On adaptive mesh refinement in wrinkling prediction analysis

Hutchinson approach has been successfully used by a number of researchers in thin sheet metal forming processes for wrinkling prediction. However, Hutchinson approach is limited to regions of the sheet that are free of any contact. Therefore, a new wrinkling indicator that can be used in the contact areas is proposed. Discretisation error indicators are also used to present a comprehensive approach to wrinkling prediction analysis

Testing the assumptions of linear prediction analysis in normal vowels

This paper develops an improved surrogate data test to show experimental evidence, for all the simple vowels of US English, for both male and female speakers, that Gaussian linear prediction analysis, a ubiquitous technique in current speech technologies, cannot be used to extract all the dynamical structure of real speech time series. The test provides robust evidence undermining the validity of these linear techniques, supporting the assumptions of either dynamical nonlinearity and/or non-Gaussianity common to more recent, complex, efforts at dynamical modelling speech time series. However, an additional finding is that the classical assumptions cannot be ruled out entirely, and plausible evidence is given to explain the success of the linear Gaussian theory as a weak approximation to the true, nonlinear/non-Gaussian dynamics. This supports the use of appropriate hybrid linear/nonlinear/non-Gaussian modelling. With a calibrated calculation of statistic and particular choice of experimental protocol, some of the known systematic problems of the method of surrogate data testing are circumvented to obtain results to support the conclusions to a high level of significance

Strainrange partitioning behavior of an automotive turbine alloy

This report addresses Strainrange Partitioning, an advanced life prediction analysis procedure, as applied to CA-101 (cast IN 792 + Hf), an alloy proposed for turbine disks in automotive gas turbine engines. The methodology was successful in predicting specimen life under thermal-mechanical cycling, to within a factor of + or - 2

Probit regression in prediction analysis

To avoid diagnostic surgery, the probability of nodal involvement of prostate cancer is modeled using the probit link function to determine whether the lymph nodes of a patients are infected. X-ray status and level of acidphosphatase in the blood serum of patients are considered as preoperative explanatory variables with the number of patients having nodal involvement as response variable. Within the framework of the probit regression model, the level of nodal involvement is predicted and the probability of nodal involvement obtained