Info!
UPDATED 1 Sept: The EI library in London is temporarily closed to the public, as a precautionary measure in light of the ongoing COVID-19 situation. The Knowledge Service will still be answering email queries via email , or via live chats during working hours (09:15-17:00 GMT). Our e-library is always open for members here: eLibrary , for full-text access to over 200 e-books and millions of articles. Thank you for your patience.
UPDATED 1 Sept: The EI library in London is temporarily closed to the public, as a precautionary measure in light of the ongoing COVID-19 situation. The Knowledge Service will still be answering email queries via email , or via live chats during working hours (09:15-17:00 GMT). Our e-library is always open for members here: eLibrary , for full-text access to over 200 e-books and millions of articles. Thank you for your patience.
Artificial neural network technology as a method to evaluate the fatigue life of weldments with welding defects. Y.-L. Han. Internat. J. Pressure Vessels Piping, 1995, 63(2), 205--209.
Neural network architecture and algorithm are described. Application of this technology to the fatigue life of weldments with welding defects is reported and this example shows the feasibility that the neural network can be used to predict the fatigue life of a welding specimen with welding defects. Tabulated experimental data are presented and discussed. 3 refs.
Abstract details
Journal title: International Journal of Pressure Vessels and Piping
Keywords: Computer applications
Subjects: Information technology, Boilermaking and Welding, Architecture, Oil and gas, Oil, Wave power
