Afshin Banazadeh

Experimental and computational investigation into the use of co-flow fluidic thrust vectoring on a small gas turbine

This paper presents the application of a relatively new technique of fluidic thrust-vectoring (FTV), named Co-flow, for a small gas-turbines. The performance is obtained via experiment and computational fluid dynamics (CFD). The effects of a few selected parameters including the engine throttle setting, the secondary air mass-flow rate and the secondary slot height upon thrust-vectoring performance are provided. Thrust vectoring performance is characterised by the ability of the system to deflect the engine thrust with respect to the delivered secondary air mass-flow rate. The experimental study was conducted under static conditions in an outdoor environment at Cranfield University workshop that was especially designed for this purpose. As part of this investigation, the system was modelled by CFD techniques, using Pointwises Gridgen software and the three-dimensional flow solver, Fluent. Also, Cranfields gas-turbine performance code (TurboMatch) was utilised to estimate boundary conditions for the CFD analysis with respect to the integrated nozzle. The presented technique is easy-to-use approach and offers better result for thrust-vectoring problems than previously published works. Experimental results do show the overall viability of the blowing slot mechanism as a means of vectoring the engine thrust, with the current configuration. Computational predictions are shown to be consistent with the experimental observations and make the CFD model a reliable tool for predicting Co-flow fluidic thrust-vectoring performance of similar systems.

Investigation on the flight characteristics of a conceptual fluidic thrust-vectored aerial tail-sitter:

Abstract The feasibility of integrating co-flow fluidic thrust-vectoring idea into the dynamics of a small flapless aerial tail-sitter is investigated in this article. The aircraft trimmability in different phases of flight and stability in take-off and level flight, are the main issues of concern for the study presented herein. In this respect, the vehicles characteristic equations are derived by linearization of the general non-linear equations of motion. Since the vehicle was supposed to be merely controlled by fluidic thrust-vectoring, the concept was novel and some new derivatives are introduced. Margins of the required thrust-vector angle, to obtain a steady-state flight condition, are provided by use of the trim analysis. In addition, stability in take-off transition and level flight is considered utilizing the values of the system poles. Non-linear simulation is developed to examine the aircraft responses to the command inputs and to generate the aircraft trajectory. It is found that the integrated fluidic thrust-vectoring system can be employed as a viable means to achieve both conventional and transition flight for the proposed vehicle. The obtained mathematical model reveals the dependence of the aircraft performance and design criteria on the presented method. This model will be used for further studies on the general aspects of flight dynamics and control systems design for such vehicle.

Co-flow Fluidic Thrust Vectoring Requirements for Longitudinal and Lateral Trim Purposes

The feasibility of using fluidic thrust-vectoring system, as a control technique for the longitudinal and lateral trim purpose was investigated in this study. For this purpose, integration of a Co-flow method into the propulsion unit of a conceptual aerial vehicle was assumed. The focus of the research presented was to estimate the required thrust vector angle in order to trim the aerial vehicle in different flight phases. Since the fluidic thrust vectoring requires secondary air flow to deflect the engine exhaust gas, this research also provides an analytical toolset for preliminary sizing of a suitable secondary air supply. It was found that thrust vectoring could be an effective mean of providing trim authority for such a vehicle in all phases of flight. The mathematical model, developed in this study, can be used as a preliminary tool for overall performance evaluation of similar future conceptual vehicles. Nomenclature c b, = span, mean aerodynamic chord b w C = wind to body transformation matrix Y D L C C C , , = lift, drag and side force coefficients n m l c c c , , = rolling, pitching and yawing moment coefficients z y x f ,

Near-optimal trajectory generation, using a compound B-spline interpolation and minimum distance criterion with dynamical feasibility correction

Trajectory generation for robotic vehicles tries to provide real time computing of a collision free path from one point to another, which usually involves minimizing a performance measure, to accomplish a desired task. A novel hierarchical method for generating near-optimal and collision free trajectories is proposed here to be used on-line in three-dimensional space. At the top level, the off-line optimal trajectory problem is solved in a complex environment, using B-spline interpolation and genetic algorithm, while considering the dynamic constraints of the vehicle. At the intermediate level, the path is modified for any possible on-line intersections with unexpected obstacles, using a minimum distance correction technique. The feasibility of the generated path is assessed at the lowest level by considering dynamic constraints of the vehicle. A novel method is presented at this level for correcting the path and obtaining near-optimal and dynamically feasible trajectories. Each part is assessed by a separate robotic vehicle to ensure the capability and performance. Lastly, the consistency between the levels of hierarchy is evaluated by presenting a differential-drive robot example. The final path is also verified with two commercial software codes for path planning and optimal trajectory generation. We proposed a technique for generating near-optimal and collision free trajectories.This technique consists of three layers to generate dynamically feasible trajectories.The off-line optimal path is created by B-spline interpolation using GA in 3D space.This technique yields more accurate results than other codes like OPTRAGEN or GPOPS.

Optimal Control of an Aerial Tail Sitter in Transition Flight Phases

The main purpose of this study is to generate optimal transition trajectories for an aerial tail sitter that uses cross-coupled thrust-vectoring control. A transition maneuver is most challenging for such configurations due to coupling of the forces and moments with instability in the most critical low-speed flight phases. Based on the classical Cauchy method, an improved gradient-based algorithm is developed in a collaborative process in order to find transition trajectories and increase the convergence rate. The cost function is defined in terms of minimum time in transition from hover to cruise and minimum altitude variations from cruise to hover. In addition, physical constraints are modeled via extended penalty functions. The results, including an optimal solution for states and controls, guarantee that the estimated trajectories are feasible, taking into account all imposed constraints. It is shown that the initial cruise speed in the landing phase will greatly affect the altitude variation and tran...

Control Oriented Modeling and Identification of Nonlinear Systems

This study describes a practical and systematic procedure for identifying and modeling nonlinear systems based on the input-output analysis. Frequency domain data is used to obtain a reduced linear models of nonlinear systems. A coherence function is introduced to specify the identification accuracy. The procedure is applied to a small vertical take-off and landing air vehicle. Control compensators are then designed based on the identified models and autonomous hovering is successfully achieved. Simulation results demonstrate the effectiveness and superiority of this method in comparison with other classical approaches.

A heuristic complexity-based method for cost estimation of aerospace systems

Cost estimation plays an essential role in the development of aerospace systems that are perhaps the most complex, time- and labor-consuming ones. Regarding this matter, it is unavoidable to take a systematic approach to build a realistic model through a deliberative, heuristical and easy-to-do process in the early stages of design. In the current study, complexity index theory is utilized to develop a heuristic complexity-based method to estimate various costs of aerospace systems. This method promises to be logically and practically more reliable and accurate than classical parametric methods. Logically, manipulating a group of parameters, instead of only one or two, reduces the probability of misrepresentation of systems and in the case of incompleteness of input data, reserves the chance for guessing them. Practically, all operations in this method are linear which makes it possible to work with matrices. With its organized and discrete nature, simulated annealing as a heuristic tool is employed to offset undesirable effects of imprecise initial assumptions. This helps to adjust complexity coefficients to more realistic magnitudes, when deriving a specific model from the heuristic complexity-based method. These coefficients may be used to estimate the cost of a new system as well as for sensitivity analysis. As a test scenario, estimation of an acquisition cost of a newly-developed unmanned aerial vehicle is concerned. Sensitivity of the complexity index to a number of complexity inducer parameters is also examined in order to achieve the most affecting parameters. Comparing by previously published results, it is seen that the current model is a remarkably accurate estimator for the acquisition cost of aerospace systems. This model shows a better R2 value, as a statistical measure of regression quality, than an already existing successful model by Technomics Corporation, regarded as a pioneer in this field.

Multi-Objective Genetic Algorithm for Hover Stabilization of an Insect-Like Flapping Wing

This paper describes latest results obtained on modeling, simulation and controller design of an insect-like Flapping Wing Micro Air Vehicle (FWMAV). Because of the highly nonlinear and time varying nature of insect flight and the inability to find an equilibrium point, linearization of the model without compromising the accuracy is not possible. Therefore, to address the problem of designing a controller capable of stabilizing and controlling the FWMAV around a hovering point, a metaheuristic optimization approach is proposed, based on the time averaging theorem. The results show that a controller, designed using the proposed method, is capable of stabilizing the FWMAV effectively around its hovering point.

Coanda Surface Geometry Optimization for Multi-Directional Co-Flow Fluidic Thrust Vectoring

The performance of Co-flow fluidic thrust vectoring is a function of secondary flow characteristics and the fluidic nozzle geometry. In terms of nozzle geometry, wall shape and the secondary slot aspect ratio are the main parameters that control the vector angle. The present study aims to find a high quality wall shape to achieve the best thrust vectoring performance, which is characterized by the maximum thrust deflection angle with respect to the injected secondary air. A 3D computational fluid dynamics (CFD) model is employed to investigate the flow characteristics in thrust vectoring system. This model is validated using experimental data collected from the deflection of exhaust gases of a small jet-engine integrated with a multi-directional fluidic nozzle. The nozzle geometry is defined by the collar radius and its cutoff angle. In order to find the best value of these two parameters, Quasi-Newton optimization method is utilized for a constant relative jet momentum rate, a constant secondary slot height and insignificant step size. In this method, the performance index is described as a function of thrust deflection angle. Optimization parameters (wall geometric parameters) are estimated in the direction of gradient, with an appropriate step length, in every iteration process. A good guess of initial optimization parameters could lead to a rapid convergence towards an optimal geometry and hence maximum thrust deflection angle. Examination over a range of geometric parameters around the optimum point reveals that this method promises the best performance of the system and has potential to be employed for all the other affective factors.Copyright

Development, instrumentation, and dynamics identification of a coanda air vehicle

Identification of the dynamic behavior and determination of a mathematical model for aerial vehicles are important steps in design, development, test and evaluation. Obtaining rough estimates of dynamic behavior in early stages of design and development reduces the costs and prevents failure in the development process. One of the important factors in designing a successful aerial vehicle is ensuring the quality of its dynamic responses. Generally, experimental and theoretical models are used to predict dynamic characteristics of aerial vehicles. In some cases, like unconventional configurations or severe flight conditions, these models are inaccurate and unsatisfactory. Nonlinear effects like coupling between fuselage and rotor dynamics and cross-coupling between axes lead to difficulties in derivation of such models, especially for unconventional robotic air vehicles. Due to the expanded use of these vehicles in recent years, many innovative aerial concepts are introduced.