Damage detection and model refinement using elemental stiffness perturbations with constrained connectivity

A new optimal update method for the correlation of dynamic structural finite element models with modal data is presented. The method computes a minimum-rank solution for the perturbations of the elemental stiffness parameters while constraining the connectivity of the global stiffness matrix. The resulting model contains a more accurate representation of the dynamics of the test structure. The changes between the original model and the updated model can be interpreted as modeling errors or as changes in the structure resulting from damage. The motivation for the method is presented in the context of existing optimal matrix update procedures. The method is demonstrated numerically on a spring-mass system and is also applied to experimental data from the NASA Langley 8-bay truss damage detection experiment. The results demonstrate that the proposed procedure may be useful for updating elemental stiffness parameters in the context of damage detection and model refinement

Discrete Optimization of Isolator Locations for Vibration Isolation Systems

An analytical and experimental study is conducted to investigate the effect of isolator locations on the effectiveness of vibration isolation systems. The study uses isolators with fixed properties and evaluates potential improvements to the isolation system that can be achieved by optimizing isolator locations. Because the available locations for the isolators are discrete in this application, a Genetic Algorithm (GA) is used as the optimization method. The system is modeled in MATLAB ™ and coupled with the GA available in the DAKOTA optimization toolkit under development at Sandia National Laboratories. Design constraints dictated by hardware and experimental limitations are implemented through penalty function techniques. A series of GA runs reveal difficulties in the search on this heavily constrained, multimodal, discrete problem. However, the GA runs provide a variety of optimized designs with predicted performance from 30 to 70 times better than a baseline configuration. An alternate approach is also tested on this problem: it uses continuous optimization, followed by "rounding " of the solution to neighboring discrete configurations. Results show that this approach leads to either infeasible or poor designs. Finally, a number of "optimized " designs obtained from the GA searches are tested in the laboratory and compared to the baseline design. These experimental results show a 7 to 46 times improvement in vibration isolation from the baseline configuration