铝热剂燃烧:建模的当前趋势和未来展望

IF 5 Q2 ENERGY & FUELS
Alain Esteve, Carole Rossi
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引用次数: 0

摘要

铝基反应性复合材料,如铝热剂,代表了一类独特的高能材料,其特点是高能量密度,可调的燃烧性能和安全性。这些材料采用机械混合、研磨和物理气相沉积等技术制备,有望实现超越传统含能材料能力的含能功能。应用包括热堵塞,智能起爆,热熔引信在民用设备中,使用炸药是不可行的。不幸的是,工程师和研究人员面临着缺乏预测燃烧模型来优化铝热剂材料的给定应用。原因是对反应和燃烧机理以及控制它们的关键变量的认识和量化不足。这就是为什么在过去的几十年里,从原子尺度的建模到使用计算流体动力学的宏观模拟,开发了几种方法和模型,并在本文中进行了回顾。这些方法提供了对关键反应途径,点火机制和火焰传播动力学的见解。尽管取得了这些进步,但仍存在很大的差距,特别是在高温燃烧过程中多相流动动力学和亚氧化物凝聚/成核过程的捕捉方面。边界分辨瞬态直接数值模拟方法和粒子分辨数值技术将允许获取气体-粒子和粒子-粒子相互作用的知识。机器学习方面的最新突破将进一步加速铝热剂的设计和优化,使其能够建立预测的定量结构-性质关系,以补充大量详细的物理模型。本文综述了铝热剂材料的基础理论发展,并强调需要跨学科的努力,特别是流体动力学家和凝聚态物理学家之间的努力,以充分发挥这些多功能高能材料的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Thermite combustion: Current trends in modeling and future perspectives

Thermite combustion: Current trends in modeling and future perspectives
Aluminum-based reactive composites, such as thermites, represent a unique class of energetic materials characterized by their high energy densities, tunability in combustion properties and safety. Prepared using techniques such as mechanical mixing, milling, and physical vapor deposition, these materials are promising for achieving energetic functions beyond the capabilities of traditional energetic materials. Applications include thermal plugging, smart initiation, pyro-fusing in civilian devices where the use of explosives is not feasible. Unfortunately, engineers and researchers face the lack of predictive combustion models to optimize the thermite materials to a given application. The reason is the insufficient knowledge and quantification of reaction and combustion mechanisms and the key variables governing them. That is why, over the past decades, several approaches and models ranging from atomic-scale modeling to macroscopic simulations using computational fluid dynamics, were developed and are reviewed in this article. These methods provided insights into key reaction pathways, ignition mechanisms, and flame propagation dynamics. Despite these advancements, substantial gaps remain, particularly in capturing multiphase flow dynamics and suboxides condensation/nucleation process during the combustion at high temperature. Boundary-resolved transient direct numerical simulation approach and particle-resolved numerical techniques will allow acquiring knowledge in gas–particle and particle–particle interaction. Recent breakthroughs in machine learning will further accelerate the design and optimization of thermites by enabling the establishment of predictive quantitative structure–property relationships in complement of heavy detailed physical models. This review highlights foundational theoretical developments for thermite materials, and emphasize the need for interdisciplinary efforts particularly between fluid dynamicists and condensed matter physicists to realize the full potential of these versatile energetic materials.
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CiteScore
4.20
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