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Alternative Emergency Response Procedures to Mitigate Impacts of Front-End Failures in Ethylene Production Plants 缓解乙烯生产装置前端故障影响的备选应急响应程序
IF 3.4 Pub Date : 2025-06-02 DOI: 10.1021/acs.chas.5c00027
Guan-Wun Chen,  and , Chuei-Tin Chang*, 

In general, equipment that facilitates product generation in a chemical process is termed the “front-end” unit. The units placed behind the front end form the “back end,” which are usually used for purification purpose. In any practical environment, it is impossible to avoid unexpected front-end failure(s) after a long period of continuous operations, and the back-end responses can often be adopted to mitigate the resulting harmful effects. Therefore, it is beneficial to figure out effective counter measures during the design stage for manipulating the back-end process against such hazards that are identifiable a priori. Our research objective is to conjecture a few remedial strategies to eliminate/reduce the effects of the front-end failures on the basis of sound engineering judgment, previous operational experiences, and rigorous simulation results. For convenience of illustration, the ethylene production process has been chosen as a working example. Although the procedures obtained with such a heuristic approach may not be as rigorous as those created by the fashionable tools nowadays, e.g., an AI agent, these proposed operations should at least be reliable and can be used as the basis for further improvements. Note also that this procedure synthesis strategy may be carried out much more quickly without the need to secure a large amount of training data in advance. Furthermore, the proposed approach may be extended to manipulate any other plant with the same process structure after front-end malfunction(s) develops. This generalizable feature is considered to be the most useful contribution of the present study.

一般来说,在化学过程中促进产品生成的设备被称为“前端”单元。放置在前端后面的单元形成“后端”,通常用于净化目的。在任何实际环境中,经过长时间的连续操作后都不可能避免意外的前端故障,通常可以采用后端响应来减轻由此产生的有害影响。因此,在设计阶段找出有效的应对措施,以操纵后端流程来应对这些可先验识别的危害是有益的。我们的研究目标是在合理的工程判断、以往的操作经验和严格的仿真结果的基础上,推测出一些消除/减少前端故障影响的补救策略。为便于说明,选取乙烯生产过程作为实例。尽管使用这种启发式方法获得的程序可能不如当今流行的工具(例如人工智能代理)创建的程序严格,但这些建议的操作至少应该是可靠的,并且可以用作进一步改进的基础。还请注意,这种程序综合策略可以更快地执行,而无需事先获得大量训练数据。此外,所提出的方法可以扩展到在前端故障发生后操纵具有相同工艺结构的任何其他工厂。这种可推广的特征被认为是本研究最有用的贡献。
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引用次数: 0
Optimization of Hydrogen Road Transport Routes Based on Combinatorial Assignment and Gray Correlation Analysis 基于组合分配和灰色关联分析的氢燃料公路运输路线优化
IF 3.4 Pub Date : 2025-05-28 DOI: 10.1021/acs.chas.5c00053
Tingting Luan, Yukun Zhao, Xiaoyun Li, Kai Wang and Guoliang Yang*, 

Hydrogen, as an efficient and clean energy carrier, is confronted with significant challenges during road transportation due to its inherent risks of flammability, explosion, and easy diffusion. These risks not only pose high safety concerns but also bring substantial economic challenges. To address these issues and enhance transportation efficiency while ensuring safety, this paper proposes a novel multiobjective optimization model. This model integrates a combination weighting method with gray correlation analysis to quantitatively evaluate and optimize transportation paths. It comprehensively considers multiple critical factors, including population casualty risk, environmental diffusion risk, and economic loss risk, from the perspectives of safety, economy, and time. The model’s effectiveness in identifying high-risk paths and optimizing transportation decisions is validated through the calculation of an actual transportation network. The research results indicate that this method can effectively achieve multidimensional risk trade-offs, providing a safer and more efficient transportation path scheme. Moreover, it offers valuable theoretical support and practical guidance for risk management and path optimization in hydrogen road transportation.

氢作为一种高效、清洁的能源载体,由于其固有的易燃性、易爆性和易扩散的危险,在道路运输中面临着巨大的挑战。这些风险不仅带来了高度的安全问题,也带来了巨大的经济挑战。为了解决这些问题,在保证安全的同时提高运输效率,本文提出了一种新的多目标优化模型。该模型将组合加权法与灰色关联分析法相结合,对运输路径进行定量评价和优化。它从安全、经济和时间的角度综合考虑了人口伤亡风险、环境扩散风险和经济损失风险等多个关键因素。通过实际交通网络的计算,验证了该模型在识别高风险路径和优化交通决策方面的有效性。研究结果表明,该方法可以有效地实现多维风险权衡,提供更安全、更高效的运输路径方案。为氢能道路运输的风险管理和路径优化提供了有价值的理论支持和实践指导。
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引用次数: 0
Pub Date : 2025-05-26
Qi-zheng Yang,  and , Shi-Yao Yang*, 
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引用次数: 0
Pub Date : 2025-05-26
Haifeng Xu*, 
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引用次数: 0
Pub Date : 2025-05-26
Wissam Ghach, Sara Abou Ibrahim*, Mona Aridi, Jihan Safwan, Sahar T. Issa and Michael T. Issa, 
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引用次数: 0
Pub Date : 2025-05-26
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引用次数: 0
Pub Date : 2025-05-26
Fanxi Bu*, Yuheng He, Xingwang Wang, Qingxiu Lu, Zhuoran Lv and Chunmiao Leng, 
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引用次数: 0
Pub Date : 2025-05-26
Amaury Kasprowiak, Pierre Kulinski, Cindy Depecker, Francine Cazier-Dennin and Pierre-Edouard Danjou*, 
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引用次数: 0
Pub Date : 2025-05-26
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引用次数: 0
Pub Date : 2025-05-26
Lubinda Nabiwa*, Joseph Simfukwe, Patrick Hayumbu, Daniel Masilu Masekameni, Nandi Mumba, Mwaba Sifanu and Stephanus J. L. Linde, 
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引用次数: 0
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Journal of chemical health & safety
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