Nonlinear Pretensioning and Geometry Preservation of Spatial Structures

In this dissertation, three nonlinear techniques of prestressing, analysis, and preservation were developed based on the principles of the force method to address geometric nonlinearities in pin-jointed spatial structures. These techniques provide a comprehensive framework for accurately performing prestressing, analysing, and preserving spatial assemblies, validated through rigorous numerical and experimental investigations.

The research introduces direct nonlinear approaches especially for prestressing and preservation, overcoming the limitations of iterative and linear approximation-based methods. The derived nonlinear equations, expressed as functions of joint displacements, were efficiently solved using MATLAB’s fsolve function, demonstrating robust applicability to both simple and complex spatial systems. The proposed prestressing technique computes the desired prestress level by accurately accounting for nonlinear member alterations, preventing cable slack, and maintaining alignment with software solvers under predetermined actuation conditions.

The developed analysis method is efficient and precise, capable of calculating internal member stresses and axial forces for both rigid and flexible members while incorporating geometric nonlinearities under different loading conditions. Similarly, the preservation technique reliably restores disturbed geometries, nodal displacements, and internal forces, with targeted control of specific parameters. The effectiveness of the preservation process depends on actuator placement, bar sensitivity analysis, and the appropriate selection of actuation targets.

Validation of these techniques included numerical case studies and experimental testing on a hyperbolic paraboloid space cable net model with 64 members and 41 joints. The results demonstrated strong agreement, with maximum and minimum discrepancy ratios of 7% and 0%, respectively, between theoretical and experimental measurements. This dissertation presents a novel framework that significantly enhances the precision, efficiency, and control of structural response prediction, making substantial advancements in the field of pin-jointed spatial structures.