Temperature effects on the mass flow rate in the SBI and similar heat‐release rate test equipment

In various medium‐to‐large‐scale fire test equipments like the ISO room corner test (RC), and more recently, the single burning item test (SBI) the mass flow rate measurement of the combustion gases plays a key role in the determination of the heat‐release rate and smoke‐production rate. With the knowledge of the velocity profile and the temperature of the flow, the mass flow rate is obtained by measuring the velocity on the axis of the duct. This is done by means of a bi‐directional probe based on the pitot principle. However, due to the variation of the mean temperature and the temperature gradient in any cross section of the duct, introduced by ever changing combustion gas temperatures, the velocity nor the density profile are constant in time. This paper examines the resulting uncertainty on the mass flow rate. Copyright © 2006 John Wiley & Sons, Ltd.     

Improvement of levitation characteristics in a magnetic bearing system using HTSC‐permanent magnet hybrid structure

Magnetic bearing using pinning force of a permanent magnet and a high‐temperature superconductor has been developed. Additional permanent magnet is introduced to increase the levitation force of the magnetic bearing. In this hybrid magnetic bearing system, levitation force is mainly given by the repulsive force of the permanent magnets, and stability for the lateral direction is given by pinning force of the superconductor. The experimental device is developed. A ring‐type superconductor and a bulk one are examined. Levitation characteristics of the hybrid magnetic bearing are measured. The bulk superconductor shows better characteristics of both levitation and lateral stability than the ring one. Levitation force of the hybrid system becomes about twice as large as that of the nonhybrid one. Although, the repulsive force of the permanent magnet decreases the lateral stability of the system, its influence becomes small by choosing an adequate position of the permanent magnets and the superconductor. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(1): 71–77, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10350     

Performance prediction of a hybrid‐excitation synchronous machine with axially arranged excitation poles and permanent‐magnet poles

This paper presents a method of predicting the steady‐state performance of a new hybrid‐excitation synchronous machine (HESM) theoretically. The field pole of this HESM is axially divided into two parts; one is an excitation part and the other a permanent‐magnet (PM) part. A nonlinear equivalent circuit, which can include the saliency of the rotor and the magnetic saturation due to the iron core, is derived. Based on this equivalent circuit, the steady‐state performance of the HESM is calculated, and the results are confirmed through experiments. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 150(2): 43–49, 2005; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20033     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.