This doctoral thesis deals with suspension cable roof structures above a circular and elliptical plan. The methodology of analysis is based on a basic annular cable roof structure of an external diameter of 70 m. The roof structure is designed as a prestressed membrane from the precast panels made from lightweight structural concrete which are supported with the bearing and prestressing tendons that are radially led between the two peripheral rings. The structural arrangement and the process of construction are described. The static system is specified and the terms like self-anchored system or equilibrium state are also defined. Finally, the results of static analysis are discussed in detail. The main aim of the doctoral thesis is to design a roofing of football stadium terraces using the structures of a basic annular cable roof; and present two alternatives – above circular and elliptical plan. The circular alternative comes directly from basic annulus, only the main dimensions of the new-designed structure are correspondingly extended. The elliptical alternative is an alteration of the circular design. As the radial tendons are anchored to the flexible peripheral curved girders, and the structures form the self-anchored system, the horizontal tendon forces load the peripheral girders radially. Because of that, it is essential to design a state of stress in tendon to prevent the undesirable global bending moments on the peripheral girders, and subsequently large non-uniform horizontal and vertical displacements of structure. Therefore, a study of the optimal load of ellipse is carried out. On the basis of the study, two basic requirements to structural arrangement of the elliptical roof are formulated. To illustrate the importance of a correct design, the optimal and unsuitable structural arrangements are compared. Finally, the results of static analysis of the circular and elliptical roof are again discussed in detail.

The aim of this research is to calibrate conductive polymer nanocomposite materials for large strain sensing and develop a structural health monitoring algorithm for gossamer structures by using nanocomposites as strain sensors. Any health monitoring system works on the principle of sensing the response (strain, acceleration etc.) of the structure to an external excitation and analyzing the response to find out the location and the extent of the damage in the structure. A sensor network, a mathematical model of the structure, and a damage detection algorithm are necessary components of a structural health monitoring system. In normal operating conditions, a gossamer structure can experience normal strain as high as 50%. But presently available sensors can measure strain up to 10% only, as traditional strain sensor materials do not show low elastic modulus and high electrical conductivity simultaneously. Conductive polymer nanocomposite which can be stretched like rubber (up to 200%) and has high electrical conductivity (sheet resistance 100 Ohm/sq.) can be a possible large strain sensor material. But these materials show hysteresis and relaxation in the variation of electrical properties with mechanical strain. It makes the calibration of these materials difficult. We have carried out experiments on conductive polymer nanocomposite sensors to study the variation of electrical resistance with time dependent strain. Two mathematical models, based on the modified fractional calculus and the Preisach approaches, have been developed to model the variation of electrical resistance with strain in a conductive polymer. After that, a compensator based on a modified Preisach model has been developed. The compensator removes the effect of hysteresis and relaxation from the output (electrical resistance) obtained from the conductive polymer nanocomposite sensor. This helps in calibrating the material for its use in large strain sensing. Efficiency of both the mathematical models and the compensator has been shown by comparison of their results with the experimental data. A prestressed square membrane has been considered as an example structure for structural health monitoring. Finite element analysis using ABAQUS has been carried out to determine the response of the membrane to an uniform transverse dynamic pressure for different damage conditions. A neuro-fuzzy system has been designed to solve the inverse problem of detecting damages in the structure from the strain history sensed at different points of the structure by a sensor that may have a significant hysteresis. Damage feature index vector determined by wavelet analysis of the strain history at different points of the structure are taken by the neuro-fuzzy system as input. The neuro-fuzzy system detects the location and extent of the damage from the damage feature index vector by using some fuzzy rules. Rules associated with the fuzzy system are determined by a neural network training algorithm using a training dataset, containing a set of known input and output (damage feature index vectors, location and extent of damage for different damage conditions). This model is validated by using the sets of input-output other than those which were used to train the neural network. / Ph. D.