Optoelectronic oscillators (OEOs) are hybrid systems consisting of optical and radio-frequency (RF) parts that are used to produce ultralow phase noise RF oscillations. Dual-loop OEOs can overcome some problems incorporated with single-loop OEOs such as the mode-hopping phenomenon and the large spurious peaks in the phase noise. Therefore, they are usually considered the practical implementation of many OEOs. Here, a frequency-domain steady-state and phase noise analysis approach of these systems is presented, based on the conversion matrix approach. Compared with the existing time-domain analysis approaches, it requires much smaller run times. Compared with the other frequency-domain modeling approaches, such as the linear-time-invariant phase transmission models, it can take all noise-transferring phenomena between various sidebands and all amplitude-noise to phase-noise conversions and vice versa into account. Therefore, it can be regarded as a comprehensive analysis approach to dual-loop OEOs. The validity of the new approach is verified by comparing its results with those of the previously published formulations in the literature.
SummaryThe sun and wind as renewable energy sources are attracting more regard as alternative energy sources. In addition to the decreasing fuel sources, pollution and global warming are important problems. Fuel cells are a beneficial energy technology that generates electric energy through the reaction between the fuel sources rich in hydrogen and oxygen. In comparsion with combustion engines, fuel cells have many advantages, such as high efficiency and low emissions. Furthermore the by-products of fuel cells are heat and water. Proton exchange membrane fuel cells (PEMFCs) have attracted much interests recently. PEM fuel cells are Pollution-Free high-efficiency power sources for urban vehicles that recently corporate by legislative initiatives. Previously, some research on modeling and simulation of PEMFC has been performed (Secanell et al. 2014). The fundamental structure of a PEMFC can be described as two electrodes (anode and cathode) separated by a solid polymer membrane that acting as an electrolyte. The hydrogen gas is the Best fuel for fuel cell powered vehicles, because of the highest conversion efficiency for fuel, generating zero tail-pipe emission and producing water as an only product of the reaction between hydrogen and air .By flowing hydrogen fuel through a network of channels to the anode, hydrogen separates into protons that transfer via the membrane to the cathode. Collection of electrons in the two electrodes causes the creation of electrical current in an electrical circuit that linked to the electrodes. Through a similar network of channels the oxygen that comes from the air, named oxidant, flows to the cathode and then, the electrons coming from the external electrical circuit will be received by oxygen and finally, produce water and heat from the protons that flow via the electrolyte membrane (Feroldi and Basualdo 2011;Gottesfeld 1999).With a valid mathematical model, PEMFC system performance can be better understood. Moreover, the time and cost are reduced in the analysis and design of FC systems. Nowadays, programming in other sciences has a very special place because the importance of computers cannot be ignored as a very effective application in technical and research affairs. The OPEM software (open proton exchange membrane) written in Python Programming language that is very powerful for developers but is also accessible to scientists. Simulation models in PEMFC include dynamic and static models. Static models focus more on electrochemical techniques and can predict the performance of PEMFC. Simulated parametric models combined with the empirical approach that describes the important concepts such PEMFC polarization losses, efficiency, and Nernst voltage. Dynamic models improve static models and complete the simulation process. In dynamic models, the science of fluid and material merge with electrochemical principles and dynamic concepts. Consideration the rules of absorption and penetration of gases based on their pressure and density, causes the simulation of fuel cell to be more ...
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