On The Role of Higher-Order Terms in Local Piston Theory

The use of second- and third-order classical piston theory [1] (CPT) is commonplace, with the role of the higher-order terms being well understood [2]. The advantages of local piston theory (LPT) relative to CPT have been demonstrated previously [3]. Typically, LPT has been used to perturb a mean-steady solution obtained from the Euler equations, and recently, from the Navier-Stokes equations [4]. The applications of LPT in the literature have been limited to first-order LPT [5–7]. The reasoning behind this has been that the dynamic linearization used assumes small perturbations. The present note clarifies the role of higher-order terms in LPT. It is shown that second-order LPT makes a non-zero contribution to the normal-force prediction, in contrast to second-order CPT

Dynamic stability of a seaplane in takeoff

This research is based on the investigation into the dynamic stability associated with seaplanes during takeoff. Various forces acting on a hydroplaning hull form have been empirically defined. Such empirical data have shown that, under a certain set of conditions, a hydroplaning hull will begin to porpoise: an instability oscillation in both the vertical direction and about the center of gravity. To investigate the porpoising motion, a shallow water flume was used. It was the first time that such a facility had been used to simulate the dynamic motion of hydroplaning hull forms. An experimental method derived from the store release experiments was derived for the dynamics measurements. The equipment developed led to an analysis of a flat-plate hull porpoising in a supercritical channel. The porpoising limit was then very well defined.http://arc.aiaa.org/loi/jahb2016Mechanical and Aeronautical Engineerin

Multi-Layered Optimal Navigation System For Quadrotors UAV

Purpose This paper aims to propose a new multi-layered optimal navigation system that jointly optimizes the energy consumption, improves the robustness and raises the performance of a quadrotor unmanned aerial vehicle (UAV). Design/methodology/approach The proposed system is designed as a multi-layered system. First, the control architecture layer links the input and the output spaces via quaternion-based differential flatness equations. Then, the trajectory generation layer determines the optimal reference path and avoids obstacles to secure the UAV from collisions. Finally, the control layer allows the quadrotor to track the generated path and guarantees the stability using a double loop non-linear optimal backstepping controller (OBS). Findings All the obtained results are confirmed using several scenarios in different situations to prove the accuracy, energy optimization and the robustness of the designed system. Practical implications The proposed controllers are easily implementable on-board and are computationally efficient. Originality/value The originality of this research is the design of a multi-layered optimal navigation system for quadrotor UAV. The proposed control architecture presents a direct relation between the states and their derivatives, which then simplifies the trajectory generation problem. Furthermore, the derived differentially flat equations allow optimization to occur within the output space as opposed to the control space. This is beneficial because constraints such as obstacle avoidance occur in the output space; hence, the computation time for constraint handling is reduced. For the OBS, the novelty is that all controller parameters are derived using the multi-objective genetic algorithm (MO-GA) that optimizes all the quadrotor state’s cost functions jointly

Eulerian derivation of non-inertial Navier–Stokes and boundary layer equations for incompressible flow in constant pure rotation

The paper presents an Eulerian derivation of the non-inertial Navier–Stokes equations as an alternative to the Lagrangian fluid parcel approach. To the best knowledge of the authors, this is the first instance where an Eulerian approach is used for such a derivation. This work expands on the work of Kageyama and Hyodo (2006) who derived the incompressible momentum equation in constant rotation for geophysical applications. In this paper the derivation is done for the full set of Navier–Stokes equations in incompressible flow for pure rotation. It is shown that the continuity equation as well as the conservation of energy equation are invariant under transformation from the inertial frame to the rotational frame. From these equations the non-inertial boundary layer equations for flow on a flat plate subjected to rotation is derived in both the Cartesian and cylindrical co-ordinate systems

A Fully Autonomous Search and Rescue System Using Quadrotor UAV

In order to deal with critical missions a growing interest has been shown to the UAVs design. Flying robots are now used fire protection, surveillance and search & rescue (SAR) operations. In this paper, a fully autonomous system for SAR operations using quadrotor UAV is designed. In order to scan the damaged area, speeds up the searching process and detect any possible survivals a new search strategy that combines the standard search strategies with the probability of detection is developed. Furthermore the autopilot is designed using an optimal backstepping controller and this enables the tracking of the reference path with high accuracy and maximizes the flying time. Finally a comparison between the applied strategies is made using a study case of survivals search operation. The obtained results confirmed the efficiency of the designed system

Experimental and computational analysis of a tangent ogive slender body at incompressible speeds

© 2017 Elsevier Masson SAS A combined computational and experimental analysis was performed on a tangent ogive body with very low aspect ratio wings in the ‘+’ (plus) orientation at Mach numbers 0.1, 0.2 and 0.3, with the aim of developing a database of global force and moment loads. Three different span to body diameter ratios were tested with aspect ratios of 0.022, 0.044 and 0.067. Aerodynamic loads were obtained and flow visualization was performed to gain an understanding of the lee side flow features. It was found that the global loads were independent of Mach number as is expected at incompressible speeds. The numerical centre-of-pressure predictions were validated experimentally for angles of attack higher than 6 degrees. The correlation below 6 degrees was only reasonable due to the relative higher balance uncertainties. Vortex separation was observed for all three span to body diameter configurations, whose locations did not correlate to that of an impulsively started flow for a flat plate. This indicated possible configuration specific phenomena or body-wing interactions

Monte Carlo Simulation of Supply and Demand for Payload Limited Routes

Large commercial aircraft by design are typically not capable of transporting maximum fuel capacity and maximum payload simultaneously. Beyond the maximum payload range, fuel requirements reduce payload capability. Varying environmental conditions further impact payload capability noticeably. An airline’s commercial department requires prior knowledge of any payload restrictions, to restrict booking levels accordingly. Current forecasting approaches use monthly average performance, at, typically, the 85 probability level, to determine such payload capability. Such an approach can be overly restrictive in an industry where yields are marginal, resulting in sellable seats remaining empty. Monte Carlo simulation principles were applied to model the variance in environmental conditions, as well as in the expected payload demand

Generalized formulation and review of piston theory for airfoils

The present work presents a brief review of some of the notable contributions to piston theory and of its theoretical basis. A generalized formulation of piston theory is given, applicable to both local and classical piston theory. A consistent generalized formulation of the downwash equation is given, accounting for arbitrary motion in the plane of the airfoil. The formulation reduces to established downwash equations through appropriate definition of the cylinder orientation. The theoretical range of validity of Lighthill’s classical piston theory is examined, and the relative accuracy of a number of approximate theories encapsulated by the formulation as applied to a planar wedge is considered. The relative importance of higher-order terms in piston theory is examined, with the significance of recent literature extending the fidelity of the firstorder term highlighted. It is subsequently suggested that current implementations of local piston theory may be improved through the use of a first-order term of suitable accuracy.Armaments Corporation of South Africa through the Fluxion grant.http://arc.aiaa.org/loi/aiaajhb2016Mechanical and Aeronautical Engineerin

Intelligent Cyclist Modelling of Personal Attribute and Road Environment Conditions to Predict the Riskiest Road Infrastructure Type

Infrastructure selection, design and planning play a pivotal role in creating a safe travel environment for road users, especially the vulnerable road user. In this work, it is aimed to develop a predictive intelligent safety model for the riskiest cyclist infrastructure, based upon the prevalent environment, traffic flow conditions, and specific users using the infrastructure; and also develop an understanding of how these factors affect safety alone and in combination with each other. The study area of Northumbria in the northeast of England is selected for investigation. A hybrid methodology is proposed: a) Crash data collection, b) Predictive model (deep learning), and c) Variable interaction model (deep learning variable importance and principal component analysis). A complex deep learning model with a neural network classifier, and backpropagation error function is used to model this complex and nonlinear relationship. An accurate model is developed with an average accuracy of 86. Through variable interaction, it is found that critical variables affecting safety are the riders age, gender, environmental conditions, sudden change in the road hierarchy, and the traffic flow regime. It is found that the adverse environmental conditions and different traffic flow regimes complicate the cyclist interactions, having varied safety implications for different infrastructure types. The traffic flow regime poses a varying level of risk to the cyclist to which riders belonging to different genders react differently. The traffic flow conditions and the infrastructure variables alone are critical variables affecting the safety of cyclists. The study results help develop a better understanding of risk variation for different infrastructure types and predict the riskiest infrastructure type. It will contribute towards better planning of the cyclist infrastructure and thus contribute towards the development of a sustainable transportation syste

Deep neural network-based hybrid modelling for development of the cyclist infrastructure safety model

This paper is concerned with modelling cyclist road safety by considering various factors including infrastructure, spatial, personal and environmental variables affecting cycling safety. Age is one of the personal attributes, reported to be a significant critical variable affecting safety. However, very few works in the literature deal with such a problem or undertaking modelling of this variable. In this work, we propose a hybrid approach by combining statistical and supervised deep learning with neural network classifier, and gradient descent backpropagation error function for road safety investigation. The study area of Tyne and Wear County in the north-east of England is used as a case study. An accurate dynamic road safety model is constructed, and an understanding of the key parameters affecting the cyclist safety is developed. It is hoped that this research will help in reducing the cyclist crash and contribute towards sustainable integrated cycling transportation system, by making use of cut above methodologies such as deep learning neural network