2018
DOI: 10.1016/j.promfg.2018.07.203
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Computer simulations of austenite decomposition of hot formed steels during cooling

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Cited by 14 publications
(8 citation statements)
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“…This can also be seen in Figure 3. By taking into account all of the effects mentioned above together with the role of heating rate on the austenitization start and finish temperature, the empirical model (Pohjonen et al , 2018a; Pohjonen et al , 2018b) was used to calculate the fractions of the various microstructural components for each layer of the pipe thickness (Table II). There is a gradual transition from the hard-martensitic layers to the ductile, mainly bainitic, layers, which ought to result in excellent performance during slurry transportation.…”
Section: Resultsmentioning
confidence: 99%
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“…This can also be seen in Figure 3. By taking into account all of the effects mentioned above together with the role of heating rate on the austenitization start and finish temperature, the empirical model (Pohjonen et al , 2018a; Pohjonen et al , 2018b) was used to calculate the fractions of the various microstructural components for each layer of the pipe thickness (Table II). There is a gradual transition from the hard-martensitic layers to the ductile, mainly bainitic, layers, which ought to result in excellent performance during slurry transportation.…”
Section: Resultsmentioning
confidence: 99%
“…It can be seen that when austenitization is complete, almost 100% martensite can be achieved when the cooling rate is 60 °C/s or more while polygonal ferrite appears when the cooling rate is less than about 10 °C/s. To be able to estimate the phase fraction distribution for any continuous cooling path, not just linear cooling, an empirical model [6,11] has been built around the dilatometry results. The different cooling paths for every millimeter of pipe thickness resulting from water quenching is presented in Figure 4 The simulated temperature profile of every millimeter of pipe thickness as a function of time is presented in Figure 2(a).…”
Section: Figurementioning
confidence: 99%
“…The optimization is performed for two separate industrial processes: induction hardening of a medium carbon, low-alloy pipe steel (Javaheri et al, 2019b) and a water cooling of a hot rolled low carbon steel strip (Pohjonen et al, 2018a). The optimization workflow consists of first setting the desired amounts of microstructural constituents, and subsequent optimization of the thermal path, which produces these desired amounts applying the phase transformation model described in (Pohjonen et al, 2018a;Pohjonen et al, 2018b;Javaheri et al, 2019b). For the water cooling of a steel strip, we additionally employed previously developed tool (Paananen, 2015;Pohjonen et al, 2016) to calculate the cooling water fluxes that are needed to realize the optimized cooling path in water cooling line after hot rolling.…”
Section: Aimsmentioning
confidence: 99%
“…The phase transformation module has been described in detail generally in (Pohjonen et al, 2018b), in context of induction hardening of medium carbon steel (Javaheri et al, 2019b) and in the context of water cooling of hot rolled low carbon steel in (Pohjonen et al, 2018a), where (Javaheri et al, 2019b) and (Pohjonen et al, 2018a) also include the transformation model parameters fitted for the steels that were used in these examples.…”
Section: Sims 61mentioning
confidence: 99%
“…We have previously developed a coupled heat conduction and mean field (MF) phase transformation model [14][15][16][17], that has been applied for simulating austenite decomposition in cooling of a steel coil [15] as well as in slow cooling of low temperature ausformed steel, which leads to the formation of fine bainitic structure [18]. The mean field phase transformation model has been also used for simulating microstructure evolution to aid the design of induction hardening of a medium carbon pipeline material [19] where the model can be used for optimizing the cooling path and strategy so that desired fractions of different phases can be obtained [20,21] through the pipe thickness.…”
Section: Introductionmentioning
confidence: 99%