AMIRKABIR
Year:2007 | Volume:17 | Issue:65-B|Papers Count:10

Real-world experiments are often multi-response. The correlation between responses and the cost of experimenting lead one to cast the problem as a multi-response model. Generation of a multi-response optimal design is a challenging problem. There exist three general algorithms and all of them generate approximate design and no method for multi-response n-exact design has been cited in the literature. The existing methods have some drawbacks such as the necessity of solving many optimization problems in the process of generating an optimal design, cumbersome manual operations and the complexity of performing sensitivity analysis. In this paper, we propose a Semi-Definite Programming (SDP) model for multi-response optimal design. The proposed method is efficient because of solving a one shot optimization problem instead of many optimization problems, enjoying the recent advancements of interior-point solution algorithms and elimination of cumbersome manual operations. The proposed model has been tested on several test problems and proved to be very efficient since the optimal designs were found very quickly in all cases. The robustness of the generated designs with respect to the variance-covariance matrix is also assessed for those test problems in order to show how sensitivity analysis can be performed. The characteristics of the proposed method are also compared with those of other existing methods.

Analysis of means (ANOM) is a graphical method for evaluating equality of several treatment means. Estimates of treatment means are plotted on a chart equipped with lower and upper decision limits to determine equality of the means. Normality of observations is an implicit assumption considered in the ANOM. When this assumption fails then the results can be affected. One way to overcome this problem is transform the non-normal data to normal data. Transformation of data is a common remedy suggested to be performed prior to the ANOM. This paper provides a method for conducting ANOM when the assumption of normality does not hold.

In this paper, a model has been provided for selection of the right portfolio in stock exchange. Industries ranking and companies ranking have been applied for selection of the right stocks in this model. These rankings have been done through the PROMETHEE decision making method. Two linear programming problems have been used for determining the amounts of investment per superior industries and superior companies in proportion to capital. Given the investor's strategies, these problems can be solved. A survey has been done for determining the effective criteria over industry and company evaluation. The developed model has been applied in Tehran Stock Exchange (TSE) as a real case and sample problems have been solved. It is concluded that industries ranking, companies ranking and then portfolio selection results could be different due to using different investment strategies. Therefore model results are largely dependent upon the investor's strategies and the investor should determine these strategies accurately.

Paulhausen integral techniques together with Johnson, Redford and Jungho correlations are used in predicting transition onset, separation point position and penetration of free stream turbulence into transitional boundary layer in a diffusing flow. Free stream turbulence intensities are set to variety of values covering both linear and non-linear disturbances. In addition, diffuser half angle opening is assumed to vary in ranges not more than that bringing separation point into transitional zone. Results show that the free stream turbulence intensity and positive pressure gradient have both direct effects to bring transition onset closer to indifference stability point. Separation point, however, moves closest towards diffuser's inlet point as pressure gradient increases and moves away as FSTI increase. FSTI effects on near wall turbulence intensity, primarily causing its increase to a maximum and later approaching to a limit for the rest of boundary layer length.

In this paper, nonlinear control for path tracking of a 2-DOF Wheeled Mobile Robot (WMR) is presented. This problem nowadays has been tackled by many authors in various applications. Nonlinear control for WMRs requires unknown parameters estimation. This paper fully examines the effects of new dynamical models in both local and global coordinates on both estimation and tracking. The dynamic model in global coordinates has a profound effect on designing a nonlinear control, because it makes perfect compensation for initial off-track conditions and let the regressor matrix be highly exited leading to a better parameter estimation. A nonlinear controller whose parameters are tuned using fuzzy computations is developed. It is shown that fuzzy tuning of the controller instead of keeping the gains fixed makes the overall system more robust against noise while the input torque is remarkably reduced. This paper further introduces a fuzzy controller merely based on linguistic rules to control the WMR tracking problem. In this approach, in order to make the design simple and yet efficient, the process of parameter estimation which is very time consuming is eliminated.

For spark ignition engines, the fuel-air mixture preparation process is known to have a significant influence on engine performance and exhaust emissions. In this paper, an experimental study is made to characterize the spray characteristics of an injector with multi-disc nozzle used in the engine. The distributions of the droplet size and velocity and volume flux were characterized by a PDA system. Also a model of a 4 cylinders multi-point fuel injection engine was prepared using a fluid dynamics code. By this code one-dimensional, unsteady, multiphase flow in the intake port has been modeled to study the mixture formation process in the intake port. In addition, one-dimensional air flow and wall fuel film flow and a two-dimensional fuel droplet flow have been modeled, including the effects of in-cylinder mixture back flows into the port. The accuracy of model was verified using experimental results of the engine testing showing good agreement between the model and the real engine. As a result, predictions are obtained that provide a detailed picture of the air-fuel mixture properties along the intake port. A comparison was made on engine performance and exhaust emission in different fuel injection timing for 2600 and 6000 rpm and different loads. According to the present investigation, optimum injection timing for different engine operating conditions was found.

Manufacturing feature recognition is a basic component for systems that automatically generate manufacturing processes. When compared to the set of low level entities existing in a component's CAD model, features are a set of higher level entities that model the correspondence between design information and manufacturing activities. Graph-based methods, which use the part adjacency graph to recognize features, are among the most common techniques in the existing feature recognition literature. In this paper, some techniques are proposed which significantly improve the performance of traditional graph-based algorithms. The approach is more general and efficient than common graph-based approaches dealing with the problem of feature interactions. The scope of the graph-based approaches is also extended in this paper to include curved and 3D features in addition to polyhedral features, where most of the existing graph-based algorithms have focused only on the polyhedral objects.

In this paper, imposing torque and accuracy constraints, a new method for determination of Dynamic Load Carrying Capacity (DLCC) in Flexible Joint Robots (FJR) has been presented. The method is based on Sliding Mode Control algorithm as a robust control algorithm so it has the ability of determination of maximum dynamic load carrying capacity in the presence of disturbance. Algorithms are represented in both case of absence and presence of the disturbance for determination of maximum dynamic load carrying capacity. Also, in each condition in order to evaluate the performance of the proposed method simulation test is carried out. Results of the maximum dynamic load carrying capacities are discussed.