A design platform for airship shape optimization with propeller is established with computational fluid dynamics and optimization techniques. Firstly, Hicks-Henne shape functions were used to parameterize hull of the airship. Then,a hybrid dynamic mesh generation method was presented based on inverse distance weighting (IDW) interpolation and transfinite interpolation (TFI). An actuator disk model of propeller was employed to simulate viscous flow around the airship. LOTTE airship was chosen as the initial shape, and drag coefficient was chosen as the objective function. Airship volume was selected as a constraint. The optimized shape based on non-linear programming by quadratic lagrangian (NLPQL) algorithm was obtained. It shows that afterbody shape of the optimized airship is relatively flat and location of the maximum diameter moves forward. Aerodynamic performance of the new shape is significantly improved. Compared with that of the LOTTE hull,drag coefficient of the optimized shape is reduced by 26.88%.

An improved cuckoo search (ICS) algorithm is developed to identify temperature dependent thermal conductivity for transient heat conduction problems. Kirchhoff transformation is adopted to transform nonlinear transient heat conduction problems into linear problems. The direct problems are solved by boundary element method. Inversion of thermal conductivity is transformed to estimate unknown coefficients, which is solved by ICS algorithm. ICS algorithm is less sensitive to iterative initialization than conjugate gradient method and ICS algorithm has high efficient convergence compared with cuckoo search (CS) algorithm. For ICS, numerical examples indicate that increase of measured point number causes increase of iteration numbers, whereas increase of nest number decreases iteration numbers. The less the measured noise is, the higher the precision of results is. Iteration numbers decrease at the same time. It shows that ICS algorithm is an accurate and efficient method for identification of thermal conductivity.