scholarly journals Improving the Drive-by Bridge Inspection Performance by Vehicle Parameter Optimization

Abstract. Recently, there has been an increasing emphasis in the Indirect bridge health monitoring method employing passing vehicles, which is regarded as one of the most effective approaches in bridge damage screening. However, few researches have been conducted on the Drive-by bridge inspection method using vehicle displacement profile as damage indicator due to the challenges in displacement measurement and result accuracy. This paper proposes an optimization approach of designing the optimum vehicle parameters to improve the performance of vehicle displacement-based Drive-by bridge damage inspection. A generalized Vehicle-Bridge Interaction (VBI) system is built in MATLAB, where the bridge is modelled as a simply supported beam with 10 elements and the passing vehicle is represented as a simplified quarter car. Employing the Monte Carlo methods, the optimum parameters are determined by numerous simulations processed under diverse damage scenarios. Results show that by employing the optimal vehicle parameters, the bridge damages can be detected effectively and accurately for general damage scenarios based on the vehicle displacement profile. The proposed optimization method can contribute to the wide application of vehicle displacement-based Drive-by bridge damage inspection, providing merits in simplicity and visualization.

2021 ◽  
Vol 9 (4B) ◽  
Author(s):  
Yifu Lan ◽  

Recently, there has been an increasing emphasis on the Indirect bridge health monitoring method employing passing vehicles, which is regarded as one of the most effective approaches in bridge damage screening. However,few researches have been conducted on the drive-by bridge inspection method using vehicle displacement profile as damage indicator. This paper proposes a new drive-by inspection method based on vertical vehicle displacementprofile with parameter optimization. A generalized Vehicle-Bridge Interaction (VBI) system is built in MATLAB, where the bridge is modelled as a simply supported beam with 10 elements, and the passing vehicle is represented as a simplified quarter car. To improve the result sensitivity to bridge damage, the parameter optimization of vehicle configuration is processed employing the Monte Carlo methods. Results show that the proposed method can successfully detect and localize bridge damage by using vertical vehicle displacement profile as damage indicator only, and its performance may depend on the vehicle configuration. The proposed approach provides merits in simplicity and efficiency, which can be applied widely to the bridge damage detection problems.


10.29007/zw9k ◽  
2020 ◽  
Author(s):  
Kazuhide Nakata ◽  
Kazuki Umemoto ◽  
Kenji Kaneko ◽  
Ryusuke Fujisawa

This study addresses the development of a robot for inspection of old bridges. By suspending the robot with a wire and controlling the wire length, the movement of the robot is realized. The robot mounts a high-definition camera and aims to detect cracks on the concrete surface of the bridge using this camera. An inspection method using an unmanned aerial vehicle (UAV) has been proposed. Compared to the method using an unmanned aerial vehicle, the wire suspended robot system has the advantage of insensitivity to wind and ability to carry heavy equipments, this makes it possible to install a high-definition camera and a cleaning function to find cracks that are difficult to detect due to dirt.


2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.


2016 ◽  
Vol 19 (1) ◽  
pp. 115-122 ◽  
Author(s):  
Milan Cisty ◽  
Zbynek Bajtek ◽  
Lubomir Celar

In this work, an optimal design of a water distribution network is proposed for large irrigation networks. The proposed approach is built upon an existing optimization method (NSGA-II), but the authors are proposing its effective application in a new two-step optimization process. The aim of the paper is to demonstrate that not only is the choice of method important for obtaining good optimization results, but also how that method is applied. The proposed methodology utilizes as its most important feature the ensemble approach, in which more optimization runs cooperate and are used together. The authors assume that the main problem in finding the optimal solution for a water distribution optimization problem is the very large size of the search space in which the optimal solution should be found. In the proposed method, a reduction of the search space is suggested, so the final solution is thus easier to find and offers greater guarantees of accuracy (closeness to the global optimum). The method has been successfully tested on a large benchmark irrigation network.


Author(s):  
Lifang Zeng ◽  
Dingyi Pan ◽  
Shangjun Ye ◽  
Xueming Shao

A fast multiobjective optimization method for S-duct scoop inlets considering both inflow and outflow is developed and validated. To reduce computation consumption of optimization, a simplified efficient model is proposed, in which only inflow region is simulated. Inlet pressure boundary condition of the efficient model is specified by solving an integral model with both inflow and outflow. An automated optimization system integrating the computational fluid dynamics analysis, nonuniform rational B-spline geometric representation technique, and nondominated sorting genetic algorithm II is developed to minimize the total pressure loss and distortion at the exit of diffuser. Flow field is numerically simulated by solving the Reynolds-averaged Navier–Stokes equation coupled with k–ω shear stress transport turbulence model, and results are validated to agree well with previous experiment. S-duct centreline shape and cross-sectional area distribution are parameterized as the design variables. By analyzing the results of a suggested optimal inlet chosen from the obtained Pareto front, total pressure recovery has increased from 97% to 97.4%, and total pressure distortion DC60 has decreased by 0.0477 (21.7% of the origin) at designed Mach number 0.7. The simplified efficient model has been validated to be reliable, and by which the time cost for the optimization project has been reduced by 70%.


2019 ◽  
Vol 32 (1) ◽  
pp. 59-70 ◽  
Author(s):  
Yu-Li Huang ◽  
Sarah M. Bach ◽  
Sherry A. Looker

Purpose The purpose of this paper is to develop a chemotherapy scheduling template that accounts for nurse resource availability and patient treatment needs to alleviate the mid-day patient load and provide quality services for patients. Design/methodology/approach Owing to treatment complexity in chemotherapy administration, nurses are required at the beginning, end and during treatment. When nurses are not available to continue treatment, the service is compromised, and the resource constraint is violated, which leads to inevitable delay that risks service quality. Consequently, an optimization method is used to create a scheduling template that minimizes the violation between resource assignment and treatment requirements, while leveling patient load throughout a day. A case study from a typical clinic day is presented to understand current scheduling issues, describe nursing resource constraints, and develop a constraint-based optimization model and leveling algorithm for the final template. Findings The approach is expected to reduce the variation in the system by 24 percent and result in five fewer chemo chairs used during peak hours. Adjusting staffing levels could further reduce resource constraint violations and more savings on chair occupancy. The actual implementation results indicate a 33 percent reduction on resource constraint violations and positive feedback from nursing staff for workload. Research limitations/implications Other delays, including laboratory test, physician visit and treatment assignment, are potential research areas. Originality/value The study demonstrates significant improvement in mid-day patient load and meeting treatment needs using optimization with a unique objective.


2020 ◽  
Vol 8 (11) ◽  
pp. 876
Author(s):  
Gwanghee Park ◽  
Ki-Yong Oh ◽  
Woochul Nam

A tuned mass damper (TMD) is a system that effectively reduces the vibrations of floating offshore wind turbines (FOWTs). To maximize the performance of TMDs, it is necessary to optimize their design parameters (i.e., stiffness, damping, and installation location). However, this optimization process is challenging because of the existence of multiple local minima. Although various methods have been proposed to determine the global minimum (e.g., exhaustive search, genetic algorithms, and artificial fish swarm algorithms), they are computationally intensive. To address this issue, a novel optimization approach based on a parent nested optimizing structure and approximative search is proposed in this paper. The approximative search determines an initial parameter set (close to the optimal set) with fewer calculations. Then, the global minimum can be rapidly determined using the nested and parent optimizers. The effectiveness of this approach was verified with an FOWT exposed to stochastic winds. The results show that this approach is 30–55 times faster than a conventional global optimization method.


Author(s):  
CHAOFANG HU ◽  
SHAOYUAN LI

This paper proposes an enhanced interactive satisfying optimization method based on goal programming for the multiple objective optimization problem with preemptive priorities. Based on the previous method, the approach presented makes the higher priority achieve the higher satisfying degree. For three fuzzy relations of the objective functions, the corresponding optimization models are proposed. Not only can satisfying results for all the objectives be acquired, but the preemptive priority requirement can also be simultaneously actualized. The balance between optimization and priorities is realized. We demonstrate the power of this proposed method by illustrative examples.


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