IEEE 802.22 wireless regional area network (WRAN) is a cognitive radio-based network. WRANs are intended to be deployed by different service providers and designed to opportunistically utilize the unused TV bands. WRANs have to self-coexist with other overlapped WRANs in a distributed manner. Therefore, every service provider tries to acquire a band free of interference from others to satisfy a required quality of service. This self-coexistence problem is one of the major challenges in WRAN. In this paper, we propose a Markov-based distributed approach for mitigating this problem. We model the problem as an absorbing discrete-time Markov chain. In this model, if two or more overlapped WRANs select the same band, then each one should either stay or switch to another band according to a certain switching probability. This process continues until each one of the WRANs finds an interference-free band. In this case, the Markov chain reaches the absorbing state. This model is employed to find the optimal switching probability, which in turn minimizes the time required to reach the absorbing state. The switching probability is numerically found as a function of the number of overlapped WRANs and available bands. Extensive simulation has been conducted to validate our numerical results.
Most of the schemes that were proposed to improve the performance of transmission control protocol (TCP) over mobile ad hoc networks (MANETs) are based on a feedback from the network, which can be expensive (require extra bandwidth) and unreliable. Moreover, most of these schemes consider only one cause of packet loss. They also resume operation based on the same stand-by parameters that might vary in the new route. Therefore, we propose two techniques for improving the performance of TCP overMANETs. The first one, called TCP with packet recycling (TCP-PR), allows the nodes to recycle thepackets instead of dropping them after reaching the retransmission limit at the MAC layer. In the second technique, which is called TCP with adaptive delay window (TCP-ADW), the receiver delays sending TCP ACK for a certain time that is dynamically changed according to the congestion window and the trip time of the received packet. TCP-PR and TCP-ADW are simple, easy to implement, do not require network feedback, compatible with the standard TCP, and do not require distinguishing between the causes of packet loss. Our thorough simulations show that the integration of our two techniques improves theperformance of TCP over MANETs.
In this paper, the solution of inverse kinematics problem of robot manipulators using genetic algorithms (GA) is presented. Two versions of genetic algorithms are used which include the conventional GA and the continuous GA. The inverse kinematics problem
is formulated as an optimization problem based on the concept of minimizing the accumulative path deviation in the absence of any obstacles in the workspace. Simulation results show that the continuous GA outperforms the conventional GA from all aspects. The superiority of the continuous GA is seen in that it will always provide smooth and faster solutions as compared with the conventional GA.
A robust computational technique for model order reduction (MOR) of multi-time-scale discrete systems (single input single output (SISO) and multi-input multioutput (MIMO)) is presented in this paper. This work is motivated by the singular perturbation of multi-time-scale systems where some specific dynamics may not have significant influence on the overall system behavior. The new approach is proposed using genetic algorithms (GA) with the advantage of obtaining a reduced order model, maintaining the exact dominant dynamics in the reduced order, and minimizing the steady state error. The reduction process is performed by obtaining an upper triangular transformed matrix of the system state matrix defined in state space representation along with the elements of B, C, and D matrices. The GA computational procedure is based on maximizing the fitness function corresponding to the response deviation between the full and reduced order models. The proposed computational intelligence MOR method is compared to recently published work on MOR techniques where simulation results show the potential and advantages of the new approach.
A new model order reduction (MOR) technique for linear multi time scale discrete systems with substructure preservation is presented in this paper. The reduction process is performed based on two steps; system transformation and singular perturbation approximation (SPA). The system transformation step is performed to maintain the system substructure preservation, while the SPA is used to obtain the intended reduced order model. The new MOR approach is presented with the advantages of obtaining the desired reduced order model, minimizing the steady state error, preserving a system substructure (dominant dynamics), in addition to the advantage of a relatively fast convergence of the system steady state behavior. The proposed modelling technique is investigated by applying it to a power system model with a comparison of quality of performance to other model order reduction techniques. The potential and advantages of the new approach are clearly seen in the illustrative simulation results.
Magneto-hydrodynamic (MHD) principle is an important interdisciplinary field. One of
the most important applications of this effect is pumping of materials that are hard to pump using
conventional pumps. In this work, the progress achieved in this field is surveyed and organized
according to the type of application. The literature of the past 27 years is searched for the major
developments of MHD applications. MHD seawater thrusters are promising for a variety of applications requiring high flow rates and velocity. MHD molten metal pump is important replacement
to conventional pumps because their moving parts cannot stand the molten metal temperature.
MHD molten salt pump is used for nuclear reactor coolants due to its no-moving-parts feature.
Nanofluid MHD pumping is a promising technology especially for bioapplications. Advantages
of MHD include silence due to no-moving-parts propulsion. Much progress has been made, but
with MHD pump still not suitable for wider applications, this remains a fertile area for future research.
The optimum implementation of a thermoelectric generator (TEG) is investigated. In order to study the feasibility of such system, a model for a large-scale TEG is designed and optimized to convert thermal energy into electricity. The mathematical formulation of the system comprising multiple TEG modules is modeled and simulated. It is assumed that the source of the thermal energy comes from concentrated solar receiver. Temperature solutions and heat transfer coefficients are obtained. The major geometrical and thermal parameters affecting the efficiency of the system are identified and optimized for best performance. Design aspects, such as the leg length, and heat transfer conditions have a significant impact on generated output power and efficiency.
The reliability of solar concentrator is investigated using finite element (FE) modelling. An FE model of the receiver absorber is built and simulated using latin hypercube sampling. A transient thermal structural simulation is conducted, and the maximum thermal stress affecting the absorber is determined. Based on the failure criterion, the most effective parameters are determined and assigned as random variables. A stochastic simulation is performed resulting in a probability density function (PDF) of the thermal stress-life. The PDF is used to estimate the reliability of the absorber. Different designs and materials of the absorber tubes are investigated. Consequently, methods to improve the reliability of the absorber are identified.
A broad reliability prediction method that can deal with complex thermo-fluidic systems is introduced. The procedure provides an engineering tool by integrating multiple computational packages that enable the simulation of a wide array of systems, especially those involving physics interactions such as fluid flow and solid medium. Computational Fluid Dynamics, Finite Element Method, Monte Carlo Simulation and fatigue analysis tools are integrated within this physics-based reliability prediction approach. The complete procedure is demonstrated using a simple example, and then validated using boiler pipes experimental data. CFD simulations are used to determine the convective terms necessary for the transient FEM thermal analysis. The thermal analysis provides maximum thermal stress whereby the fatigue life of the component is evaluated. As a result of input parameters uncertainty, the expected life will be in the form of a Probability Density Function, which enables the calculation of the reliability of the component.