Cloud-Verhulst hybrid prediction model for dam deformation under uncertain conditions

Uncertainties existing in the process of dam deformation negatively influence deformation prediction. However, existing deformation pre- diction models seldom consider uncertainties. In this study, a cloud-Verhulst hybrid prediction model was established by combing a cloud model with the Verhulst model. The expectation, one of the cloud characteristic parameters, was obtained using the Verhulst model, and the other two cloud characteristic parameters, entropy and hyper-entropy, were calculated by introducing inertia weight. The hybrid prediction model was used to predict the dam deformation in a hydroelectric project. Comparison of the prediction results of the hybrid prediction model with those of a traditional statistical model and the monitoring values shows that the proposed model has higher prediction accuracy than the traditional sta- tistical model. It provides a new approach to predicting dam deformation under uncertain conditions.

Analysis method of thermal dam deformation

Based on the internal temperature variation of a dam lagging behind the ambient temperature variation,the ambient temperature of continuous variation is disctetized,and the functional expression of the thermal displacement component of the dam caused by single instantaneous temperature variation is obtained.Considering the temporal and spatial distribution law of the ambient temperature and its relation with air and water temperature,the function is expanded into a Taylor series.As a result,the improved thermal displacement component expression for a dam monitoring model is obtained.