燃烧技术的进步:对创新、方法和实际应用的回顾

IF 7.6 Q1 ENERGY & FUELS Energy Conversion and Management-X Pub Date : 2025-04-01 Epub Date: 2025-03-13 DOI:10.1016/j.ecmx.2025.100964
Abdellatif M. Sadeq , Raad Z. Homod , Husam Abdulrasool Hasan , Bilal Naji Alhasnawi , Ahmed Kadhim Hussein , Ali Jahangiri , Hussein Togun , Masoud Dehghani-Soufi , Shahbaz Abbas
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引用次数: 0

摘要

本综述全面考察了燃烧技术、多尺度建模方法和实验诊断方面的关键进展,强调了它们对提高能源效率、减少排放和推进可持续能源解决方案的贡献。均匀电荷压缩点火(HCCI)的热效率可达50%,而反应性控制压缩点火(RCCI)可将氮氧化物排放量降低90%,将制动热效率提高43%,显示出低排放发电的巨大潜力。压力增益燃烧(PGC)实现了热力学效率的提高,压力比达到2.0,而等离子辅助燃烧(PAC)将点火延迟缩短了35%,能够在稀薄条件下稳定运行。多尺度建模技术,如混合DNS-LES模型,在火焰速度预测中实现了5%的误差范围,自适应网格细化(AMR)在不影响精度的情况下将计算成本降低了50%。实验诊断,包括激光诱导荧光(LIF)、粒子图像测速(PIV)和可调谐二极管激光吸收光谱(TDLAS),提供高分辨率的测量,PIV捕获超过10 kHz的流场,高速成像记录高达100 kHz的瞬态燃烧事件。未来的研究方向强调推进低温燃烧策略,整合人工智能(AI)驱动的建模技术,以及开发用于实时燃烧分析的混合诊断方法。这些进步共同支持向更清洁、更高效的燃烧系统过渡,为可持续能源解决方案做出贡献,并指导燃烧科学和技术的未来创新。
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Advancements in combustion technologies: A review of innovations, methodologies, and practical applications
This review comprehensively examines key advancements in combustion technologies, multi-scale modeling approaches, and experimental diagnostics, highlighting their contributions to enhancing energy efficiency, reducing emissions, and advancing sustainable energy solutions. Homogeneous Charge Compression Ignition (HCCI) achieves thermal efficiencies up to 50 %, while Reactivity Controlled Compression Ignition (RCCI) reduces NOx emissions by up to 90 % and improves brake thermal efficiency by 43 %, demonstrating significant potential for low-emission power generation. Pressure Gain Combustion (PGC) achieves thermodynamic efficiency improvements with pressure ratios reaching 2.0, while Plasma-Assisted Combustion (PAC) shortens ignition delay by 35 %, enabling stable operation under lean conditions. Multi-scale modeling techniques, such as hybrid DNS-LES models, achieve a 5 % error margin in flame speed predictions, and Adaptive Mesh Refinement (AMR) reduces computational costs by 50 % without compromising accuracy. Experimental diagnostics, including Laser-Induced Fluorescence (LIF), Particle Image Velocimetry (PIV), and Tunable Diode Laser Absorption Spectroscopy (TDLAS), deliver high-resolution measurements, with PIV capturing flow fields at over 10 kHz and high-speed imaging recording transient combustion events at up to 100 kHz. Future research directions emphasize advancing low-temperature combustion strategies, integrating Artificial Intelligence (AI)-driven modeling techniques, and developing hybrid diagnostic methods for real-time combustion analysis. These advancements collectively support the transition to cleaner, more efficient combustion systems, contributing to sustainable energy solutions and guiding future innovations in combustion science and technology.
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来源期刊
CiteScore
8.80
自引率
3.20%
发文量
180
审稿时长
58 days
期刊介绍: Energy Conversion and Management: X is the open access extension of the reputable journal Energy Conversion and Management, serving as a platform for interdisciplinary research on a wide array of critical energy subjects. The journal is dedicated to publishing original contributions and in-depth technical review articles that present groundbreaking research on topics spanning energy generation, utilization, conversion, storage, transmission, conservation, management, and sustainability. The scope of Energy Conversion and Management: X encompasses various forms of energy, including mechanical, thermal, nuclear, chemical, electromagnetic, magnetic, and electric energy. It addresses all known energy resources, highlighting both conventional sources like fossil fuels and nuclear power, as well as renewable resources such as solar, biomass, hydro, wind, geothermal, and ocean energy.
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