ENGINEERING AND CFD

Piping systems perform the essential function of facilitating coolant transport within a power plant. Being a vast infrastructure, power plants have an extensive network of piping serving different purposes. Ensuring the integrity and functional capability of piping systems throughout their service life are important for the safe operation. Thermal loading imposed on the piping structure by the underlying fluid flow results in some of the unexpected material degradation and failure. Thermal fatigue was identified as a challenge to power plant safety during the 1970s and 1980s when new loading conditions (e.g. thermal stratification, valve leaks) that were not considered during the design stage resulted in fatigue cracks at different locations during the operation. Research efforts were subsequently made to understand these issues by the research community. This lead to thermal fatigue caused by clearly identifiable thermal loading on the structure to be well understood over the years.

On the other hand, a new challenge emerged whereby thermal fatigue in structures caused by thermal loading that could not be monitored using conventional plant instrumentation systems resulted in frequently reported damage of piping systems. Predominantly caused by mixing between flows (e.g. at T-junctions) at significant temperature differences (∆Ts) as shown in Fig. 1, the issue is still being widely investigated and no consensus exists internationally on assessing the fatigue damage caused by such thermal mixing events.

The Challenge

While experimental studies of T-junction flow mixing was conducted around the world to understand the factors leading to thermal fatigue, advances in high-performance computing over the past two decades enabled computational fluid dynamics (CFD) investigations of T-junction flows in much greater detail than was deemed possible before. CFD has complemented experiments in providing reliable information and description of the flow field at locations that are otherwise inaccessible using instrumentation. Thus a combination of measurements at high ∆T representing realistic power plant temperatures and high-fidelity CFD calculations validating the measurement data would provide a very complete description of the underlying flow behavior enabling a more accurate assessment of thermal fatigue. So the fluid-structure interaction (FSI) facility was commissioned at University of Stuttgart with capabilities to conduct flow mixing measurements at ∆Ts comparable to power plants (see Fig. 2) while large-eddy simulation (LES) method was chosen to simulate the turbulent mixing behavior. This represented the first time a LES calculation at such a high ∆T (up to 
200 °C) was performed in the literature and is the main highlight of this project work.

The need for high-performance computing (HPC)

Since LES was chosen to be the numerical methodology, highly intensive computations are to be expected making it necessary to opt for HPC to numerically investigate a wide range of inflow conditions (e.g. temperature, velocity) to understand their effect on flow mixing behavior. The computational domain on average contained about 8 – 15 million nodes and the LES was planned to simulate at least 30 seconds of physical flow mixing with a small time step (0.2 ms) to resolve the relevant flow scales and making it easier to compare the relevant parameters (mean temperature, temperature fluctuations and its frequency spectrum) against measurement data. About 300 – 1000 CPU cores are required for each computation and nearly 100 such computations were performed in the frame work of this project. Thus HPC using the CRAY XC40 supercomputer Hazel Hen provided the highest possibility of performing the vast number of simulations intended to be performed within the time frame of this project.

Findings from the work

• Flow mixing is observed to be incomplete in all the investigated cases due to the low Reynolds number flow from the branch pipe being insufficient to cause complete mixing of fluids. Thus a thermally stratified flow pattern emerges after the mixing between fluids at the T-junction.

• The nature of the thermally stratified flow illustrates the difference caused by ∆T between the mixing fluids. An unstable stratified flow being subjected to extreme oscillations is seen at low ∆T (e.g. 65 °C) whereas the opposite case of stable stratification is observed at higher 
∆T (> 140°C) between flows (see Figs. 3 and 4). This could be attributed to the significant increase in buoyancy forces that is brought about by the substantial increase in ∆T between fluids.