Optimization of furnace residence time and loading pattern during heat treatment of large size forgings

Abstract

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.

Influence of Spacers and Skid Sizes on Heat Treatment of Large Forgings within an Industrial Electric Furnace

“…It can be seen that both bl rienced significant non-uniformities during the heat treatment process. Such formity was also reported for gas-fired furnaces [9,16]. This temperature non-u is not usually considered in metallurgical investigations of the heat treatmen where the main attention is concentrated on the temperature gradient between and surface of the block.…”

“…However, in recent years, with the implementation of new regulations on the reduction of global carbon dioxide emissions and fossil fuel usage, there has been significant growth in the employment of electrical batch-type furnaces for steel heat treatment processes, but, in contrast to gas-fired furnaces, very little data is available in the case of electrical furnaces, particularly industrial-sized ones. Thus, the accurate prediction and control of the transient temperature distribution and heat transfer to products in electrical furnaces are critical in order to optimize temperature uniformity and fluid flow circulation, similar to what was previously reported by Bohlooli et al for gas-fired furnaces [11,12]. The optimization process becomes even more complex when, due to production imperatives, multiple loading patterns and stacking configurations must be taken into account as they significantly affect the temperature distributions around the parts [9].…”

“…Thus, the accurate prediction and control of the transient temperature distribution and heat transfer to products in electrical furnaces are critical in order to optimize temperature uniformity and fluid flow circulation, similar to what was previously reported by Bohlooli et al for gas-fired furnaces [11,12]. The optimization process becomes even more complex when, due to production imperatives, multiple loading patterns and stacking configurations must be taken into account as they significantly affect the temperature distributions around the parts [9].…”

“…These metallurgical interactions, such as the hardness reduction of brittle quench-hardened steel, improved toughness, and stress relieving, fundamentally depend on the tempering temperature and holding time in the heat treatment furnace [6,7]. It has been reported that non-uniform temperature distribution may result in non-uniform properties around the products and in some cases scrapping of the part [8,9]. At the present time, most of the existing heat treatment furnaces in the steel industry use natural gas as the heating source, and significant efforts have been devoted to the optimization of the tempering process in such furnaces [10].…”

“…The model mainly focused on the heat generation rate of the energy source developed using FLUENT user-defined function (UDF); a proportional integral derivative (PID) method was proposed to regulate furnace temperature according to the thermal scheme. Arkhazloo et al [9], investigating the thermal interactions inside an industrial gas-fired furnace, reported the significant effect of stacking patterns (such as their relative locations and distances) on the uniformity of the tempering process. Such influence on the temperature uniformity of the product was also mentioned by Wang and Shang [15] and Macchion et al [32] in their numerical studies of small-scale steel parts' heat treatment within a high pressure gas quenching chamber.…”