Metaheuristic Approaches to Solve a Complex Aircraft Performance Optimization Problem

The increasing demands for travelling comfort and reduction of carbon dioxide emissions have been considered substantially in the stage of conceptual aircraft design. However, the design of a modern aircraft is a multidisciplinary process, which requires the coordination of information from several specific disciplines, such as structures, aerodynamics, control, etc. To address this problem with adequate accuracy, the multidisciplinary analysis and optimization (MAO) method is usually applied as a systematic and robust approach to solve such complex design issues arising from industries. Since MAO method is tedious and computationally expensive, genetic programming (GP)-based metamodeling techniques incorporating MAO are proposed as an effective approach to minimize the wing stiffness of a large aircraft subject to aerodynamic, aeroelastic and stability constraints in the conceptual design phase. Based on the linear small-disturbance theory, the state-space equation is employed for stability analysis. In the process of multidisciplinary analysis, aeroelastic response simulations are performed using Nastran. To construct metamodels representing the responses of the interests with high accuracy as well as less computational burden, optimal Latin hypercube design of experiments (DoE) is applied to determine the optimized distribution of sampling points. Following that, parametric optimization is carried out on metamodels to obtain the optimal wing geometry shape, elastic axis positions and stiffness distribution, and then the solution is verified by finite element simulations. Finally, the superiority of the GP-based metamodel technique over genetic algorithm is demonstrated by multidisciplinary design optimization of a representative beam-frame wing structure in terms of accuracy and efficiency. The results also show that GP metamodel-based strategy for solving MAO problems can provide valuable insights to tailoring parameters for the effective design of a large aircraft in the conceptual phase.

The Analyses of Vehicle-to-Pedestrian Accidents by Integrating Rigid-Body Simulation and Robust Optimization Techniques

The objective of this study is to propose an approach for improving the efficiency of accident reconstruction and obtaining the probabilistic distribution of pre-impact parameters through integrating numerical simulation and robust optimization techniques. First, the ranges and probabilistic distribution of collision parameters are determined by investigators. Then, the optimal Latin hypercube design is used to generate sample points in predefined design space and corresponding responses are obtained by PC-Crash. The radial basis functions method is used to construct the surrogate models, accuracy evaluation is conducted using the cross-validation method. Finally, a robust optimization is completed to obtain the probabilistic distribution of collision parameters. Furthermore, a real-world vehicle-to-pedestrian accident is reconstructed to specifically explain and validate the method. The results show that the numerical simulation coupled with robust optimization technique is an effective means of obtaining the probabilistic distribution of pre-impact inputs. The proposed approach will help the traffic accident to scientifically conduct the traffic accident identification.

Metamodel-assisted design optimization of piezoelectric flex transducer for maximal bio-kinetic energy conversion

Energy-harvesting devices have been widely used to generate electrical power from the bio-kinetic energy of human body movement. A novel piezoelectric flex transducer based on the Cymbal device has been proposed by other researchers for the purpose of energy harvesting. To further improve the efficiency of the device, optimal design of the piezoelectric flex transducer for maximum output power subject to stress and displacement constraints is carried out in this article. Sequential quadratic programming on metamodels generated with genetic programming from a 140-point optimal Latin hypercube design of experiments is used in the optimization. Finally, the optimal design is validated by finite element simulations. The simulations show that the magnitude of the electrical power generated from this optimal piezoelectric flex transducer harvesting device can be up to 6.5 MW when a safety design factor of 2.0 is applied.