Low observable uncrewed aerial vehicle wind tunnel model design, manufacturing, and aerodynamic characterization

Developing wind tunnel models is time consuming, labor intensive, and expensive. Rapid prototyping for wind tunnel tests is an effective, faster, and cheaper method to obtain aerodynamic performance results while considerably reducing acquisition time and cost for the models. Generally, the rapid prototyping models suffer from insufficient stiffness or strength to withstand the loads generated during a wind tunnel test. In the present study, a rapid prototype model reinforced with metallic inserts was produced to experimentally investigate the aerodynamic characteristics of an uncrewed aerial vehicle with various wingtip deflections. The fused deposition modeling process was used to make the outer mold, whereas the metallic parts were produced using laser cutting and the computer numerical control machining process. Then, the model was evaluated both experimentally and numerically. The test campaign presented in this work was conducted in the de Havilland low-speed wind tunnel facility at the University of Glasgow. For better characterization of flow patterns dominated by leading edge vortices, numerical simulations were run using OpenFOAM 8.0 and validated with experimental data. The experimental data obtained from the hybrid rapid-prototyped model agreed well with the numerical results. This demonstrates the efficacy of hybrid rapid-prototyped models in providing reliable results for initial baseline aerodynamic database development within a short period and at a reduced cost for wind tunnel tests

Advanced Experiments on Gaussian Process-based Multi-fidelity Methods over Diverse Mathematical Characteristics

Advanced applications of multi-fidelity surrogate modelling techniques provide significant improvements in optimization and uncertainty quantification studies in many engineering fields. Multi-fidelity surrogate modelling can efficiently save the design process from the computational time burden caused by the need for numerous computationally expensive simulations. However, no consensus exists about which multi-fidelity surrogate modelling technique usually exhibits superiority over the other methods given for certain conditions. Therefore, the present paper focuses on assessing the performances of the Gaussian Process-based multi-fidelity methods across selected benchmark problems, especially chosen to capture diverse mathematical characteristics, by experimenting with their learning processes concerning different performance criteria. In this study, a comparison of Linear-Autoregressive Gaussian Process and NonlinearAutoregressive Gaussian Process methods is presented by using benchmark problems that mimic the behaviour of real engineering problems such as localized behaviours, multi-modality, noise, discontinuous response, and different discrepancy types. Our results indicate that the considered methodologies were able to capture the behaviour of the actual function sufficiently within the limited amount of budget for 1-D cases. As the problem dimension increases, the required number of training data increases exponentially to construct an acceptable surrogate model. Especially in higher dimensions, i.e. more than 5-D, local error metrics reveal that more training data is needed to attain an efficient surrogate for Gaussian Process based strategies

Predictions of the low-speed aerodynamic characteristics of generic UCAVs

At low speeds, the leading-edge sweep angle influences the flight performance of swept wings. The flow behavior of the moderate to highly swept wings is affected by the vortex flow structures, which form at low angles of attack because of leading-edge flow separation. This topic of investigation gained momentum recently due to its application to unmanned combat aerial vehicle (UCAV) configurations that are significantly affected by flow separation at high angles of attack. The present work investigates the flowfield and low-speed aerodynamic characteristics of the generic UCAV models with constant and non-constant leading-edge sweep for a wide range of angles of attack. The open-source computational fluid dynamics (CFD) code OpenFOAM 8.0 was employed for the numerical simulations. The present numerical simulation results matched well with the experimental data in the literature. It was found that the lift and drag characteristics of the UCAV are sensitive to the leading-edge sweep angle, and a non-constant leading-edge sweep angle variant exhibited delayed stall and enhanced aerodynamic performance

Numerical investigations on low-speed aerodynamic characteristics of generic UCAV configurations

No abstract available

A Multifidelity Aerodynamic Surrogate Model Implementation for Aeroelastic Optimization of a Nonplanar Lifting Surface

No abstract available

PID Parameter Optimization of an UAV Longitudinal Flight Control System

In this paper, an automatic control system design based on Integral Squared Error (ISE) parameter optimization technique has been implemented on longitudinal flight dynamics of an UAV. It has been aimed to minimize the error function between the reference signal and the output of the plant. In the following parts, objective function has been defined with respect to error dynamics. An unconstrained optimization problem has been solved analytically by using necessary and sufficient conditions of optimality, optimum PID parameters have been obtained and implemented in control system dynamics

Conceptual design of a non-constant leading-edge flying wing UCAV model

No abstract available