• Geomechanics and Engineering
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• 제27권6호
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• pp.561-571
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• 2021

Cofferdams made of teel sheet piles are commonly utilized as support structures for excavation of sea-crossing bridge foundations. As cofferdams are often subject to tide variation, it is imperative to consider potential effects of tide on stability and serviceability of sheet piles, particularly, ultralong steel sheet piles (USSPs). In this study, a real USSP cofferdam constructed using new construction technology in Nanxi River was reported. The design of key parts of USSP cofferdam in the presence of tidal action was first introduced followed by the description of entire construction technology and associated monitoring results. Subsequently, a three-dimensional finite-element model corresponding to all construction steps was established to back-analyze measured deflection of USSPs. Finally, a series of parametric studies was carried out to investigate effects of tide level, soil parameters, support stiffness and construction sequence on lateral deflection of USSPs. Monitoring results indicate that the maximum deflection during construction occurred near the riverbed. In addition, measured stress of USSPs showed that stability of USSP cofferdam strengthened as construction stages proceeded. Moreover, the numerical back-analysis demonstrated that the USSP cofferdam fulfilled the safety requirements for construction under tidal action. The maximum deflection of USSPs subject to high tide was only 13.57 mm at a depth of -4 m. Sensitivity analyses results showed that the design of USSP cofferdam system must be further improved for construction in cohesionless soils. Furthermore, the 5th strut level before concreting played an indispensable role in controlling lateral deflection of USSPs. It was also observed that pumping out water before concreting base slab could greatly simplify and benefit construction program. On the other hand, the simplification in construction procedures could induce seepage inside the cofferdam, which additionally increased the deflection of USSPs by 10 mm on average.

• Smart Structures and Systems
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• 제31권3호
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.