6卷 第7期
厨余垃圾气化制氢燃爆风险预测:进展与挑战
厨余垃圾气化制氢燃爆风险预测:进展与挑战
- 2025年6卷第7期 页码:98-102
纸质出版日期:2025-07-30
DOI:10.12184/wspkjllysjWSP2634-792X22.20250607
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6卷 第7期
重庆科技大学安全科学与工程学院,重庆 401331
纸质出版日期:2025-07-30
Scan QR Code
邹德斌,吕星,刘胜露.厨余垃圾气化制氢燃爆风险预测:进展与挑战[J].科技理论与实践,2025,06(07):98-102.
邹德斌, 吕星, 刘胜露. 厨余垃圾气化制氢燃爆风险预测:进展与挑战[J]. Theory and practice of science and technology, 2025, 6(7): 98-102.
邹德斌,吕星,刘胜露.厨余垃圾气化制氢燃爆风险预测:进展与挑战[J].科技理论与实践,2025,06(07):98-102. DOI: 10.12184/wspkjllysjWSP2634-792X22.20250607.
邹德斌, 吕星, 刘胜露. 厨余垃圾气化制氢燃爆风险预测:进展与挑战[J]. Theory and practice of science and technology, 2025, 6(7): 98-102. DOI: 10.12184/wspkjllysjWSP2634-792X22.20250607.
在“双碳”背景下,厨余垃圾气化制氢技术因兼具资源循环与能源转型优势而受关注,但其复杂组分气化产生的H
2
、CO、CH
4
等可燃气体易引发燃爆事故,制约产业化与安全运行。本文系统梳理了该过程燃爆风险的形成机理、影响因素及特征,综述了主要预测方法:物理化学数值模拟、数据驱动机器学习及机理-数据融合混合方法。同时,指出当前研究中存在的主要挑战,包括原料波动性、多尺度模拟精度、数据质量与模型可靠性等方面。最后提出需加强智能监测预警、建立共享风险数据库平台、完善产业政策,以推动该技术安全高效的可持续发展。
刘雪松 , 沈骏 , 刘雪莲 . 厨余垃圾资源化利用技术研究进展 [J ] . 现代化工 , 2023 , 43 ( 4 ): 23 - 26,31 .
韩震晴 , 沈骏 , 刘雪松 , 等 . 厨余垃圾热转化利用技术进展 [J ] . 低碳化学与化工 , 2025 , 50 ( 1 ): 54 - 64,86 .
Dong R , Jia H , Tian J , et al . Thermodynamic analysis and life cycle assessment of the preferred supercritical water gasification coupled system for energy self-sufficiency: From food waste to hydrogen [J ] . Energy , 2025 , 317 , 134553 .
Zhang C . Review of catalytic reforming of biomass pyrolysis oil for hydrogen production [J ] . FRONTIERS IN CHEMISTRY , 2022 , 10 : 962587 .
Matamba T , Tahmasebi A , Yu J , et al . A review on biomass as a substitute energy source: Polygeneration influence and hydrogen rich gas formation via pyrolysis [J ] . Journal of Analytical and Applied Pyrolysis , 2023 , 175 , 106221 .
Ye L , Zhang J , Xu R , et al . Gasification of organic solid waste for syngas: Physicochemical and conversion mechanism investigation [J ] . International Journal of Hydrogen Energy , 2024 , 49 , 384 - 397 .
Ma Y , Ge Z , Zeng M , et al . Steam co-gasification of organic solid waste for hydrogen-rich syngas: Synergistic performance and mechanism [J ] . International Journal of Hydrogen Energy , 2024 , 88 , 748 - 759 .
Ma Y , Zha Z , Huang C , et al . Gasification characteristics and synergistic effects of typical organic solid wastes under CO2/steam atmospheres [J ] . Waste Management , 2023 , 168 , 35 - 44 .
Elgazar Y.G , Khalifeh H . A, Alkhedher M, et al. A review of hydrogen production from food waste through gasification process[J ] . International Journal of Hydrogen Energy , 2024 , 67 , 959 - 969 .
Jiao F , Zhang H , Li W , et al . Experimental and numerical study of the influence of initial temperature on explosion limits and explosion process of syngas-air mixtures [J ] . International Journal of Hydrogen Energy , 2022 , 47 ( 52 ): 22261 - 22272 .
Xiao J , He P , Li X , et al . Computational fluid dynamics model based artificial neural network prediction of flammable vapor clouds formed byliquid hydrogen releases [J ] . International Journal of Energy Research , 2022 , 46 ( 8 ): 11011 - 11026 .
Zhao B , Li S , Gao D , et al . Research on intelligent prediction of hydrogen pipeline leakage fire based on Finite Ridgelet neural network [J ] . International Journal of Hydrogen Energy , 2022 , 47 ( 55 ): 23316 - 23323 .
李宇峰 , 申宏栋 . 管内合成气爆炸压力特性的试验与机理研究 [J ] . 安全与环境学报 , 2024 , 24 ( 4 ): 1362 - 1370 .
尚融雪 , 庄紫喧 , 杨悦 , 等 . 初始压力对合成气爆炸下限的影响研究 [J ] . 中国安全科学学报 , 2022 , 32 ( 8 ): 120 - 125 .
Sun Z.Y , LIU S . -Y. A comparative study on the turbulent explosion characteristics of syngas between CO-enriched and H2-enriched [J ] . Energy , 2022 , 241 : 122941 .
Shi J , Chang B , Khan F , et al . Stochastic explosion risk analysis of hydrogen production facilities [J ] . International Journal of Hydrogen Energy , 2020 , 45 ( 24 ): 13535 - 13550 .
Khodabandehlou R , Norouzi H. R , Larimi A , et al . Analysis of biomass gasification in a fluidized bed using CFD-DEM [J ] . Energy , 2025 , 320 , 135395 .
Kong D , Wang S , Luo K , et al . Three-dimensional simulation of biomass gasification in a full-loop pilot-scale dual fluidized bed with complex geometric structure [J ] . Renewable Energy , 2020 , 157 , 466 - 481 .
Sakhraji M , Ramos A , Monteiro E , et al . Plasma gasification process using computational fluid dynamics modeling [J ] . Energy Reports , 2022 , 8 , 1541 - 1549 .
Ngamsidhiphongsa N , Limleamthong P , Prasertcharoensuk P , et al . A review on computational fluid dynamics modeling of fixed-bed biomass gasifiers: Recent advances and design analysis [J ] . International Journal of Hydrogen Energy , 2025 , 130 , 654 - 671 .
Li J , Liang W , Han W . Predicting the explosion limits of hydrogen-oxygen-diluent mixtures using machine learning approach [J ] . International Journal of Hydrogen Energy , 2024 , 50 , 1306 – 1313 .
Xu Q , Chen G , Su S , et al . Prediction of venting gas explosion overpressure based on a combination of explosive theory and machine learning [J ] . Expert Systems With Applications , 2023 , 234 , 121044 .
He X , Kong D , Yang G , et al . Hybrid neural network-based surrogate model for fast prediction of hydrogen leak consequences in hydrogen refueling station [J ] . International Journal of Hydrogen Energy , 2024 , 59 : 187 – 198 .
Kang J , Su T , Jin H , et al . Risk analysis of boiler overpressure explosion based on complex network and fuzzy Bayesian inference [J ] . Engineering Failure Analysis , 2025 , 170 , 109261 .
Umenweke G.C , Afolabi I . C, Epelle E. I, et al. Machine learning methods for modeling conventional and hydrothermal gasification of waste biomass: A review [J ] . Bioresource Technology Reports , 2022 , 17 , 100976 .
Zhang D , Anjum T , Chu Z , et al . Simulation of multiphase flow with thermochemical reactions: A review of computational fluid dynamics (CFD) theory to AI integration [J ] . Renewable and Sustainable Energy Reviews , 2025 , 221 , 115895 .
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