An analytical investigation of oscillations within a circular harbor over a Conical Island

Wang, Gang; Stanis, Ze Eyezo'o Giresse; Fu, Danjuan; Zheng, Jinhai; Gao, Junliang

doi:10.1016/j.oceaneng.2019.106711

Cited by 22 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, within the resonant caisson positioned in fully open water, the expression of resonance effects is less restricted, potentially yielding a more prominent and persistent resonance phenomenon. Similarly, if we focus on the harbor resonance of a semi-enclosed island, we will obtain results similar to those of a resonant caisson [26]. The layout of such a harbor is actually analogous to the structure of a resonant caisson.…”

Section: Introductionmentioning

confidence: 80%

The Wave Amplification Mechanism of Resonant Caisson

Hao,

Ding,

et al. 2024

JMSE

View full text Add to dashboard Cite

Previous studies have introduced a resonant caisson designed to enhance wave energy extraction in regions with low wave energy density; however, its operational mechanism remains poorly understood. This paper seeks to elucidate the operational mechanism of the resonant caisson by leveraging Star-CCM+ for Computational Fluid Dynamics (CFD) simulations, focusing on the influence of guides and their dimensions on the water levels, flow velocities, and vortex dynamics. The findings demonstrate the remarkable wave-amplification capabilities of the resonant caisson, with the maximum amplification factor reaching 2.31 at the calculated frequency in the absence of guides. Incorporating guides and expanding their radii substantially elevate the flow rates, accelerate the water currents, and alter the vortex patterns, thereby further enhancing the amplification factor. This study will provide a reference for optimizing the design of resonant caissons and wave energy converters based on resonant caissons, thus promoting the effective use of wave energy resources.

show abstract

Section: Introductionmentioning

confidence: 80%

The Wave Amplification Mechanism of Resonant Caisson

Hao,

Ding,

et al. 2024

JMSE

View full text Add to dashboard Cite

show abstract

“…However, the sea dike risk due to climate change is determined by both the changes in extreme storm surge levels and the original sea dike crest levels, which are determined by historical data and different alone the coast of the estuaries. Therefore, it is necessary to investigate the changes in return periods of water levels due to climate change, to provide reference for future planning of coastal and offshore projects such as sea levees (Pan et al, 2015a;Pan et al, 2015b), harbours (Gao et al, 2020;Wang et al, 2020;Gao et al, 2021), offshore wind power fields (Guan et al, 2019;He et al, 2019), artificial beaches (Pan et al, 2017;Pan et al, 2018;Li et al, 2021;Li et al, 2022), etc. In this paper, the effects of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta are investigated via a serious of numerical experiments. Although global climate change comes with a serious of effects, e.g., sea level rise, increasing maximum wind speed of tropical cyclones, and changes in the tracks of tropical cyclones, this study only focus on the effects of increasing maximum wind speed of tropical cyclones.…”

Section: Introductionmentioning

confidence: 99%

An investigation on the effects of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta

Pan

Tan

et al. 2023

Front. Mar. Sci.

View full text Add to dashboard Cite

This paper investigates the impact of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta. To conduct this study, a series of numerical experiments are performed using historical tropical cyclones that impacted the Yangtze River Delta from 1949 to 2019. The aim is to analyze the effects of global climate change on extreme water levels and the corresponding return periods. To obtain the historical water levels in the sea areas of the Yangtze River Delta, a storm surge model is driven by the selected tropical cyclones. The simulated astronomical tidal levels during the same period are also used. The extreme water levels of different return periods are then calculated. The maximum wind speeds of the selected tropical cyclones are increased by 11% according to the expected amount of increase under global climate change. The extreme water levels of different return periods under this scenario are calculated with the same procedure. The results of the study show that the impact of increasing maximum wind speed of tropical cyclones on the increases of extreme water levels and the decrease of return periods is more significant in the inner area of the estuaries than in the outer areas. Moreover, the responses of the extreme water levels and the corresponding return periods in the Yangtze River Estuary and the Hangzhou Bay show different characteristics. The results of this study provide significant reference value for the management of future coastal disaster prevention and mitigation in the Yangtze River Delta. Furthermore, the methodology used in this study can be applied in other estuaries to investigate the potential impacts of changes in climate and hydrology factors on extreme water levels and the corresponding return periods.

show abstract

“…For example, the waves in a port caused the mooring ships to move excessively and made it impossible to unload cranes [1], which in turn affected the operation of Hambantota Port and the construction of the maritime Silk Road. Therefore, the research on a fast and reliable prediction method of significant wave height (SWH) in the port can help reduce the vibration of moored ships [2], and improve the port operation plan, and it is also very important for improving the safety of coastal engineering and shipping planning.…”

Section: Introductionmentioning

confidence: 99%

PWPNet: A Deep Learning Framework for Real-Time Prediction of Significant Wave Height Distribution in a Port

Xie

Liu

Man

et al. 2022

JMSE

View full text Add to dashboard Cite

In this paper, a 2-stage cascaded deep learning framework, Port Wave Prediction Network (PWPNet), is proposed for real-time prediction of significant wave height (SWH) distribution in a port. The PWP-out model of the first stage, predicting port-entrance wave parameters, utilizes three branches, the first branch using a Long Short Term Memory (LSTM) module to learn the temporal dependencies of time sequences of port-entrance wave parameters, the second branch using Wave and Wind field Feature Extraction (WWFE) modules, composed of a residual network with spatial and channel attention, to capture spatiotemporal characteristics of outside-port 2D wave and wind field data, the third branch using multi-scale time encoding to capture the periodic characteristics of waves and wind. The PWP-in model of the second stage, estimating the in-port SWH distribution, uses port-entrance wave parameters based on a customized Artificial Neural Network (ANN) and takes PWP-out’s output as its input. A comparison of the performance of PWP-out and mainstream machine learning models including LSTM, GRU, BPNN, SVR, ELM, and RF at Hambantota Port shows that PWP-out outperforms all other models regarding medium-term (25–48 h), med–long-term (49–72 h), and long-term (73–96 h) predictions, and ablation experiments proved the effectiveness of the three branches. Furthermore, the performance comparison of our PWPNet and other 2-stage models of LSTM, GRU, BPNN, SVR, ELM, and RF cascaded with PWP-in shows that PWPNet outperforms those cascaded models for medium-term to long-term predictions of SWH distribution in a port.

show abstract

An analytical investigation of oscillations within a circular harbor over a Conical Island

Cited by 22 publications

References 21 publications

The Wave Amplification Mechanism of Resonant Caisson

The Wave Amplification Mechanism of Resonant Caisson

An investigation on the effects of increasing maximum wind speed of tropical cyclones on the return periods of water levels in the sea area of the Yangtze River Delta

PWPNet: A Deep Learning Framework for Real-Time Prediction of Significant Wave Height Distribution in a Port

Contact Info

Product

Resources

About