郑鸿泽,何正磊,洪蒙纳,满奕.造纸废水处理过程温室气体排放代理模型研究[J].中国造纸学报,2023,38(2):59-68 本文二维码信息
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造纸废水处理过程温室气体排放代理模型研究
Study on Surrogate Model of Greenhouse Gas Emission in Papermaking Wastewater Treatment Process
投稿时间:2023-02-09  
DOI:10.11981/j.issn.1000-6842.2023.02.59
中文关键词:  高维模型表征  Kriging  温室气体  造纸废水  代理模型
Key Words:high dimensional model representation  Kriging  greenhouse gas  papermaking wastewater  surrogate model
基金项目:国家自然科学基金项目(5200100319);广州市科技计划项目基础与应用基础研究项目(202201010356);人工智能与数字经济广东省实验室(广州)青年学者项目(PLZ2021KF0019)。
作者单位邮编
郑鸿泽* 华南理工大学制浆造纸工程国家重点实验室广东广州510640 510640
何正磊 华南理工大学制浆造纸工程国家重点实验室广东广州510640 510640
洪蒙纳 华南理工大学制浆造纸工程国家重点实验室广东广州510640 510640
满奕 华南理工大学制浆造纸工程国家重点实验室广东广州510640
琶洲实验室广东广州510335 
510335
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中文摘要:
      造纸废水处理过程具有高维、非线性和不稳定性等特点,并且其温室气体排放受诸多因素影响,目前缺乏可描述该过程的模型,因此难以对造纸废水处理过程的温室气体排放进行有效地管控与优化。本课题基于造纸废水处理温室气体产生机理,提出将响应面模型(Response Surface Model,RSM)、Kriging等方法与高维模型表征(High Dimensional Model Representation,HDMR)相结合,建立造纸废水处理过程中温室气体排放的代理模型,保障模型精度,同时降低优化设计所需计算成本。研究结果表明,对比于RSM-HDMR,Kriging-HDMR具有更高的近似精度,其验证结果R2大于0.95,更适用于高维、非线性的造纸废水处理过程。最后还基于Kriging-HDMR进行了关键参数的灵敏度分析,发现溶解氧传递系数和外循环流量对造纸废水处理温室气体减排最为关键。
Abstract:
      Papermaking wastewater treatment process has the characteristics of high dimension, nonlinearity, and instability, and greenhouse gas emissions during which are affected by many factors. Models describing papermaking wastewater treatment process are currently lacking, rendering it difficult to effectively optimize and control greenhouse gas emissions during the process. In this study, the response surface model (RSM) and Kriging method were combined with high dimensional model representation (HDMR) to establish a surrogate model for greenhouse gas emissions generated from papermaking wastewater treatment, which could ensure the accuracy and reduce computational cost for optimizing design. The results showed that Kriging-HDMR had higher approximation accuracy than RSM-HDMR, with R2 of above 0.95, indicating that Kriging-HDMR was more suitable for high dimensional and nonlinear papermaking wastewater treatment process. The sensitivity analysis based on Kriging-HDMR showed that dissolved oxygen transfer coefficient and external circulation flow were the key parameters for greenhouse gas emission reduction.
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