criteria of uniqueness and stability. The unique and stable fixture plans are then checked for both translational and rotational accessibilities and the fixture plan with maximum accessibility angle is selected as the best plan. Characteristics of dowel pin based modular fixturing systems are considered in generating the fixture plans based on 3-2-1 and 3-1-1-1 principles. Complete geometric information of the workpiece CAD model is automatically extracted from a neutral IGES source file. The system is successfully tested for fixture planning of complex geometries with concave features and free form surfaces.
Machining parameters tables provided by the machine tool manufacturers often do not meet the operator requirements and sometimes even do no provide efficient guidelines to manufacturing engineers. This may lead to the act of adjustment in the customer's requirements, which may result in poor quality, and ultimately rejection of the final product by them. Hence, a suitable selection of machining parameters of CNC wire cut electro discharge machining (WEDM) process is necessary. In this, present study, optimization of Kerf Width using Taguchi's dynamic design of experiments is proposed for WEDM operations. Experimentation was planned as per Taguchi's L'32 (21 X 44) mixed orthogonal array. Each experiment has been performed under different cutting conditions of gap voltage, pulse ON time, pulse OFF time, wire feed and dielectric flushing pressure. Stainless Steel grade 304L was selected as a work material to conduct the experiments. From experimental results, the Kerf Width was determined for each machining performance criteria. Signal to noise ratio was applied to measure the performance characteristics deviating from the actual value. Finally, experimental confirmation was carried out to identify the effectiveness of this proposed method.
Friction liners being the part of braking system that actually rub against the rotating drum of trucks, need a material which has sufficient cross breaking strength against shear failure and hardness against wear. In addition to cross breaking strength and hardness, there are other requirements also that a brake liner material has to fulfill. Indian Standard 2742 prescribes a list of ingredients of a composite material for brake liners of trucks to fulfill those variety of requirements. It also prescribes the limiting values of the important properties. Due to a large number of ingredients, finding an optimum composition of them in a composite material becomes an important problem. In the present work, a non linear programming problem is formulated to optimize the composition of the composite material prescribed by Indian Standard 2742 for brake liners of trucks. The objective is to maximize the cross breaking strength, while keeping hardness within the permissible limits. Equation of the desired properties have been modeled from the experimental data. The analysis of the problem is done computationally using MATLAB. The computational results have been compared with
those obtained by Taguchi method of analysis.
The triaxiality of the stress state is known to greatly influence the amount of plastic strain which a material may undergo before ductile failure occurs. It is defined as the ratio of hydrostatic pressure, or mean stress, to the von Mises equivalent stress. This paper discusses the effects of stress triaxiality on yielding behavior of anisotropic materials. Hillvon
Mises's criteria for anisotropic material have been used with triaxiality factor (TF). Mathematical model that combines the yield stress and anisotropic ratio R (ratio of width strain to thickness strain) along with triaxiality have been formulated. This model is considered as an objective function subjected to inequality constraint. Constrained optimization is solved using genetic algorithm. The results obtained give the set of principal stresses along with corresponding critical triaxiality which is the maximum value at which the material can sustain without failure. If triaxiality extends further more the material will go to plastic deformation and may prone to failure. In this way the critical triaxiality of materials can be determined to avoid fracture and failure of materials. This article is important from the industrial application point of view by considering triaxiality as a design parameter while designing the component.
This paper represents fast hash based IP address lookup algorithm. In the proposed method, binary strings are converted into decimal numbers and a unique tree structure is constructed to handle the IP address lookup problem. For L, the length of longest prefix in the table the proposed algorithm produces the result in O(L). It has been observed the proposed algorithm results no collision effect and its efficiency is independent of the number of prefixes. The proposed algorithm works efficiently for fixed data set routers having large number of prefixes of normal length.
The Generalized Caseview method (GCm) is a pixelization method. It is presented here by the way of a new formalism proposed recently. The Method identifies so to speak, each informational entity in the table with a cell of a physical support to create what we call an “infoxel”. The sum of all colouredinfoxels becomes an image, the Generalized Caseview. The method consists of two steps: the first one is to define the reference frame while the second is to visualize data through the reference frame. The infoxels that constitute the reference frame should be organized according to three criteria:al and ordinal. The case studies are about prostate cancer, sleep apnea syndrome diagnosis and genetics data .The heuristic value of the method is emphasized through the knowledge crystallization metaphor.
In this paper, performance of iterative Wiener filter in restoration of color images is evaluated A comparative analysis of the restoration results, obtained from inverse filter, single step wiener filter and iterative wiener filter, is also made. A color image is degraded using motion blur function and corrupted with addictive Gaussian noise. This image is
restored with single step Wiener filter and inverse filter. An iterative algorithm for Wiener filter is Implemented to minimize the mean square error between the blurred image and the restored image. Experimental results are included to illustrate the effectiveness of proposed image restoration algorithm. The algorithm is used in different image sets.