A Comprehensive Database Of Tests On Axially Loaded Piles Driven In Sand

A Comprehensive Database of Tests on Axially Loaded Piles Driven in Sand

A Comprehensive Database of Tests on Axially Loaded Piles Driven in Sand

A Comprehensive Database of Tests on Axially Loaded Driven Piles in Sands reviews the critical need to develop better load-test databases for piles driven in sands. The key quality parameters, population of current entries and reporting formats are described before offering preliminary results obtained from comparisons between axial capacities calculated by various predictive approaches and site measurements. This book also shows that the "simplified" and "offshore" ICP and UWA variants proposed by some practitioners are over-conservative and that their use could be discontinued. The new pile capacity and stiffness database offers a broad scope for evaluating potential prediction biases relating to a wide range of soil and pile parameters. Submission of further high quality tests for inclusion in regularly updated versions is encouraged. - Presents a comprehensive and updated database for piles driven in predominantly silica sands - Features reviews of the design procedures for driven piles in sand - Assesses the performance of various mainstreams design procedures applied for piles driven in sand - Provides comprehensive information of case histories of pile load tests

Model Uncertainties in Foundation Design

Model Uncertainties in Foundation Design is unique in the compilation of the largest and the most diverse load test databases to date, covering many foundation types (shallow foundations, spudcans, driven piles, drilled shafts, rock sockets and helical piles) and a wide range of ground conditions (soil to soft rock). All databases with names prefixed by NUS are available upon request. This book presents a comprehensive evaluation of the model factor mean (bias) and coefficient of variation (COV) for ultimate and serviceability limit state based on these databases. These statistics can be used directly for AASHTO LRFD calibration. Besides load test databases, performance databases for other geo-structures and their model factor statistics are provided. Based on this extensive literature survey, a practical three-tier scheme for classifying the model uncertainty of geo-structures according to the model factor mean and COV is proposed. This empirically grounded scheme can underpin the calibration of resistance factors as a function of the degree of understanding – a concept already adopted in the Canadian Highway Bridge Design Code and being considered for the new draft for Eurocode 7 Part 1 (EN 1997-1:202x). The helical pile research in Chapter 7 was recognised by the 2020 ASCE Norman Medal.