Numerical simulation of Zn coating solidification

A numerical model, which simulates nucleation and growth of Zn grains, has been developed in order to describe quantitatively the solidification of Zn coatings during the hot-dipping process. The inputs of the model are the nucleation distribution, which has been measured by electron backscattered diffraction (EBSD), and the dendritic growth kinetics, calculated with an analytical model of a parabolic dendrite tip modified to account for the interactions with the coating interfaces. The model predicts the shapes of the grain envelopes as a function of the grain orientation and the texture induced by growth. Three types of grain envelopes have been evidenced, depending on the angle between the c-axis and the normal to the coating plane. Moreover, it has been shown that growth reinforces the already existing {00.1} nucleation texture, in good agreement with experimental data. The model also predicts the cooling curve, including recalescence, and the grain size. Thus, it is used to describe the effects of Pb additions on solidification. In particular, it has been shown that Pb increases the nucleation undercooling and strongly decreases the density of active nuclei, thus resulting in a much larger grain size.     

Determination du coefficient d'extinction molaire de OH− dans les verres fluores a base de metaux lourds

The extinction coefficient ? at 2.9 μm for OH in fluoride glasses is measured by determining the amount of HF evolved during heating of the glass under steam and the corresponding intensity of the OH absorption band. This coefficient is respectively equal to 31 litre mole^?1 cm^?1 for BTYbZ glass (15 BaF₂ - 29 ThF₄ - 28 YbF₃ - 28 ZnF₂) and 19.5 litre mole^?1 cm^?1 for BALLA glass (34 BaF₂ - 57 ZrF₄ - 4 AlF₃ - 5 LaF₃).     

Epidemiology of Trauma and Posttraumatic Stress Disorder in Mexico.

Prevalence rates of trauma and posttraumatic stress disorder (PTSD) were estimated from a probability sample of 2,509 adults from 4 cities in Mexico. PTSD was assessed according to Diagnostic and Statistical Manual of Mental Disorders (American Psychiatric Association, 1994) criteria using the Composite International Diagnostic Interview (CIDI; WHO, 1997). Lifetime prevalence of exposure and PTSD were 76% and 11.2%, respectively. Risk for PTSD was highest in Oaxaca (the poorest city), persons of lower socioeconomic status, and women. Conditional risk for PTSD was highest following sexual violence, but nonsexual violence and traumatic bereavement had greater overall impact because of their frequency. Of lifetime cases, 62% became chronic; only 42% received medical or professional care. The research demonstrates the importance of expanding the epidemiologic research base on trauma to include developing countries around the world. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Revising deductive knowledge and stereotypical knowledge in a student model

A user/student model must be revised when new information about the user/student is obtained. But a sophisticated user/student model is a complex structure that contains different types of knowledge. Different techniques may be needed for revising different types of knowledge. This paper presents a student model maintenance system (SMMS) which deals with revision of two important types of knowledge in student models: deductive knowledge and stereotypical knowledge. In the SMMS, deductive knowledge is represented by justified beliefs. Its revision is accomplished by a combination of techniques involving reason maintenance and formal diagnosis. Stereotypical knowledge is represented in the Default Package Network (DPN). The DPN is a knowledge partitioning hierarchy in which each node contains concepts in a sub-domain. Revision of stereotypical knowledge is realized by propagating new information through the DPN to change default packages (stereotypes) of the nodes in the DPN. A revision of deductive knowledge may trigger a revision of stereotypical knowledge, which results in a desirable student model in which the two types of knowledge exist harmoniously.     

Le décodage pondere en tant que procédé de réévaluation d’une distribution de probabilité

We propose to redefine weighted decoding of a redundant code as consisting of reestimating a given prior probability distribution in order to take into account the code constraints. The optimum solution of this problem results from using the « minimum cross-entropy » principle and is shown to coincide with the computation of the probabilities to be compared in order to perform maximum likelihood decoding when the prior distribution is exactly known. The principle however also holds when the prior distribution is approximate or biased, which explains the robustness of decoding with respect to weighting information. Such a redefinition also enables using the intermediate steps of decoding, in the case of codes associated by concatenation or product, as a source of weighting information for the subsequent steps. One is led for simplicity’s sake to an estimate of the posterior probability in separable form with respect to the information symbols ; its definition is given and certain of its applications are discussed.     

Dynamical modelling of an activated sludge system of a petrochemical plant operating at high temperatures.

The Mexican petrochemical industry, Morelos S.A. de C.V., is one of the biggest and more important petroleum industries in Mexico and Latin America. It has an activated sludge system to treat its wastewater flow, which is approximately 7,000 m3/d. The wastewater contains volatile organic carbon substances classified as toxics. The old surface aeration system was changed for fine bubble diffusers; however, one major drawback of the new aeration system is that the temperature in the bioreactor has increased due to the compression of the air, which at the compressor exit reaches 85 degrees C. This effect results in the temperature in the bioreactor attaining 32 degrees C during the fall, whereas in the spring and summer, the bioreactor temperature reaches higher values than 40 degrees C. The high temperatures reduce the microorganism activity and cause a higher volatilisation rate of volatile compounds, among other effects, which affect the performance of the biological treatment. This work was performed to obtain a better modelling of the wastewater treatment from the petrochemical industry. The model describes the effect of the temperature on the performance of the biological treatment. The model was obtained from tests that were carried out in laboratory reactors with 14 L capacity, which were operated at different temperatures (from 30 to 45 degrees C), with the same wastewater and conditions as the actual system.     

Decision Making Effectiveness in Wildfire Incident Management Teams

During large scale wildfires, suppression activities are carried out under the direction of an Incident Management Team (IMT). The aim of the research was to increase understanding of decision processes potentially related to IMT effectiveness. An IMT comprises four major functions: Command, Operations, Planning, and Logistics. Four methodologies were used to study IMT processes: computer simulation experiments; analyses of wildfire reports; interviews with IMT members; and cognitive ethnographic studies of IMTs. Three processes were important determinants of IMT effectiveness: information management and cognitive overload; matching component function goals to overall goals; and team metacognition to detect and counter task‐disruptive developments. These processes appear to be complex multi‐person analogues of individual Incident Command processes identified previously. The findings have implications for issues such as: creating IMTs; training IMTs; managing IMTs; and providing decision support to IMTs.