Article
Green & Sustainable Science & Technology
Vincent S. Neary, Seongho Ahn
Summary: Interest in offshore wind, wave, and tidal energy has led to studies on ocean wave climate, including extreme wave conditions for project risk assessment and wave load design. This study uses global and coastal hindcast models, along with buoy data, to estimate and map global distribution of significant wave heights. A linear correction method is applied to address systematic underbias in the models, resulting in a significant increase in corrected values. The generated atlas provides important metrics for resource characterization and industry standards development.
Article
Engineering, Ocean
Jie Ding, Fangyu Deng, Qi Liu, Jichao Wang
Summary: Most studies only focus on single-point wave forecasting, while regional wave forecasting is more important for ocean engineering construction, navigation safety, and disaster warning. A novel hybrid model called EOF-EEMD-SCINet is proposed to solve the problems of high computational cost and poor performance in regional wave forecasting. The model combines EOF analysis, EEMD, and SCINet to accurately forecast the changes in significant wave height (SWH) and mean wave period (MWP) with time. The model outperforms other models in terms of forecasting precision for regional waves, and the increase of wave lead time has less negative effect on its performance.
APPLIED OCEAN RESEARCH
(2023)
Article
Engineering, Marine
Tommaso Caloiero, Francesco Aristodemo, Danilo Algieri Ferraro
Summary: An analysis of a 40-year wave time series in the Mediterranean basin reveals different trends in wave parameters, with overall increases in mean values, especially energy period, while increases in maximum values are limited. Negative trends are identified in specific areas of the Mediterranean Sea, particularly for significant wave height and wave power.
Article
Engineering, Civil
Francesco De Leo, Giovanni Besio, Riccardo Briganti, Erik Vanem
Summary: This study examines the reliability of non-stationary extreme value analysis of significant wave height and peak period in the Mediterranean Sea under the assumption of linear trend. It proposes a methodology to assess the significance of the results and explores the use of non-stationary Generalized Extreme Value probability distribution. Results suggest that careful consideration should be given to the hypothesis of linear trend and the length of reference data when applying NEVA for coastal and marine applications.
COASTAL ENGINEERING
(2021)
Article
Engineering, Marine
Hao Dai, Shaoping Shang, Famei Lei, Ke Liu, Xining Zhang, Guomei Wei, Yanshuang Xie, Shuai Yang, Rui Lin, Weijie Zhang
Summary: This study uses the CRBM-DBN model to predict significant wave height in the Gulf of Mexico and finds that univariate input of significant wave height leads to the best results for short-term predictions, while a multivariate pattern including significant wave height, dominant wave direction, wind speed, and wind direction performs optimally near 26°N for longer lead times. The superiority of the multivariate pattern diminishes as latitude increases.
Article
Engineering, Marine
Weinan Huang, Sheng Dong
Summary: This study focuses on the joint distribution of significant wave height and zero-up-crossing wave period with a mixture copula distribution model for total sea data. The results suggest that the mixture copula model provides improved performance compared to the conditional model, especially in accurately estimating return levels. Additionally, the study investigates the effects of seasonality and short-term dependency on the joint behavior of spectral parameters.
Article
Engineering, Mechanical
Anders Hildeman, David Bolin, Igor Rychlik
Summary: Sea state, which describes the distribution of ocean waves in a specific region of space and time, plays a crucial role in assessing risks and wear associated with ship journeys. This study proposes a joint spatial model for significant wave height and mean wave period in the north Atlantic ocean, using a bivariate Gaussian random field. The model, estimated from data using a stepwise maximum likelihood method, accurately predicts accumulated fatigue damage and capsizing risk for a transatlantic route.
PROBABILISTIC ENGINEERING MECHANICS
(2022)
Article
Environmental Sciences
Xiaolei Wang, Xiufeng He, Jian Shi, Shu Chen, Zijin Niu
Summary: Monitoring oceanographic parameters is crucial for marine engineering construction, coastal safety, marine analysis, and climatic analysis. The GNSS-interferometry reflectometry (GNSS-IR) technology based on global navigation satellite systems (GNSS) can be used to estimate sea level, wind direction, significant wave height (SWH), and wave peak period.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Engineering, Marine
Guowei Bai, Zongli Ruan, Jichao Wang
Summary: This paper presents the bivariate region frequency analysis method to investigate extreme sea state in the South China Sea, providing a comprehensive understanding for the design and construction of offshore structures. The South China Sea is divided into 35 homogeneity regions based on multivariate L-moments, and discordance test and homogeneity test are conducted. The model effect is verified in the Huangyan Island and Nansha Island near area, and the goodness of fit between empirical and theoretical distributions is indicated through diagnostic figures.
Article
Oceanography
Gwendal Marechal, Fabrice Ardhuin
Summary: Advances in understanding surface currents have shown the importance of internal waves, mesoscale, and submesoscale features on wind waves, but the quantitative impact of currents on waves remains unclear. Comparing satellite altimetry data and numerical wave models, it is found that high-resolution current fields (around 30 km or less) and directional resolution of 7.5 degrees can accurately represent significant wave height gradients in the Agulhas current.
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
(2021)
Article
Engineering, Marine
A. Anusree, V. Sanil Kumar
Summary: This study investigates the short-term statistics of waves in the eastern Arabian Sea at a water depth of 15 m. The results show that during the monsoon season, individual wave characteristics such as height, period, length, and steepness are higher compared to the non-monsoon period. The wave spectrum also exhibits multi-peaked patterns during the non-monsoon, with low-frequency swells and high-frequency wind-seas. The exceedance probabilities of higher wave heights show significant inter-annual variability.
Article
Engineering, Marine
Seongho Ahn
Summary: A regression model is developed in this study using buoy wave measurements and hindcast data to improve the accuracy of estimating wave energy periods. The coefficients for wind sea, swell, and total sea vary geographically, with the approach leading to better agreements in energy period estimation compared to traditional parametric spectrum models.
Article
Engineering, Aerospace
Saleh Abdalla
Summary: Jason-2 was launched in 2008 with the main purpose of measuring significant wave height and surface wind speed. Despite multiple orbit changes, the data from Jason-2 has been proven to be effective, recommending continuous support and maintenance of the satellite in orbit.
ADVANCES IN SPACE RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Yan Li, Xue Qin, Daoheng Zhu
Summary: A fusion prediction model based on MIC and LSTM is proposed to predict significant wave heights of nearshore ocean hydrographic data in Yangjiang City, China and the NDBC deep-sea buoy data. Compared with other models, the MIC-LSTM model shows smaller deviation, fewer feature variables in the public dataset, and higher screening efficiency, thereby improving the efficiency and effectiveness of nearshore significant wave height prediction.
EARTH SCIENCE INFORMATICS
(2023)
Article
Environmental Sciences
Daniel Pascual, Maria Paola Clarizia, Christopher S. Ruf
Summary: This article introduces a method for improved estimation of sea surface wind speed measured by CYGNSS satellites using significant wave height as external reference data. By correcting a 2D look-up table with input from CYGNSS wind speed and collocated reference SWH, the sensitivity to large wind speeds increases and the root mean square difference with ECMWF winds decreases. The influence of ECMWF winds on the corrected winds is analyzed, showing no significant impact when compared with other reference data sources.
Article
Computer Science, Artificial Intelligence
M. Sivachitra, R. Savitha, S. Suresh, S. Vijayachitra
Article
Engineering, Marine
N. Krishna Kumar, R. Savitha, Abdullah Al Mamun
Article
Computer Science, Artificial Intelligence
N. Krishna Kumar, R. Savitha, Abdullah Al Mamun
Article
Chemistry, Physical
Felipe Oviedo, Zekun Ren, Shijing Sun, Charles Settens, Zhe Liu, Noor Titan Putri Hartono, Savitha Ramasamy, Brian L. DeCost, Siyu I. P. Tian, Giuseppe Romano, Aaron Gilad Kusne, Tonio Buonassisi
NPJ COMPUTATIONAL MATERIALS
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Liu Guimeng, Guo Yang, Cheryl Wong Sze Yin, Ponnuthurai Nagartnam Suganathan, Ramasamy Savitha
Summary: This paper proposes a method for unsupervised generative continual learning by combining architectural pruning and neuron addition in generative variational models. Evaluations on standard benchmark data sets demonstrate the superior generative ability of the proposed method.
2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP
(2022)
Proceedings Paper
Acoustics
Yanpeng Zhou, Maosen Wang, Manas Gupta, Arulmurugan Ambikapathi, Ponnuthurai Nagaratnam Suganthan, Savitha Ramasamy
Summary: In this work, the robustness of biologically inspired Hebbian learning algorithm is thoroughly investigated. The experimental results show that compared to conventional learning algorithms like CNNs, Hebbian learning methods perform significantly better, with an improvement of up to 18% on the CIFAR-10 dataset under the addition of noise. The key factor contributing to this improvement is the more robust representations learned by the Hebbian method. Ablation experiments also demonstrate the importance of representation capacity in achieving robustness.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Acoustics
Cheryl Sze Yin Wong, Guo Yang, Arulmurugan Ambikapathi, Ramasamy Savitha
Summary: The article introduces an online continual learning algorithm based on an enhanced Random Vector Functional Link Network, which can effectively learn a continuous sequence of tasks without the need for additional memory storage of samples. The algorithm updates weights through recursive least squares to prevent catastrophic forgetting of past tasks.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Acoustics
Cheryl Sze Yin Wong, Guo Yang, Nancy F. Chen, Ramasamy Savitha
Summary: This paper presents a study on the problem of data distribution drift in knowledge tracing and proposes an incremental context aware approach. The effectiveness of the approach in adapting to data drift and ranking question difficulty is demonstrated through empirical evaluation.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Proceedings Paper
Acoustics
Yang Guo, Jeanette Wen Jun Poh, Cheryl Sze Yin Wong, Savitha Ramasamy
Summary: This paper proposes a method for learning from a sequence of time-series tasks, which can handle missing values in multi-variate time-series and has good robustness.
2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
(2022)
Article
Automation & Control Systems
Abeegithan Jeyasothy, Sundaram Suresh, Savitha Ramasamy, Narasimhan Sundararajan
Summary: This article introduces a new approach to interpret a spiking neural network classifier by transforming it into a multiclass additive model and demonstrates its interpretability on the multiclass Iris dataset. The performance evaluation on ten benchmark datasets shows that both the Mc-SEFRON and DIMA classifiers have similar accuracies, with DIMA providing better interpretability. Furthermore, on three real-world credit scoring problems, DIMA improves classification accuracy by up to 12% compared to other interpretable classifiers.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Chemistry, Physical
Shijing Sun, Noor T. P. Hartono, Zekun D. Ren, Felipe Oviedo, Antonio M. Buscemi, Mariya Layurova, De Xin Chen, Tofunmi Ogunfunmi, Janak Thapa, Savitha Ramasamy, Charles Settens, Brian L. DeCost, Aaron G. Kusne, Zhe Liu, Siyu I. P. Tian, Ian Marius Peters, Juan-Pablo Correa-Baena, Tonio Buonassisi
Proceedings Paper
Computer Science, Artificial Intelligence
A. Ashutosh, R. Savitha, S. Suresh
2017 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2017)
Proceedings Paper
Engineering, Electrical & Electronic
Savitha Ramasamy, Kanagasabai Rajaraman
TENCON 2017 - 2017 IEEE REGION 10 CONFERENCE
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Krishna N. Kumar, R. Savitha, Abdullah Al Mamun
2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2016)
Article
Engineering, Marine
Chunhao Jiang, Lin Lin, Nian-Zhong Chen
Summary: A novel type of side structure for enhancing the crashworthiness of double-hull vessels is proposed based on auxetic materials. Numerical simulation demonstrates the resistance to collision of three different unit cells. A comparative study shows that the proposed side structures have superior energy absorption and collision resistance compared to traditional side structures.
Article
Engineering, Marine
Lihua Xu, Jiasong Wang, Michael S. Triantafyllou, Dixia Fan
Summary: This paper presents a data assimilation method based on the POD-DeepONet structure to fuse two types of fidelity data from vortex-induced vibration (VIV) problems. The POD-DeepONet structure provides better accuracy and more stable predictions for amplitude response, successfully capturing the changing trend with the oncoming flow speed. The exponentially fitted MSE formula allows for quick determination of the required case number under the expected error.
Article
Engineering, Marine
Ilias Gavriilidis, Aris G. Stamou, Christos Palagas, Efthimios Dourdounis, Nikos Voudouris, Athanasios Tazedakis, Spyros A. Karamanos
Summary: This study investigated the collapse resistance of thick-walled steel pipes fabricated with the JCO-E process for deep offshore applications. It conducted a comprehensive analysis using experimental, numerical, and analytical approaches to examine the effects of heat treatment on the collapse behavior of two JCO-E pipes. The results were compared with the predictions of the DNV-ST-F101 standard, and the fabrication factor afa was discussed. The study also explored the impact of yield strength recovery due to heat treatment on the collapse of pipes with different D/t ratios.
Article
Engineering, Marine
Sung-Jae Kim, Chungkuk Jin, MooHyun Kim
Summary: This study evaluates the effects of tsunami waves on the global performance of a spread-moored Floating Storage Unit (FSU) through tsunami-floater-mooring coupled dynamics simulations. The results show that larger tsunami heights and relatively short durations result in significantly increased motions and mooring tensions of the FSU.
Article
Engineering, Marine
Ling Zhu, Zhihui Zhou, Preben Terndrup Pedersen
Summary: Ship grounding experiments are crucial for validating numerical analysis and theoretical formulations. In this study, small-scale ship model grounding tests on a sharp rock were conducted in a water tank to observe and record different damage modes, ship bottom plate damage extents, and ship motion. The test results were used to analyze the energy dissipation process and the influence of initial conditions on ship response and damage.
Article
Engineering, Marine
Zhiping Zheng, Yanlin Shao, Jikang Chen
Summary: This study investigates the effect of horizontal low-frequency (LF) displacements and velocities on the responses of floating structures in irregular waves, focusing on a deep-draft spar buoy. The study finds that incorporating LF displacements and velocities in the seakeeping analysis is essential for reducing surge and pitch responses. The standard deviations of LF surge and pitch motions scale with significant wave height, highlighting viscous damping as the dominating damping mechanism.
Article
Engineering, Marine
Birendra Chaudhary, Hewenxuan Li, Akongnwi Nfor Ngwa, Helio Matos
Summary: This study investigates the long-term performance and effectiveness of coating systems for 3D-printed pressure vessels subjected to accelerated aging. The results show that the application of polyurethane coating systems significantly slows the degradation process, reducing critical operational depth and increasing pressure differential. This research contributes important insights into enhancing the longevity and performance of 3D-printed pressure vessels through coating systems.
Article
Engineering, Marine
Yuelin Song, Qin Dong, Jiping Zhang, Guoqiang Li, Dongfang Xu, Ping Yang
Summary: The objective of this research is to study the characteristics of low-cycle fatigue crack propagation from the perspective of accumulative plastic damage and propose a reliable prediction model for crack growth in EH-36 steel under high stress levels. Experimental findings demonstrate that increasing the mean stress and stress amplitude accelerates the progression of fatigue damage.
Article
Engineering, Marine
Hao Ding, Bo Huang, Liang Cheng, Ke Li, Qingyang Ren
Summary: This study investigates the dynamic response and cable forces of a submerged floating tunnel (SFT) under wave and wave-current interactions. Experimental results show that wave height, current velocity, and ratio of wavelength to structure size are important factors affecting the dynamic response of SFT and cable forces. The multi-anchor cable arrangement used in the experiments distributes cable forces more effectively and reduces potential safety hazards caused by cable breakage.
Article
Engineering, Marine
Baoshun Zhou, Zhixun Yang, Mostafa Amini-Afshar, Yanlin Shao, Harry B. Bingham
Summary: In the hydroelastic analysis of large floating structures, accurate prediction of response relies on the structural stiffness. However, obtaining exact structural stiffness is challenging due to the complexity of modern ship structures. This study proposes an efficient analysis technique that combines finite element and finite difference methods to calculate structural stiffness and solve hydrodynamic problems.
Article
Engineering, Marine
Xinwei Chen, Yang Yu, Lei Wang
Summary: This study introduces a framework to evaluate and compare scour prediction models, focusing on design robustness. By applying this framework, the study recommends the most favorable scour prediction model and optimal design for monopiles in OWTs.
Article
Engineering, Marine
Yu Lei, Wei Li, Xiang Yuan Zheng, Huadong Zheng, Shan Gao, Shengxiao Zhao
Summary: This paper compares the numerical results of a floating offshore wind turbine integrated with a steel fish farming cage (FOWT-SFFC) against experimental data. The study shows that the simulated responses are in good agreement with the experimental data and reveals the important influence of second-order wave forces on the simulation results.
Article
Engineering, Marine
Chenyu Luan, Torgeir Moan, Knut Andreas Kvale, Zhengshun Cheng
Summary: This paper deals with the study of the shear lag effect on the bending moment distribution in pontoon-type floating bridges. Comparative and parametric studies are carried out using beam and linear shell models to analyze the influence of shear lag on the bending stiffness and eigenmode shapes of the bridges. The study shows that elementary beam models may inaccurately predict the bending moments in bridges with large width and short span lengths, and a practical method is proposed to determine when caution is needed in using these models. The paper also highlights the complex boundary conditions near the bank abutment and the significant influence of shear lag on the bending moments in this region.
Article
Engineering, Marine
Akira Tatsumi, Yuji Kageyama
Summary: This study proposes a methodology to quantify the uncertainty of the ultimate strength of stiffened panels in steel ships and offshore structures due to the welding initial deflection. A statistical model of the initial deflection shape is developed based on measured data, and probability distributions of the ultimate strength are calculated using Monte Carlo simulation.
Article
Engineering, Marine
Zhenmian Li, Yang Yu, Xin Liu, Xiaowei Liu, Xiangyang Wang, Leige Xu, Jianxing Yu
Summary: This study evaluates the local collapses and propagating buckles of offshore pipelines under external overpressure, reverse fault displacements, and collapse failures. Different designs of integral arrestors are tested in a numerical model, and the effects of fault dip angles are investigated. The results show that integral arrestors are effective in preventing propagating buckles.