对参数和吸附异热模型的统计分析
Felipe R Pinto1, Caio F C Marcellos1, Carla Manske1
1Programa de Pós-Graduação em Engenharia de Processos Químicos e Bioquímicos (EPQB), Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
Environmental science and pollution research international
|February 3, 2024
概括
这项研究使用频率主义和贝叶斯统计学来比较Langmuir和Tóth在13X热带石上的二氧化碳吸附模型. 托斯模型显示的相关参数较少,准确的不确定性评估对于模型评估至关重要.
科学领域:
- 吸附科学 吸附科学
- 化学工程是化学工程的重要组成部分.
- 物理化学 物理化学
背景情况:
- 吸附过程在化学工程和环境应用中至关重要.
- 准确的参数估计和统计分析对于理解吸附现象至关重要.
- 兰穆尔和托斯等热量是描述固体表面气体吸附的常用模型.
研究的目的:
- 为了比较Langmuir和Toth的二氧化碳 (CO2) 吸附在13X热带石上的等温模型.
- 评估参数估计和统计分析方法,包括频率主义和贝叶斯式方法.
- 评估实验不确定性对模型性能和参数评估的影响.
主要方法:
- 分析了在不同温度 (303423 K) 的13X热上对二氧化碳的吸附异温数据.
- 频率主义统计分析采用最大概率估计 (MLE) 与信心区域 (圆近似,概率区域) 和千平方统计.
- 贝叶斯统计分析利用马尔科夫链蒙特卡洛 (MCMC) 参数概率密度函数和不确定性传播.
主要成果:
- 对信心区域的圆近似为参数估计提供了不良匹配,特别是对于相关的参数.
- 与三参 Langmuir 模型相比,四个参数的 Tóth 模型的参数相关性较小.
- 通过MCMC的贝叶斯分析有效地重建了参数概率密度函数和传播的不确定性.
结论:
- 托斯模型相对于兰穆尔模型具有优势,因为在这个CO2/地岩系统中,参数相关性减少了.
- 对于非线性吸附模型,频率主义的信心区域近似值可能不可靠.
- 在吸附研究中,准确评估实验不确定性对于稳健的模型选择和参数确定至关重要.
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