Statistically Designed Optimization of a Glass Composition
Authors:
- 1 November 1984
- journal article
- Published by Wiley in Journal of the American Ceramic Society
- Vol. 67 (11) , 763-768
Abstract
An efficient, statistically based methodology for development and optimization of multicomponent materials is presented. The approach is illustrated with a five‐component nuclear waste glass. A composition field is defined, test compositions are statistically chosen, and their measured property data are used to fit empirical models. These models are then used to predict the optimum composition. The following nuclear waste glass components were investigated: SiO 2 , B 2 O 3 , Na 2 O, CaO, and simulated nuclear waste. The following properties were modeled: viscosity, chemical durability, and crystallinity. Successful models were constructed by using data from 27 test melts. This methodology could be applied to a wide range of ceramic mixture problems.Keywords
This publication has 26 references indexed in Scilit:
- Defining Consistent Constraint Regions in Mixture ExperimentsTechnometrics, 1983
- Measuring Component Effects in Constrained Mixture ExperimentsTechnometrics, 1982
- A Mixtures Model with Inverse TermsTechnometrics, 1977
- Discussion of: The Use of Gradients to Aid in the Interpretation of Mixture Response SurfacesTechnometrics, 1975
- The Use of Gradients to Aid in the Interpretation of Mixture Response SurfacesTechnometrics, 1975
- The Use of Gradients to Aid in the Interpretation of Mixture Response SurfacesTechnometrics, 1975
- Test Statistics for Mixture ModelsTechnometrics, 1974
- Test Statistics for Mixture ModelsTechnometrics, 1974
- Techniques for the Analysis of Mixture DataTechnometrics, 1973
- Extreme Vertices Design of Mixture ExperimentsTechnometrics, 1966