• Journal of the Society of Naval Architects of Korea
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• v.52 no.2
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• pp.110-118
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• 2015

Weather routing method is one of the best practices of SEEMP (Ship Energy Efficiency Management Plan) for fuel-efficient operation of ship. KR is carrying out a basic research for development of the weather routing algorithm and making a monitoring system by FOC (Fuel Oil Consumption) analysis compared to the reference, which is the great circle route. The added resistances applied global sea/weather data can be calculated using ship data, and the results can be corrected to ship motions. The global sea/weather data such as significant wave height, ocean current and wind data can be used to calculate the added resistances. The reference route in a usual navigation is the great circle route, which is the shortest distance route. The global sea/weather data can be divided into grids, and the nearest grid data from a ship's position can be used to apply a ocean going vessel's sea conditions. Powell method is used as an optimized routing technique to minimize FOC considered sea/weather conditions, and FOC result can be compared with the great circle route result.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.152-154
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• 2015

최적기상항로 추정의 주요 평가지수중 하나인 파랑중 부가저항의 모형시험을 이용하여 실해역의 불규칙파중 부가저항을 도출하였으며, 이를 평가지수로 갖는 A*알고리듬을 도입하여 최적기상항로를 추정하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.767-773
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• 2014

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and there have been various systems which have been recently studied. For a successful economic ship routing system, it is needed to properly control an engine power or change a geographical path considering weather forecast. An optimal geographical path is difficult to be determined, though, because it is a minimal dynamic-cost path search problem where the actual fuel consumption is dynamically variable by the weather condition when the ship will pass the area. In this paper, we propose an geographical path-search algorithm based on evolutionary strategy to efficiently search a good quality solution out of tremendous candidate solutions. We tested our approach with the shortest path-based sailing method over seven testing routes and observed that the former reduced the estimated fuel consumption than the latter by 1.82% on average and the maximum 2.49% with little difference of estimated time of arrival. In particular, we observed that our method can find a path to avoid bad weather through a case analysis.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.2
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• pp.99-106
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• 2014

Weather routing of a ship provides an optimal route to the destination by using minimal time or fuel in a given sea condition. These days, weather routing came into a spotlight with soaring fuel price and the environmental regulations of IMO and several countries. This study presents three scenarios of voyaging strategies for a ship and compared them in terms of the fuel consumption. The first strategy fixes the speed of a ship as a constant value for entire sailing course, the second fixes the RPM of the ship as constant for entire course, and the third determines the RPMs of the ship for each segment of the course. For each strategy, a ship route is optimized by using the $A^*$ search method. Wind, ocean current and wave are considered as ocean environment factors when seeking the optimal routes. Based on 7000 TEU container ship's sea trial records, simulation has been conducted for three scenarios, and the most efficient routing scenario is determined in the view of fuel consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.412-421
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• 2011

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and many such systems have been recently developed. Most of them assume that sailing is carried out with a constraint like a fixed output of engine-power or a fixed sailing speed. However, if the output of engine-power is controlled, it is possible to reduce the fuel consumption by sailing a ship under a relatively good weather condition. In this paper, we propose a novel economic ship routing system which can search optimal outputs of the engine-power for each part of a path by employing an evolutionary strategy. In addition, we develope an $A^*$ algorithm to find the shortest path and a method to enhance the degree of curve representation. These make the proposed system applicable to an arbitrary pair of departure and destination points. We compared our proposed system with another existing system not controlling output of the engine-power over 36 scenarios in total, and observed that the former reduced the estimated fuel consumption than the latter by 1.3% on average and the maximum 5.6% with little difference of estimated time of arrival.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.1 s.139
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• pp.57-63
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• 2005

This paper introduces basic research of optimum routing assessment system as voyage support purpose which can obtain safe and efficient route. In view point of safety, the prediction of ship motion should be evaluated in the condition of rough weather This part includes general seakeeping estimation based on 3 dimensional panel method and parametric roil prediction. For increasing voyage efficiency, ETA(Estimated Time of Arrival) and fuel consumption should be calculated considering speed reduction and power increase due to wave effects based on added resistance calculation and ship performance characteristics. Basically, the weather forecast is assumed to be prepared previously to operate this system. The idea of these factors in this system will be helpful to escape from dangerous voyage situation by wave conditions and to make optimum route planning based on ETA and fuel consumption.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.263-269
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• 2015

This paper proposes a new approach for solving the weather routing problem by dividing it into two phases with the goal of fuel saving. The problem is to decide two optimal variables: the heading angle and speed of the ship under several constraints. In the first phase, the optimal route is obtained using the Real-Time Adaptive A* algorithm with a fixed ship speed. In other words, only the heading angle is decided. The second phase is the speed scheduling phase. In this phase, the original problem, which is a nonlinear optimization problem, is converted into a geometric programming problem. By solving this geometric programming problem, which is a convex optimization problem, we can obtain an optimal speed scheduling solution very efficiently. A simple case of numerical simulation is conducted in order to validate the proposed method, and the results show that the proposed method can save fuel compared to a constant engine output voyage and constant speed voyage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.233-240
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• 2011

A field server was developed by using ubiquitous sensor network technology to monitor the abrupt weather variation in local or mountain area. The data transmissions between deployed field servers in local terrain are very important technology in disaster prevention monitoring system. Weather related information such as temperature, humidity, illumination, atmospheric pressure, dew point and meteorological data are collected from the designated field at a regular interval. The received information from the multiple sensors located at the sensor field is used flooding routing protocol transmission techniques and the sensing data is transferred to gateway through multi-hop method. Telosb sensor node are programmed by nesC language in TinyOS platform to monitor the weather parameters of the local terrain.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1564-1571
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• 2022

Wireless sensor network(WSN) is being used in various fields such as reconnaissance, echelon scale identification, weather observation, etc. using small sensors in an environment without a network infrastructure environment. In addition, WSN uses limited battery power, so study on routing protocols to extend the lifetime of the network is important. PEGASIS, a hierarchical routing protocol, accounts for the majority of energy-efficient routing protocol studies and is well known as a representative protocol. In this study, based on PEGASIS, we propose a protocol that constructs multiple chains rather than one chain using the AoA of nodes. The proposed protocol has the advantage of reducing the transmission distance of nodes and eliminating unnecessary transmissions, thereby increasing energy efficiency compared to the existing protocols.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.79-86
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• 2012

An economic ship routing means to sail a ship with a goal of minimizing the fuel consumption by utilizing weather forecast information, and various such systems have been recently studied. For a successful economic ship routing system, an efficient algorithm is needed to search an optimal geographical path, and most of the previous systems were approaching to that problem through a minimal static-cost path search algorithm based on the Dijkstra algorithm. To apply that kind of search algorithm, the cost of every edge assigned with the estimated fuel consumption should be constant. However, that assumption is not practical at all considering that the actual fuel consumption is determined by the weather condition when the ship will pass the edge. To overcome such a limitation, we propose a new optimal ship routing system based on a minimal dynamic-cost path search algorithm by properly modifying the Dijkstra algorithm. In addition, we propose a method which efficiently reduces the search space by using the $A^*$ algorithm to decrease the running time. We compared our system with the shortest path-based sailing method over ten testing routes and observed that the former reduced the estimated fuel consumption than the latter by 2.36% on average and the maximum 4.82% with little difference of estimated time of arrival.