<p dir="ltr">This thesis explores novel methods of steel reheating, simulating hydrogen as a cleaner fuel in the combustion furnace and magnetic induction heating as a viable alternative, by utilizing advanced numerical simulations, including Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA), to assess their performance and feasibility.</p><p dir="ltr">Hydrogen, known for its potential to significantly reduce carbon dioxide emissions, is examined as a substitute for natural gas. Simulations revealed that hydrogen combustion results in higher flame temperatures and heat fluxes. While the CFD model achieved a high level of accuracy, with a maximum temperature error of 3% and an average deviation of 7% from real-world data, hydrogen fuel caused an increase in heat flux by up to 12% and higher slab surface temperatures. These changes led to steeper thermal gradients and increased stress, with peak stress levels reaching 90% of material limit. This simulation approach provides valuable data on the performance of different furnace fuels, helping to identify optimal fuel blends and configurations that minimize the risk of material failure while enhancing furnace efficiency.</p><p dir="ltr">The impact of scale formation on steel surfaces during reheating was also investigated. A mathematical model based on linear-parabolic equations was integrated into CFD simulations to predict scale growth. This model was validated against experimental data, showing an average error of 6%. The presence of scale led to a reduction in core temperature by up to 31 K and a 7.6% decrease in heat flux, which negatively affected heating efficiency. Scale formation also caused a significant drop in thermal conductivity, impacting heat transfer and slab uniformity. Pre-heating zone contributed minimally to overall scale formation despite its extended duration whereas a majority of scale growth was observed in the heating zone. Applications of this model include improving reheat furnace model efficiency and optimizing furnace operation to minimize scale.</p><p dir="ltr">Magnetic induction heating was also explored as an alternative to combustion-based reheating, assessing its potential benefits and challenges. The simulation results, validated with an average error of approximately 7% compared to literature data. showed uniform temperature distribution, and reduced stress levels with optimal power settings around 80 kW. A 3D transient simulation modeled an adaptive power cycle to minimize thermal stress highlighting the effectiveness of adaptive soaking strategies over continuous soaking in managing thermal stress, improving heating efficiency and material integrity.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/26524072 |
| Date | 08 August 2024 |
| Creators | Misbahuddin Husaini Syed (19353673) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/NUMERICAL_SIMULATION_OF_INDUCTION_AND_COMBUSTION_BASED_REHEAT_FURNACES/26524072 |
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