Frequency Domain Response of Jacket Platforms under Random Wave Loads

Han, Xiaoshuang; Qiao, Weiliang; Zhou, Bo

doi:10.3390/jmse7100328

Cited by 7 publications

(2 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An OJP as a real case study is considered in the North Sea encountered harsh environmental conditions to demonstrate the application of the proposed methodology. Some conventional studies have been conducted to investigate the OJPs' performance in the North Sea; however, the structures have not been exposed to harsh environmental conditions [28,29]. In the present paper, an OJP encountered a harsh environmental condition in different return periods due to extreme wave loading for evaluating the structure's nonlinear dynamic behavior in survival conditions.…”

Section: Application Of the Developed Methodology: A Case Studymentioning

confidence: 97%

Predicting Extreme Dynamic Response of Offshore Jacket Platform Subject to Harsh Environment

Khalaj¹,

BahooToroody²,

Leoni

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Offshore jacket platforms (OJPs) may be exposed to harsh environmental conditions during their operation in different return periods. It is necessary to evaluate the dynamic performance of the OJPs subjected to extreme wave loadings to secure a safe operation. In the earlier studies, various approaches were introduced to analyze the response of an OJP in different sea states. However, the serious shortcoming of the proposed methods is computationally time consuming and requires a considerable amount of simulations to evaluate the performance of the OJP. Accordingly, these approaches would not analyze the dynamic performance of the OJP realistically. In this study, the dynamic performance of an OJP subject to a harsh environment is evaluated considering a time-domain simulation. The developed model will result in a more realistic response by simulating the whole structure subjected to 1800 seconds of extreme wave loading in the light of the sea environment randomness. The application of the methodology is demonstrated by assessing the performance of a fabricated OJP subjected to extreme wave loadings in the North Sea. The dynamic analysis shows that among all assigned probability distribution functions (PDFs), the most suitable distribution for predicting the maximum deck displacement in all return periods was generalized extreme value (GEV). Moreover, the results show that the response of the structure is likely to remain in the safe limit condition in the 1 -year return period. In contrast, in other return periods, the OJP will exceed the safe limit condition. The proposed method is beneficial for future risk and reliability analyses that require a great deal of data derived from numerical simulations.

show abstract

Section: Application Of the Developed Methodology: A Case Studymentioning

confidence: 97%

Predicting Extreme Dynamic Response of Offshore Jacket Platform Subject to Harsh Environment

Khalaj¹,

BahooToroody²,

Leoni

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Moreover, due to the introduction of fast Fourier transform (FFT) and other algorithms [33], the operational efficiency of frequency domain algorithms has also been greatly improved. Therefore, frequency domain algorithms have been more and more widely used [34][35]. Therefore, frequency domain analysis is adopted for vibration signal analysis in this experiment.…”

Section: Vibration Signal Analysismentioning

confidence: 99%

Research on fault diagnosis method of electromechanical transmission system based on one-dimensional convolutional neural network with variable learning rate

Liu¹,

Chen²,

Yu³

et al. 2023

J. vibroeng.

View full text Add to dashboard Cite

As an important part of many mechanical equipment, the mechanical transmission system is very important to carry out efficient and accurate fault monitoring and diagnosis. Compared with traditional fault diagnosis techniques, such as spectrum analysis, deep learning has been widely used in the field of mechanical system fault diagnosis due to its powerful data expression ability, and has achieved certain research results. One-dimensional convolutional neural network is a widely used model for deep learning, so in this paper, the one-dimensional convolutional neural network (1D-CNN) in the deep learning theory and the vibration signal analysis method are integrated and applied to the fault identification of mechanical transmission system to achieve accurate diagnosis and classification of faults. The experiment is mainly to collect the vibration signal data of different fault states such as broken teeth, cracking, shaft unbalance, bearing wear, and excessive friction of the driven wheel of the mechanical transmission system, it was divided into training set and testing set according to an appropriate proportion, and 1D-CNN was built using Python. The deep learning model deeply analyzed the influence of different data sample sizes and different model parameters on the recognition accuracy, and obtained an ideal diagnostic model based on variable learning rate through parameter adjustment and comparative analysis. This experimental results show that the recognition method based on one-dimensional convolutional neural network can be effectively applied to the fault diagnosis of related mechanical transmission, and has a high diagnosis accuracy.

show abstract

Frequency-Domain 3D Computer Program for Predicting Motions and Loads on a Ship in Regular Waves

Abbasnia,

Sutulo,

Soares

2024

J. Marine. Sci. Appl.

View full text Add to dashboard Cite

The development of an in-house computer program for determining the motions and loads of advancing ships through sea waves in the frequency domain, is described in this paper. The code is based on the potential flow formulation and originates from a double-body code enhanced with the regular part of the velocity potential computed using the pulsing source Green function. The code is fully developed in C++ language with extensive use of the object-oriented paradigm. The code is capable of estimating the excitation and inertial radiation loads or arbitrary incoming wave frequencies and incidence angles. The hydrodynamic responses such as hydrodynamic coefficients, ship motions, the vertical shear force and the vertical bending moment are estimated. A benchmark container ship and an LNG carrier are selected for testing and validating the computer code. The obtained results are compared with the available experimental data which demonstrate the acceptable compliance for the zero speed whereas there are some discrepancies over the range of frequencies for the advancing ship in different heading angles.

show abstract

Frequency Domain Response of Jacket Platforms under Random Wave Loads

Cited by 7 publications

References 16 publications

Predicting Extreme Dynamic Response of Offshore Jacket Platform Subject to Harsh Environment

Predicting Extreme Dynamic Response of Offshore Jacket Platform Subject to Harsh Environment

Research on fault diagnosis method of electromechanical transmission system based on one-dimensional convolutional neural network with variable learning rate

Frequency-Domain 3D Computer Program for Predicting Motions and Loads on a Ship in Regular Waves

Contact Info

Product

Resources

About