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采用综合方法确定影响混合培养物厌氧产氢的因素的影响优先级。

An integrated approach to identify the influential priority of the factors governing anaerobic H2 production by mixed cultures.

机构信息

Department of Chemistry, University of Science and Technology of China, Hefei, 230026 China.

出版信息

Water Res. 2010 May;44(10):3234-42. doi: 10.1016/j.watres.2010.03.001. Epub 2010 Mar 4.

DOI:10.1016/j.watres.2010.03.001
PMID:20347115
Abstract

An integrated approach incorporating response surface methodology, grey relational entropy, and fuzzy analytic hierarchy process is established to prioritize the influence of main factors governing the anaerobic H(2) production process and their influential priority. Response surface methodology is employed to design experiments, and the grey relational entropy is used to evaluate the influential grade of the three input factors, i.e., pH, temperature and initial substrate concentration (S(ini)), on the H(2) yield, maximum H(2) production rate and volatile fatty acid yield. In addition, through a combination of grey relational entropy, fuzzy analytic hierarchy process, which is used to determine the weight, and accelerating genetic algorithm, which is employed to minimize the nonlinear function in fuzzy analytic hierarchy process, the overall H(2) production process performance could be comprehensively evaluated. The results show that pH is the most important factor influencing the yields of H(2) and volatile fatty acids, while S(ini) has the most significant effect on the maximum H(2) production rate. Compared to pH and S(ini), temperature has a less important effect on the overall H(2) production reactor performance. This approach provides an appropriate way to identify the influential priority of input factors and to evaluate the overall performance for the anaerobic H(2) production process, and it can also be used for other complex biological and non-biological wastewater treatment systems.

摘要

建立了一种综合方法,该方法结合了响应面法、灰色关联熵和模糊层次分析法,以确定影响厌氧 H 2 生产过程的主要因素及其影响优先级。响应面法用于设计实验,灰色关联熵用于评估三个输入因素(即 pH 值、温度和初始底物浓度(S ini ))对 H 2 产量、最大 H 2 产率和挥发性脂肪酸产量的影响等级。此外,通过灰色关联熵、模糊层次分析法(用于确定权重)和加速遗传算法(用于最小化模糊层次分析法中的非线性函数)的组合,可以综合评估整体 H 2 生产过程的性能。结果表明,pH 值是影响 H 2 和挥发性脂肪酸产量的最重要因素,而 S ini 对最大 H 2 产率的影响最大。与 pH 值和 S ini 相比,温度对整体 H 2 生产反应器性能的影响较小。该方法为确定输入因素的影响优先级和评估厌氧 H 2 生产过程的整体性能提供了一种合适的方法,也可用于其他复杂的生物和非生物废水处理系统。

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