Search

The reliability of long-term axial capacity predictions for large, offshore-scale, piles is uncertain. Current databases of static load tests include very few entries with diameters ≥ 1m, and none >2m. Also, most of the available tests were conducted at relatively early ages after driving. The PAGE Joint Industry Project addressed this knowledge gap by collating and analysing dynamic driving data from 25 offshore piles with 1.6 to 3.4m outside diameters and contrasting these with dynamic re-strike tests conducted between 1h and 1 year after driving. Systematic signal matching was performed with two independent codes that applied different soil models and the outcomes were compared with predictions from modern CPT-based static capacity design methods. Additional supporting analyses were performed on other piles, where static and dynamic tests had been conducted, to help assess the relationships between statically and dynamically measured resistances. Piles with 0.3 to 3.5m outside diameters followed broadly common trends over the first 30 days after driving, with shaft capacities approximately doubling. While smaller ( at onshore/nearshore sites display marked further capacity growth, larger offshore piles showed little additional capacity gain after 30 days. The CPT-based Unified offshore pile design method offered conservative predictions for long-term shaft resistance, while no bias was apparent with the ICP-05 approach. An inverse relationship was identified between long-term shaft setup and diameter, which is ascribed to enhanced dilatancy applying at the pile-sand interface. The base capacities interpreted from dynamic analyses consistently fell far below the monotonic loading capacities predicted by current design methods and showed no significant trend to increase over time.

Based on the Driver-Pressure-State-Impact-Response (DPSIR) framework, this paper constructs the input, expected output, and unexpected output of China's sustainable development. This paper calculates the sustainable development efficiency of 31 provinces and cities in China using a super-slack-based measure (SBM) model that eliminates the influence of scale factors through a three-stage data envelope analysis (DEA) approach. Taking the level of science and technology as the control variable, and the relative scale efficiency as the threshold variable, this paper calculates the effects of the absolute scale of labor force, education, economy, enterprise, and transportation on sustainable development efficiency. The results show that: (1) there is an upward trajectory for sustainable development efficiency of China's provinces and municipalities overall from 0.65 in 2004 to 0.68 in 2017, with significant regional differences in which the ecological efficiency in the Eastern region is 0.26 higher than that of the Central region, (2) it enhances the absolute scale of the labor force, education, and transportation, in order to reduce the inhibition on sustainable development efficiency, and (3) shifts our attention to the promotion of absolute economic scale to the promotion of green economic development, and increases control of polluting enterprises.