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Applied Sciences
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Structural Dynamic Analysis and Optimization Design for Multifunctional Materials
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Structural Dynamic Analysis and Optimization Design for Multifunctional Materials

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 1940

Special Issue Editors

Prof. Dr. Dongwei Wang

E-Mail Website
Guest Editor
School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: structural dynamics; seismic design; smart materials; structural experiments; numerical analysis; structural optimization; urban road-to-freeway interchange; navigation map
Dr. Panxu Sun

E-Mail Website
Guest Editor Assistant
School of Civil Engineering, Zhengzhou University, Zhengzhou 450001, China
Interests: structural dynamics; damping models; seismic analysis; multifunctional materials; numerical analysis; structural optimization; performance evaluation

Special Issue Information

Dear Colleagues,

The optimization and design of the dynamic performance of engineering structures is an important issue. Dynamic performance depends on multifunctional materials and structural design. The aim of modern methods of structural performance optimization is to conduct theoretical analysis, numerical simulations, and experimental testing of materials, components, and parts of or full structures in order to promote the performance of engineering structures.

The scope and topics of this Special Issue include, but are not limited to: structural dynamic models; seismic analysis; wind-resistant analysis; vehicle–bridge coupling; damping characteristics of multifunctional materials; fatigue performance of structures; structural design and optimization; experimental and numerical analysis of modal parameter identification; and uncertainty quantification of dynamic performance.

We welcome original research papers and review articles with new insights and perspectives on pioneering developments and their applications, including case studies in civil engineering. Authors who are experts in these fields of study are invited and encouraged to submit their contributions to this Special Issue.

Prof. Dr. Dongwei Wang
Guest Editor

Dr. Panxu Sun
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural dynamics
  • seismic performance of engineering structures
  • wind-resistant analysis
  • vehicle–bridge coupling
  • damping characteristics of materials
  • multifunctional materials
  • fatigue performance of structures
  • structural design and optimization
  • machine learning
  • modal parameter identification

Published Papers (2 papers)

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Research

17 pages, 8477 KiB  
Article
Analysis of Vehicle-Bridge Coupling Vibration Characteristics of Curved Girder Bridges
by Hengtao Cao, Yao Lu and Daihai Chen
Appl. Sci. 2024, 14(5), 2021; https://doi.org/10.3390/app14052021 - 29 Feb 2024
Viewed by 685
Abstract
When vehicles move on a bridge, the coupling effect between vehicles and bridges can affect driving safety and comfort, especially for curved bridges, therefore, choosing reasonable design parameters for curved bridges is crucial. In this article, a three-span curved continuous box-girder bridge was [...] Read more.
When vehicles move on a bridge, the coupling effect between vehicles and bridges can affect driving safety and comfort, especially for curved bridges, therefore, choosing reasonable design parameters for curved bridges is crucial. In this article, a three-span curved continuous box-girder bridge was taken as the research object; the entire process of vehicle-bridge coupling vibration of highway curved girder bridges was conducted via numerical simulation and the vehicle-bridge coupling vibration analysis program Cmck 1.0 was developed. Then, the influence factors such as curvature radius, constraint mode, and vehicle characteristics on the vehicle-bridge coupling vibration of curved girder bridges were explored. The results showed that as the curvature radius increased, the dynamic response of the bridge offered a gradually decreasing trend and compared to the vertical dynamic response, the torsional response was more sensitive to the influence of the curvature radius. Different constraint methods significantly impacted the dynamic response of bridges, and the vertical and torsional dynamic responses of bridges under general constraint arrangement of straight bridges were increased compared to those under boundary conditions for curved beam bridges. As the axle load of the car decreases, the bridge mid-span vertical and torsional dynamic responses showed a decreasing trend. In contrast, the lateral dynamic response gradually increased. Full article
(This article belongs to the Special Issue Structural Dynamic Analysis and Optimization Design for Multifunctional Materials)
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15 pages, 3016 KiB  
Article
Coordination Optimization of Real-Time Signal Priority of Self-Driving Buses at Arterial Intersections Considering Private Vehicles
by Hui Li, Shuxin Li and Xu Zhang
Appl. Sci. 2023, 13(19), 10803; https://doi.org/10.3390/app131910803 - 28 Sep 2023
Cited by 1 | Viewed by 898
Abstract
Transit Signal Priority (TSP) is a system designed to grant right-of-way to buses, yet it can lead to delays for private vehicles. With the rapid advancement of network technology, self-driving buses have the capability to efficiently acquire road information and optimize the coordination [...] Read more.
Transit Signal Priority (TSP) is a system designed to grant right-of-way to buses, yet it can lead to delays for private vehicles. With the rapid advancement of network technology, self-driving buses have the capability to efficiently acquire road information and optimize the coordination between vehicle arrival and signal timing. However, the complexity of arterial intersections poses challenges for conventional algorithms and models in adapting to real-time signal priority. In this paper, a novel real-time signal-priority optimization method is proposed for self-driving buses based on the CACC model and the powerful deep Q-network (DQN) algorithm. The proposed method leverages the DQN algorithm to facilitate rapid data collection, analysis, and feedback in self-driving scenarios. Based on the arrival states of both the bus and private vehicles, appropriate actions are chosen to adjust the current-phase green time or switch to the next phase while calculating the duration of the green light. In order to optimize traffic balance, the reward function incorporates an equalization reward term. Through simulation analysis using the SUMO framework with self-driving buses in Zhengzhou, the results demonstrate that the DQN-controlled self-driving TSP optimization method reduces intersection delay by 27.77% and 30.55% compared to scenarios without TSP and with traditional active transit signal priority (ATSP), respectively. Furthermore, the queue length is reduced by 33.41% and 38.21% compared to scenarios without TSP and with traditional ATSP, respectively. These findings highlight the superior control effectiveness of the proposed method, particularly during peak hours and in high-traffic volume scenarios. Full article
(This article belongs to the Special Issue Structural Dynamic Analysis and Optimization Design for Multifunctional Materials)
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