A method to determine the tightening sequence for standing rigging of a mast

The article proposes an alternative method to determine the sequence of generation of pre-tension forces in standing rigging of a mast. The proposed approach has been verified on both a virtual simulation experiment and laboratory tests. In this method, the desired tension values are obtained using the influence matrix which allows to calculate the effect of tension change in an individual rope on the tension distribution in the remaining ropes in the system. Unlike the presently used method, in which the desired tension distribution is obtained in a long-lasting iterative process burdened with relatively large errors of final values, the proposed method makes it possible to achieve the final tension distribution in a finite number of steps. In the case of FEM analyses, the new method can be a useful tool for determining an arbitrary distribution of tension forces in ropes via solving a system of linear equations.

Simple Computational Methods in Predicting Limit Load of High-Strength Cold-Formed Sections due to Local Buckling: A Case Study

Cold-formed thin-walled sections are prone to local buckling caused by residual stresses, geometrical imperfections and inconsistency of material properties. We present a real case of buckling failure and conduct a numerical and experimental study aimed to identify methods capable of predicting such failures. It is important because designers of structures are getting more FEA-oriented and tend to avoid lengthy procedures of cold-formed structures design. Currently adopted methods are complicated and require patience and caution from a designer which is reasonable in case of the most important structural members but not necessarily so in ordinary design. Since it is important, we offer an insight into several FEA and manual methods which were sufficient to predict the failure while remaining fairly simple. Using a non-uniform partial safety factor was still necessary. We hope that this paper will be of interest for people performing a lot of routine analyses and worrying about reliability of their computations.