Film boiling from horizontal plates with low thermal capacity

The object of this investigation was to obtain data for saturated film pool boiling from a low thermal capacity flat plate at atmospheric pressure. A test plate, constructed from resistance strip, was placed horizontally in a pool of liquid, and was heated electrically. Refrigerant-11 and nitrogen were used as the boiling liquids. Heat transfer results were obtained in both fluids over a temperature range of approximately 1200F⁰ (400-1600⁰F). Surface size, roughness and orientation effects were observed for flat horizontal heated surfaces with one dimension near the most dangerous wavelength. No surface material effect was observed. Excellent correlation of the data is achieved by a slight modification to the Berenson equation --Abstract, page i

Applying the Mahalanobis-Taguchi System to Vehicle Handling

The Mahalanobis-Taguchi system (MTS) is a diagnosis and forecasting method using multivariate data. Mahalanobis distance (MD) is a measure based on correlations between the variables and patterns that can be identified and analyzed with respect to a base or reference group. The MTS is of interest because of its reported accuracy in forecasting using small, correlated data sets. This is the type of data that is encountered with consumer vehicle ratings. MTS enables a reduction in dimensionality and the ability to develop a scale based on MD values. MTS identifies a set of useful variables from the complete data set with equivalent correlation and considerably less time and data. This article presents the application of the MTS, its applicability in identifying a reduced set of useful variables in multidimensional systems, and a comparison of results with those obtained from a standard statistical approach to the problem

The Utility of Nonlinear Programming Algorithms: A Comparative Study -- Part II

A comprehensive comparative study of nonlinear programming algorithms, as applied to problems in engineering design, is presented. Linear approximation methods, interior penalty and exterior penalty methods were tested on a set of thirty problems and are rated on their ability to solve problems within a reasonable amount of computational time. In this paper, we give and discuss numerical results and algorithm performance curves

An Evaluation of Mahalanobis-Taguchi System and Neural Network for Multivariate Pattern Recognition

The Mahalanobis-Taguchi System is a diagnosis and predictive method for analyzing patterns in multivariate cases. The goal of this study is to compare the ability of the Mahalanobis- Taguchi System and a neural-network to discriminate using small data sets. We examine the discriminant ability as a function of data set size using an application area where reliable data is publicly available. The study uses the Wisconsin Breast Cancer study with nine attributes and one class