A recently proposed strain-energy-function for elastomeric materials is discussed, together with ... more A recently proposed strain-energy-function for elastomeric materials is discussed, together with some recent experiments about the entropic nature of rubberlike elasticity.
Computer-Aided Civil and Infrastructure Engineering, 2010
ABSTRACT In this article, an approach is introduced which permits the numerical prediction of fu... more ABSTRACT In this article, an approach is introduced which permits the numerical prediction of future structural responses in dependency of uncertain load processes and environmental influences. The approach is based on recurrent neural networks trained by time-dependent measurement results. Thereby, the uncertainty of the measurement results is modeled as fuzzy processes which are considered within the recurrent neural network approach. An efficient solution for network training and prediction is developed utilizing α-cuts and interval arithmetic. The capability of the approach is demonstrated by means of the prediction of the long-term structural behavior of a reinforced concrete plate strengthened by a textile reinforced concrete layer.
A recently proposed strain-energy-function for elastomeric materials is discussed, together with ... more A recently proposed strain-energy-function for elastomeric materials is discussed, together with some recent experiments about the entropic nature of rubberlike elasticity.
Computer-Aided Civil and Infrastructure Engineering, 2010
ABSTRACT In this article, an approach is introduced which permits the numerical prediction of fu... more ABSTRACT In this article, an approach is introduced which permits the numerical prediction of future structural responses in dependency of uncertain load processes and environmental influences. The approach is based on recurrent neural networks trained by time-dependent measurement results. Thereby, the uncertainty of the measurement results is modeled as fuzzy processes which are considered within the recurrent neural network approach. An efficient solution for network training and prediction is developed utilizing α-cuts and interval arithmetic. The capability of the approach is demonstrated by means of the prediction of the long-term structural behavior of a reinforced concrete plate strengthened by a textile reinforced concrete layer.
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