International Journal of Engineering
Volume:22 Issue: 1, Feb 2009

This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time-varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the proposed system there is no need for using offline estimation. The proposed method consists of two steps: a noise controller which is based on an FxLMS algorithm, and a variable step size (VSS) LMS algorithm which is used to adapt the modeling filter with the secondary path. In order to increase performance of the algorithm in a faster convergence and accurate performance, we stop the VSS-LMS algorithm at the optimum point. The results of computer simulation shown in this paper indicate effectiveness of the proposed method.

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory for implementing as a home security system and also using sensor data fusion have been considered. The benefits of multisensor fusion with direct connection to the control unit, in comparison with the traditional single sensor systems, have been shown.

This paper presents a novel, multi-objective mixed-integer nonlinear programming (MINLP) model for a cell formation problem (CFP) with alternative means. Due to existing contradiction among objectives, three are considered: 1) Minimizing the total cost consisting of; intercellular movements, purchasing, operation, and maintenance; 2) maximizing the utilization of machines in the system; 3) minimizing the deviation levels between the cell utilization (i.e., balancing the workload between cells). Furthermore, alternative process for each part, which is a key characteristic for flexible manufacturing systems, is considered in this paper. The main goals of our proposed model are to; 1) Select a process plan for each part with minimum cost, simultaneous machine grouping and complete series of all parts; 2) Identify the appropriate level of overall utilization of machines; 3) Balancing the workload among the cells in the production system.

There is a significant interaction between sizing a fleet of rail cars and its utilization. This paper presents a new multi-period mathematical model and a solution procedure to optimize the rail-car fleet size and freight car allocation, wherein car demands, and travel times, are assumed to be deterministic, and unmet demands are backordered. This problem is considered NP-complete. In other words, the traditional exact optimization approaches cannot solve a real-life size problem of this kind in a reasonable time. To tackle this problem, an efficient meta-heuristic algorithm based on simulated annealing (SA) is proposed. This algorithm works efficiently on a neighborhood search within solution space and probable acceptance of inferior solutions to escape from being trapped in local optima. A number of numerical examples are solved to check for efficiency and validity of the proposed SA algorithm. We conclude that the proposed model and algorithm are useful to identify good strategies for the sizing of rail car fleets and allocation of related cars.

Semi-Circular Bending (SCB) Test is a fast and accurate three-point bending test, which was originally used in rock mechanics. SCB test is going to be an accepted test method for asphalt concrete pavements. Different asphalt-mixture property-values such as tensile strength, stress intensity factor and fatigue can be obtained by this test. In this study, static and dynamic tests including SCB test, Stiffness modulus and fatigue tests using Nottingham Asphalt Tester (NAT), Indirect Tensile Strength test (ITS) and Triaxial Hveem test, were conducted on asphalt concrete specimens with different bitumen and filler contents, using two standard aggregate grades. The results obtained from different common tests were compared with the semi-circular bending test; assure that, SCB is a true-accurate test for prediction of both short-term and long-term mechanical properties of asphalt mixtures.

The powering requirement of a land yacht is one of the most important aspects of its design. In this respect the wind tunnel testing is an effective design tool. In fact, changing the parameters of the vehicle and testing the changes in the wind tunnel will give us a better understanding of the most efficient vehicle, and yet it is time consuming, expensive, and has inherent scaling errors. Another set of design tools are Computational Fluid Dynamics and parametric prediction. Computational Fluid Dynamics (CFD) codes are not yet wholly proven in its accuracy. Parametric prediction is the starting point for most engineering studies. It will be used to calculate the land yacht’s performance and provide a steady-state trim solution for the dynamic simulation. This tool is absolutely self validating. In present work, parametric prediction tool has been used for velocity prediction of a radio control land yacht with a rigid airfoil and cloth sail. The lift and drag coefficient of the rigid wing and cloth sail are obtained from the wind tunnel. The results show that the maximum velocity of the land yacht model with rigid wing is higher than cloth sail which occurs at 100 to 130 degree angle, courses.

This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 and the angle-of-attack at 18-deg conditions. Then, group method of data handling (GMDH) type neural networks are used for modeling the effects of the actuators parameters (momentum coefficient, reduced frequency, angle with respect to the wall) on both developed time-averaged lift (CL) and time-averaged drag (CD), using some numerically obtained training and test data. To use the obtained polynomial neural network models, multi-objective genetic algorithms (GAs) (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving the mechanism, which is then used for Pareto based optimization of control parameters considers two conflicting objectives such as lift (CL) and drag (CD). It is shown that some interesting and important relationships as useful optimal design principles are involved in the performance of stall control on NACA0015 airfoil. Using a synthetic jet actuator can be discovered by the Pareto based multi-objective optimization of polynomial models. Such important optimal principles would not have been obtained without the use of both GMDH-type neural network modeling and Pareto optimization approach.

State-of-the-art data analysis in production allows engineers to characterize reservoirs using production data. This saves companies large sums that should otherwise be spend on well testing and reservoir simulation and modeling. There are two shortcomings with today’s production data analysis: It needs bottom-hole or well-head pressure data in addition to data for rating reservoirs’ characterization. Analysis remains at the individual well level. It does not offer integration of results from individual wells to create a field-wide analysis. A new technique called Intelligent Production Data Analysis, IPDA, addresses both of these short-comings. Through an iterative technique, IPDA integrates Decline Curve Analysis, Type Curve Matching, and Numerical Reservoir Simulation (History Matching) in order to converge to a set of reservoir characteristics, compatible with all three techniques. Furthermore, once reservoir characteristics for individual wells in the field are identified through above process, and by using a unique Fuzzy Pattern Recognition technology the results are mapped on the entire field in order to evaluate reserve estimates, pin-point optimum infill drilling locations, track fluid flow and depletion, remaining reserves and finally identify under-performer wells.