A study of slag corrosion of oxides and oxide-carbon refractories during steel refining

The use of ceramic material as refractories in the manufacturing industry is a common practice worldwide. During usage, for example in the production of steel, these materials do experience severe working conditions including high temperatures, low pressures and corrosive environments. This results in lowered service lives and high consumptions of these materials. This, in turn, affects the productivity of the whole steel plant and thereby the cost. In order to investigate how the service life can be improved, studies have been carried out for refractories used in the inner lining of the steel ladles. More specifically, from the slag zone, where the corrosion is most severe. By combining thermodynamic simulations, plant trails and post-mortem studies of the refractories after service, vital information about the behaviour of the slagline refractories during steel refining and the causes of the accelerated wear in this ladle area has been achieved. The results from these studies show that the wear of the slagline refractories of the ladle is initiated at the preheating station, through reduction-oxidation reactions. The degree of the decarburization process is mostly dependent on the preheating fuel or the environment. For refractories without antioxidants, refractory decarburization is slower when coal gas is used in ladle preheating than when a mixture of oil and air is used. In addition, ladle preheating of the refractories without antioxidants leads to direct wear of the slagline refractories. This is due to the total loss of the matrix strength, which results in a sand-like product. Thermal chemical changes that take place in the slagline refractories are due to the MgO-C reaction as well as the formation of liquid phases from impurity oxides. In addition, the decrease in the system pressure during steel refining makes the MgO-C reaction take place at the steel refining temperatures. This reduces the refractory’s resistance to corrosion. This is a serious problem for both the magnesia-carbon and dolomite-carbon refractories. The studies of the reactions between the slagline refractories and the different slag compositions showed that slags rich in iron oxide lead mostly to the oxidation of carbon/graphite in the carbon-containing refractories. This leads to an increased porosity and wettability and therefore an enhanced penetration of slag into the refractory structure. If the slag contains high contents of alumina and or silica (such as the steel refining slag), reactions between the slag components and the dolomite-carbon refractory are promoted. This leads to the formation of low-temperature melting phases such as calcium-aluminates and silicates. The state of these reaction products during steel refining leads to an accelerated wear of the dolomite-carbon refractory. The main products of the reactions between the magnesia-carbon refractory and the steel refining slag are MgAl2O4 spinels, and calcium-aluminates, and silicates. Due to the good refractory properties of MgAl2O4 spinels, the slag corrosion resistance of the magnesiacarbon refractory is promoted.

Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups

This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

Likelihood prediction for generalized linear mixed models under covariate uncertainty

This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles : a simulation study

Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

The fall descriptions and health characteristics of older adults with hip fracture : a mixed methods study

Background: In light of the multifactorial etiology of fall-related hip fracture, knowledge of fall circumstances may be especially valuable when placed in the context of the health of the person who falls. We aimed to investigate the circumstances surrounding fall-related hip fractures and to describe fall circumstances in relation to participants' health and functional characteristics. Methods: The fall circumstances of 125 individuals (age >= 50 years) with hip fracture were investigated using semi-structured interviews. Data concerning participants' health (comorbidities and medications) and function (self-reported performance of mobility, balance, personal activities of daily living and physical activity, previous falls and hand grip strength) were collected via medical records, questionnaires and dynamometry. Using a mixed methods design, both data sets were analysed separately and then merged in order to provide a comprehensive description of fall events and identify eventual patterns in the data. Results: Fall circumstances were described as i) Activity at the time of the fall: Positional change (n = 24, 19%); Standing (n = 16, 13%); Walking (n = 71, 57%); Balance challenging (n = 14, 11%) and ii) Nature of the fall: Environmental (n = 32, 26%); Physiological (n = 35, 28%); Activity-related indoor (n = 8, 6%) and outdoor (n = 8, 6%); Trips and slips on snow (n = 20, 16%) and in snow-free conditions (n = 12, 10%) and Unknown (n = 10, 8%). We observed the following patterns regarding fall circumstances and participants' health: those who fell i) during positional change had the poorest functional status; ii) due to environmental reasons (indoors) had moderate physical function, but high levels of comorbidity and fall risk increasing medications; iii) in snow-free environments (outdoors) appeared to have a poorer health and functional status than other outdoor groups. Conclusions: Our findings indicate that patterns exist in relation to the falls circumstances and health characteristics of people with hip fracture which build upon that previously reported. These patterns, when verified, can provide useful information as to the ways in which fall prevention strategies can be tailored to individuals of varying levels of health and function who are at risk for falls and hip fracture.