A computational strategy to establish algebraic parameters for the Reference Resistance Design of metal shell structures. (July 2017) - Sadowski, Adam J.; Fajuyitan, O. Kunle; Wang, Jie
Highlights: Approved EN RRD design method for metal shells exploits advanced FE analyses. Challenge is now to establish databases of RRD parameters for important shell systems. RRD parameters require vast parametric studies of thousands of nonlinear FEA. Tools given for automated model generation, submission, termination and processing. Automated termination of 'Riks' analyses upon multiple failure criteria for shells. Abstract: The new Reference Resistance Design (RRD) method, recently developed by Rotter[1], for the manual dimensioning of metal shell structures effectively permits an analyst working with only a calculator or spreadsheet to take full advantage of the realism and accuracy of an advanced nonlinear finite element (FE) calculation. The method achieves this by reformulating the outcomes of a vast programme of parametric FE calculations in terms of six algebraic parameters and two resistances, each representing a physical aspect of the shell's behaviour. The formidable challenge now is to establish these parameters and resistances for the most important shell geometries and load cases. The systems that have received by far the most research attention for RRD are that of a cylindrical shell under uniform axial compression and uniform bending. Their partial algebraic characterisations required thousands of finite element calculations to be performed across a four-dimensional parameter hyperspace (i.e. length, radius to thickness ratio, imperfection amplitude, linear strain hardening modulus). Handling so many nonlinear finite element models is time-consuming and the quantities of data generated can be overwhelming. This paper illustrates a computational strategy to deal with both issues that may help researchers establish sets of RRD parameters for other important shell systems with greater confidence and accuracy. The methodology involves full automation of model generation, submission, termination and processing with object-oriented scripting, illustrated using code and pseudocode fragments.