Morphing Wing Structural Optimization Using Opposite-Based Population-Based Incremental Learning and Multigrid Ground Elements

This paper has twin aims. Firstly, a multigrid design approach for optimization of an unconventional morphing wing is proposed. The structural design problem is assigned to optimize wing mass, lift effectiveness, and buckling factor subject to structural safety requirements. Design variables consist of partial topology, nodal positions, and component sizes of a wing internal structure. Such a design process can be accomplished by using multiple resolutions of ground elements, which is called a multigrid approach. Secondly, an opposite-based multiobjective population-based incremental learning (OMPBIL) is proposed for comparison with the original multiobjective population-based incremental learning (MPBIL). Multiobjective design problems with single-grid and multigrid design variables are then posed and tackled by OMPBIL and MPBIL. The results show that using OMPBIL in combination with a multigrid design approach is the best design strategy. OMPBIL is superior to MPBIL since the former provides better population diversity. Aeroelastic trim for an elastic morphing wing is also presented

Aircraft morphing wing design by using partial topology optimization

A morphing wing concept has been investigated over the last decade because it can effectively enhance aircraft aerodynamic performance over a wider range of flight conditions through structural flexibility. The internal structural layouts and component sizes of a morphing aircraft wing have an impact on aircraft performance i.e. aeroelastic characteristics, mechanical behaviors, and mass. In this paper, a novel design approach is proposed for synthesizing the internal structural layout of a morphing wing. The new internal structures are achieved by using two new design strategies. The first design strategy applies design variables for simultaneous partial topology and sizing optimization while the second design strategy includes nodal positions as design variables. Both strategies are based on a ground structure approach. A multiobjective optimization problem is assigned to optimize the percentage of change in lift effectiveness, buckling factor, and mass of a structure subject to design constraints including divergence and flutter speeds, buckling factors, and stresses. The design problem is solved by using multiobjective population-based incremental learning (MOPBIL). The Pareto optimum results of both strategies lead to different unconventional wing structures which are superior to their conventional counterparts. From the results, the design strategy that uses simultaneous partial topology, sizing, and shape optimization is superior to the others based on a hypervolume indicator. The aeroelastic parameters of the obtained morphing wing subject to external actuating torques are analyzed and it is shown that it is practicable to apply the unconventional wing structures for an aircraft

Numerically thermal analysis of a turbine vane at high temperature

Using conjugate heat transfer, thermal analysis of a turbine vane coated with thermal barrier coating (TBC) at a high temperature is presented. Numerical results are carried out at two turbine inlet temperatures (T&infin;) i.e. 783 K (low) and 1566 K (high) under two turbulence intensities (Tus) i.e. 8.3% and 16.6%. The main findings of this research are that for both Tus, the metal surface temperature reduction at the high temperature is higher than that at the low temperature because of the lower heat-flux ratio at the higher temperature. Based on the metal temperature reduction, the increasing inlet temperature has a greater influence than the increasing turbulence intensity. The results also indicate that at T&infin; = 783 K, on the pressure side (PS) the metal surface temperature reduction at Tu = 8.3% is lower than that at Tu = 16.6%, while on the suction side (SS) no significant difference happens when Tu increases. Interestingly, an inverse phenomenon happens for both PS and SS, that is the metal surface temperature reduction at Tu = 8.3% increases above that at Tu = 16.6% when T&infin; increases. This discrepancy may suggest the instability of the surface heat-flux ratio due to complex heat convection at the different inlet temperatures.</p

Investigation of Cooling Performances of a Non-Film-Cooled Turbine Vane Coated with a Thermal Barrier Coating Using Conjugate Heat Transfer

The aim of this paper is to numerically investigate cooling performances of a non-film-cooled turbine vane coated with a thermal barrier coating (TBC) at two turbulence intensities (Tu = 8.3% and 16.6%). Computational fluid dynamics (CFD) with conjugate heat transfer (CHT) analysis is used to predict the surface heat transfer coefficient, overall and TBC effectiveness, as well as internal and average temperatures under a condition of a NASA report provided by Hylton et al. [NASA CR-168015]. The following interesting phenomena are observed: (1) At each Tu, the TBC slightly dampens the heat transfer coefficient in general, and results in the quantitative increment of overall cooling effectiveness about 16-20%, but about 8% at the trailing edge (TE). (2) The protective ability of the TBC increases with Tu in many regions, that is, the leading edge (LE) and its neighborhoods on the suction side (SS), as well as the region from the LE to the front of the TE on the pressure side (PS), because the TBC causes the lower enhancement of the heat transfer coefficient in general at the higher Tu. (3) Considering the internal and average temperatures of the vane coated with two different TBCs, although the vane with the lower thermal conductivity protects more effectively, its role in the TE region reduces more significantly. (4) For both TBCs, the increment of Tu has a relatively small effect on the reduction of the average temperature of the vane