Modeling and simulation to optimize cargo tank heating

• Main Author: Lim, Xiu Wen
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Final Year Project
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering
• Online Access: http://hdl.handle.net/10356/61017
• Institution: Nanyang Technological University

High consumption of fuel oil concurrent with the increase in fuel pricing have prompted the research into optimizing the cargo oil heating process during marine transportation so as to maximize the efficiency of fuel oil consumption. Project started off with industrial collaboration with AET Tankers (Singapore) Pte Ltd to effectively manage the heat system in the ship. Cargo oil heating time is the key to save energy and optimize fuel oil consumption, and one of the methods is to study the heat loss of the cargo heating system. Taking into account that cargo heating system consist of piping system and cargo tanks, this project analyses the heat loss of piping system, which consists of return-water and steam pipelines. This project also study the effects of various parameters on heat loss of pipelines which includes mass flow rate of water and steam, relative wind speed, air temperature and steam pressure. Steam piping system was split into two different sections, lower deck pipe and main deck pipe. Lower deck pipe is inside the ship and insulated with glass-wool while main deck pipe are not insulated and are exposed to the surrounding. 2-branched water and steam pipelines were first modelled using Solidworks software and simulations were conducted using ANSYS FLUENT. In order to save computational time and cost using ANSYS FLUENT, an analytical model was developed based on thermodynamics theory using MATLAB software. The source code was then validated against the CFD (Computational Fluid Dynamics) results. The validation results have shown that the deviation error is well within the acceptable range with highest deviation error in water pipeline of 11% and 13% in steam pipeline. Therefore, the same model can be used for the generation of database for 12-branched water and steam pipeline with acceptable accuracy. By developing a new fast optimization algorithm for the pipeline heating system, it helps the company to save costs by optimizing the boiler fuel consumption. The development of this source code will enable the ship captain to have a better gauge in cargo heating duration hence, improving the company’s cargo heating operations and management.