scholarly journals Design and Construction of a Modular Pump-Jet Thruster for Autonomous Surface Vehicle Operations in Extremely Shallow Water

2019 ◽  
Vol 7 (7) ◽  
pp. 222 ◽  
Author(s):  
Angelo Odetti ◽  
Marco Altosole ◽  
Gabriele Bruzzone ◽  
Massimo Caccia ◽  
Michele Viviani
Keyword(s):  
Environmental Monitoring ◽  
Water Depth ◽  
Electric Propulsion ◽  
Shallow Waters ◽  
3D Printer ◽  
Flat Bottom ◽  
Autonomous Surface Vehicles ◽  
Autonomous Surface Vehicle ◽  
Innovative Materials ◽  
Propulsion Unit

This paper describes a customized thruster for Autonomous Surface Vehicles (ASV). The thruster is a Pump-Jet Module (PJM), which has been expressly designed, modeled, constructed, and tested for small-/medium-sized ASVs that perform environmental monitoring in extremely shallow waters such as wetlands (rivers, lakes, swamps, marshes), where water depth is only a few centimeters. The PJM is a fully-electric propulsion unit with a 360-degree continuous steering capability. Its main advantage is that the unit is flush with the flat bottom of the vehicle. This makes the PJM suitable for operation in extremely shallow waters because the risk of damaging the thrusting unit in case of grounding is very limited. The PJM was produced using innovative materials, and the hydraulic components were all constructed using a 3D printer.

scholarly journals RESPONSE OF POSIDONIA OCEANICA TO WAVE MOTION IN SHALLOW-WATERS - PRELIMINARY EXPERIMENTAL RESULTS

2011 ◽  
Vol 1 (32) ◽  
pp. 49 ◽  
Author(s):  
Luca Cavallaro ◽  
Carlo Lo Re ◽  
Giovanni Paratore ◽  
Antonino Viviano ◽  
Enrico Foti
Keyword(s):  
Laboratory Investigation ◽  
Water Depth ◽  
Wave Motion ◽  
Aquatic Vegetation ◽  
Plastic Material ◽  
Posidonia Oceanica ◽  
Shallow Waters ◽  
Experimental Laboratory ◽  
The Waves ◽  
Acquisition Technique

Aim of the present work is to contribute to the knowledge about the interaction between the flow induced by wave and the aquatic vegetation. More in details the results of preliminary tests of an experimental laboratory investigation about the response of a Posidonia Oceanica meadow to wave motion in shallow waters is reported. A wide attention was posed to the behavior of a synthetic plants with plastic material. To this aim an image acquisition technique was used to analyze and compare the movement of both the artificial plant and the real one. The experiments carried out about the interaction between the artificial meadow and the waves showed a significant wave dumping, in particular in the case of plants having the same length of the water depth.

scholarly journals Diffuse reflectance of oceanic shallow waters: Influence of water depth and bottom albedo

1994 ◽  
Vol 39 (7) ◽  
pp. 1689-1703 ◽  
Author(s):  
Stéphane Maritorena ◽  
André Morel ◽  
Bernard Gentili
Keyword(s):  
Water Depth ◽  
Diffuse Reflectance ◽  
Shallow Waters ◽  
Influence Of Water ◽  
Bottom Albedo

Dynamic Model Identification of Marine Electric Propulsion System

2012 ◽  
Vol 503-504 ◽  
pp. 1357-1359
Author(s):  
Qiang Wu ◽  
Hao Xiong ◽  
Guang Wei Meng ◽  
Li Bing Zhou
Keyword(s):  
Dynamic Model ◽  
Electric Propulsion ◽  
System Analysis ◽  
Model Identification ◽  
Propulsion System ◽  
Experimental Result ◽  
Experiment Data ◽  
Electric Propulsion System ◽  
Identification Technique ◽  
Propulsion Unit

This paper applies identification technique to the marine electric propulsion system analysis, adopts the recursive extended least squares (RELS) algorithm to estimate the structure and parameters of the model, employs the variable forgetting factors into the algorithm to improve the tracking characteristic of the parameters, establishes the dynamic model of a simulated electric propulsion unit under the excitation control based on the experiment data, and finally verifies the validity of the method through the consistency between simulation result and experimental result.

scholarly journals An Experimental Investigation of the Trim Effect on the Behaviour of a Containership in Shallow Water

2019 ◽  
Author(s):  
Khaled Elsherbiny ◽  
Tahsin Tezdogan ◽  
Mohamed Kotb ◽  
Atilla Incecik ◽  
Sandy Day
Keyword(s):  
Experimental Investigation ◽  
Water Depth ◽  
Experimental Work ◽  
Water Resistance ◽  
Suez Canal ◽  
Shallow Waters ◽  
Container Ship ◽  
Ship Model ◽  
New Suez Canal ◽  
The University

Abstract A new division of the Suez Canal in Egypt, termed the New Suez Canal, was opened for international navigation in August 2015. It is therefore important to ensure the safety of ships navigating this new section of the canal. Measures to avoid grounding and/or drifting to the canal banks are necessary. Additionally, accurate prediction data for ship squat and under keel clearance is crucial. This paper presents the results of experimental work carried out at the Kelvin Hydrodynamic Laboratory at the University of Strathclyde, Glasgow, to study the effect of trim on containership sailing characteristics in shallow waters using Kriso Container Ship (KCS) model. A series of model tests were conducted to measure the resistance, sinkage variations with speed, water depth and loading conditions under different trimming angles at 1:75 scale. The objective of this work is to examine the range of ship trim for safe and efficient sailing in restricted water in both depth and width. The study also aimed to provide data to be used in validating numerical computations to be carried on the same type of vessel to detect the best trim angle for ships during sailing in restricted waters to reduce resistance and therefore fuel consumption. For depth Froude numbers higher than 0.4, the results show that the ship model sinkage is less for aft trim than for level trim or forward trim. Concurrently, it can be observed that there is less water resistance for aft trim than for forward trim, albeit level trim shows the least resistance. The test was conducted for one value of model draft which was 0.144 m. Side bank effect were also examined.

scholarly journals BOUSSINESQ-TYPE EQUATIONS WITH VARIABLE COEFFICIENTS FOR NARROW-BANDED WAVE PROPAGATION FROM ARBITRARY DEPTHS TO SHALLOW WATERS

2012 ◽  
Vol 1 (33) ◽  
pp. 5
Author(s):  
Gonzalo Simarro ◽  
Alvaro Galan ◽  
Alejandro Orfila
Keyword(s):  
Wave Propagation ◽  
Water Depth ◽  
Variable Coefficients ◽  
Shallow Waters ◽  
Type Model ◽  
Fully Nonlinear ◽  
Deep Waters ◽  
Proposed Model ◽  
Local Water ◽  
Wave Decomposition

A fully nonlinear Boussinessq-type model with 7 Nwogu’s α-like coefficients is considered. The model is one-layer and low-order to simplify the numerical solvability. The coefficients of the model are here considered functions of the local water depth so as to allow an improvement of the dispersive properties for narrow banded trains in very deep waters. The proposed model is fully nonlinear in weakly dispersive conditions, so that nonlinear wave decomposition in shallower waters is well reproduced.

scholarly journals Shoreline Detection and Land Segmentation for Autonomous Surface Vehicle Navigation with the Use of an Optical System

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2799
Author(s):  
Stanisław Hożyń ◽  
Jacek Zalewski
Keyword(s):  
Image Processing ◽  
Adaptive Filtering ◽  
Weather Conditions ◽  
Optical Systems ◽  
Probabilistic Clustering ◽  
Autonomous Surface Vehicles ◽  
Autonomous Surface Vehicle ◽  
Clustering Model ◽  
Surrounding Landscape ◽  
Traditional Image

Autonomous surface vehicles (ASVs) are a critical part of recent progressive marine technologies. Their development demands the capability of optical systems to understand and interpret the surrounding landscape. This capability plays an important role in the navigation of coastal areas a safe distance from land, which demands sophisticated image segmentation algorithms. For this purpose, some solutions, based on traditional image processing and neural networks, have been introduced. However, the solution of traditional image processing methods requires a set of parameters before execution, while the solution of a neural network demands a large database of labelled images. Our new solution, which avoids these drawbacks, is based on adaptive filtering and progressive segmentation. The adaptive filtering is deployed to suppress weak edges in the image, which is convenient for shoreline detection. Progressive segmentation is devoted to distinguishing the sky and land areas, using a probabilistic clustering model to improve performance. To verify the effectiveness of the proposed method, a set of images acquired from the vehicle’s operative camera were utilised. The results demonstrate that the proposed method performs with high accuracy regardless of distance from land or weather conditions.

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