Advanced Aerostructural Optimization Techniques for Aircraft Design

Abstract

Traditional coupled aerostructural design optimization (ASDO) of aircraft based on high-fidelity models is computationally expensive and inefficient. To improve the efficiency, the key is to predict aerostructural performance of the aircraft efficiently. The cruise shape of the aircraft is parameterized and optimized in this paper, and a methodology named reverse iteration of structural model (RISM) is adopted to get the aerostructural performance of cruise shape efficiently. A new mathematical explanation of RISM is presented in this paper. The efficiency of RISM can be improved by four times compared with traditional static aeroelastic analysis. General purpose computing on graphical processing units (GPGPU) is adopted to accelerate the RISM further, and GPU-accelerated RISM is constructed. The efficiency of GPU-accelerated RISM can be raised by about 239 times compared with that of the loosely coupled aeroelastic analysis. Test shows that the fidelity of GPU-accelerated RISM is high enough for optimization. Optimization framework based on Kriging model is constructed. The efficiency of the proposed optimization system can be improved greatly with the aid of GPU-accelerated RISM. An unmanned aerial vehicle (UAV) is optimized using this framework and the range is improved by 4.67% after optimization, which shows effectiveness and efficiency of this framework.

Numerical Modelling of Static Aeroelastic Deformations of Slender Wing in Aerodynamic Design

“…Correctly predicting aerodynamic and aeroelastic effects and implementing design solutions early in developing a new aircraft can bring multiple benefits, such as reduced development costs and time and improved economic efficiency, safety, and comfort. For a slender wing with a high aspect ratio, designers must anticipate and designate several different wing shapes dependent on the angle of attack and load coefficient [1]. These factors are interdependent through the internal structure (stiffness) and loads (aerodynamic and mass).…”

Energy Management Strategy for High-Altitude Solar Aircraft Based on Multiple Flight Phases

“…Due to the rapid development of solar cell technology, solar energy can gradually play a leader role in exploring the field of renewable and clean energy [1][2][3]. erefore, making use of solar energy to fly is a research hotspot, which has attracted a lot of research groups all around the world during the past few years [4][5][6][7][8][9][10].…”

“…Since the solar energy is renewable and inexhaustible, it has the potential to redefine and increase the flight endurance of aircraft. In the last ten years, many countries and research teams have made great efforts to develop the high-altitude solar aircraft (HSA) [2,[6][7][8][9][10][11][12] for the reason that the HSA have the ability to stay over a wide area at high altitude for long endurance; they can function as geostationary satellites, but they are much economical [13,14]. ey are ideally suited to be widely employed in many applications such as natural monitoring, border patrol, planetary exploration, communications relay, remote sensing, field investigations, network services, and electronic warfare [14].…”

RPAS Design : an MDO Approach

“…In [170], an MDO advisory system, coupled to an optimization configurator for a Process Integration and Design Optimization (PIDO) system is presented; [171] introduces a platform that automatically creates and performs aeroelastic and mass calculations with a FEM model; in [172], a system for aircraft systems integration is explained and ,additionally, [173] provides a tool to manually generate RPAS configurations from a database and estimate their performance; also, in [174], a similar tool is developed, aimed at calculating manufacturing costs. Even though the last four works do not perform any kind of optimization, this type of tools are part of more complex MDO structures, such as the one in [175], which consists of different and progressively detailed optimization loops for more; or [176], where Reverse Iteration of Structural Model (RISM) is proposed as a technique to be used with surrogate models to solve faster, and with enough precision, aircraft designing problems; in [177] the authors present pyOpt, a framework for optimization mostly employing SQP, SLSQP and MMA, but with several other algorithms available; and [178], another MDO framework linked to CAD solvers. In most methods there is also the choice to allow the model to study unfeasible solutions.…”