Mechanism of the early stages of α1 plate formation in a Cu-39 Pct Zn alloy

The early stages in the formation of α₁ plates in the ordered β′ matrix of a Cu-39 pct Zn alloy have been studied with transmission electron microscopy (TEM). The early stage plates were found to be free of stacking faults. Their contrast features are indeed those normally expected from small coherent plates. Electron microdiffraction confirms that these plates have the 9R structure characteristic of α₁ with the same lattice parameters and orientation relationships reported by previous investigators at much later stages of growth. Similarly, the 9R structure was disordered, even though it was formed in an ordered matrix, again repeating previous results obtained at a later stage of growth. These results further support the view that the α₁ Cu-Zn plates form by a diffusion-controlled mechanism. This article is based on a presentation made at the Pacific Rim Conference on the “Roles of Shear and Diffusion in the Formation of Plate-Shaped Transformation Products,” held December 18-22, 1992, in Kona, Hawaii, under the auspices of ASM INTERNATIONAL’S Phase Transformations Committee.     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

A generalized approach to the reconstruction of a restricted class of digitized planar curves

Reconstruction of an original continuous curve and the estimation of its parameters from the digitized version of the curve is a challenging problem, as quantization always causes some loss of information. In this paper, we have developed a scheme for reconstruction which is applicable to a class of curves having at the most two parameters. The class of curves for which the scheme works has also been characterized. We have shown that for one-parameter curves the exact domain of values of the parameter can be obtained. But in the two-parameter case, only the smallest rectangle containing the domain can be realised. The distinctive feature of our scheme is that it provides a unified approach to solve the reconstruction and the domain-finding problem for a class of curves.     

An integrated modeling approach to predict flooding on urban basin.

Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.     

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.     

The sliding-window packet switch: a new class of packet switch architecture with plural memory modules and decentralized control

Shared-memory based packet switches are known to provide the best possible throughput performance for bursty data traffic in high-speed packet networks and internets compared with other buffering strategies under conditions of identical memory resources deployed in the switch. However, scaling of shared-memory packet switches to a larger size has been restricted mainly due to the physical limitations imposed by the memory-access speed and the centralized control for switching functions in shared-memory switches. A new scalable architecture for a shared-memory packet switch, called the sliding-window (SW) switch, is proposed to overcome these limitations. The SW switch introduces a new class of switching architecture, where physically separate multiple memory modules are logically shared among all the ports of the switch, and the control is decentralized. The SW switch alleviates the bottleneck caused by the centralized control of switching functions in large shared-memory switches. Decentralized switching functions enable the SW switch to operate in a pipeline fashion to enhance scalability and switching capacity compared with that of previously known classes of shared-memory switch architecture.     

Theoretical investigation of penetration characteristics in gas metal-arc welding using finite element method

In the modeling of the gas metal-arc (GMA) welding process, heat inputs to the workpiece by the arc and the metal transfers have been considered separately. The heat energy delivered due to the metal transfer has been approximated in the form of a cylindrical volumetric heat source, whose dimensions of the radius and the height are dependent on the molten metal droplet characteristics. The pinch instability theory (PIT) and the static force balance theory (SFBT) of drop detachment have independently been used to obtain the expressions for various characteristics of the drop,i.e., the drop radius, the drop velocity, and the drop frequency at various welding parameters. The occurrence or the nonoccurrence of finger penetration, routinely found in the GMA welding at high welding currents, has been satisfactorily explained by the cylindrical heat source model. The effect of various welding parameters,e.g., the welding current, the wire radiusetc., on the weld bead penetration characteristics has been investigated. In this modeling effort, the heat conduction equation has been solved in three dimensions.