A neural network for error prediction in a true triaxial apparatus with flexible boundaries

✍ Scribed by L. Dihoru; D. Muir Wood; T. Sadek; M. Lings

• Publisher: Elsevier Science
• Year: 2005
• Tongue: English
• Weight: 1016 KB
• Volume: 32
• Category: Article
• ISSN: 0266-352X
• DOI: 10.1016/j.compgeo.2005.01.003

✦ Synopsis

The true triaxial apparatus with flexible boundaries (TTAF) is a versatile tool for characterizing the stress-strain behaviour of soils. The evaluation of the deformations suffered by soil in a TTAF must account for the effects of the sample membrane and of the pressurizing cushion, the non-uniform spatial stiffness of the frame of the apparatus, and the electronic errors. In order to overcome the difficulty associated with such a complex set of factors of influence, a neural network (NN) approach was used to predict the errors that may affect the displacements. The current performance of the prediction system is reported.