International Journal of Engineering
Volume:21 Issue: 1, Feb 2008

Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction''s accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several methods have been introduced for prediction of solar activity indices especially the sunspot number, which is a common measure of solar activity. In this paper, the problem of embedding dimension estimation for solar activity chaotic time series based on polynomial models is considered. The optimality of embedding dimension has an important role in computational efforts, Lyapunov exponents'' analysis and efficiency of prediction. The method of this paper is based on the fact that the reconstructed dynamics of an attractor should be a smooth map, i.e. with no self intersection in the reconstructed attractor. To check this property, a local general polynomial autoregressive model is fitted to the given data and a canonical state space realization is considered. Then, the normalized one-step forward prediction error for different orders and various degrees of nonlinearity in polynomials is evaluated. Besides the estimation of the embedding dimension, a predictive model is obtained which can be used for prediction and estimation of the Lyapunov exponents. This algorithm is applied to indicate the minimum embedding dimension of sunspot numbers (SSN), Disturbance Storm Time or Dst. and Proton Flux indices are some of the most important among solar activity indices and results depict the power of the proposed method in embedding dimension estimation.

This paper introduces a model to make decision on the maintenance of a mechanical component subject to condition monitoring. A stochastic model is used to determine what maintenance action should be taken at a monitoring check and the follow up inspection times. The condition of component has a stochastic relation with measurements. A new state space model is developed and used, to predict the hazard rate and condition monitoring measurements, to indirectly asses the hazard rate of the system. The Proportional Covariate Model (PCM) which was proposed by Yong Sun (2004) was also used to develop the model. The known Kalman Filter was employed to derive the probability of the conditional hazard rate, which is predicted and updated for condition monitoring. The maintenance is being performed based on the estimated hazard rate so that the desired level of reliability is achieved, in a cost effective approach. This approach is validated by using the experimental data obtained from gearboxes which ran and failed on the Mechanical Diagnostic Test Bed (MDTB) at the Penn State University Applied Research Laboratory.

A detailed modular modeling of an absorbent cooling system is presented in this paper. The model including the key components is described in terms of design parameters, inputs, control variables, and outputs. The model is used to simulate the operating conditions for estimating the behavior of individual components and system performance, and to conduct a sensitivity analysis based on the given control variables. The proposed model has been validated by means of comparing the predicted results with the experimental data in a full-scale absorbent cooling system installed at MERC. Careful attention was given to estimate the behavior of the system at transient mode. Based on operating conditions, a range of time-constant start-up time had been estimated for generator and evaporator. The results indicated that the model predictions were in good agreement with experimental data. Sensitivity analysis also showed that the performance characteristics of the system could be approximated by generalized polynomial functions of order 2 in terms of control variables. Finally typical performance results are discussed.

Design, modeling, manufacturing and experimental analysis of a six degree freedom robot, suitable for industrial applications, has been described in this paper. The robot was designed on the assumption that, each joint has an independent DC motor actuator, with gear reduction and measuring sensor for angular joint position. Mechanical design of the robot was done using Mechanical Desktop and manufacturing process plan, the mechanical parts of the robot was developed. Kinematics and dynamics modeling of the robot was done using Mathematical and also MATLAB Robotics Toolbox and ADAMS software. The results from the kinematics and dynamics solution of the robot which was done mathematically, using Mathematical software, have been compared with the developed models of the robot, using MATLAB and ADAMS software for verification. An efficient geometric algorithm for the inverse kinematics problem of the robot was proposed. Finally, Experimental analysis and operational performance tests, including pose and path accuracy/repeatability of the robot''s end-effecter, according to ISO 9283 standard was completed and the results are presented below.

The objective of this paper is to examine the effectiveness of wall oscillation as a control scheme of drag reduction. Two flow configurations are considered: constant flow rate and constant mean pressure gradient. The Navier-Stokes equations are solved using Fourier-Chebyshev spectral methods and the oscillation in sinusoidal form is enforced on the walls through boundary conditions for the spanwise and streamwise (for the case of inclination cycle) velocity components. Results include the effects of oscillation frequency, amplitude, oscillation orientation, and peak wall speed on drag reduction at a Reynolds number of 180 based on wall-shear velocity and channel half-width as well as the Reynolds number dependency in both flow configurations. Drag reduction as a function of peak wall speed is compared with both experimental and numerical data and the agreement is good in the trend and in the quantity. Comparison between these two flow configurations in the transient response to the sudden start of wall oscillation, turbulence statistics, and instantaneous flow fields is detailed and differences are clearly shown. This analysis and comparison have allowed some light to be shed on the way that oscillations interact with wall turbulence.