This paper concerns the experimental validation of two surrogate models through a benchmark study involving two different variable shape mould prototype systems. The surrogate models in question are different methods based on kriging and proper orthogonal decomposition (POD), which were developed in previous work. Measurement data used in the benchmark study are obtained using digital image correlation (DIC). For determining the variable shape mould configurations used for the training, and test sets used in the study, sampling is carried out using a novel constrained nested orthogonal-maximin Latin hypercube approach. This sampling method allows for generating a space filling and high-quality sample plan that respects mechanical constraints of the variable shape mould systems. Through the benchmark study, it is found that mechanical freeplay in the modeled system is severely detrimental to the performance of the studied surrogate models. By comparing surrogate model performance for the two variable shape mould systems, and through a numerical study involving simple finite element models, the underlying cause of this effect is explained. It is concluded that for a variable shape mould prototype system with a small degree of mechanical freeplay, the benchmarked surrogate models perform very well.
Experimental Validation of Surrogate Models for Predicting the Draping of Physical Interpolating Surfaces
Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received November 5, 2016; final manuscript received September 5, 2017; published online November 9, 2017. Assoc. Editor: Gary Wang.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Christensen, E. T., Lund, E., and Lindgaard, E. (November 9, 2017). "Experimental Validation of Surrogate Models for Predicting the Draping of Physical Interpolating Surfaces." ASME. J. Mech. Des. January 2018; 140(1): 011401. https://doi.org/10.1115/1.4038073
Download citation file:
- Ris (Zotero)
- Reference Manager