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Statistical Evaluation of Non-Linear Parameter Estimation Procedures for Adsorption Equilibrium Models

机译:吸附平衡模型非线性参数估计程序的统计评估

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摘要

Adsorption equilibrium is a fundamental concept in the adsorption science and relates the equilibrium between the quantity of the adsorbed material and its concentration in the bulk phase. Several models have been proposed for prediction of adsorption equilibrium and all models depend on parameters whose values must be estimated from available experimental data. Although linear parameter estimation procedures can be used for model fitting, through transformation of available experimental data and model parameters, non-linear parameter estimation procedures lead to more reliable results and allow for direct comparison of results obtained with different adsorption equilibrium models. The main objective of this work is to present and compare different non-linear procedures for parameter estimation of adsorption equilibrium models, based on theoretical arguments and also on the numerical estimation of adsorption equilibrium parameters, using available experimental data for adsorption of methylene blue onto activated carbon. The results obtained indicate that the best parameter estimation procedure is the one that relies on available equilibrium concentrations in the bulk phase as a function of the fluid volume, adsorbent mass and initial concentrations in the bulk phase, without transformation of measured experimental values and model parameters. Besides, it is shown that parameter estimates should be obtained through proper minimization of weighted least-squares objective function, in accordance with maximum likelihood procedures.
机译:吸附平衡是吸附科学中的一个基本概念,它涉及吸附材料的数量与其在本体相中的浓度之间的平衡。已经提出了几种用于预测吸附平衡的模型,并且所有模型都依赖于参数,这些参数的值必须从可用的实验数据中进行估算。尽管可以将线性参数估计程序用于模型拟合,但是通过转换可用的实验数据和模型参数,非线性参数估计程序可以得出更可靠的结果,并可以直接比较使用不同吸附平衡模型获得的结果。这项工作的主要目的是基于理论论据以及吸附平衡参数的数值估算,利用可用的实验数据将亚甲基蓝吸附到活性炭上,提出并比较不同的非线性程序进行吸附平衡模型的参数估算。碳。获得的结果表明,最佳的参数估计程序是一种依赖于本体相中可用平衡浓度的函数,该平衡浓度是本体相中流体体积,吸附剂质量和初始浓度的函数,而无需转换测量的实验值和模型参数。此外,它表明,应该根据最大似然程序,通过适当最小化加权最小二乘目标函数来获得参数估计值。

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