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Modern Trends in Nonlinear Dynamics in Ocean Engineering
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Modern Trends in Nonlinear Dynamics in Ocean Engineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 1402

Special Issue Editors

Dr. Ye Tang

E-Mail Website
Guest Editor
Ocean Institute, Northwestern Polytechnical University, Xian 710072, China
Interests: dynamic analysis and optimization; nonlinear control; nonlinear vibration; marine engineering
Dr. Yaxin Zhen

E-Mail Website
Guest Editor
School of Mathematics and Physics, North China Electric Power University, Beijing 100096, China
Interests: dynamic analysis and optimization; vibration control; mechanics of materials

Special Issue Information

Dear Colleagues,

With the development of science and technology, the exploitation of ocean resources has become an effective pathway to obtain sources of great economic value. However, more complex and harsh operating environments have resulted from the high uncertainty and remarkable destructive power in extreme sea conditions, such as typhoons, huge waves, and internal waves. Consequently, nonlinear phenomena exist in ocean engineering structures, such as marine systems and floating platforms. It is therefore necessary for scholars to study the nonlinear dynamics in ocean engineering, elucidate the dynamic mechanisms, and establish appropriate control methods to suppress the nonlinear vibration. Meanwhile, marine environmental noise induced by the nonlinear vibration has a certain research value and application prospects in the fields of engineering and marine health. By extracting and analyzing the numerical characteristics of marine environmental noise, its application value in engineering fields, such as hydrodynamics, ship dynamics, and fluid dynamics, as well as the impact of marine noise on marine organisms and human perception can be explored. Therefore, investigating the nonlinear dynamics and vibration control as well as noise problems will be an interesting topic in the field of ocean engineering.

Dr. Ye Tang
Dr. Yaxin Zhen
Guest Editors

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. Mathematics 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 2600 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

  • nonlinear dynamics
  • vibration and control
  • ocean engineering
  • engineering dynamics
  • intelligent design
  • marine noise
  • intelligent algorithm
  • numerical analysis

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Published Papers (2 papers)

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Research

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20 pages, 4466 KiB  
Article
Nonlinear Perception Characteristics Analysis of Ocean White Noise Based on Deep Learning Algorithms
by Tao Qian, Ying Li and Jun Chen
Mathematics 2024, 12(18), 2892; https://doi.org/10.3390/math12182892 - 17 Sep 2024
Cited by 1 | Viewed by 880
Abstract
Caused by nonlinear vibration, ocean white noise exhibits complex dynamic characteristics and nonlinear perception characteristics. To explore the potential application of ocean white noise in engineering and health fields, novel methods based on deep learning algorithms are proposed to generate ocean white noise, [...] Read more.
Caused by nonlinear vibration, ocean white noise exhibits complex dynamic characteristics and nonlinear perception characteristics. To explore the potential application of ocean white noise in engineering and health fields, novel methods based on deep learning algorithms are proposed to generate ocean white noise, contributing to marine environment simulation in ocean engineering. A comparative study, including spectrum analysis and auditory testing, proved the superiority of the generation method using deep learning networks over general mathematical or physical methods. To further study the nonlinear perception characteristics of ocean white noise, novel experimental research based on multi-modal perception research methods was carried out within a constructed multi-modal perception system environment, including the following two experiments. The first audiovisual comparative experiment thoroughly explores the system’s user multi-modal perception experience and influence factors, explicitly focusing on the impact of ocean white noise on human perception. The second sound intensity testing experiment is conducted to further explore human multi-sensory interaction and change patterns under white noise stimulation. The experimental results indicate that user visual perception ability and state reach a relatively high level when the sound intensity is close to 50 dB. Further numerical analysis based on the experimental results reveals the internal influence relationship between user perception of multiple senses, showing a fluctuating influence law to user visual concentration and a curvilinear influence law to user visual psychology from the sound intensity of ocean white noise. This study underscores ocean white noise’s positive effect on human perception enhancement and concentration improvement, providing a research basis for multiple field applications such as spiritual healing, perceptual learning, and artistic creation for human beings. Importantly, it provides valuable references and practical insights for professionals in related fields, contributing to the development and utilization of the marine environment. Full article
(This article belongs to the Special Issue Modern Trends in Nonlinear Dynamics in Ocean Engineering)
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Review

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32 pages, 4387 KiB  
Review
Recent Progress in Ocean Intelligent Perception and Image Processing and the Impacts of Nonlinear Noise
by Huayu Liu, Ying Li, Tao Qian and Ye Tang
Mathematics 2025, 13(7), 1043; https://doi.org/10.3390/math13071043 - 23 Mar 2025
Viewed by 269
Abstract
Deep learning network models are crucial in processing images acquired from optical, laser, and acoustic sensors in ocean intelligent perception and target detection. This work comprehensively reviews ocean intelligent perception and image processing technology, including ocean intelligent perception devices and image acquisition, image [...] Read more.
Deep learning network models are crucial in processing images acquired from optical, laser, and acoustic sensors in ocean intelligent perception and target detection. This work comprehensively reviews ocean intelligent perception and image processing technology, including ocean intelligent perception devices and image acquisition, image recognition and detection models, adaptive image processing processes, and coping methods for nonlinear noise interference. As the core tasks of ocean image processing, image recognition and detection network models are the research focus of this article. The focus is on the development of deep-learning network models for ocean image recognition and detection, such as SSD, R-CNN series, and YOLO series. The detailed analysis of the mathematical structure of the YOLO model and the differences between various versions, which determine the detection accuracy and inference speed, provides a deeper understanding. It also reviewed adaptive image processing processes and their critical support for ocean image recognition and detection, such as image annotation, feature enhancement, and image segmentation. Research and practical applications show that nonlinear noise significantly affects underwater image processing. When combined with image enhancement, data augmentation, and transfer learning methods, deep learning algorithms can be applied to effectively address the challenges of underwater image degradation and nonlinear noise interference. This work offers a unique perspective, highlighting the mathematical structure of the network model for ocean intelligent perception and image processing. It also discusses the benefits of DL-based denoising methods in signal–noise separation and noise suppression. With this unique perspective, this work is expected to inspire and motivate more valuable research in related fields. Full article
(This article belongs to the Special Issue Modern Trends in Nonlinear Dynamics in Ocean Engineering)
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