Harbor and coastal structures: A review of mechanical fatigue under random wave loading

Jimenez-Martinez, Moises

doi:10.1016/j.heliyon.2021.e08241

Cited by 19 publications

(7 citation statements)

References 132 publications

(148 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ref. [9] employed the ensemble of random Gaussian Laplace eigenfunctions on 3D arithmetic random waves and studied the distribution of their nodal surface area. In their study, they have shown that the nodal area variance follows an asymptotic and thus, the expected area is proportional to the square root of the eigenvalue (energy) of the eigenfunction.…”

Section: Literature Reviewmentioning

confidence: 99%

An Analysis of the Atlantic Ocean Wave Via Random Cosine and Sine Alternate Wavy ARIMA Functions

Olanrewaju¹,

Jallow²,

Olanrewaju³

2022

IJISA

View full text Add to dashboard Cite

In this research, alternate random wave sine and cosine for discrete time-varying processes via Autoregressive Integrated Moving Average (ARIMA) in a deterministic manner were developed. The mean and variance of the cosine and sine periodical time-varying wavy functions were derived such that Maclaurin series via full Taylor series expansion was used to rewrite the mean and variance functions. Wavy buoys of sea temperature, significant wave height, and mean wave direction of Belmullet Inner (Berth B) and Belmullet Outer (Berth A) of the Atlantic Ocean based on the west coastal of Ireland were subjected to the random sine and cosine wave functions of ARIMA. Cosine-ARIMA (1, 1, 3) and cosine-ARIMA (0, 1, 1) were the sea temperature inner and outer oceanic climate wave buoys of Berth B and A with time-periods of 8437.5 and 8035.714 respectively. Cosine-ARIMA (5, 1, 0) gave minimum performance for peak direction of inner and outer oceanic climate wave buoys of both Berth B and A, but with different time-periods of 168750 and 56250 respectively. Lastly, cosine-ARIMA (2, 1, 2) and sine-ARIMA (0, 1, 5) put in the ideal generalization for wave height of Berth B and A with the same associated wave time-periods of 56250, that is, it takes 56250 seconds to complete one swaying cycle.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

An Analysis of the Atlantic Ocean Wave Via Random Cosine and Sine Alternate Wavy ARIMA Functions

Olanrewaju¹,

Jallow²,

Olanrewaju³

2022

IJISA

View full text Add to dashboard Cite

show abstract

“…Wave climate change can greatly affect the life of offshore structures due to its significant alternations during the year, and because it depends on different agents, such as tidal and moon impacts, temperature, typhoons, etc. [60]. Du et al reported that if the simultaneous effects of marine corrosion and wave climate change on fatigue life are overlooked, it is possible that fatigue life evaluation faces up to a 35% error in the long term [61].…”

Section: Reliability and Failure Probabilitymentioning

confidence: 99%

A Comprehensive Review on Design, Monitoring, and Failure in Fixed Offshore Platforms

Amiri

Shaterabadi

Kashyzadeh

et al. 2021

JMSE

View full text Add to dashboard Cite

Offshore platforms have had diverse applications in the marine industry, for example, oil or gas platforms can provide facilities to store the oil and gas before transport those to refineries. Offshore wind turbines are another well-known use of the offshore platform for generating power. As platforms encounter various strong forces from water and wind currents, the materials used for these structures are mainly steel or concrete. These platforms are classified into different types, according to the depth of water and their applications. In addition, offshore platforms, as artificial reefs may be used for decades at different marine conditions. Consequently, their design and maintenance are very important, otherwise, they can cause irreparable damage to the environment. This paper presents the latest and most significant design and monitoring methods, such as the optimal probabilistic seismic demand model, multi-objective optimization, dynamic response assessment, robust fault-tolerant control, etc., under different environmental and geographical conditions. Moreover, the effective factors on the life and failure of these offshore structures are comprehensively introduced to enhance awareness of them, which can be very helpful to improve the design and construction of more reliable and durable structures.

show abstract

“…In maritime environments, systems are more susceptible to faults than in other environments due to environmental perturbations [ 1 , 2 ], corrosive conditions [ 3 , 4 ], and floating debris [ 5 , 6 , 7 ]. Moreover, recent research on navigational efficiency [ 8 , 9 ], use of renewable energy [ 10 , 11 , 12 , 13 , 14 ], situation awareness [ 11 , 15 ], improved communication methods [ 16 , 17 ], etc., applied to surface platforms is broadening spatial and temporal boundaries for unmanned surface platforms.…”

Section: Introductionmentioning

confidence: 99%

Unmanned Surface Vehicle Thruster Fault Diagnosis via Vibration Signal Wavelet Transform and Vision Transformer under Varying Rotational Speed Conditions

Cho,

Park,

Choo

et al. 2024

Sensors

View full text Add to dashboard Cite

Among unmanned surface vehicle (USV) components, underwater thrusters are pivotal in their mission execution integrity. Yet, these thrusters directly interact with marine environments, making them perpetually susceptible to malfunctions. To diagnose thruster faults, a non-invasive and cost-effective vibration-based methodology that does not require altering existing systems is employed. However, the vibration data collected within the hull is influenced by propeller-fluid interactions, hull damping, and structural resonant frequencies, resulting in noise and unpredictability. Furthermore, to differentiate faults not only at fixed rotational speeds but also over the entire range of a thruster’s rotational speeds, traditional frequency analysis based on the Fourier transform cannot be utilized. Hence, Continuous Wavelet Transform (CWT), known for attributions encapsulating physical characteristics in both time-frequency domain nuances, was applied to address these complications and transform vibration data into a scalogram. CWT results are diagnosed using a Vision Transformer (ViT) classifier known for its global context awareness in image processing. The effectiveness of this diagnosis approach was verified through experiments using a USV designed for field experiments. Seven cases with different fault types and severity were diagnosed and yielded average accuracy of 0.9855 and 0.9908 at different vibration points, respectively.

show abstract

Harbor and coastal structures: A review of mechanical fatigue under random wave loading

Cited by 19 publications

References 132 publications

An Analysis of the Atlantic Ocean Wave Via Random Cosine and Sine Alternate Wavy ARIMA Functions

An Analysis of the Atlantic Ocean Wave Via Random Cosine and Sine Alternate Wavy ARIMA Functions

A Comprehensive Review on Design, Monitoring, and Failure in Fixed Offshore Platforms

Unmanned Surface Vehicle Thruster Fault Diagnosis via Vibration Signal Wavelet Transform and Vision Transformer under Varying Rotational Speed Conditions

Contact Info

Product

Resources

About