Estimation of heat flux distribution in a continuous casting mould by inverse heat transfer algorithms - Paper No. DETC2011-47435

In the continuous casting process of steel, the control of the mould heat removal is a key parameter, since it directly affects the shell growth and the stresses and strains that are produced in the mould. An inverse heat conduction model was developed to calculate mould heat transfer from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain; the 2D geometry concerns only a longitudinal section of the mould, while in the 3D domain a whole face is considered. The inverse problem was solved using a Conjugate Gradient algorithm, a Genetic Algorithm and the Nelder - Mear SIMPLEX algorithm. For the 3D geometry, the heat flux profile calculated at the axis of the face is close to that obtained from the 2D model, although the former is slightly lower. For both geometries, there is a good agreement between numerical and experimental temperatures. Moreover, the 3D model provides a better estimate of the outlet water temperature

Heat Flux Estimation in a Continuous Casting Mould by Inverse Heat Transfer Algorithms

Inverse Heat Transfer Problems rely on temperature measurements for the estimation of unknown quantities (e.g. boundary or initial conditions, thermophysical properties); this kind of problems is classified as ill-posed. An application of the inverse analysis in the continuous casting process of steel is here presented. The aim is the estimation of the mould heat transfer starting from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain. The inverse problem was solved using Gradient algorithms, Genetic Algorithms and SIMPLEX. For both geometries, a good agreement between numerical and experimental temperature values is observed; moreover, the 3D model provides a better estimate of the outlet temperature of the cooling water

Estimation of Heat Flux Distribution in a Continuous Casting Mould by Inverse Heat Transfer Algorithms

Inverse Heat Transfer Problems rely on temperature measurements for the estimation of unknown quantities (e.g. boundary or initial conditions, thermophysical properties); this kind of problems is classified as ill-posed. An application of the inverse analysis in the continuous casting process of steel is here presented. The aim is the estimation of the mould heat transfer starting from temperature measurements, recorded using thermocouples buried inside the copper mould wall. The mould is water-cooled to solidify the hot metal directly in contact with it. The direct stationary conduction problem was solved both on a 2D and a 3D domain. The inverse problem was solved using Gradient algorithms, Genetic Algorithms and SIMPLEX. For both geometries, a good agreement between numerical and experimental temperature values is observed; moreover, the 3D model provides a better estimate of the outlet temperature of the cooling water

Inverse relationship between scores on the quality of lie questionnaire SF-12 and on the Aging Males

Objectives. To analyse the relation between results of the Aging Males' Symptoms (AMS) questionnaire for aging males, and of quality of life (QOL) questionnaire SF-12 and cardiovascular risk factors. Methods. 1,927 men aged 55-85 years were interviewed by 56 general practitioners. During the interview the men were asked to fill in the AMS scale and the QOL questionnaire SF-12. Results. Of 1,927 men 1,806 men filled correctly the AMS questionnaire. The mean SF-12 mental index was respectively 55.9 in men with a total AMS score indicating no impairment, 50.9 mild, 42.8 moderate, and 32.8 severe impairment. The corresponding values for the physical index were 51.2, 46.7, 40.8 and 32.3. A history of diabetes was associated with an increased risk of reporting moderate/severe impairment: in relation to the total AMS score the odds ratio, (OR), of moderate/severe impairment in comparison with no impairment was 1.6 (95%CI 1.2-2.1). A history of myocardial infarction and hypertension increased the risk (respectively OR 1.4 (95%CI 1.1-18) and 1.7 (95%CI 1.2-2.4)). Conclusions. This study shows that higher AMS scores are associated with lower SF-12 indices and suggests that elevated values of the AMS score are associated with cardiovascular risk factors or diseases