This article reports on the development of a fast method for generating the aerodynamic database for subsonic flow over a missile. At present, this is typically achieved using RANS-based CFD, which is expensive for the complex missile geometries and the multiplicity of operating conditions to be evaluated. The presented reduced-order model (ROM) provides a reasonably accurate prediction of the aerodynamic coefficients of the missile (and, in fact, the full flow field around it) within half a minute. In particular, in the interpolative regime, prediction errors for all coefficients are typically less than 1% of their respective maximum values encountered in the database, with extrapolation incurring more error. The empirical approach ‘learns’ from the CFD solutions calculated for a few operating conditions, and then is able to make predictions for any other condition within a feasible set. The learning employs proper orthogonal decomposition (POD) to characterise the most important features of the flow. The prediction is posed as an optimisation problem that aims to find the flow solution as a linear combination of the above POD modes that minimises the residual of the governing equations. Innovations on the prevailing POD-ROM approach include novel implementation of boundary conditions, simplified computation of the aerodynamic coefficients, and a procedure for choosing modelling parameters based on extensive cross-validation. Challenges overcome in application to a problem of industrial relevance are discussed.

Several critical load cases during the aircraft design process result from atmospheric turbulence. Thus, rapidly performable and highly accurate dynamic response simulations are required to analyse a wide range of parameters. A method is proposed to predict dynamic loads on an elastically trimmed, large civil aircraft using computational fluid dynamics in conjunction with model reduction. A small-sized modal basis is computed by sampling the aerodynamic response at discrete frequencies and applying proper orthogonal decomposition. The linear operator of the Reynolds-averaged Navier-Stokes equations plus turbulence model is then projected onto the subspace spanned by this basis. The resulting reduced system is solved at an arbitrary number of frequencies to analyse responses to 1-cos gusts very efficiently. Lift coefficient and surface pressure distribution are compared with full-order, non-linear, unsteady time-marching simulations to verify the method. Overall, the reduced-order model predicts highly accurate global coefficients and surface loads at a fraction of the computational cost, which is an important step towards the aircraft loads process relying on computational fluid dynamics.

The study investigates three-dimensional kinematics of lower limb for female Chinese population during normal squatting activity. 25 young female and 25 elder female Chinese subjects were recruited. With each subject's data collected, the means of three-dimensional rotation angles of knee, hip, and ankle joints of those two groups were calculated and analyzed. Measured results showed that the maximal eccentric range of hip flexion/extension of 128.6° for the young female group (P < 0.05) was compared with that of 158.8° for the elder female group. Thus, the elder female undergoes more hip flexion/extension angles than the young female in the posture of squatting. The mean range of motion (ROM) of knee flexion/extension was 140.2° for the young female group and 138.7° (significant level P > 0.05) for the elder female group. The mean ROM of ankle flexion/extension was 47.90° for the young female group and 31.9° (P > 0.05) for the elder female group. The ROMs obtained in the experiment during squatting were greater than the reported ones achieved after joint arthroplasty. These data may be invaluable in providing designers of lower limb prosthesis with basic mechanical parameters, and assessing the effect of kinematics of low limb on rehabilitation for the Chinese population.