Optimal design for the connector of bridge prefabricated concrete barriers

The current optimization research on the connectors of prefabricated barriers uses experimental comparisons only and lacks theoretically based optimization methods as guidance. The primary objective of this study was to propose an efficient optimization approach to the connector design of prefabricated bridge barriers. This paper presents an efficient two-stage optimization approach to the connector design of prefabricated bridge barriers. In the first stage, the hybrid cellular automaton algorithm is used to perform dynamic topology optimization on the connector, and the best material distribution in the design domain is obtained. In the second stage, a kriging metamodel and genetic algorithm are combined to further optimize the size of the connector structure. With a prefabricated bridge as the engineering background, finite element models of a barrier system under impact load caused by a car crash were established. The above approach is utilized to optimize the design of the barrier connector. Results showed that the optimized connector structure greatly improved the overall performance of the barrier system while reducing the material consumption and costs. The proposed optimization approach can determine the optimal material distribution and size of the connector structure, thus providing guiding significance for the design and construction of connectors of prefabricated components.

Kriging Metamodel-Based Seismic Fragility Analysis of Single-Bent Reinforced Concrete Highway Bridges

Uncertainty quantification is an important issue in the seismic fragility analysis of bridge type structures. However, the influence of different sources of uncertainty on the seismic fragility of the system is commonly overlooked due to the costly re-evaluation of numerical model simulations. This paper aims to present a framework for the seismic fragility analysis of reinforced concrete highway bridges, where a data-driven metamodel is developed to approximate the structural response to structural and ground motion uncertainties. The proposed framework to generate fragility curves shows its efficiency while using a few finite element simulations and accounting for various modeling uncertainties influencing the bridge seismic fragility. In this respect, a class of single-bent bridges available in the literature is taken as a case study, whose three-dimensional finite element model is established by the OpenSees software framework. Twenty near-source records from different sources are selected and the Latin hypercube method is applied for generating the random samples of modeling and ground motion parameters. The Kriging metamodel is then driven on the structural response obtained from nonlinear time history analyses. Component fragility curves of the reinforced concrete pier column are derived for different damage states using the Kriging metamodel whose parameters are established considering different modeling parameters generated by Monte Carlo simulations. The results demonstrate the efficiency of the proposed framework in interpolating the structural response and deriving the fragility curve of the case study with any input conditions of the random variables.

Simulation-Based Optimization for the Operation of Toll Plaza at Car Park Exit with Mixed Types of Tollbooths and Waiting-Time-Dependent Service

This study presents an approach of simulation-based optimization to the operation of the toll plaza at the car park exit. We first propose a simulation model, as the representation of the queueing system for the toll plaza with mixed-type customers and servers where the service time is dependent on the waiting time of customer. Then, a simulation-based integer programming model is developed to design more traffic-efficient yet cost-effective operation schemes. It is decomposed by a rolling horizon approach into subproblems which are all solved via the Kriging metamodel algorithm. A numerical example is presented to illustrate the model and offer insight on how to achieve traffic efficiency and cost-effectiveness.

Design and CFD Self-Propulsion Analysis of a Ducted Propeller for a DARPA SUBOFF Hull Autonomous Underwater Vehicle

This paper presents the design and the CFD self-propulsion analysis of a ducted propeller to operate in a DARPA SUBOFF hull Autonomous Underwater Vehicle (AUV). The ducted propeller is of the pump jet type with 9 blades at the rotor and 11 blades at the stator. The interactive process of design and optimization uses the potential lifting line theory and CFD RANS analysis for obtaining the self-propulsion point, with the propeller placed behind the AUV hull. During the lifting line design, the rotor diameter, hub diameter, design rotation, blade section chord and length of the duct are modeled by a Kriging Metamodel technique and optimized through random sampling in order to maximize the quasi propulsive coefficient. The optimized configuration from the lifting line and Kriging Metamodel is analyzed using Ansys Fluent 2019 solver. The CFD analysis behind the hull allows including wake effects, thrust deduction factor and viscous effects directly into the model. The lifting line and CFD processes are used interactively to optimize the pitch, the circulation and the camber until the required thrust is achieved.