ASME STP-PT-079:2016 pdf free download – LOCAL HEATING OF PIPING: THERMAL ANALYSIS

02-19-2022 comment

ASME STP-PT-079:2016 pdf free download – LOCAL HEATING OF PIPING: THERMAL ANALYSIS
2 ANALYSIS METHODOLOGY
The approach was to perform conjugate heat transfer (CHT) analysis using the Star CCM+ computational fluid dynamics (CFD) software [2]. This is a fully functional and validated commercial CFD solver. It has the capability of performing the CHT analysis and solving for temperature distributions in the piping and in the surrounding air. The advantage of using a CFD solver, as opposed to using a finite element analysis (FEA) code, is that the natural convection on the solid surfaces can be directly accounted for, rather than applying approximate boundary conditions. The project was broken up into two phases, a calibration phase and a prediction phase. The calibration phase consisted of two pipe geometries with different heating band configurations. Experimental temperature data was collected and provided to Quest Integrity by ASME. This data was then used to calibrate the CFD models by tuning the contact resistance between the heating band and pipe. The prediction phase expanded on the calibrated CFD models to examine post weld heat treatment (PWHT) in pipes of differing diameters and thicknesses. For the prediction phase, five different pipe diameters with three different schedule thicknesses were modeled, changing the heat band length iteratively until a maximum 15°F difference existed in the soak band. These results were then used to suggest new PWHT heat band sizing guidelines.
The configuration modeled consists of the piping with a band of ceramic electrical resistance heating elements. This in turn is covered by two layers of insulation over the heating band and one layer of insulation extending a distance beyond the heating band. The entire assembly is contained in a domain representing the surrounding air. Figure 2-1 and Figure 2-2 show the configuration of the half-symmetric model, with the ambient domain shown in blue, the piping shown in yellow, the heating layer in green, and the insulation layers in gray and purple. Heat flows from the heating band into the piping and to the insulation via conduction. Heat is lost to the surroundings via natural convection and radiation. Figure 2-2 shows the configuration of the soak band (SB), the heat band (HB), and the gradient control band (GCB). For all cases, the domain was assumed to be ten times the pipe length in the axial direction, and five times the pipe length in the transverse directions.
solutions with computational modeling. As a part of the numeric solution, some assumptions are necessary; these assumptions frequently include the Reynolds decomposition that breaks the velocity field into components of its mean and fluctuation. Employing this assumption leads to an inequality between equations and variables, which requires the use of a turbulence model [4]. The k-ε turbulence model is formulated from the far field flow and therefore captures flow best in that region, however it often requires a wall function to capture turbulence near any boundary. The k-ω turbulence model is formulated in the near-wall region and therefore captures flow best in that region, however its accuracy is less in the far field flow. The k-ω SST turbulence model uses the k-ω turbulence model in the near-wall region and the k-ε turbulence model in far field flow. It combines the models using a blending function in the transition region to produce an accurate turbulence model for both far field flow and boundary layer flow [5]. Although these models are primarily concerned with pipe temperatures, natural convection plays a significant role in overall heat transfer, therefore the k-ω SST turbulence model was implemented for the steady state CHT CFD analyses.

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