Analysis of the Transient Cooldown of Sub-Sea Pipelines

Author(s):  
J. Jhordann Barrera Escobedo ◽  
Angela O. Nieckele ◽  
Luis Fernando A. Azevedo

A precise analysis of the transient cooldown of subsea pipelines is crucial for offshore flow assurance, to avoid, for example, hydrate formation or wax deposition. Flow assurance in transportation lines, where column separation can occur due to large temperature drop coupled with large pressure drop, must also be addressed. Usually, pipeline thermal insulation is designed for steady state conditions. However, during shutdowns, the temperature drop experienced by the stagnant fluid is more pronounced, eventually reaching some critical temperature level, that can lead to flow line blockage and flow re-start problems. Thus, the determination of the temperature and pressure distributions along the pipeline under transient conditions is important to maintain the line operating safely. To determine the transient heat transfer in pipelines, the fluid flow conservation equations coupled with the heat conduction equation applied to the pipeline wall were numerically solved. The heat loss from the pipeline was determined by solving the transient heat conduction equation for the pipewall layers, utilizing a simple one-dimensional model in the radial direction. The coupled system was solved numerically employing the finite difference method. Transient analyses were performed for two scenarios. In the first one, the cooldown process of oil in a subsea pipeline was evaluated, with the effect of variable thermal properties on the temperature profile being investigated. The dependence of the temperature on the thermal conductivity and specific heat capacity was analyzed. In the second scenario, gas flows inside the pipeline, and the effect of temperature variation on a stagnant fluid is presented. Tests for different values of thermal diffusivity corresponding to new and old thermal insulations were performed.

2016 ◽  
Vol 15 (1) ◽  
pp. 96
Author(s):  
E. Iglesias-Rodríguez ◽  
M. E. Cruz ◽  
J. Bravo-Castillero ◽  
R. Guinovart-Díaz ◽  
R. Rodríguez-Ramos ◽  
...  

Heterogeneous media with multiple spatial scales are finding increased importance in engineering. An example might be a large scale, otherwise homogeneous medium filled with dispersed small-scale particles that form aggregate structures at an intermediate scale. The objective in this paper is to formulate the strong-form Fourier heat conduction equation for such media using the method of reiterated homogenization. The phases are assumed to have a perfect thermal contact at the interface. The ratio of two successive length scales of the medium is a constant small parameter ε. The method is an up-scaling procedure that writes the temperature field as an asymptotic multiple-scale expansion in powers of the small parameter ε . The technique leads to two pairs of local and homogenized equations, linked by effective coefficients. In this manner the medium behavior at the smallest scales is seen to affect the macroscale behavior, which is the main interest in engineering. To facilitate the physical understanding of the formulation, an analytical solution is obtained for the heat conduction equation in a functionally graded material (FGM). The approach presented here may serve as a basis for future efforts to numerically compute effective properties of heterogeneous media with multiple spatial scales.


1980 ◽  
Vol 102 (1) ◽  
pp. 121-125 ◽  
Author(s):  
S. K. Fraley ◽  
T. J. Hoffman ◽  
P. N. Stevens

A new approach in the use of Monte Carlo to solve heat conduction problems is developed using a transport equation approximation to the heat conduction equation. A variety of problems is analyzed with this method and their solutions are compared to those obtained with analytical techniques. This Monte Carlo approach appears to be limited to the calculation of temperatures at specific points rather than temperature distributions. The method is applicable to the solution of multimedia problems with no inherent limitations as to the geometric complexity of the problem.


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