Local Web Buckling in Tapered Composite Beams: A Parametric Study

Composite flooring systems supported by tapered (varying web depth) beams are very attractive from an economic point of view. However, the tapered beam sections are fabricated from plate by welding, and are susceptible to imperfection effects. These may interact with the localised compressive stress field that is generated in the web at a slope change in the lower flange to cause local web buckling. A substantial parametric study using a non-linear elasto-plastic finite element program and covering practical ranges of the important parameters including the area of the tension flange, taper slope and web thickness is reported. Moment-rotation relations, peak moments and failure mechanisms have been predicted. The validity of the work is supported by the good correlation obtained between the results of the parametric study and experimental data.

Survival analysis: a tool in the study of post-harvest diseases in peaches

Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.