Including detailed chemistry features in the modeling of emerging low-temperature reactive flows: A review on the application to diluted and MILD combustion systems

Giancarlo Sorrentino , Giovanni Battista Ariemma , Federica Ferraro , Benoit Fiorina
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Abstract

Developing and optimizing new reactive systems with carbon-neutral fuels like biofuels, e-fuel, hydrogen, or ammonia is crucial for sustainable energy. This requires advanced technologies capable of fuel flexibility, high efficiency, and minimal pollutant emissions. However, these energy carriers still produce pollutants, especially NOx. To address this, engineers aim to lower combustion process temperatures by adopting different strategies such as burned gas recirculation, staging or increasing the air-to-fuel ratio. Yet, lean flames, though effective at emission reduction, are prone to instability and extinction, posing safety and mechanical risks. Emerging technologies like MILD Combustion, based on burned gas recirculation and reactant dilutions offer interesting solutions. The review article begins by synthesizing experimental studies and numerical simulations of MILD turbulent combustion. It then explores fundamental phenomena specific to diluted combustion (where MILD regimes are included as sub-sets), including autoignition and flame propagation. Using high-fidelity simulations and advanced experiments, it examines flow and mixing roles in reactive zones stabilization. Moving forward, the review paper addresses the inclusion of detailed chemical properties in modeling turbulent combustion systems. Scientific challenges revolve around modeling the intricate interactions between combustion chemistry and flow turbulence while maintaining computational efficiency compatible with industrial constraints. To address this, various simplified chemistry methods – such as reduced, tabulated, or optimized chemistry – have been developed. Additionally, turbulence/chemistry coupling modeling remains unresolved in simulations, with three main routes – geometrical, statistical, or reactor-based approaches – available for turbulent combustion modeling. The state-of-the-art in simplified chemistry and turbulent combustion modeling for low-temperature regimes is then focused on capturing MILD regimes, where there is a crucial impact of dilution by burnt gases, heat transfer, and turbulence mixing on the chemical flame structure. Recent advancements enabled by machine learning and deep learning algorithms are also highlighted. Lastly, the article underscores the critical need for data to validate models, emphasizing the importance of scale-bridging experiments.
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在新出现的低温反应流建模中加入详细的化学特征:稀释和 MILD 燃烧系统应用综述
开发和优化使用生物燃料、电子燃料、氢气或氨等碳中性燃料的新型反应系统对于可持续能源至关重要。这就要求采用先进的技术,以实现燃料的灵活性、高效率和最低的污染物排放。然而,这些能源载体仍然会产生污染物,尤其是氮氧化物。为了解决这个问题,工程师们采用了不同的策略,如燃烧气体再循环、分级或增加空气与燃料的比例,以降低燃烧过程的温度。然而,贫焰虽然能有效减少排放,但容易出现不稳定和熄灭现象,带来安全和机械风险。基于燃烧气体再循环和反应物稀释的新兴技术(如 MILD Combustion)提供了有趣的解决方案。综述文章首先综合了 MILD 湍流燃烧的实验研究和数值模拟。然后,文章探讨了稀释燃烧(MILD 状态作为子集)特有的基本现象,包括自燃和火焰传播。利用高保真模拟和先进的实验,研究了反应区稳定过程中的流动和混合作用。展望未来,综述论文探讨了将详细的化学特性纳入湍流燃烧系统建模的问题。科学挑战围绕着对燃烧化学和流动湍流之间错综复杂的相互作用进行建模,同时保持符合工业限制的计算效率。为解决这一问题,人们开发了各种简化化学方法,如简化化学、表格化学或优化化学。此外,湍流/化学耦合建模在模拟中仍未得到解决,湍流燃烧建模主要有三种途径--几何、统计或基于反应器的方法。低温条件下简化化学和湍流燃烧建模的最新技术主要集中在捕捉 MILD 条件下,燃烧气体的稀释、热传递和湍流混合对化学火焰结构有着至关重要的影响。文章还重点介绍了机器学习和深度学习算法的最新进展。最后,文章强调了数据对验证模型的关键需求,强调了规模桥接实验的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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