Search Results (4)

In this research, the architecture and the functionalities of the LAMBDA (Laboratory of Aircraft Multidisciplinary Knowledge-Based Design and Analysis) framework for the design, analysis, and optimization of civil aircraft are presented. The framework is developed in MATLAB R2022a and comprises a modular architecture, which gives the potential for the use of different methods and fidelities for each discipline. The methods can be selected from a set of built-in methods or custom user-defined scripts. Disciplinary modules of the LAMBDA are Requirements, Weight, Sizing, Geometry, Aerodynamics, Engine, Performance, Cost, Emission, and Optimization. This framework has been used for different types of design and optimization problems. When it is applied for the design and optimization of a novel regional TBW (Truss-Braced Wing) aircraft, the operating cost has been reduced by 7.7% in the optimum configuration compared to the base configuration. Full article

Currently, the aviation industry is facing an oil and energy crisis and is contributing much more greenhouse gas emissions to the environment. Aircraft design approaches, such as aerodynamic shape optimization, new configuration concepts, and active control technology, have been the primary and effective means of achieving goals concerning fuel burn, noise, and emissions. For now, the design problems of relaxed static stability (RSS, an active control technique) and truss-braced wing (TBW) configurations with high-fidelity aerodynamic shape optimization methods have been investigated widely to promote aerodynamic performance. Nevertheless, they are studied almost always separately, and the combination of exploration and refined design is rarely presented. Therefore, the purposes of this work are to evaluate the benefits of RSS on a full TBW wing–body–tail configuration under various flight conditions and the effects on multi-components and to further explore the potential and analyze the aerodynamic features with the combination of shape optimization and RSS. To address these issues, on the one hand, a range of seven static stability margins are adopted to evaluate its effects with a high-fidelity Reynolds-averaged Navier–Stokes solver. On the other hand, seven cases of drag minimization multipoint aerodynamic design optimization are performed, which are with 600 shape variables and 13 twist variables, subject to lift coefficient, trim, and thickness constraints. The results indicate that with RSS only, the initial configuration has a 2.39% drag reduction under cruise conditions and a 3.01% and a 5.24% drag reduction under two off-design conditions. Additionally, the effects on the multi-components are observed and analyzed. Moreover, all of the optimized configurations with RSS have 2.13%, 2.42%, and 2.12% drag reductions under cruise conditions, drag divergence conditions, and near-buffet-onset conditions, respectively. The most promising optimized configuration has a lift-to-drag ratio of 24.48 with an aerodynamic efficiency of 17.14. The evaluations with a series of off-design points also present high-level aerodynamic efficiency. Full article

As part of the United Arab Emirates’ and the world’s aviation goal of reaching net-zero greenhouse gas emissions by 2050, this paper studied the potential of successfully implementing both biofuel “drop-in” alternatives and aerodynamically efficient configurations to decarbonize the aviation industry. By investigating various proposed designs through a PUGH analysis, it was concluded that the optimum design has a Transonic Truss-Braced Wing configuration and runs on 60% biofuel. Although the design stipulates a 1.3% increase in weight, this does not negate the reduction in emissions and fuel consumption. This study also explored the various types of biofuels and found camelina seeds to be the best choice. The effects of biofuels in comparison with Jet-A fuel were further deliberated in a fuel combustion simulation performed on the Ansys-Fluent software. The results of the simulation showed a reduction of 50% in carbon monoxide (CO) and 24% in carbon dioxide (CO₂) emissions when burning camelina biofuel rather than Jet-A, making it an ideal alternative to those conventional jet fuels. A primary cost analysis of biofuel applications showed an increase of 453 USD (1653.18 AED) per passenger flying on board 100%-biofuel-powered aircrafts. Yet, considering the trend of the cost increase with the biofuel blend ratio, a solution may exist to the increased cost of biofuel-powered aircrafts. Full article

Attitude control of a novel regional truss-braced wing (TBW) aircraft with low stability characteristics is addressed in this paper using Reinforcement Learning (RL). In recent years, RL has been increasingly employed in challenging applications, particularly, autonomous flight control. However, a significant predicament confronting discrete RL algorithms is the dimension limitation of the state-action table and difficulties in defining the elements of the RL environment. To address these issues, in this paper, a detailed mathematical model of the mentioned aircraft is first developed to shape an RL environment. Subsequently, Q-learning, the most prevalent discrete RL algorithm, will be implemented in both the Markov Decision Process (MDP) and Partially Observable Markov Decision Process (POMDP) frameworks to control the longitudinal mode of the proposed aircraft. In order to eliminate residual fluctuations that are a consequence of discrete action selection, and simultaneously track variable pitch angles, a Fuzzy Action Assignment (FAA) method is proposed to generate continuous control commands using the trained optimal Q-table. Accordingly, it will be proved that by defining a comprehensive reward function based on dynamic behavior considerations, along with observing all crucial states (equivalent to satisfying the Markov Property), the air vehicle would be capable of tracking the desired attitude in the presence of different uncertain dynamics including measurement noises, atmospheric disturbances, actuator faults, and model uncertainties where the performance of the introduced control system surpasses a well-tuned Proportional–Integral–Derivative (PID) controller. Full article