Integration Of Strength and Process Modelling of Friction-Stir-Welded Fuselage Panels

In order to reduce potential uncertainties and conservatism in welded panel analysis procedures, understanding of the relationships between welding process parameters and static strength is required. The aim of this study is to determine and characterize the key process induced properties of advanced welding assembly methods on stiffened panel local buckling and collapse performance. To this end, an in-depth experimental and computational study of the static strength of a friction stir welded fuselage skin-stiffener panel subjected to compression loading has been undertaken. Four welding process effects, viz. the weld joint width, the width of the weld Heat Affected Zone, the strength of material within the weld Heat Affected Zone and the magnitude of welding induced residual stress, are investigated. A fractional factorial experiment design method (Taguchi) has been applied to identify the relative importance of each welding process effect and investigate effect interactions on both local skin buckling and crippling collapse performance. For the identified dominant welding process effects, parametric studies have been undertaken to identify critical welding process effect magnitudes and boundaries. The studies have shown that local skin buckling is principally influenced by the magnitude of welding induced residual stress and that the strength of material in the Heat Affected Zone and the magnitude of the welding induced residual stress have the greatest influence on crippling collapse behavior.


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Integration of shading and texture cues: testing the linear model

One of the first attempts to develop a formal model of depth cue integration is to be found in Maloney and Landy's (1989) "human depth combination rule". They advocate that the combination of depth cues by the visual sysetem is best described by a weighted linear model. The present experiments tested whether the linear combination rule applies to the integration of texture and shading. As would be predicted by a linear combination rule, the weight assigned to the shading cue did vary as a function of its curvature value. However, the weight assigned to the texture cue varied systematically as a function of the curvature value of both cues. Here we descrive a non-linear model which provides a better fit to the data. Redescribing the stimuli in terms of depth rather than curvature reduced the goodness of fit for all models tested. These results support the hypothesis that the locus of cue integration is a curvature map, rather than a depth map. We conclude that the linear comination rule does not generalize to the integration of shading and texture, and that for these cues it is likely that integration occurs after the recovery of surface curvature.