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<p>This study focuses on numerical modeling of the oleogelation process using grape seed oil and beeswax and its validation using experimental approach. The main goal is to investigate how the cooling rate affects this process. The necessary physical and thermal properties of the oleogel for modeling were determined through experiments. Additionally, differential scanning calorimetry was used to characterize phase transitions. The apparent heat capacity method was applied in the numerical modeling to simulate the phase change process, and the energy equation was solved using the finite element method. The numerical model demonstrated a maximum relative error of 5.4%, indicating a strong agreement between the numerical results and experimental data. After validating the numerical model, five different cooling rates were investigated. The findings showed that oleogelation begins near the bottom boundary of the setup and then propagates toward the center. Furthermore, the fraction of the total time required for the phase change to complete varied between 0.35 and 0.04 as the cooling rate decreased. This indicates that slower cooling rates provide more time for heat transfer, allowing for more thorough gelation and completing the phase transition in a smaller fraction of the total time. The proposed model can save time and costs while delivering accurate data on creating a beneficial oleogel.</p>

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Numerical simulation and experimental validation of the oleogel formation from grape seed oil and beeswax

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月7日

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  • Zohreh Baratian Ghorghi,
  • Ali Faezian,
  • Samira Yeganehzad,
  • Mohammad Ali Hesarinejad,
  • Alireza Sheikhi Darani,
  • Marcello Fidaleo,
  • Hashem Ahmadi Tighchi

摘要

This study focuses on numerical modeling of the oleogelation process using grape seed oil and beeswax and its validation using experimental approach. The main goal is to investigate how the cooling rate affects this process. The necessary physical and thermal properties of the oleogel for modeling were determined through experiments. Additionally, differential scanning calorimetry was used to characterize phase transitions. The apparent heat capacity method was applied in the numerical modeling to simulate the phase change process, and the energy equation was solved using the finite element method. The numerical model demonstrated a maximum relative error of 5.4%, indicating a strong agreement between the numerical results and experimental data. After validating the numerical model, five different cooling rates were investigated. The findings showed that oleogelation begins near the bottom boundary of the setup and then propagates toward the center. Furthermore, the fraction of the total time required for the phase change to complete varied between 0.35 and 0.04 as the cooling rate decreased. This indicates that slower cooling rates provide more time for heat transfer, allowing for more thorough gelation and completing the phase transition in a smaller fraction of the total time. The proposed model can save time and costs while delivering accurate data on creating a beneficial oleogel.