signature=cfd355d9699274ad10eb13c018748c0e,Improved signature prediction through coupling of ShipIR ...

本文提出了一种新的功能接口,将北约标准的船舶红外特征模型(ShipIR)与ANSYS Fluent模型相结合,实现了热辐射预测的双向映射。此接口允许在CFD解决方案迭代后更新壁面和流体温度,并反馈到ShipIR以细化局部热传递系数,最终实现两模型间的收敛,误差在0.3°C内。该方法通过未公开研究船只(CFAV Quest)的热/红外模拟进行了详细展示,并讨论了使用实船测量验证未来模型的方法。

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Paper Abstract

Most existing platform signature models use semi-empirical correlations to predict flow convection on internal and

external surfaces, a key element in the prediction of accurate skin signature. Although these convection algorithms are

capable of predicting bulk heat transfer coefficients between each surface and the designated flow region, they are not capable

of capturing local effects such as flow stagnation, flow separation, and flow history. Most computational fluid dynamics

(CFD) codes lack the ability to predict changes in background solar and thermal irradiation with the environment and sun

location, nor do they include multi-bounce radiative surface exchanges by default in their solvers. Existing interfaces between

CFD and signature prediction typically involve a one-directional mapping of CFD predicted temperatures to the signature

model. This paper describes a new functional interface between the NATO-standard ship signature model (ShipIR) and the

ANSYS Fluent model, where a bi-directional mapping is used to transfer the thermal radiation predictions from ShipIR to

Fluent, and after re-iteration of the CFD solution, transfer the wall and fluid temperatures back to ShipIR for further

refinement of local-area heat transfer coefficients, and re-iteration of the ShipIR thermal solution. Both models converge

to an RMS difference of 0.3 °C within a few successive iterations (5-6). This new functional interface is described through

a detailed thermal/IR simulation of an unclassified research vessel, the Canadian Forces Auxiliary Vessel (CFAV) Quest.

Future efforts to validate this new modelling approach using shipboard measurements are also discussed.

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