Use conjugate heat transfer CFD simulations to predict heat transfer coefficients during the start-up phase of steam turbines.
Turbine operation patterns are changing to fulfill new demand patterns from intermittent renewable energy supplies. This switch to flexible use increases the number of turbine start-ups and shutdowns. It’s critical to understand this effect on blade turbine stress, part lifetime, and maintenance costs. Watch this webinar to learn how B&B-AGEMA use conjugate heat transfer CFD simulations to predict heat transfer coefficients during the start-up phase of steam turbines. These are essential to accurately predict metal temperature distribution, required for thermal stress analyses and lifetime assessment. The transient simulation results are more accurate than standard analytical correlation data and can be used in component stress analyses.
To predict metal temperature distribution in turbine components, you need both surrounding fluid temperatures and component heat transfer coefficients. Modern steam turbine design usually relies on analytical correlations for heat transfer boundary conditions but there is a limit to their accuracy. In this study, B&B-AGEMA performed conjugate heat transfer (CHT) simulations using Simcenter STAR-CCM+. They were able to predict the component heat transfer coefficients during the turbine startup phase by running both steady-state and transient CHT simulations. The transient simulations showed that the local convective heat transfer coefficient generally increases with increasing axial and circumferential Reynolds’ number and is mostly influenced by vortex systems such as passage and horseshoe vortices.
Watch this webinar to see how standard analytical correlations underestimate the convective heat transfer over the startup procedure by about 40% compared to CHT simulation results. Incorporating transient CHT simulations into the design workflow increases the accuracy of heat transfer correlations and thermal stress analyses. This leads to minimized safety factors and thus reduced component and operation costs.
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