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首页> 外文期刊>Journal of food engineering >Rheological parameters estimation of non-Newtonian food fluids by finite elements model inversion
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Rheological parameters estimation of non-Newtonian food fluids by finite elements model inversion

机译:用有限元模型反演估算非牛顿流体的流变参数

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摘要

The knowledge of fluid food rheological properties plays an important role in process engineering. Unfortunately, characterization of non-Newtonian fluids requires a notable effort in terms of time and resources. As a consequence, the aim of this research was to set up an method, based on the combination of the inversion of a simple finite element model and a laboratory measurement, carried on with a simplified tool. Although the method has a more general applicability, for illustrative purpose, it is here mainly shown with reference to power-law rheological model and two different materials (tara gum mixture and dough of water and flour). To measure the rheological parameters, the square of distance between simulated and experimental data was considered as an objective function, and some well-known optimization algorithms were tested. In order to verify the feasibility of the method, the experimental rheological characterization of the considered materials were carried out using a rotational rheometer. The calculated rheological parameter values were comparable with those obtained by traditional procedure (mean percentage error 6.47 +/- 5.57). The most efficient optimization algorithm, in terms of iterations number, computational speed and minimum of the objective function, was the Levenberg-Marquardt one, but even other tested algorithms drove to similar final results (maximum difference of 18% between the optimized k and n values). The results demonstrated also that the precision of the calculated rheological parameters does not depend on the initial parameter values.
机译:流体食品流变特性的知识在过程工程中起着重要作用。不幸的是,非牛顿流体的表征需要耗费大量时间和资源。因此,本研究的目的是建立一种基于简单有限元模型的反演和实验室测量结果的简化方法的方法。尽管该方法具有更普遍的适用性,但出于说明目的,此处主要参考幂律流变模型和两种不同的材料(塔拉胶混合物以及水和面粉的面团)进行显示。为了测量流变参数,将模拟数据与实验数据之间的距离的平方视为目标函数,并测试了一些著名的优化算法。为了验证该方法的可行性,使用旋转流变仪对所考虑的材料进行了实验流变学表征。计算的流变参数值与通过传统方法获得的流变参数值相当(平均百分比误差6.47 +/- 5.57)。就迭代次数,计算速度和目标函数的最小值而言,最有效的优化算法是Levenberg-Marquardt算法,但即使是其他经过测试的算法也得出了相似的最终结果(优化的k和n之间的最大差值为18%)值)。结果还表明,计算的流变参数的精度不取决于初始参数值。

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