Metamodelling of Ignition Delay Time for Natural Gas Blends Under Gas Turbine Operating Conditions

Sajjad Yousefian, G. Bourque, R. Monaghan
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Abstract

Characterisation of autoignition risk is crucial for designing and optimising low-emission combustion systems as there is an increased demand for highly reactive and novel fuel mixtures. Achieving a residence time to prevent autoignition and obtaining an adequate mixing quality is a challenging trade-off for these fuels in lean-premixed combustion systems. The level of complexity increases further due to low-temperature chemical pathways and pressure-dependent reactions that strongly influence ignition delay at engine operating conditions. Detailed chemical kinetic mechanisms with hundreds of species and thousands of reactions are developed and employed to address this complexity and predict ignition delay accurately, especially for heavier hydrocarbons. However, direct implementation of these kinetic mechanisms is computationally prohibitive in high-fidelity CFD approaches such as large eddy simulation (LES) and stochastic simulation tools that require a large number of evaluations. Advanced stochastic methods are essential tools to quantify uncertainties due to the inherent variabilities in ambient, operating conditions and fuel composition on ignition delay time calculation for practical applications. This study introduces and implements a computationally efficient method based on metamodellig to predict ignition delay time over a wide range of operating conditions and fuel compositions for gas turbine combustion systems. A metamodel or surrogate model is an accurate and quick approximation of the original computational model based on a detailed chemical kinetic mechanism. Polynomial chaos expansion (PCE) as an advanced method is employed to build metamodels using a limited set of runs of the original ignition delay time model based on NUIGMech1.0 chemical kinetic mechanism as the most detailed and state-of-the-art chemical kinetic mechanism for natural gas. Developed metamodels for ignition delay time are valid over operating conditions of P = 20–40 bar and T = 700–900 K for natural gas containing C1 to C7 hydrocarbons at stoichiometric condition. These metamodels provide a fast, robust, and considerably accurate framework instead of a detailed chemical kinetic model that facilitates (a) characterising ignition delay time at different operating conditions and fuel compositions, (b) designing and optimising premixers and burners and (c) conducting uncertainty quantification and stochastic modelling studies.
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燃气轮机工况下天然气混合物点火延迟时间的元建模
随着对高活性和新型燃料混合物的需求不断增加,自燃风险的表征对于设计和优化低排放燃烧系统至关重要。实现停留时间,以防止自燃和获得适当的混合质量是一个具有挑战性的权衡这些燃料在稀预混燃烧系统。由于低温化学途径和压力依赖性反应对发动机工作条件下的点火延迟有很大影响,因此复杂性进一步增加。数百种物质和数千种反应的详细化学动力学机制被开发和应用,以解决这一复杂性,并准确预测点火延迟,特别是对于较重的碳氢化合物。然而,在需要大量评估的高保真CFD方法(如大涡模拟(LES)和随机模拟工具)中,直接实现这些动力学机制在计算上是禁止的。在实际应用中,先进的随机方法是量化由于环境、操作条件和燃料成分的内在变异性而导致的点火延迟时间计算中的不确定性的重要工具。本文介绍并实现了一种基于元建模的高效计算方法,用于燃气轮机燃烧系统在多种工况和燃料成分下的点火延迟时间预测。元模型或替代模型是基于详细的化学动力学机制的原始计算模型的精确和快速近似。采用多项式混沌展开(PCE)作为一种先进的方法,利用基于NUIGMech1.0化学动力学机理的原始点火延迟时间模型的有限运行集建立元模型,NUIGMech1.0化学动力学机理是目前最详细、最先进的天然气化学动力学机理。所建立的点火延迟时间元模型在P = 20 ~ 40 bar, T = 700 ~ 900 K的化学计量条件下对含C1 ~ C7烃的天然气是有效的。这些元模型提供了一个快速、稳健且相当准确的框架,而不是一个详细的化学动力学模型,它有助于(a)表征不同操作条件和燃料成分下的点火延迟时间,(b)设计和优化预混器和燃烧器,以及(c)进行不确定性量化和随机建模研究。
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