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A KIA Soul was instrumented to measure the relative velocity (magnitude and yaw angle) at the front of the vehicle and in-cabin sound at a location close to the side glass near the A-pillar vortex impingement. Tests were conducted at a proving ground under a range of conditions from low wind conditions (~3 m/s) to moderate (7-8 m/s) wind speeds. For any given set of atmospheric conditions the velocity and sound data at any given position on the proving ground were noted to be very repeatable, indicating that the local wakes dominated the "turbulent" velocity field. Testing was also conducted in an aeroacoustic wind tunnel in smooth flow and with a number of novel turbulence generating methods. The resulting sounds were analyzed to study the modulation at frequencies likely to result in fluctuation strength type noise.

In this paper the finite element model of an Unmanned Aerial Vehicle is updated by using experimental data coming from a standard ground vibration test in order to improve the numerical-experimental correlation. A sensitivity-based updating methodology that iteratively minimizes a residual vector, defined on the modal parameters (e.g. natural frequencies and mode shapes), is considered to identify the unknown values of the updating parameters. The structure under investigation is the Clarkson University Golden Eagle UAV. An initial numerical model of the structure is obtained by assembling the individual components previously updated which included wings, fuselage, horizontal tail, vertical tails and tail booms. As a result the identification procedure shifts its focus on the joints between UAV elements which could not be modeled accurately in earlier investigations.

The implementation of Synthetic Jet Actuators (SJAs) on Unmanned Aerial Vehicles (UAVs) provides a safe test-bed for analysis of improved performance, in the hope of certification of this technology on commercial aircraft in the future. The use of high resolution numerical methods (i.e. CFD) to capture the details of the effects of SJAs on flows and on the hosting lifting surface are computationally expensive and time-consuming, which renders them ineffective for use in real-time flow control implementations. Suitable alternatives include the use of Reduced Order Models (ROMs) to capture the lower resolution overall effects of the jets on the flow and the hosting structure. This research paper analyses the effects of SJAs on aircraft wings using a ROM for the purpose of determining the unsteady aerodynamic forces modified by the presence of the SJAs. The model developed is a 3D unsteady panel code where the jets are represented by source panels.

Wind noise sources are described including those from the A-pillar region, cavities and bluff bodies. Hydrodynamic pressure fluctuations results from flow separations (in such areas as the A-pillars and mirrors) that generate relatively broad band in-cabin noise. The influence on local radii of the A-pillar is outlined and shown to be a dominant factor in determining hydrodynamic pressure fluctuations in the side-glass regions. Small cavities (eg. styling or water management channels on the mirror casing) generate high-frequency acoustic tones that can also be heard in the cabin and an example of tones from a whistling mirror cavity is shown. A spectrogram of in-cabin noise obtained whilst driving in strong winds is used to illustrate the variability of noise that can be heard on-road and to consider the influence of the relative wind speed.

The self-locking gear has great potential application in controlling the position stability of gearbox, which is a critical requirement in some precision machineries and instruments. This study provides important knowledge about the dynamic performance of self-locking gear pairs. An analytical model of variation ratio of contact length (VRCL) was established. The tooth root stress, bearing force, and axial acceleration of three self-locking gear pairs are investigated by using transient dynamic finite element analysis (FEA). The FEA results presented the influences of VRCL on the meshing performance of self-locking gear pairs. The obtained results provide significant knowledge for predicting the dynamic performance of self-locking gear pairs, optimizing their design parameters, and diagnosing possible design errors in self-locking gear pair design.

This paper summarises the effects of turbulence on the aerodynamics of road vehicles, including effects on forces and aero-acoustics. Data are presented showing that a different design of some vehicles may result when turbulent flow is employed. Methods for generating turbulence, focusing on physical testing in full-size wind tunnels, are discussed. The paper is Part Two of a review of turbulence and road vehicles. Part One (Cooper and Watkins, 2007) summarised the sources and nature of the turbulence experienced by surface vehicles.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

Vortices formed around the A-pillar region dictates the pressure distribution on the side panels of a passenger vehicle and also can lead to aerodynamic noise generation. This paper compares the suitability of various turbulence models in simulating the flow behind a vehicle A-pillar region under laboratory operating conditions. Commercial software's (FLUENT and SWIFT) were used to compare the performance of various turbulence models. In FLUENT, a simplified vehicle model with slanted A-pillar geometry was generated using GAMBIT and in SWIFT, the simplified vehicle model was generated using Fame Hybrid. Computational Fluid Dynamics (CFD) simulations were carried out using FLUENT under steady state conditions using various turbulence models (k-, k- Realize, k- RNG, k- and Spalart Allamaras). In SWIFT, k-, A-RSM and HTM2 turbulence models were used for the steady state simulations. Investigations were carried out at velocities of 60, 100 and 140km/h and at 0-degree yaw angle.

This paper describes a high-speed electrical machine for an aircraft starter-generator. A surface mounted permanent magnet machine is designed to have minimal rotor losses and a novel cooling system for the stator. An inner stator sleeve is adopted to allow for a flooded stator whilst minimizing rotor windage losses. Different slot-pole combinations are compared in view of attaining an optimal combination that provides minimum losses whilst satisfying the electromagnetic, mechanical and thermal constraints.

Effective rear view vision from external mirrors is compromised at high speed due to rotational vibration of the mirror glass. Possible causes of the mirror vibration are reviewed, including road inputs from the vehicle body and a variety of aerodynamic inputs. The latter included vibrations of the entire vehicle body, vibrations of the mirror “shell”, the turbulent flow field due to the A-pillar vortex (and to a lesser extent the approach flow) and base pressure fluctuations. Experiments are described that attempt to understand the relative influence of the causes of vibration, including road and tunnel tests with mirrors instrumented with micro accelerometers. At low frequencies, road inputs predominate, but some occur at such low frequencies that the human eye can track the moving image. At frequencies above about 20Hz the results indicate that at high speeds aerodynamics play a dominant role.

The aim of this paper is to develop a new concept of unconventional airship based on morphing a lenticular shape while preserving the volumetric dimension. Lenticular shape is known to have relatively poor aerodynamic characteristics. It is also well known to have poor static and dynamic stability after the certain critical speed. The new shape presented in this paper is obtained by extending one and reducing the other direction of the original lenticular shape. The volume is kept constant through the morphing process. To improve the airship performance, four steps of morphing, starting from the lenticular shape, were obtained and compared in terms of aerodynamic characteristics, including drag, lift and pitching moment, and stability characteristics for two different operational scenarios. The comparison of the stability was carried out based on necessary deflection angle of the part of tail surface.

Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers.

Contrails and aircraft-induced cirrus clouds are reputed being the largest components of aviation-induced global warming, even greater than carbon dioxide (CO2) exhaust emissions by aircraft. This article presents a contrail model algorithm specifically developed to be integrated within a multi-objective flight trajectory optimization software framework. The purpose of the algorithm is to supply to the optimizer a measure of the estimated radiative forcing from the contrails generated by the aircraft while flying a specific trajectory. In order to determine the precise measure, a comprehensive model is employed exploiting the Schmidt-Appleman criterion and ice-supersaturation regions. Additional parameters such as the solar zenith angle, contrail lifetime and spread are also considered.

When presented with new technology that removes past constraints, it is often beneficial to revisit old learning's to see if they still hold, and to understand how these can be best applied to the new technology. Brake-By-Wire (BBW) systems replace all the mechanical linkages of conventional hydraulic brake systems with ‘dry’ electrical components [2],[3]. The advent of this technology poses the possibility of revisiting conventional ABS control systems by utilizing the continuous nature that BBW offers. Presented is a BBW model based wheel slip controller using a generic continuous time Model Predictive Control (MPC) algorithm [15]. The result being the first of many steps taken in understanding the full potential that BBW systems offer.

Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors.

Global Navigation Satellite Systems (GNSS) can support the development of low-cost and high performance navigation and guidance architectures for Unmanned Aircraft Systems (UAS) and, in conjunction with suitable data link technologies, the provision of Automated Dependent Surveillance (ADS) functionalities for cooperative Sense-and-Avoid (SAA). In non-cooperative SAA, the adoption of GNSS can also provide the key positioning and, in some cases, attitude data (using multiple antennas) required for automated collision avoidance. A key limitation of GNSS for both cooperative (ADS) and non-cooperative applications is represented by the achievable levels of integrity. Therefore, an Avionics Based Integrity Augmentation (ABIA) solution is proposed to support the development of an Integrity-Augmented SAA (IAS) architecture suitable for both cooperative and non-cooperative scenarios.

The maturity reached in the development of Unmanned Air Vehicles (UAVs) systems is making them more and more attractive for a vast number of civil missions. Clearly, the introduction of UAVs in the civil airspace requiring practical and effective regulation is one of the most critical issues being currently discussed. As several civil air authorities report in their regulations “Sense and Avoid” or “Detect and Avoid” capabilities are critical to the successful integration of UAV into the civil airspace. One possible approach to achieve this capability, specifically for operations beyond the Line-of-Sight, would be to equip air vehicles with a vision-based system using cameras to monitor the surrounding air space and to classify other air vehicles flying in close proximity. This paper presents an image-based application for the supervised classification of air vehicles.

Noise, vibration, and harshness (NVH) attribute is needed to be included in the vehicle structure design since improving the NVH characteristics enhances the ride quality experienced by the occupants. In this regard, an efficient method was proposed to investigate the structural dynamic response of an automotive body considering low-frequency NVH performances. Moreover, the improvement of an automotive structure under the constraint of NVH behavior was investigated by using the design of experiments (DOEs) method. The DOEs methodology was for screening of the design space and generating approximation models. Here, the thicknesses of panels consisting of a body-in-white (BIW) of an automotive were employed as design variables for optimization, whose objective was to increase the first torsional and bending natural frequencies. Central composite design (CCD) for DOEs sampling and response surface methodology (RSM) were employed to optimize the dynamic stiffness.

Characterizing the acoustic properties of sound-absorbing materials is costly and time consuming. The acoustic material database helps the automotive designers design their interior trims in accordance with target level for interior noise. In this paper, a two-microphone impedance tube was used to measure the normal sound absorption coefficient. The main parameters that are used in the theoretical model for interior noise level assessment are investigated. These parameters include thickness, airflow resistivity, porosity, tortuosity, viscous and thermal characteristics length. The measured results have been validated by the theoretical models. The validation of normal sound absorption coefficient was found to be in agreement with its corresponding measurement data. Finally, the sensitivity of the sound absorption coefficient which is related to the physical properties mentioned above is further analyzed.