Adjoint-Based Optimization for the Venturi Mixer of a Burner

Min Xu, Akram Radwan, Yu Xia
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Abstract

The optimization of Venturi mixers in burners is critical for enhancing combustion efficiency and minimizing emissions. In this study, we utilize the adjoint method to analyze and refine the design of a Venturi mixer. Our numerical simulations integrate the species transport equation with the Eddy Dissipation Model (EDM) for reacting flow and the generalized k-omega (GEKO) model to simulate turbulence. By solving adjoint equations, we effectively compute the shape sensitivity for various observables, including pressure drop, outlet fuel variance/uniformity deviation index, air and fuel mass flow rates, and outlet CO mass fraction. The shape sensitivity analysis uncovers the interplay between the observables and the appropriate weights for multiple objective optimizations. Subsequently, we perform gradient-based optimizations to enhance the mixer's performance, employing both shape sensitivity and mesh morphing techniques. We conduct a series of case studies focusing on both cold and reacting flows. The optimization of cold flow provides an in-depth exploration of various optimization strategies, encompassing single-objective and multi-objective optimization with diverse weight combinations. Following this, the optimization of reacting flow enhances the mixer's functionality under combustion conditions, emphasizing the reduction of emissions and the increase of combustion efficiency. Our findings showcase the potential of an adjoint-based optimization framework in designing Venturi mixers that are efficient and emit lower levels of pollutants.
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燃烧器文丘里混合器的邻接优化
燃烧器中文丘里混合器的优化对于提高燃烧效率和减少排放至关重要。在本研究中,我们利用邻接法分析并完善了文丘里混合器的设计。我们的数值模拟将物种传输方程与用于反应流的涡流耗散模型 (EDM) 和用于模拟湍流的广义 k-omega (GEKO) 模型相结合。通过求解邻接方程,我们有效地计算了各种观测指标的形状敏感性,包括压降、出口燃料方差/均匀性偏差指数、空气和燃料质量流量以及出口一氧化碳质量分数。形状灵敏度分析揭示了观测值之间的相互作用以及多目标优化的适当权重。随后,我们采用形状灵敏度和网格变形技术进行基于梯度的优化,以提高混合器的性能。我们针对冷流和反应流进行了一系列案例研究。冷流优化深入探讨了各种优化策略,包括单目标和多目标优化,以及不同的权重组合。随后,反应流的优化增强了混合器在燃烧条件下的功能,强调了减少排放和提高燃烧效率。我们的研究结果展示了基于邻接的优化框架在设计高效且污染物排放量较低的文丘里混合器方面的潜力。
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