The Wave Heights Distribution of Random Wave Based on Ocean Basin

Firdaus, Nurman; Ali, Baharuddin; Nasir, Mochammad; Muryadin, M

doi:10.14710/kapal.v17i3.31021

Cited by 2 publications

(1 citation statement)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is because there is a suitability for archipelagic waters such as Indonesian [11]. The equation of Jonswap spectra model used to generate the irregular waves in ocean basin can be seen from this reference [12]. The wave spectra used in the present experimental condition are shown in Figure 5.…”

Section: Experimental Conditionmentioning

confidence: 99%

Experimental Study on Coupled Motion of Floating Crane Barge and Lifted Module in Irregular Waves

Firdaus

Djatmiko

Prastianto

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

Self Cite

View full text Add to dashboard Cite

Installation and decommissioning activities of offshore structures often applied a floating crane barge for a lifting operation. The excessive movement response of lifted module affected by the motion of floating crane barge in waves can increase a large amplitude. However, the coupled motions of a floating crane barge and lifted module are not easy to predict accurately due to the dynamic movement of a lifted module and the complex coupling system. The coupled motion responses of a floating crane barge and a lifted module during lifting operation were investigated based on time domain by experimental method in this study. The model tests are carried out at Manoeuvring and Ocean Basin of Indonesian Hydrodynamic Laboratory, BRIN. The experimental conditions include the load cases of without and with a load of lifted module in crane tip, and the lifting operation was evaluated under irregular wave conditions. The experimental results show in that the phenomena of shift resonant frequency for the dynamic responses are clearly observed on the coupled motion of multibody system. The dynamic oscillations of the lifted module have a significant effect on the motion response of the floating crane barge. And the hoisting of lifted module has an obstructed effect on the rolling motion of crane barge.

show abstract

Section: Experimental Conditionmentioning

confidence: 99%

Experimental Study on Coupled Motion of Floating Crane Barge and Lifted Module in Irregular Waves

Firdaus

Djatmiko

Prastianto

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

A novel framework for predicting active flow control by combining deep reinforcement learning and masked deep neural network

Liu,

Wang,

Zhao

et al. 2024

Physics of Fluids

View full text Add to dashboard Cite

Active flow control (AFC) through deep reinforcement learning (DRL) is computationally demanding. To address this, a masked deep neural network (MDNN), aiming to replace the computational fluid dynamics (CFD) environment, is developed to predict unsteady flow fields under the influence of arbitrary object motion. Then, a novel DRL-MDNN framework that combines the MDNN-based environment with the DRL algorithm is proposed. To validate the reliability of the framework, a blind test in a pulsating baffle system is designed. Vibration damping is considered to be the objective, and a traditional DRL-CFD framework is constructed for comparison. After training, a spatiotemporal evolution of 200 time steps under the influence of arbitrary object motion is predicted by the MDNN. The details of the flow field are compared with the CFD results, and a relative error within 5% is achieved, which satisfies the accuracy of serving as an interactive environment for DRL algorithms. The DRL-MDNN and traditional DRL-CFD frameworks are then applied to the pulsating baffle system to find the optimal control strategy. The results indicate that both frameworks achieve similar control performance, reducing vibration by 90%. Considering the resources expended in establishing the database, the computational resource consumption of the DRL-MDNN framework is reduced by 95%, and the interactive response time during each episode is decreased by 98.84% compared to the traditional DRL-CFD framework.

show abstract

The Wave Heights Distribution of Random Wave Based on Ocean Basin

Cited by 2 publications

References 16 publications

Experimental Study on Coupled Motion of Floating Crane Barge and Lifted Module in Irregular Waves

Experimental Study on Coupled Motion of Floating Crane Barge and Lifted Module in Irregular Waves

A novel framework for predicting active flow control by combining deep reinforcement learning and masked deep neural network

Contact Info

Product

Resources

About