Evaluation of galling resistance for some selected combinations of tool steels/stainless steel sheet materials/lubricants using pin-on-disc testing

Stainless steels are well known to be prone to cold welding and material transfer in sliding contacts and therefore difficult to cold form unless certain precautions as discussed in this paper are taken. In the present study different combinations of tool steels/stainless steels/lubricants has been evaluated with respect to their galling resistance using pin-on-disc testing. The results show that a high galling resistance is favored by a high stainless steel sheet hardness and a blasted stainless steel sheet surface topography. The effect of type of lubricant was found to be more complex. For example, the chlorinated lubricants failed to prevent metal-to-metal contact on a brushed sheet surface but succeeded on a blasted sheet surface of the same stainless steel material. This is believed to be due to a protective tribofilm which is able to form on the blasted surface, but not on the brushed surface.

An investigation of worn work roll materials used in the finishing stands of the hot strip mill for steel rolling

The surface failure characteristics of different work roll materials, i.e. High Speed Steel, High Chromium Iron and Indefinite Chill Iron, used in the finishing stands of a hot strip mill have been investigated using stereo microscopy, 3D optical profilometry, scanning electron microscopy and energy dispersive X-ray spectroscopy. The results show that the surface failure mechanisms of work rolls for hot rolling are very complex, involving plastic deformation, abrasive wear, adhesive wear, mechanical and thermal induced cracking, material transfer and oxidation. Despite the differences in chemical composition and microstructure, the tribological response of the different work roll materials was found to be strongly dependent on the material microstructure and especially the presence and distribution of microstructural constituents, such as the different carbide phases and graphite (in the case of Indefinite Chill Iron). Cracking and chipping of the work roll surfaces, both having a negative impact on work roll wear, are strongly influenced by the presence of carbides, carbide networks and graphite in the work roll surface. Consequently, the amount of carbide forming elements as well as the manufacturing process must be controlled in order to obtain an optimised microstructure and a predictable wear rate.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Hglm: A package for fitting hierarchical generalized linear models

We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

Final report on heat pump developments in WP 4 - MacSheep Deliverable 4.4 : MacSheep -New Materials and Control for a next generation of compact combined Solar and heat pump systems with boosted energetic and exergetic performance

FP7- MacSheep

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.

Perceptions of Sustainability and Functional Aspects on Liquid Carton Board Packaging Materials versus Competing Materials for Juice Applications in Sweden

This research explores the downstream perceptions of liquid carton board versus competing materials in packaging applications for juice. The methodology used is focus groups. The context is sustainability and functional performance, and related potential implications for the beverage industry value chain. The purpose is to get a deeper insight and understanding of functionality in relation to juice beverage packaging. The results confirm that there is no optimal packaging for every juice product, but a multitude, depending on the distribution channel, retail outlet, customer preferences, and context of consumption. There are some general packaging preferences, but the main deciding criteria for purchase seem to be the product characteristics in terms of quality, taste, brand, price and shelf life. For marketing reasons, packaging has to be adopted to the product and its positioning, liquid carton board packaging seem to have some functional advantages in distribution and is considered as sustainable and functional among many consumers. Major drawbacks seem to be shape limitations, lack of transparency, and lack of a “premium look”. To improve packaging performance and avoid sub-optimization, actors in the beverage industry value chain need to be integrated in development processes.