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28 results on '"Zhang, Longfei"'

11. Experimental and numerical analysis of steel pipe-rubber friction damper

Author

Zhang Longfei, Zuo Heng, Wan Yunhua, and Zhu Xia

Subjects
Yield (engineering), Materials science, business.industry, Numerical analysis, Structural engineering, Dissipation, Finite element method, Damper, Shock absorber, Natural rubber, visual_art, visual_art.visual_art_medium, business, Test data
Abstract

A steel pipe-rubber friction damper (FRD) is proposed for the purpose of achieving greater cost-efficiency. The theoretical calculation formula of yield load was deduced based on generalized Hooke's law, and in order to investigate the behaviour of the proposed damper quasi-static cyclic tests were carried out on 7 specimens. Besides, a numerical finite element analysis (FEA) was carried out on ten dampers. Furthermore the mechanical property of FRD was proposed. Tests and finite element analysis results show that: Hysteretic curve of the steel pipe-rubber friction damper is slippery. The seismic energy dissipation capability is stable which related to load amplitude rather than loading rate. The results of finite element analysis fit well with the test curve. The differences of yield load between the theoretical value, FEA value and experimental data are small. The simulating hysteretic curve with ideal elastoplastic model is identical to the test data, and it is feasible to adopt the ideal elastoplastic model to simulate the damper element in the analysis of a structure with the steel pipe-rubber friction damper.

Published
2021

12. An Optimal Bus Dispatching Model Based on African Buffalo Algorithm

Author

Zhang Longfei

Subjects
Product (business), Decision variables, Computer science, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Interval (mathematics), Plan (drawing), Algorithm, Scheduling (computing), Management level, Dual (category theory)
Abstract

Bus is an indispensable product of a city, and its operation reflects the management level of a city. In bus dispatching, most schemes only meet the demand of passenger flow, without considering the interests of the bus company and the satisfaction of passengers. In actual conditions, the two are often contradictory. How to balance the two interest has become a topic worth discussing. In this paper, we propose a bus scheduling optimization model that takes the interests of the bus company and the satisfaction of passengers as the dual goals. The bus departure interval is used as the decision variable, and the African buffalo optimization (ABO) algorithm is used to solve the problem. The results show that the bus departure interval varies with passenger flow. In practical applications, the future passenger flow can be predicted based on historical data, and then the model mentioned in the paper can be used to solve the optimal bus dispatch plan.

Published
2020

21. Damage Diagnosis of Radial Gate Based on RBF Neural Networks

Author

Zhang Jianwei, Zhang Longfei, Zhao Yu, and Zhang Yina

Subjects
Artificial neural network, Computer science, business.industry, Condition monitoring, Function (mathematics), Machine learning, computer.software_genre, Vibration theory of olfaction, Vibration, Hydraulic structure, Control theory, Logic gate, Artificial intelligence, business, computer, Dynamic testing
Abstract

Damage diagnosis and health monitoring of large-scale structures are becoming a hot research subject in the present structural engineering circle. Aimed at many operating safe problems of hydraulic structure, a method applied to radial gate is put forward. This method is an aggregation of vibration theory, neural networks and pattern identification, and make the combined index as input data of RBF neural networks, and make the damaged locations and degree as output data. Based on the theory, a radial gate of a hydraulic project located in the middle reaches of the main stream of the Jialing River is studied. Study shows that this method has better function to get precise identified results, and this provides a new way to online state testing and monitoring for radial gate.

Published
2009

24. Simulation-Based Testing and Evaluation Tools for Transportation Cyber–Physical Systems.

Author

Hou, Yunfei, Zhao, Yunjie, Wagh, Aditya, Zhang, Longfei, Qiao, Chunming, Hulme, Kevin F., Wu, Changxu, Sadek, Adel W., and Liu, Xuejie

Subjects
CYBER physical systems, INTELLIGENT transportation systems, VEHICLE infrastructure integration, TRAFFIC engineering, FEEDBACK control systems, TRANSPORTATION -- Computer network resources
Abstract

Transportation cyber–physical systems (TCPSs) require simulation-based testing and evaluation due to the prohibitive cost of building realistic test beds. Given the transdisciplinary nature of TCPSs, various simulation models and frameworks have been proposed in civil engineering, computer science, and related fields. Traditionally, researchers in different areas have developed their own set of simulation tools, which provide limited capability for TCPS research. In recent years, we have witnessed a growing interest of combining two or more features of traditional simulators to capture the unique characteristics of TCPSs. In this paper, we describe several mainstream simulation models used in transportation, communication, and human-factor studies in TCPS research. Moreover, we present our unique design and implementation of an integrated traffic–driving–network simulator (ITDNS). Finally, we discuss future enhancements that will promote best simulation practices for TCPS research. [ABSTRACT FROM AUTHOR]

Published
2016
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28. Symbiotic Tracker Ensemble Toward A Unified Tracking Framework.

Author

Gao, Yue, Ji, Rongrong, Zhang, Longfei, and Hauptmann, Alexander

Subjects
VIDEO surveillance, OBJECT tracking (Computer vision), DATA visualization, CORRELATION methods (Signal processing), ELECTRONIC surveillance
Abstract

Tracking people and objects is a fundamental stage toward many video surveillance systems, for which various trackers have been specifically designed in the past decade. However, it comes to a consensus that there is not any specific tracker that works sufficiently well under all circumstances. Therefore, one potential solution is to deploy multiple trackers, with a tracker output fusion step to boost the overall performance. Subsequently, an intelligent fusion design, yet general and orthogonal to any specific tracker, plays a key role in successful tracking. In this paper, we propose a symbiotic tracker ensemble toward a unified tracking framework, which is based on only the output of each individual tracker, without knowing its specific mechanism. In our approach, all trackers run in parallel, without requiring any details for tracker running, which means that all trackers are treated as black boxes. The proposed symbiotic tracker ensemble framework aims at learning an optimal combination of these tracking results. Our method captures the relation among individual trackers robustly from two aspects. First, the consistency between two successive frames is calculated for each tracker. Then, the pair-wise correlation among different trackers is estimated in the new coming frame by a graph-propagation process. Experimental results on the Caremedia dataset and the Caviar dataset demonstrate the effectiveness of the proposed method, with comparisons to several state-of-the-art methods. [ABSTRACT FROM PUBLISHER]

Published
2014
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