Prediction of atmospheric corrosion of carbon steel using artificial neural network model in local geographical regions (Record no. 183188)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01695nab a2200205 4500 |
| 008 - CÓDIGOS DE INFORMACIÓN DE LONGITUD FIJA - INFORMACIÓN GENERAL | |
| Campo de control de longitud fija | 260224s2011 xxu |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Halama, M. |
| 9 (RLIN) | 50497 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Kreislova, K. |
| 9 (RLIN) | 50498 |
| 100 1# - RESPONSABLE PERSONAL | |
| Apellido, Nombre | Van Lysebettens, J. |
| 9 (RLIN) | 50499 |
| 245 00 - TITULO | |
| Título | Prediction of atmospheric corrosion of carbon steel using artificial neural network model in local geographical regions |
| 260 ## - PUBLICACION, DISTRIBUCION, ETC | |
| Fecha de publicación, distribución, etc. | jun. 2011 |
| 270 ## - FECHA DE CARGA | |
| Fecha de carga | 27/06/2011 ; 27/06/2011 |
| 300 ## - DESCRIPCION FISICA | |
| Otra extensión | 6 p. ; 065004 |
| 520 ## - RESUMEN, ETC | |
| Resumen | Transcripción del resumen del autor. Atmospheric corrosion of metals is a complex, nonlinear process. It involves a large number of interacting and varying factors governed by material composition, form, size, testing procedure, location of exposure, and type of application. Possible environmental factors include temperature, relative humidity, wet-dry patterns, hours of sunshine, pH of rainfall, amount of precipitation, concentration of main pollutants, etc. All factors are apart of the variables in artificial neural network (ANN) modeling. The most important variables are chosen from long-term experiences as elements in the development of a prototype "artificial intelligent sensor"'a model designed for the assessment of atmospheric corrosion of carbon steel under local geographical conditions. The variable impact analysis and 2D maps gave accurate prediction of the atmospheric corrosion of carbon steel. Future climatic scenarios, mainly the calculation of mass losses under different simulated concentrations of sulfur dioxide (SO2) during exposure time, are presented. |
| 581 ## - ESTADO DE COLECCIÓN | |
| Estado de colección | 6 |
| 773 0# - CORRECCIÓN | |
| Título | Corrosion |
| Partes relacionadas | 67 |
| 942 ## - DESC. DE MATERIAL | |
| Tipo de item KOHA | Artículo de Revista |
| Fuente de clasificación | Dewey Decimal Classification |
| Biblioteca propietaria | Biblioteca actual | Fecha de adquisición | Inventario | Total de préstamos | Inventario | Fecha de carga | Tipo de item KOHA |
|---|---|---|---|---|---|---|---|
| Biblioteca Alejandro Angel Bulgheroni | Biblioteca Alejandro Angel Bulgheroni | 05/03/2026 | 200055236 | 200055236 | 05/03/2026 | Artículo de Revista |
