Mathematical Geosciences - Quantitative evaluation of fracability is essential for hydraulic fracturing design, with the distribution of in situ stress being a key parameter. This study focused on... 相似文献
It is known that a lot of uncertainties are involved in geotechnical design of energy piles. In this paper, a Bayesian updating framework is presented to characterize those uncertainties. The load-transfer model is developed to predict the thermomechanical response of energy piles. Considering the cross-case variability of the uncertainty in the axial strains of pile, the global model bias is firstly calibrated by establishing a comprehensive database consisting of 12 energy pile cases. Furthermore, the uncertainty in input parameters is considered in the Bayesian updating of model bias in a specific case. The variability of the uncertain parameters is effectively reduced after updating. The coefficient of variation of prediction is decreased from 0.34 to 0.13. The present framework can well quantify uncertain factors and improve the accuracy and reliability of the prediction model.
Natural Hazards - The U.S. 2020 hurricane season was extraordinary because of a record number of named storms coinciding with the COVID-19 pandemic. This study draws lessons on how individual... 相似文献
Natural Hazards - Jakarta is vulnerable to flooding and extreme rainfall events are always the main cause of the occurrence of heavy flood events with loss of life and property. The flood in... 相似文献