Condition assessment of concrete dams in cold climate

Sammanfattning: Dams in many countries are approaching their expected service life. Proper assessment of the aging dams structural health increase the knowledge of the current safety, and allow for better planning of renovation and rebuilding investments. The behavior of concrete dams is, to a great extent, governed by the ambient variation in temperature and water level. In cold regions, the ice sheet formed in the reservoir may subject a pressure load on the dams. Theoretically, this load has a significant impact on the structural behavior of dams. Despite this, the maximum magnitude, as well as the seasonal variation of the ice load, constitute the most considerable uncertainty in the safety assessment of dams.This thesis presents research that examines how to model the expected behavior of dams in cold climate. The underlying problem is to predict the response of dams due to variation in the external conditions. Since the ice load is such a vital part of the external conditions in cold climate, the understanding and modeling of ice loads have been given extra attention. Models suitable to predict the long-term behavior of dams can be divided between theoretical, data-based, and hybrid. Prediction accuracy is essential to set alert thresholds, and in that regard, the data-based models are generally superior.The major contribution of this thesis is the design and installation of a prototype ice load panel with direct measurement of the ice pressure acting on a dam. The panel is attached on the upstream face of the dam and is large enough so that the whole thickness of the ice sheet is in contact with the panel. The predicted ice load from the best available model that includes loads from both thermal events and water level changes did not correspond to the measured ice loads. As there are no validated models or measurement methods for ice load on the dam, continued research is necessary, both through further measurements to increase knowledge and development of models.