Abstract:
A feedwater heater is a typical component in power plants which increases the cycle efficiency. Over the last decade, renewable energies have significantly developed and been employed in the power grid. However, weather conditions are inconsistent and therefore produce variable power. Fossil fuel power stations are often required to supplement the variable renewable energies, which increased the rate of power cycling to an unforeseeable extent over the past decade. Power cycling results in changes in the flow rate, pressure, and temperature of a feedwater heater’s inlet flows. In a tubesheet-type feedwater heater, these transients induce cycling stress in the tubesheet and failures due to thermal fatigue occur. The header-type feedwater is currently employed in high pressure applications as it is more resistant to thermal fatigue compared to the tubesheet-type. However, the tubesheet-type is more cost effective to construct and maintain. It would be advantageous if the cyclic thermal stresses in the tubesheet can be better analysed and alleviated to support the use of the tubesheet-type.
A detailed transient temperature distribution of the tubesheet is required to understand the thermal fatigue. Normally, engineers opt towards a full CFD to obtain such results. However, the size and complexity of a feedwater heater is immense and cannot be simulated practically solely using CFD spatial elements. This study developed a multiscale approach that thermally couples 1D network elements, CFD spatial elements, and macroscopic heat transfer correlations to reduce the computational expense substantially. The combination of the various selected techniques and the specific application of this methodology is unique. This approach is capable of obtaining the detailed transient temperature distribution of the tubesheet in a reasonable time, as well as include the effects of the upstream and downstream components within the network model. The methodology was implemented using Flownex and Ansys Fluent for the 1D network and CFD solvers, respectively. The internal tube flow was modelled using 1D network elements, while the steam was modelled with CFD. Thermal discretisation, mapping, and convergence were considered to create a robust methodology not limited to feedwater heaters only. Additionally, a method was developed to analyse flow maldistribution in tube-bundles using the coupled 1D-3D approach. The implementation of the methodology consists of two parts, of which one is for development purposes, and the other serves as a demonstration. The development was done on a simple TEMA-FU heat exchanger which is representative of a feedwater heater. The methodology was tested by varying the primary fluid’s flow rates, changing the fluid media, and conducting transient simulations. The temperature distributions obtained were compared against a full CFD model and corresponded very well with errors less than 4%. A reduction in computational time of more than 40% was achieved but is highly dependent on the specific problem. Improvements to be made in future studies include the accuracy of the laminar case method and the stability of the flow maldistribution algorithm.
The methodology was demonstrated by applying it to an existing industrial feedwater heater. No plant data was available to use for input conditions and therefore were assumed. The steam in the DSH was modelled using 3D CFD elements and the tube flow with 1D network elements. The condensing zone’s heat transfer was approximated using an empirical correlation. A steady state case was simulated and the outlet temperatures corresponded well with the manufacturer’s data. The temperature distribution of the tubesheet and surrounding solids were obtained. Finally, assumed sinusoidal transient perturbations to the inlet conditions were imposed. It was evident that the thermal gradients of both sides of the tubesheet were misaligned which highlights the thermal lag and inertia that cause differential temperatures.
The 1D-CFD methodology was developed successfully with results that proved to correspond well, for a wide range of conditions, to full CFD. The methodology was applied and can be, in future work, validated with experimental results or extended by modelling upstream and downstream components in the network solver.