scholarly journals Multiobjective Optimization of Cable Forces and Counterweights for Universal Cable-Stayed Bridges

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhangming Wang ◽  
Nan Zhang ◽  
Xianting Du ◽  
Shilei Wang ◽  
Qikai Sun
Keyword(s):  
Optimal Solution ◽  
Optimization Method ◽  
Solution Set ◽  
Spatial Effects ◽  
Pareto Solution ◽  
Cable Stayed Bridge ◽  
Optimal Solution Set ◽  
Cable Forces ◽  
Coefficient Method ◽  
Cable Stayed Bridges

In cable-stayed bridges, especially asymmetric bridges, counterweights are always made to work together with cable pretension forces to get a reasonable finished state. To solve the optimization problem of the cable-stayed bridge considering the counterweights, the integrated optimization method (IOM) for estimating cable forces and counterweights is proposed. In this method, the counterweights are proposed to act on the anchor points. After that, the summary of the minimum weighted total bending energy and the summary of the counterweights are considered as two objective functions of a multiobjective problem. Finally, the dynamic weighted coefficient method is used to solve this problem and realize the Pareto solution set. IOM presents detailed procedures in a simple numerical model and is then applied to the Yong-ding special-shaped cable-stayed bridge. The results show that not only IOM can realize the priority selection of the loading position of the counterweights but also get a better reasonable finish state because of the introduction of the counterweight dimension; the dynamic weighted coefficient method can quickly find the Pareto optimal solution set and be further screened by decision-makers; counterweight is very helpful to reduce torsion and other spatial effects in cable-stayed bridges. IOM can be used as a universal optimization method for cable-stayed bridges.

A prediction method for cable forces of cable-stayed bridges using fuzzy processing and Bayes estimation

2021 ◽  
Author(s):  
Li Dong ◽  
Bin Xie ◽  
Dongli Sun ◽  
Yizhuo Zhang
Keyword(s):  
Prediction Method ◽  
Practical Method ◽  
Bayes Estimation ◽  
Primary Data ◽  
Force Estimation ◽  
Element Analysis ◽  
Cable Stayed Bridge ◽  
Input Parameters ◽  
Cable Forces ◽  
Cable Stayed Bridges

<p>Cable forces are primary factors influencing the design of a cable-stayed bridge. A fast and practical method for cable force estimation is proposed in this paper. For this purpose, five input parameters representing the main characteristics of a cable-stayed bridge and two output parameters representing the cable forces in two key construction stages are defined. Twenty different representative cable-stayed bridges are selected for further prediction. The cable forces are carefully optimized through finite element analysis. Then, discrete and fuzzy processing is applied in data processing to improve their reliability and practicality. Finally, based on the input parameters of a target bridge, the maximum possible output parameters are calculated by Bayes estimation based on the processed data. The calculation results show that the average prediction error of this method is less than 1% for the twenty bridges themselves, which provide the primary data and less than 3% for an under-construction bridge.</p>

Monitored structural behavior of a long span cable-stayed bridge under environmental effects

2018 ◽  
Vol 4 (4) ◽  
pp. 137 ◽  
Author(s):  
Alemdar Bayraktar ◽  
Ashraf Ashour ◽  
Halil Karadeniz ◽  
Altok Kurşun ◽  
Arif Erdiş
Keyword(s):  
Air Temperature ◽  
Environmental Effects ◽  
Monitoring Data ◽  
Structural Behavior ◽  
Steel Cable ◽  
Daily Monitoring ◽  
Cable Stayed Bridge ◽  
Long Span ◽  
Cable Forces ◽  
Cable Stayed Bridges

An accurate numerical analysis of the behavior of long-span cable-stayed bridges under environmental effects is a challenge because of complex, uncertain and varying environmental meteorology. This study aims to investigate in-situ experimental structural behavior of long-span steel cable-stayed bridges under environmental effects such as air temperature and wind using the monitoring data. Nissibi cable-stayed bridge with total length of 610m constructed in the city of Adıyaman, Turkey, in 2015 is chosen for this purpose. Structural behaviors of the main structural elements including deck, towers (pylons) and cables of the selected long span cable-stayed bridge under environmental effects such as air temperature and wind are investigated by using daily monitoring data. The daily variations of cable forces, cable accelerations, pylon accelerations and deck accelerations with air temperature and wind speed are compared using the hottest summer (July 31, 2015) and the coldest winter (January 1, 2016) days data.

scholarly journals Wear optimization of titanium alloy cutter milled with microtextured ball-end milling cutter

2020 ◽  
Vol 12 (1) ◽  
pp. 168781401989210
Author(s):  
Yuhua Zhang ◽  
Hongzhi Ji
Keyword(s):  
Tool Wear ◽  
End Milling ◽  
Optimal Solution ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Milling Cutter ◽  
Ball End Milling ◽  
Orthogonal Experiments ◽  
Texture Parameters ◽  
Optimal Solution Set

Aimed at solving the problems of tool wear and poor surface quality in milling a Ti alloy with a ball-end milling cutter, a method of applying a microtexture to a tool rake face to reduce tool wear is proposed in this article. By comparing the wear morphology of microtextured tools with that of nontextured tools after milling with the same stroke, the antifriction and antiwear mechanism of the micropit texture and the failure mode of the ball-end milling cutter are analyzed. The results of a simulation and orthogonal experiments reveal that with the increase of the micropit parameters, the wear value of the rake and rear faces first decreases and then increases. The effects of the micropit parameters on the wear value of the ball-end milling cutter decrease in the following order: distance from edge > diameter > spacing > depth. Finally, by using a multi-objective optimization method, the optimal solution set of the texture parameters of micropits is obtained by evaluating the wear values of the rake and rear faces of the ball-end milling cutters: 46 μm < diameter < 50 μm, 23 μm < depth < 26 μm, 109 μm < spacing < 112 μm, and 85 μm < distance from edge < 89 μm.

CFD Based Multi-Disciplinary Optimization Design of High-Performance Deep Sea Seismic Vessel

2017 ◽  
Author(s):  
Mao Xiaofei ◽  
Zhang Wenxu ◽  
Qian Jiankui ◽  
Wu Minghao
Keyword(s):  
High Performance ◽  
Optimization Design ◽  
Optimal Solution ◽  
Solution Set ◽  
Short Term ◽  
Hull Form ◽  
Optimal Solution Set ◽  
Computational Fluid Dynamics Cfd ◽  
The Stability

This paper focuses on the application of a ship hull form multi-disciplinary optimization (MDO) system based on the computational fluid dynamics (CFD). Using the iSIGHT software, the MDO system integrates an automatic geometry transformation program and high-fidelity CFD solvers for different sub-disciplines. Hydrodynamics analysis subsystem includes resistance, seakeeping and stability modules. The resistance and seakeeping is analyzed by commercial potential-flow CFD codes, the stability is assessed by in-house code. The geometry variation output can be automatically used by the numerical solvers. By means of the design of experiment (DOE) technique, a neural network metamodel is trained to predict short term motion response of the derived ships efficiently. The system has been used in a seismic vessel’s hull form optimization to minimize the resistance and maximize the long term seakeeping operability index. Meanwhile, the stability in waves is concerned as a constraint. The hybrid MIGA-NLPQL optimization algorithm is applied for a global-to-local search in resistance optimization. For the synthesis optimization, a Pareto optimal solution set has been obtained and the final solution is achieved by trade-off analysis of the solution set. The entire automatic optimization process can be used for the preliminary design of new high performance vessels.

scholarly journals Training v-Support Vector Classifiers: Theory and Algorithms

2001 ◽  
Vol 13 (9) ◽  
pp. 2119-2147 ◽  
Author(s):  
Chih-Chung Chang ◽  
Chih-Jen Lin
Keyword(s):  
Support Vector Machine ◽  
Numerical Experiments ◽  
Decomposition Method ◽  
Large Scale ◽  
Optimal Solution ◽  
Solution Set ◽  
Support Vector ◽  
Support Vectors ◽  
Optimal Solution Set

The ν-support vector machine (ν-SVM) for classification proposed by Schölkopf, Smola, Williamson, and Bartlett (2000) has the advantage of using a parameter ν on controlling the number of support vectors. In this article, we investigate the relation between ν-SVM and C-SVM in detail. We show that in general they are two different problems with the same optimal solution set. Hence, we may expect that many numerical aspects of solving them are similar. However, compared to regular C-SVM, the formulation of ν-SVM is more complicated, so up to now there have been no effective methods for solving large-scale ν-SVM. We propose a decomposition method for ν-SVM that is competitive with existing methods for C-SVM. We also discuss the behavior of ν-SVM by some numerical experiments.

Novelty detection of cable-stayed bridges based on cable force correlation exploration using spatiotemporal graph convolutional networks

2021 ◽  
pp. 147592172098866
Author(s):  
Shunlong Li ◽  
Jin Niu ◽  
Zhonglong Li
Keyword(s):  
Novelty Detection ◽  
The State ◽  
Spatial Dependency ◽  
Sensor Fault ◽  
Spatiotemporal Model ◽  
Convolutional Networks ◽  
Cable Stayed Bridge ◽  
Adjacency Matrices ◽  
Cable Forces ◽  
Cable Stayed Bridges

The novelty detection of bridges using monitoring data is an effective technique for diagnosing structural changes and possible damages, providing a critical basis for assessing the structural states of bridges. As cable forces describe the state of cable-stayed bridges, a novelty detection method was developed in this study using spatiotemporal graph convolutional networks by analysing spatiotemporal correlations among cable forces determined from different cable dynamometers. The spatial dependency of the sensor network was represented as a directed graph with cable dynamometers as vertices, and a graph convolutional network with learnable adjacency matrices was used to capture the spatial dependency of the locally connected vertices. A one-dimensional convolutional neural network was operated along the time axis to capture the temporal dependency. Sensor faults and structural variations could be distinguished based on the local or global anomalies of the spatiotemporal model parameters. Faulty sensors were detected and isolated using weighted adjacency matrices along with diagnostic indicators of the model residuals. After eliminating the effect of the sensor fault, the underlying variations in the state of the cable-stayed bridge could be determined based on the changing data patterns of the spatiotemporal model. The application of the proposed method to a long-span cable-stayed bridge demonstrates its effectiveness in sensor fault localization and structural variation detection.

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