Energetic, exergetic analysis and machine learning of methane chlorination process for methyl chloride production

IF 4 4区环境科学与生态学 Q2 ENVIRONMENTAL STUDIES

Energy & Environment Pub Date : 2022-06-21 DOI:10.1177/0958305X221109604

Raju Gollangi, K. Nagamalleswara Rao

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引用次数: 3

Abstract

Nowadays, with the growing demand for energy and effective utilization of various available sources with the exorable techniques and approaches to maximize the efficiency of energy systems. This work has developed the synthesis of Methyl chloride (MC) from the methane chlorination process using the ASPEN HYSYS simulation tool. A Searchable analysis has been done on thermodynamic derivatives (likely Energy, Exergy) to probation on the entire process. This analysis calculates all process components’ energy loss, destruction and energy, and exergy efficiencies. A heavier energy loss has been found at Reactor (ERV) with 1785.5 kW and exergy destruction of 18.8% share. Heat Exchanger Network (HEN) has energy loss (960.32kW) & exergy destruction (791.29kW). The proposed new retrofit sustainable model recovered the waste heat from the HEN and achieved energy efficiency of 87.6% and exergy efficiency of 87.3% of the total MC process. Four Machine learning models were developed for the reactor (ERV) process to predict exergy destruction. The artificial Neural network (ANN) gave good testing predictions, followed by the Random Forest (RF) with a determination coefficient (R2) of 0.999957 and 0.999981.

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甲烷氯化生产过程的能量分析和机器学习

如今，随着能源需求的不断增长和各种可用资源的有效利用，可采用的技术和方法可以最大限度地提高能源系统的效率。本工作利用ASPEN HYSYS模拟工具开发了甲烷氯化过程中氯甲烷(MC)的合成。一个可搜索的分析已经完成了热力学衍生物(可能是能源，能源)，以验证整个过程。该分析计算了所有过程组件的能量损失、破坏和能量，以及能源效率。反应堆(ERV)的能量损失更大，为1785.5 kW，火用损失占18.8%。热交换器网络(HEN)具有能量损失(960.32kW)和火用破坏(791.29kW)。提出的新改造可持续模式回收了HEN的废热，实现了整个MC过程的能源效率为87.6%和火用效率为87.3%。为反应器(ERV)过程开发了四个机器学习模型来预测火用破坏。人工神经网络(ANN)给出了较好的测试预测，其次是随机森林(RF)，其决定系数(R2)分别为0.999957和0.999981。

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来源期刊

Energy & Environment ENVIRONMENTAL STUDIES-

CiteScore

7.60

自引率

7.10%

发文量

157

期刊介绍： Energy & Environment is an interdisciplinary journal inviting energy policy analysts, natural scientists and engineers, as well as lawyers and economists to contribute to mutual understanding and learning, believing that better communication between experts will enhance the quality of policy, advance social well-being and help to reduce conflict. The journal encourages dialogue between the social sciences as energy demand and supply are observed and analysed with reference to politics of policy-making and implementation. The rapidly evolving social and environmental impacts of energy supply, transport, production and use at all levels require contribution from many disciplines if policy is to be effective. In particular E & E invite contributions from the study of policy delivery, ultimately more important than policy formation. The geopolitics of energy are also important, as are the impacts of environmental regulations and advancing technologies on national and local politics, and even global energy politics. Energy & Environment is a forum for constructive, professional information sharing, as well as debate across disciplines and professions, including the financial sector. Mathematical articles are outside the scope of Energy & Environment. The broader policy implications of submitted research should be addressed and environmental implications, not just emission quantities, be discussed with reference to scientific assumptions. This applies especially to technical papers based on arguments suggested by other disciplines, funding bodies or directly by policy-makers.