Techno Press
Tp_Editing System.E (TES.E)
Login Search


ose
 
CONTENTS
Volume 10, Number 4, December 2020
 

Abstract
The performance of a multi-level overtopping wave energy converter (OWEC) has been numerically and experimentally investigated in a two-dimensional wave tank in order to study the effects of opening width of additional reservoirs. The device is a fixed OWEC consisting of an inclined ramp together with several reservoirs at different levels. A particle-based numerical simulation utilizing the Lattice Boltzmann Method (LBM) is used to simulate the flow behavior around the OWEC. Additionally, an experimental model is also built and tested in a small wave flume in order to validate the numerical results. A comparison in energy captured performance between single-level and multi-level devices has been proposed using the hydraulic efficiency. The enhancement of power capture performance is accomplished by increasing an overtopping flow rate captured by the extra reservoirs. However, a noticeably large opening of the extra reservoirs can result in a reduction in the power efficiency. The overtopping flow behavior into the reservoirs is also presented and discussed. Moreover, the results of hydrodynamic performance are compared with a similar study, of which a similar tendency is achieved. Nevertheless, the LBM simulations consume less computational time in both pre-processing and calculating phases.

Key Words
wave energy; marine renewable energy; overtopping; LBM

Address
Sirirat Jungrungruengtaworn, Ratthakrit Reabroy and
Nonthipat Thaweewat: Department of Maritime Engineering, Faculty of International Maritime Studies,
Kasetsart University, Chonburi, Thailand
Beom-Soo Hyun: Department of Naval Architecture and Ocean Systems Engineering,
Korea Maritime and Ocean University, Busan, Republic of Korea



Abstract
Heave compensation is a vital part of various marine and offshore operations. It is used in various applications, including the transfer of cargo between two vessels in the open ocean, installation of topsides of an offshore structure, offshore drilling and for surveillance, reconnaissance and monitoring. These applications typically involve a load suspended from a hydraulically powered winch that is connected to a vessel that is undergoing dynamic motion in the ocean environment. The goal in these applications is to design a winch controller to keep the load at a regulated height by rejecting the net heave motion of the winch arising from ship motions at sea. In this study, we analyze and compare the performance of various control algorithms in stabilizing a suspended load while the vessel is subjected to changing sea conditions. The KCS container ship is chosen as the vessel undergoing dynamic motion in the ocean. The negative of the net heave motion at the winch is provided as a reference signal to track. Various control strategies like Proportional-Derivative (PD) Control, Model Predictive Control (MPC), Linear Quadratic Integral Control (LQI), and Sliding Mode Control (SMC) are implemented and tuned for effective heave compensation. The performance of the controllers is compared with respect to heave compensation, disturbance rejection and noise attenuation.

Key Words
active heave compensation; winch control; PD; MPC; LQI; SMC

Address
Shrenik Zinage and Abhilash Somayajula: Department of Ocean Engineering, Indian Institute of Technology Madras, Chennai, India

Abstract
A floating bridge is an innovative solution for deep-water and long-distance crossing. This paper presents a curved floating bridge's dynamic behaviors under the wind, wave, and current loads. Since the present curved bridge need not have mooring lines, its deep-water application can be more straightforward than conventional straight floating bridges with mooring lines. We solve the coupled interaction among the bridge girders, pontoons, and columns in the time-domain and to consider various load combinations to evaluate each force's contribution to overall dynamic responses. Discrete pontoons are uniformly spaced, and the pontoon's hydrodynamic coefficients and excitation forces are computed in the frequency domain by using the potential-theory-based 3D diffraction/radiation program. In the successive time-domain simulation, the Cummins equation is used for solving the pontoon's dynamics, and the bridge girders and columns are modeled by the beam theory and finite element formulation. Then, all the components are fully coupled to solve the fully-coupled equation of motion. Subsequently, the wet natural frequencies for various bending modes are identified. Then, the time histories and spectra of the girder's dynamic responses are presented and systematically analyzed. The second-order difference-frequency wave force and slowly-varying wind force may significantly affect the girder's lateral responses through resonance if the bridge's lateral bending stiffness is not sufficient. On the other hand, the first-order wave-frequency forces play a crucial role in the vertical responses.

Key Words
floating curved bridge; elastic dynamic response; coupled dynamics; bending stiffness; pontoon; wave and wind excitations; resonance; second-order wave excitation

Address
Chungkuk Jin, MooHyun Kim, Woo Chul Chung and Do-Soo Kwon: Department of Ocean Engineering, Texas A&M University, 727 Ross St, College Station, TX 77843, USA

Abstract
Detecting objects is important for the safe operation of ships, and enables collision avoidance, risk detection, and autonomous sailing. This study proposes a ship detection method from images and videos taken at sea using one of the state-of-the-art deep neural network-based object detection algorithms. A deep learning model is trained using a public maritime dataset, and results show it can detect all types of floating objects and classify them into ten specific classes that include a ship, speedboat, and buoy. The proposed deep learning model is compared to a universal trained model that detects and classifies objects into general classes, such as a person, dog, car, and boat, and results show that the proposed model outperforms the other in the detection of maritime objects. Different deep neural network structures are then compared to obtain the best detection performance. The proposed model also shows a real-time detection speed of approximately 30 frames per second. Hence, it is expected that the proposed model can be used to detect maritime objects and reduce risks while at sea.

Key Words
object detection; ship detection; deep neural network; deep learning; maritime dataset

Address
Sung-Jun Lee: Department of Naval Architecture and Ocean Engineering, Seoul National University, Republic of Korea
Myung-Il Roh: Department of Naval Architecture and Ocean Engineering, and Research Institute of Marine Systems Engineering, Seoul National University, Seoul, Republic of Korea
Min-Jae Oh: School of Naval Architecture and Ocean Engineering, University of Ulsan, Ulsan, Republic of Korea

Abstract
This paper proposes a method to estimate the underwater target object's yaw angle using a sonar image. A simulator modeling imaging mechanism of a sonar sensor and a generative adversarial network for style transfer generates realistic template images of the target object by predicting shapes according to the viewing angles. Then, the target object's yaw angle can be estimated by comparing the template images and a shape taken in real sonar images. We verified the proposed method by conducting water tank experiments. The proposed method was also applied to AUV in field experiments. The proposed method, which provides bearing information between underwater objects and the sonar sensor, can be applied to algorithms such as underwater localization or multi-view-based underwater object recognition.

Key Words
sonar GAN; underwater GAN; object detection; sonar simulator; underwater sonar image; underwater object detection; acoustic landmark

Address
Minsung Sung and Son-Cheol Yu: Department of IT Engineering, Pohang University of Science and Technology (POSTECH), 77 Cheongam-ro, Nam-gu, Pohang, Republic of Korea



Techno-Press: Publishers of international journals and conference proceedings.       Copyright © 2021 Techno-Press
P.O. Box 33, Yuseong, Daejeon 34186 Korea, Tel: +82-42-828-7996, Fax : +82-2-736-6801, Email: info@techno-press.com