Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.
Biological Systems Engineering, Washington State University, Pullman, Washington, USA.
J Food Sci. 2022 Sep;87(9):4082-4106. doi: 10.1111/1750-3841.16279. Epub 2022 Sep 1.
A hybrid mixture theory (HMT)-based unsaturated transport (pores not saturated with liquid) model was applied to a food matrix subjected to freezing and freeze-thaw cycles. The model can explain the fluid, species, and heat transport, ice formation, thermomechanical changes, and the freezing point depression occurring inside food biopolymers during freezing. Volume changes during freezing were calculated using the stresses due to pore pressure and the phase-change based mechanical strain. The Eulerian-Lagrangian transformation was performed for solving the equations using a finite element mesh in Lagrangian coordinates. The predicted temperature profiles for constant and fluctuating freezing temperature conditions showed agreement with experimental data with reasonable accuracy (RMSE = 2.86°C and 2.23°C, respectively). The multiscale transport model coupled with a physical chemistry-based relation was able to predict solute concentration and the freezing point depression in potatoes with greater accuracy than an empirical equation published in the literature. Sudden temperature fluctuations representing the opening and closing of a freezer door were investigated using this solution scheme, and conditions causing less damage to the food were identified. PRACTICAL APPLICATION: Food materials are subjected to freeze-thaw cycles during storage, shipping, and distribution to the consumers. The study uses numerical modeling and experimental validation to elucidate the principles affecting ice formation, solute migration, and temperature changes. Outcomes will allow processors to improve the quality of frozen foods with improved design of freezing operation, and storage and distribution strategies.
基于混合混合物理论(HMT)的非饱和传输(未被液体饱和的孔隙)模型被应用于经历冷冻和冻融循环的食品基质。该模型可以解释在食品生物聚合物内部发生的流体、物种和热传输、冰形成、热机械变化以及冰点降低。使用由于孔隙压力和基于相变化的机械应变引起的应力计算冷冻过程中的体积变化。使用拉格朗日坐标系中的有限元网格执行欧拉-拉格朗日变换来求解方程。对于恒定和波动冷冻温度条件的预测温度分布与实验数据具有合理的准确性(RMSE 分别为 2.86°C 和 2.23°C)。与文献中发表的经验方程相比,耦合物理化学关系的多尺度传输模型能够更准确地预测土豆中的溶质浓度和冰点降低。使用该解决方案方案研究了代表冷冻柜门打开和关闭的突然温度波动,并确定了对食品造成较小损害的条件。实际应用:在储存、运输和分发给消费者的过程中,食品材料会经历冻融循环。该研究使用数值建模和实验验证来阐明影响冰形成、溶质迁移和温度变化的原理。结果将使加工商能够通过改进冷冻操作、储存和分销策略来提高冷冻食品的质量。