Speaker
Description
The presentation will explore part of the stochastic model of phase transformations in eutectoid that had been developed (see [1,2,3]). In this model, the nucleation process is modeled using a sequence of random variables following the Bernoulli distribution with a given probability of success, which we interpret as the initiation of the nucleation. The initiation time plays a crucial role, as the volume fraction depends on the duration of the process until being measured. I will restrict my considerations to the model describing isothermal process in which the probability of nucleation occurring at a given time remains constant. For the case of the simplified model, I will present an alternative approach of generating the nucleation start time, utilizing an exponential distribution for this purpose. Moreover, I will use this distribution of the nucleation start time to determine the theoretical distribution of the volume fraction. Finally, the theoretical results will be used as a reference for the results obtained from the computer simulations to generate the benchmark function for this process. In this context, the primary goal is to determine the optimal simulation parameters that not only ensure a high level of consistency with the theoretical results but also guarantee simulation performance.
[1] Szeliga D., Czyżewska N., Klimczak K., Kusiak J., Morkisz P., Oprocha P., Pietrzyk M., Przybyłowicz P., Accounting for random character of some metallurgical phenomena and uncertainty of process parameters in modelling phase transformations in steels, Canadian Metallurgical Quarterly, 63(2), 2024, 460–467.
https://doi.org/10.1080/00084433.2023.2219948
[2] Szeliga D., Foryś J., Jażdżewska N., Kusiak J., Morkisz P., Nadolski R., Oprocha P., Pietrzyk M., Przybyłowicz P., Inverse problem in the stochastic approach to modelling of phase transformations in metallic materials during cooling after hot forming, Journal of Materials Engineering and Performance, 2024 (published on line),
https://doi.org/10.1007/s11665-024-10458-x
[3] Szeliga D., Jażdżewska N., Foryś J., Kusiak J., Nadolski R., Oprocha P., Pietrzyk M., Potorski P., Rauch Ł., Zalecki W., Stochastic model of accelerated cooling of eutectoid steel rails, Modelling and Simulation in Materials Science and Engineering, 2025, (published on line),
https://doi.org/10.1088/1361-651X/ada81c
