Applications of structural efficiency assessment method on structural-mechanical characteristics integrated design in aero-engines

In the design process of advanced aero-engines, it is necessary to carry out an effective analysis method between structural features and mechanical characteristics for a better structural optimization. Based on the structural composition and functions of aero-engines, the concept and contents of structural efficiency can reflect the relation between structural features and mechanical characteristics. In order to achieve the integrated design of structural and mechanical characteristics, one quantitative analysis method called Structural Efficiency Assessment Method (SEAM) was put forward. The structural efficiency coefficient was obtained by synthesizing the parameters to quantitatively evaluate the aero-engine structure design level. Parameterization method to evaluate structural design quality was realized. After analyzing the structural features of an actual dual-rotor system in typical high bypass ratio turbofan engines, the mechanical characteristics and structural efficiency coefficient were calculated. Structural efficiency coefficient of high-pressure rotor (0.43) is higher than that of low-pressure rotor (0.29), which directly shows the performance of the former is better, there is room for improvement in structural design of the low-pressure rotor. Thus the direction of structural optimization was pointed out. The applications of SEAM shows that the method is operational and effective in the evaluation and improvement of structural design.     

企业知识生态系统内生与外生协同机制研究

通过对企业知识生态系统协同机制的研究,设计知识生态系统内生和外生协同机制.内生协同机制包括企业知识生态系统战略协同机制、内部环境协同机制、领导协同机制、知识主体协同机制、激励协同机制的设计.外生协同机制包括外部环境协同机制设计、行业发展协同机制设计、技术协同机制设计,从而保障企业知识生态系统正常运行.     

某框基于后置程序逆向设计及数字化高效加工研究

介绍了飞机某框从逆向设计到数字化高效加工详细流程,应用以CATIA V5、VERICUT为代表的先进数字化制造技术,使零件数字化设计、数字化加工、工艺流程得到全面改进,为今后零件逆向设计及数字化加工奠定良好的基础。     

Multiscale topology optimization using feature-driven method

This paper presents a multiscale design method for simultaneous topology optimization of both macrostructures and microstructures. Geometric features are extended as design primitives at both macro and micro scales and represented by Level Set Functions (LSFs). Parameters related to the locations, sizes, and orientations of macro and micro features are considered as design variables and optimized simultaneously. In the overlapping areas of different macro features, embedded microstructures are optimally figured out as the solution of the corresponding sub-optimization problem. In this study, the eXtended Finite Element Method (XFEM) is implemented for structural and sensitivity analyses with respect to design variables. This method has the advantage of using a fixed grid independent of the topology optimization process. The homogenization procedure is applied to calculate the effective properties of considered microstructures in each macro feature. Numerical examples are presented to illustrate the effectiveness of the proposed method. Results depict that the multiscale design cannot obviously improve structural stiffness compared with a solid-material design under the linear elastic condition.     

Sliding mode control design for oblique wing aircraft in wing skewing process

When the wing of Oblique Wing Aircraft (OWA) is skewed, the center of gravity, inertia and aerodynamic characteristics of the aircraft all significantly change, causing an undesirable flight dynamic response, affecting the flying qualities, and even endangering the flight safety. In this study, the dynamic response of an OWA in the wing skewing process is simulated, showing that the three-axis movements of the OWA are highly coupled and present nonlinear characteristics during the wing skewing. As the roll control efficiency of the aileron decreases due to the shortened control arm in an oblique configuration, the all-moving horizontal tail is used for additional roll and the control allocation is performed based on minimum control energy. Given the properties of pitch-roll-yaw coupling and control input and state coupling, and the difficulty of establishing an accurate aerodynamic model in the wing skewing process due to unsteady aerodynamic force, a multi-loop sliding mode controller is formulated by the time-scale separation method. The closed-loop simulation results show that the asymmetric aerodynamics can be balanced and that the velocity and altitude of the aircraft maintain stable, which means that a smooth transition is obtained during the OWA’s wing skewing.     

Assessment on critical technologies for conceptual design of blended-wing-body civil aircraft

Civil aviation faces great challenges because of its robust projected future growth and potential adverse environmental effects. The classical Tube-And-Wing(TAW) configuration following the Cayley's design principles has been optimized to the architecture's limit, which can hardly satisfy the further requirements on green aviation. By past decades' investigations the BlendedWing-Body(BWB) concept has emerged as a potential solution, which can simultaneously fulfill metrics of noise, emission and fuel burn. The purpose of the present work is to analyze the developments of critical technologies for BWB conceptual design from a historical perspective of technology progress. It was found that the high aerodynamic efficiency of BWB aircraft can be well scaled by the mean aerodynamic chord and wetted aspect ratio, and should be realized with the trade-offs among stability and control and low-speed performance. The structure concepts of non-cylinder pressurized cabin are of high risks on weight prediction and weight penalty. A static stability criterion is recommended and further clear and adequate criteria are required by the evaluations of flying and handling qualities. The difficulties of propulsion and airframe integration are analyzed. The energy to revenue work ratios of well-developed BWB configurations are compared,which are 31.5% and 40% better than that of TAW, using state-of-art engine technology and future engine technology, respectively. Finally, further study aspects are advocated.     

Contingency target assessment,trajectory design,and analysis for NASA’s NEA scout solar sail mission

The presented study examines contingency target selection and trajectory design for NASA’s Near-Earth Asteroid Scout mission under the assumption of a missed lunar gravity assist. Two previously considered asteroids are selected as potential targets for the given scenario based on favorable orbital characteristics for launch dates ranging from June 27, 2020 through July 26, 2020. Initially, a simplified circular restricted 3-body problem + ideal solar sail model is utilized to survey trajectory options for a month-long launch window. Selected solutions from this data set are then converged in an N-body ephemeris + non-ideal sail model. Results suggest that NEA Scout can still perform asteroid rendezvous mission under the missed lunar gravity assist scenario with new targets, 2019 GF1, 2018 PK21, and 2007 UN12, based on the target launch dates. Further target assessment is carried out for 165 days beyond the current June 27, 2020 launch date.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

基于多可信度代理模型的尾喷管优化设计

尾喷管是飞行器机体/推进一体化设计中的关键部件之一,直接影响着飞行器的推阻匹配、俯仰力矩配平等特性。为了提高尾喷管优化设计效率,建立基于多可信度代理模型的多目标优化模型。以基于粗网格、无黏模型的CFD 结果作为低可信度数据,以基于细密网格、SST k-ω 湍流模型的CFD 结果作为高可信度数据,将最大化推力系数、升力系数和俯仰力矩系数作为优化目标,构建Cokriging 模型,并结合NSGA-Ⅱ算法得到Pareto 解集。结果表明：以上三个目标分别提升了2.94%、13.0% 和40.6%,误差低于0.5%,并进行了敏感性分析;优化后流场波系结构更为复杂,改变了壁面压强分布规律;与Kriging 模型相比,Cokriging 模型具有相当的预测性能,构建时间成本节省了62%。     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.