Theoretical study of a molten carbonate fuel cell stack for pressurized operation

A mathematical stack model of a molten carbonate fuel cell was numerically solved for temperature, gas dynamic pressure, and cell performance. The model assumed a steady state, constant load operation for a co‐flow stack with an external reformer. The numerical computation was done for a two‐dimensional domain with a real size of cell specifications. The effect of two stack operation variables, gas utilization and system pressure, was thoroughly analysed. The computation results were demonstrated in the form of flow fields, temperature contours, axial profiles, and plots of characteristic values. Our analysis began with an underlying fact that a high cathode gas flow is necessary for stack temperature control. The analysis result verified the effect of stack cooling by the cathode gas, and showed various aspects of stack operation and performance under pressurization. The pressurization effect is most significant in a moderate pressure range of 1–5 atm. The gas dynamic pressure, as it inevitably increases at a high gas flow rate, is regulated by pressurization. All the pressurization effects can generally be represented using a dimensionless parameter, named a pressurization factor. The relation between gas dynamic pressure and total system pressure was clarified from the related flow equations. Copyright © 2001 John Wiley & Sons, Ltd.     

新世代无线技术需知——OFDM及MIMO

无线产业虽然持续地演变着,但当前则是处于一个史无前例的转变状态.新兴的4G空中界面-WiMAX、LTE、UMB、802.20、WiBRO、新一代PHS等一所有都拥有共同的特点:其均根据正交频分多任务存取(OFDMA)、均利用MIMO(多输入多输出)、以及均拥有"平坦架构(flattenedarchitecture),同时,也都是以IP为基础(网络通信协议).     

Performance improvement of geographically distributed cosimulationby hierarchically grouped messages

To improve the performance of geographically distributed cosimulation, we propose a concept called hierarchically grouped message. The concept improves cosimulation performance, preserving the cosimulation accuracy, by hierarchically grouping messages transferred between simulators in a short period of simulated time into a single physical message, thereby reducing the number of physical messages. Applying the concept to hybrid and optimistic cosimulation, we can reduce the number of rollbacks as well as the communication overhead accompanying the message transfer. Experimental results show the efficiency of the proposed method for practical examples in an internationally distributed cosimulation environment     

M?ssbauer and Magneto Caloric Effect for?La0.7Ca0.3Mn0.99 57Fe0.01O3

The crystallographic and magneto caloric effects of La_0.7Ca_0.3Mn_0.99 ⁵⁷Fe_0.01O₃ powders were studied by using X-ray diffraction, vibrating sample magnetometer, and M?ssbauer spectroscopy. To investigate the effect of sintering conditions on LCMO, the samples were sintered in air and evacuated sealed quartz tube. The calculated magnetic entropy change in the magnetic fields of 1.5?T for the samples which sintered in air and evacuated sealed quartz tube are 1.6?J/kg?K and 3.2?J/kg?K, respectively. The temperatures of the maximum slope in dM/dT for the samples which sintered in air and evacuated sealed quartz tube are 242?K and 262?K, respectively. For the explanation of the M?ssbauer line broadening, we applied the presence the fluctuating magnetic field, which jumps between the values of hyperfine field, +H and ?H, along the z-axis with a frequency?f. We calculated anisotropy energy from M?ssbauer relaxation analysis.     

Agent formations in 3D spaces with communication limitations using an adaptive Q-structure

In this article, we further extend the Queue-formation structure (or Q-structure) in 3D spaces with additional features including: (i) specifying orientation information, (ii) a mechanism for forming sub-formations before the convergence into the final formation, and (iii) adapting the communication structure when communications are limited. The virtual Bobber-agents are used to guide each vehicle toward the appropriate queue, by acting as intermediate targets. In addition, virtual constellation-agents bias the motion of each vehicle to within a user-defined cone to the front of the vehicle so that abrupt direction changes are avoided as far as possible. The proposed scheme relies mainly on simple behaviors between embodied and virtual agents and is computationally inexpensive method. Extensive simulations show the effectiveness of the proposed method.     

High-shock silicon accelerometer with suspended piezoresistive sensing bridges

A high-shock 2000 g accelerometer with suspended piezoresistive sensing bridges has been designed, fabricated, and tested. Structural size of the accelerometer has been obtained through an optimal design process. Four resistors are electrically connected to form a Wheatstone bridge circuit. A sensitivity of 25.5 μV/g has been measured from the fabricated accelerometer with a nonlinearity of 0.2% in an acceleration range within 2000 g. The real-time response of the fabricated accelerometers accurately follows the reference accelerometer. The newly fabricated accelerometer has survived an over-shock condition of 4667 g.     

Online Detection of Repeated Structures in Point Clouds of Urban Scenes for Compression and Registration

Laser range scans of urban areas have a distinctive geometry dominated by facade and ground planes and repetitive regular fenestration. Detection of these ubiquitous features provides profound insights into the scene. We present a novel method for detecting major planes and repetitive architectural features. Armed with this knowledge we illustrate its application in compression and registration of range scans. What is more our algorithm operates online, processing the scan as it is retrieved by the scanner. This realtime approach opens up new possibilities in range data segmentation, compression and registration.     

Petroleum reservoir characterization with the aid of artificial neural networks

We introduce a new application of artificial neural network technology in the characterization of reservoir heterogeneity. Different reservoir properties, such as porosity, permeability and fluid saturation, in highly heterogeneous formations can be predicted with good accuracy using information deduced from readily available geophysical well logs. The methodology by which this is carried out is based on the intelligent and adaptive pattern recognition capabilities of an artificial neural network (three-layer feed forward, back propagation). The need for expensive processes to acquire porosity, permeability and fluid saturation data (such as well testing and extensive coring of the formation) may therefore be greatly reduced. Examples of several neural networks developed during this study are presented.