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Optimum design of cable stayed bridges depends on number of parameters. Design of Cable stayed bridge satisfying all practical constraints is challenging to the designers. Considering the huge number of design variables and practical constraints, Genetic Algorithms (GA) is most suitable for optimizing the cable stayed bridge. In the present work the optimum design is carried out by taking total material cost of bridge as objective function. During problem formulation most of the practical design variables and constraints are considered. Using genetic algorithms some parametric studies such as effect of geometric nonlinearity, effect of grouping of cables, effect of practical site constraints on tower height and side span, effect of bridge material, effect of cable layout, effect of extra-dosed bridges on optimum relative cost have been presented. Data base is prepared for new designers to estimate the relative cost of bridge

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Every year, a massive amount of literature is published on many aspects of microwave applications. Over the past few years, the need for progressive methods for assessing different properties of concrete, as well as for maintenance and monitoring of structures, has led to the development of microwave nondestructive testing (MNDT) techniques for preserving the civil infrastructure. As the number of studies being published in this eld is growing fast, it is important to categorize the studies at deeper levels. In this paper, a concrete cube of M20 grade has been created in ANSYS HFSS for simulation purposes. An arti cial rectangular crack was developed in the concrete cube and the simulation was run at dielectric constants from 1-10 with 0.5 intervals, loss tangents from 0.001,0.1 &0.2, and the gap between sample and circular waveguide from 0-7cm with 1cm interval. The arti cial neural network was developed in python for Mean square Error(MSE) analysis and prediction of Electromagnetic properties(Dielectric constant and Loss tangent) with inputs as the S-parameter(real and imaginary) data of the Homogenous sample and sample with Rectangular crack. The result analysis shows the variation in Mean squared error for crack and No-crack concrete samples.

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