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A combination of unsteady 3D CFD simulations and experimental temperature measurements was employed to determine the effect of loading patterns on the temperature distribution within steel forgings inside a gas-fired heat treatment furnace. This was aimed to obtain a more homogenous temperature distribution. Besides, a hybrid methodology using 3D numerical simulations and a high-resolution dilatometer allowed improving residence time of forgings inside the heat treatment furnace. The influence of the loading patterns and skids on temperature distribution and residence time of forgings was examined using thermal analysis four different loading patterns.Comprehensive unsteady thermal analysis of the products heating allowed quantifying the impact of skids usage and their dimensions on the extent of the uniformity of temperature distribution.The results were interpreted in terms of the inter-relationship between the skids usage, their geometry, absorbed radiation and convective heat fluxes. The analysis showed that temperature non-uniformities of up to 331 K could be produced for non-optimum loading patterns. Using the developed CFD approach it was possible to reduce the temperature non-uniformity of different sizes of blocks up to 32% via changing the loading pattern inside the furnace. Further, the slab's residence time was improved by almost 15.5% when employing the proposed hybrid approach. This approach could directly be applied to the optimization of different heat treatment cycles of forged blocks in different grades of steels.

The influence of stacking patterns, through the different spacer and skid sizes, on the transient temperature distribution uniformity of large-size forgings in a 112-m3 electrical heat treatment furnace was investigated by conducting CFD simulations and real-scale experimental validation. A 3D CFD model of the electrical furnace was generated, including a heat-treating chamber, axial flow fans, large size blocks, skids, and spacers. Real-scale temperature measurements on instrumented test blocks during the heat treatment process were carried out to validate the CFD simulations. Results indicated that the CFD model was capable enough to determine the transient temperature evolution of the blocks with a maximum average deviation of about 6.62% compared to the experimental measurements. It was found that significant temperature non-uniformities of up to 379 K on the surfaces of the blocks due to the non-optimum stacking pattern were experienced by the blocks. Such non-uniformities could be reduced between 24% to 32% if well-adapted spacer and skid sizes were used in the stacking configurations. Based on simulation results and experimental validation work, optimum spacer and skid sizes for uniform temperature distribution were proposed for different stacking patterns.

Simulation and analysis of thermal interactions during heat treatment is of great importance for accurate prediction of temperature evolution of work pieces and consequently controlling the final microstructure and mechanical properties of products. In the present study, a three-dimensional CFD model was employed to predict the heating process of large size forged ingots inside an industrial gas-fired heat treatment furnace. One-ninth section of a loaded furnace, including details such as fixing bars and high-momentum cup burners, was employed as the computational domain. The simulations were conducted using the ANSYS-FLUENT commercial CFD package. The k-ε, P-1 and Probability Density Function (PDF) in the non-premix combustion, as low computational cost numerical approaches were employed to simulate the turbulent fluid flow, thermal radiation, combustion and conjugate heat transfer inside the furnace. Temperature measurement at different locations of the forged ingot surfaces were used to validate the transient numerical simulations. Good agreement was obtained between the predictions of the CFD model and the experimental measurements, demonstrating the reliability of the proposed approach and application of the model for process optimization purposes. Detailed analysis of conjugate heat transfer together with the turbulent combustion showed that the temperature evolution of the product was significantly dependant on the furnace geometry and the severity of turbulent flow structures in the furnace.