SHEAR STRESS ANALYSIS OF TIMOSHENKO'S BEAM WITH MULTIPLY CONNECTED CROSS SECTION

In this paper, a finite element method is developed to numericallyevaluate the shear coefficient of Timoshenko's beam with multiplyconnected cross section. With focus on analyzing shear stressesdistributed at the neutral axis of the beam, an improved definitionof the shear coeffi- cient is presented. Based on this definition, aGalerkin-type finite element formulation is proposed to analyze theshear stresses and shear deflections. Numerical solutions of theexamples for some typical cross-sections are compared with thetheoretical results. The shear coefficient of tower sections of theTsing Ma Bridge is calculated by use of the proposed approach, sothat the finite element modeling of The bridge can be developed withthe accurate values of the sectional properties.

Numerical Simulations of Intraband Crosstalk in Optical Cross Connect

All optical network based on wavelength division multiplexing transmission system with optical cross connect (OXC) is an essential approach for optical commumications.Crosstalk introduced by OXC (specially large scale one) is a key limiting factor for its capacity. Optical signal passing through a typical OXC is analyzed in this paper, followed by description of the generation and effect of intraband crosstalk.The power penalties induced by intraband crosstalk versus the number of multiplexed wavelengths M and the number of input fibers N have been given by numerical simulations. The results show that the coherent crosstalk is the most critical limitation on OXC and depends more closely on the number of multiplexed wavelengths M than the number of input fibers N . Crosstalk is suppressed by doubly filtering, fixing optimum decision-threshold and appropriately choosing the number of multiplexed wavelengths M .

DISCRETE BIDIRECTIONAL ASSOCIATIVE MEMORY WITH LEARNING FUNCTION

In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.

40 Gbit/s Transparent Network Based on Wavelength-Selective Optical Cross Connect

This paper discusses a 40-Gbit/s transparent optical network focusing on the optical transport performance. We show 1200-km transmission with two WSOXC' sspaced by 400 km. In addition, network control issues are briefly addressed.