scholarly journals Impact Analysis of Trim Tab Inclination Angles Variation to Propulsion Power Requirement of 6 Meter’s Speed Boat

Author(s):  
Amiadji Amiadji ◽  
Achmad Baidowi ◽  
Aufal Nanda Oktova
2012 ◽  
Vol 28 (01) ◽  
pp. 10-19
Author(s):  
Khairul Hassan ◽  
Maurice F. White ◽  
Cosmin Ciorta

When considering the design of a ship, an important objective is to always try and develop one that allows for maximum cargo capacity with the lowest propulsion power requirement while providing a sufficient amount of strength and stability for its safe operation. The ship with the lowest propulsion power consumes the least amount of fuel and produces the lowest amount of exhaust gas that may be harmful to the environment. In some cases, the aerodynamic resistance can be neglected, but for a high speed vessel such as a modern containership, the air resistance can be in the range of 2% to 10% of the total resistance. Aerodynamic resistance can therefore have a significant effect on power requirements and is strongly influenced by the height, breadth, and the number of container stacks on the deck. The freeboard, beam of the ship, deck house design, ship speed, wind speed, and water flow direction will also contribute significantly to a ship's resistance and required propulsive power. This paper outlines the application of computational fluid dynamic simulation as a design tool to find a strategy for the optimal arrangement of the container stacks on deck so that the vessel uses the lowest effective propulsion power to achieve a fuel efficient ship. It is deduced that an optimal stack arrangement can reduce air resistance by about 30%.


Author(s):  
Fangfang Wang ◽  
Han P. Bao

Current practice of emission estimate for ocean-going vessels largely relies on the conventional propeller law for determining power consumption. This practice tends to underestimate the actual emission when sea states and winds are ignored. This paper presents an evaluation of two approaches on the prediction of power of a container vessel. The first approach estimates vessel power as a function of the vessel speed according to the propeller law. While the propeller law approach is cost-effective and time-saving in computing vessel propulsion power, it generally under-estimates vessel propulsion power due to the omission of many other influencing factors including vessel course, engine model, ocean states and weather conditions. The second approach derives vessel propulsion power as a function of the vessel speed and resistance forces. The propulsion power required for a particular vessel behavior is determined based on vessel towing resistance, added resistance from waves and winds, and a variety of propeller and hull dependent efficiencies. Because of the incorporation of external factors, this approach should be more accurate than the propeller law in reflecting the actual vessel power requirement. Comparative analysis is conducted among the two estimate results and real measurement data on engine power output. The results clearly show that power estimated from the propeller law underestimate the vessel propulsion power and the gap increases much faster for higher vessel speeds. Power estimate from the second approach provides more accurate results as they greatly match the measured power values. The ups and downs of the prediction results precisely reflect real power variation along with speed changes. Improved power prediction leads to more reliable emission inventory calculation. However, the improvement of accuracy should be balanced with the increased requirement on data sources and computing efforts.


2011 ◽  
Author(s):  
Eric M. Dunleavy ◽  
Nancy T. Tippins ◽  
Frederick L. Oswald

CICTP 2020 ◽  
2020 ◽  
Author(s):  
Yanli Wang ◽  
Hao Sun ◽  
Sicheng Hao ◽  
Bing Wu

2020 ◽  
pp. 116-122
Author(s):  
Emre Öztürk ◽  
Mehmet Aktaş ◽  
Tunç Şenyüz

The purpose of this research is to reach good correlation between sun load simulation and solar focusing test for exterior automotive lighting products. Light coming from sun is highly collimated (parallel rays) and focusable from lenses with concave structure. Focusing incidence leads to a hot spot on lens surrounding plastic parts which may cause melting failures at high temperature zones. Sun load simulation is performing to eliminate risk of discoloration, deformation, out gassing, coating failures and fire with prolonged exposure from field. Irradiance values in W/m2 defined in simulation as heat source depending of an angle of incidence of the sun radiation. At first step, simulation is performing with 5 degree intervals to define the critical zones then intervals decreased to 2 degree to detect the critical azimuth and inclination angles. Critical azimuth and inclination angles is checking with ray trace analysis to check the bouncing of sun rays and possible solution to eliminate focuses with design solutions. After numerical analysis to release and validate the automotive lighting products regarding the sun load test, measurement with first parts is necessary. Measurement is performing for all critical angles which have been detected at simulation with thermal camera under ultra high-collimation solar simulator. Measured temperatures are settled according to environment conditions and correlation is checking with simulations.


The university is considered one of the engines of growth in a local economy or its market area, since its direct contributions consist of 1) employment of faculty and staff, 2) services to students, and supply chain links vendors, all of which define the University’s Market area. Indirect contributions consist of those agents associated with the university in terms of community and civic events. Each of these activities represent economic benefits to their host communities and can be classified as the economic impact a university has on its local economy and whose spatial market area includes each of the above agents. In addition are the critical links to the University, which can be considered part of its Demand and Supply chain. This paper contributes to the field of Public/Private Impact Analysis, which is used to substantiate the social and economic benefits of cooperating for economic resources. We use Census data on Output of Goods and Services, Labor Income on Salaries, Wages and Benefits, Indirect State and Local Taxes, Property Tax Revenue, Population, and Inter-Industry to measure economic impact (Implan, 2016).


2012 ◽  
Vol 2 (8) ◽  
pp. 12-14 ◽  
Author(s):  
H. P. Singh H. P. Singh ◽  
◽  
R. P. S. Shaktawat R. P. S. Shaktawat ◽  
Durga Singh Durga Singh ◽  
S. C. Srivastava S. C. Srivastava

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