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Uncertainty-based design optimization of NLF airfoil for high altitude long endurance unmanned air vehicles

机译:基于不确定性的NLF翼型设计优化,高海拔长耐力无人机

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Purpose The high probability of the occurrence of separation bubbles or shocks and early transition to turbulence on surfaces of airfoil makes it very difficult to design high-lift and high-speed Natural-Laminar-Flow (NLF) airfoil for high-altitude long-endurance unmanned air vehicles. To resolve this issue, a framework of uncertainty-based design optimization (UBDO) is developed based on an adjusted polynomial chaos expansion (PCE) method.Design/methodology/approach The Re-t transition model combined with the shear stress transport k- turbulence model is used to predict the laminar-turbulent transition. The particle swarm optimization algorithm and PCE are integrated to search for the optimal NLF airfoil. Using proposed UBDO framework, the aforementioned problem has been regularized to achieve the optimal airfoil with a tradeoff of aerodynamic performances under fully turbulent and free transition conditions. The tradeoff is to make sure its good performance when early transition to turbulence on surfaces of NLF airfoil happens.Findings The results indicate that UBDO of NLF airfoil considering Mach number and lift coefficient uncertainty under free transition condition shows a significant deterioration when complicated flight conditions lead to early transition to turbulence. Meanwhile, UBDO of NLF airfoil with a tradeoff of performances under both fully turbulent and free transition conditions holds robust and reliable aerodynamic performance under complicated flight conditions.Originality/value In this work, the authors build an effective uncertainty-based design framework based on an adjusted PCE method and apply the framework to design two high-performance NLF airfoils. One of the two NLF airfoils considers Mach number and lift coefficient uncertainty under free transition condition, and the other considers uncertainties both under fully turbulent and free transition conditions. The results show that robust design of NLF airfoil should simultaneously consider Mach number, lift coefficient (angle of attack) and transition location uncertainty.
机译:目的,在翼型表面上发生分离气泡或冲击的高概率和对翼型表面的湍流的早期过渡使得设计高升力和高速自然层流(NLF)翼型以获得高空的长耐久性无人驾驶飞行器。若要解决此问题,基于调整后的多项式混沌扩展(PCE)方法开发了一种基于不确定性的设计优化(UBDO)的框架.Design/methodology/ApproCh与剪切应力传输K-湍流相结合模型用于预测层流湍流过渡。粒子群优化算法和PCE集成以搜索最佳NLF翼型。使用所提出的UBDO框架,已经规范化了上述问题,以实现最佳翼型在完全湍流和自由过渡条件下具有空气动力学性能的权衡。权衡是为了确保当早期过渡到NLF翼型的表面上的湍流时的良好表现。挑战结果表明,在复杂的飞行条件下,考虑马赫数和升力系数不确定的NLF翼型的UBDO显示出在复杂的飞行条件下的显着恶化早期过渡到湍流。同时,NLF翼型的UBDO具有在完全湍流和自由过渡条件下进行性能的缩减,在复杂的飞行条件下具有稳健且可靠的空气动力学性能。这项工作中的程度/价值,基于一个有效的基于不确定性的设计框架调整后的PCE方法并应用框架设计两种高性能NLF翼型。两个NLF翼型中的一个在自由过渡条件下考虑马赫数和提升系数不确定性,另一个在完全湍流和自由过渡条件下考虑不确定性。结果表明,NLF翼型的鲁棒设计应同时考虑马赫数,提升系数(攻角)和过渡位置不确定。

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