Influence of grinding operations on surface integrity and chloride induced stress corrosion cracking of stainless steels

Stainless steels were developed in the early 20th century and are used where both the mechanical properties of steels and corrosion resistance are required. There is continuous research to allow stainless steel components to be produced in a more economical way and be used in more harsh environments. A necessary component in this effort is to correlate the service performance with the production processes. The central theme of this thesis is the mechanical grinding process.  This is commonly used for producing stainless steel components, and results in varied surface properties that will strongly affect their service life. The influence of grinding parameters including abrasive grit size, machine power and grinding lubricant were studied for 304L austenitic stainless steel (Paper II) and 2304 duplex stainless steel (Paper I). Surface integrity was proved to vary significantly with different grinding parameters. Abrasive grit size was found to have the largest influence. Surface defects (deep grooves, smearing, adhesive/cold welding chips and indentations), a highly deformed surface layer up to a few microns in thickness and the generation of high level tensile residual stresses in the surface layer along the grinding direction were observed as the main types of damage when grinding stainless steels. A large degree of residual stress anisotropy is interpreted as being due to mechanical effects dominating over thermal effects. The effect of grinding on stress corrosion cracking behaviour of 304L austenitic stainless steel in a chloride environment was also investigated (Paper III). Depending on the surface conditions, the actual loading by four-point bend was found to deviate from the calculated value using the formula according to ASTM G39 by different amounts. Grinding-induced surface tensile residual stress was suggested as the main factor to cause micro-cracks initiation on the ground surfaces. Grinding along the loading direction was proved to increase the susceptibility to chloride-induced SCC, while grinding perpendicular to the loading direction improved SCC resistance. The knowledge obtained from this work can provide a reference for choosing appropriate grinding parameters when fabricating stainless steel components; and can also be used to help understanding the failure mechanism of ground stainless steel components during service.

Residual-based test for Nonlinear Cointegration with application in PPPs

Nested by linear cointegration first provided in Granger (1981), the definition of nonlinear cointegration is presented in this paper. Sequentially, a nonlinear cointegrated economic system is introduced. What we mainly study is testing no nonlinear cointegration against nonlinear cointegration by residual-based test, which is ready for detecting stochastic trend in nonlinear autoregression models. We construct cointegrating regression along with smooth transition components from smooth transition autoregression model. Some properties are analyzed and discussed during the estimation procedure for cointegrating regression, including description of transition variable. Autoregression of order one is considered as the model of estimated residuals for residual-based test, from which the teststatistic is obtained. Critical values and asymptotic distribution of the test statistic that we request for different cointegrating regressions with different sample sizes are derived based on Monte Carlo simulation. The proposed theoretical methods and models are illustrated by an empirical example, comparing the results with linear cointegration application in Hamilton (1994). It is concluded that there exists nonlinear cointegration in our system in the final results.

Movements and mechanical stresses in gas-filled flat plate solar collectors

Sealed gas filled flat plate solar collectors will have stresses in the material since volume and pressure varies in the gas when the temperature changes. Several geometries were analyzed and it could be seen that it is possible reducing the stresses and improve the safety factor of the weakest point in the construction by using larger area and/or reducing the distance between glass and absorber and/or change width and height relationship so the tubes are getting longer. Further it could be shown that the safety factor won't always get improved with reinforcements. It is so because when an already strong part of the collector gets reinforced it will expose weaker parts for higher stresses. The finite element method was used for finding out the stresses.

Residual-based Inference for Common Nonlinear Features

This paper investigates common nonlinear features in multivariate nonlinear autore-gressive models via testing the estimated residuals. A Wald-type test is proposed and itis asymptotically Chi-squared distributed. Simulation studies are given to examine thefinite-sample properties of the proposed test.

Genetic Control of Residual Variance for Teat Number in Pigs

The genetic improvement in litter size in pigs has been substantial during the last 10-15 years. The number of teats on the sow must increase as well to meet the needs of the piglets, because each piglet needs access to its own teat. We applied a genetic heterogeneity model on teat numberin sows, and estimated medium-high heritability for teat number (0.5), but low heritability for residual variance (0.05), indicating that selection for reduced variance might have very limited effect. A numerically positive correlation (0.8) between additive genetic breeding values for mean and for variance was found, but because of the low heritability for residual variance, the variance will increase very slowly with the mean.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.