Inicio  /  Nauka ta Progres Transportu  /  Núm: 33 Par: 0 (2010)  /  Artículo
ARTÍCULO
TITULO

THE ESTIMATION OF DEVELOPMENT SELF -CONSISTENT DAMAGES OF SLIMY STEEL CONSTRUCTIONS

V. R. Skalskiy    
D. V. Rudavskiy    
P. Ya. Galan    
I. M. Lyasota    
P. P. Velikiy    
Ya. D. Tolopko    

Resumen

The procedure for testing the prismatic steel specimens of heavy constructions to build the kinetic diagrams of fatigue fracture is described in the paper. The kinetic diagrams obtained have been approximated by analytical dependences with unknown parameters, which were found using least squares method.

 Artículos similares

       
 
Eduard Angelats, Alban Gorreja, Pedro F. Espín-López, M. Eulàlia Parés, Eva Savina Malinverni and Roberto Pierdicca    
The seamless integration of indoor and outdoor positioning has gained considerable attention due to its practical implications in various fields. This paper presents an innovative approach aimed at detecting and delineating outdoor, indoor, and transitio... ver más

 
Xie Lian, Xiaolong Hu, Liangsheng Shi, Jinhua Shao, Jiang Bian and Yuanlai Cui    
The parameters of the GR4J-CemaNeige coupling model (GR4neige) are typically treated as constants. However, the maximum capacity of the production store (parX1) exhibits time-varying characteristics due to climate variability and vegetation coverage chan... ver más
Revista: Water

 
Flavia D. Frederick, Malvin S. Marlim and Doosun Kang    
Chlorine decay over time and distance travelled poses challenges in maintaining consistent chlorine levels from treatment plants to demand nodes in water distribution networks (WDNs). Many studies have focused on optimizing chlorine booster systems and a... ver más
Revista: Water

 
Suiji Wang    
An anastomosing river is a stable multiple-channel system separated by inter-channel wetlands, and there are serious difficulties in observing the hydrodynamics of such river patterns in situ. Therefore, there are few reports on the hydrodynamic data of ... ver más
Revista: Water

 
Beata Baziak, Marek Bodziony and Robert Szczepanek    
Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimat... ver más
Revista: Hydrology