Dean Vucinic

A review of thrust-vectoring in support of a V/STOL non-moving mechanical propulsion system

The advantages associated to Vertical Short-Take-Off and Landing (V/STOL) have been demonstrated since the early days of aviation, with the initial technolology being based on airships and later on helicopters and planes. Its operational advantages are enormous, being it in the field of military, humanitarian and rescue operations, or even in general aviation. Helicopters have limits in their maximum horizontal speed and classic V/STOL airplanes have problems associated with their large weight, due to the implementation of moving elements, when based on tilting rotors or turbojet vector mechanical oriented nozzles. A new alternative is proposed within the European Union Project ACHEON (Aerial Coanda High Efficiency Orienting-jet Nozzle). The project introduces a novel scheme to orient the jet that is free of moving elements. This is based on a Coanda effect nozzle supported in two fluid streams, also incorporating boundary layer plasma actuators to achieve larger deflection angles. Herein we introduce a state-of-the-art review of the concepts that have been proposed in the framework of jet orienting propulsion systems. This review allows to demonstrate the advantages of the new concept in comparison to competing technologies in use at present day, or of competing technologies under development worldwide.

Propulsion of Photovoltaic Cruiser-Feeder Airships Dimensioning by Constructal Design for Efficiency Method

The European project MAAT (Multi-body Advanced Airship for Transport) is producing the design of a transportation system for transport of people and goods, based on the cruiser feeder concept. This project defined novel airship concepts capable of handling safer than in the past hydrogen as a buoyant gas. In particular, it has explored novel variable shape airship concepts, which presents also intrinsic energetic advantages. It has recently conduced to the definition of an innovative design method based on the constructal principle, which applies to large transport vehicles and allows performing an effective energetic optimization and an effective optimization for the specific mission. While the traditional constructal method performs an optimization with a down-to-top approach, it produces an optimization process in two stages: the first one defines the optimal characteristics of the system understood as a unitary system to achieve the desired performances; the second analyzes the subsystems, examining those most disadvantaged, in order to optimize its performance for the desired goal. It has been deeply tested on a traditional shaped airship allowing verifying that a changing volume airship has globally better energetic performances than a fixed volume one. This paper performs a preliminary analysis of the method for the design of a cruiser/feeder multibody airship such as the one, which is going to be designed inside the MAAT project. The model presented defines the guidelines for the optimization of the system considering the magnitudes involved in flight physics to achieve the goal of energetic self-sufficiency.

Space Weather Prediction and Exascale Computing

Space weather can have a great effect on Earths climate. Predicting the impact of space environment disturbances on Earth presents a challenge to scientists. The authors present the ExaScience Labs efforts, which use exascale computing and new visualization tools to predict the arrival and impact of space events on Earth.

Integrated Approach to Computational and Experimental Flow Visualization of a Double Annular Confined Jet

The cold flow of a prototype industrial burner in a cylindrical combustion chamber is investigated. Two concentric annular axial jets simulate this complex flow field, which is investigated using Laser Sheet flow Visualization (LSV), Digital Particle Image Velocimetry (DPIV), Laser Doppler Velocimetry (LDV) and Computational Fluid Dynamics (CFD). The aim is to advance the physical understanding of combustion chamber flow fields and to assist the development of CFD codes specialized in such flows. These simulations generate large amount of data for various measured and calculated quantities. Thus, visualization and comparison procedures are applied for the validation of obtained results. The study reported here is one of the experiments applied in the design of the Quantitative Flow Field Visualization (QFView) software, a web-based environment which supports distributed data access. The application of QFView data analysis greatly improved the understandings about the various transition regions of the flow under investigation.

Increasing Aeronautic Electric Propulsion Performances by Cogeneration and Heat Recovery

The present work was performed as part of Project MAAT | Multibody Advanced Airship for Transport | with ref. 285602, supported by European Union through the 7th Framework Programme

A novel MPI reduction algorithm resilient to imbalances in process arrival times

Reduction algorithms are optimized only under the assumption that all processes commence the reduction simultaneously. Research on process arrival times has shown that this is rarely the case. Thus, all benchmarking methodologies that take into account only balanced arrival times might not portray a true picture of real-world algorithm performance. In this paper, we select a subset of four reduction algorithms frequently used by library implementations and evaluate their performance for both balanced and imbalanced process arrival times. The main contribution of this paper is a novel imbalance robust algorithm that uses pre-knowledge of process arrival times to construct reduction schedules. The performance of selected algorithms was empirically evaluated on a 128 node subset of the Partnership for Advanced Computing in Europe CURIE supercomputer. The reported results show that the new imbalance robust algorithm universally outperforms all the selected algorithms, whenever the reduction schedule is precomputed. We find that when the cost of schedule construction is included in the total runtime, the new algorithm outperforms the selected algorithms for problem sizes greater than 1 MiB.

Preliminary implementation study of ACHEON thrust and vector electrical propulsion on a STOL light utility aircraft

One of the best airplanes ever realized by the European Aircraft industry was the Dornier Do 28D Skyservant, an extraordinary STOL light utility aircraft with the capability to carry up to 13 passengers. It has been a simple and rugged aircraft capable also of operating under arduous conditions and very easy and simple maintenance. The architecture of this airplane, which has operated actively for more than 20 years, is very interesting analyzing the implementation of a new propulsion system because of the unusual incorporation of two engines, as well as the two main landing gear shock struts of the faired main landing gear attached to short pylons on either side of the forward fuselage. This unconventional design allows an easy implementation of different propulsion units, such as the history of different experimental versions allowed. This paper presents the preliminary definition of an increased performance cogeneration system for optimizing the energy efficiency and maximizing the thrust of ducted fan propeller. It then produces an effective design of the ACHEON nozzle for such an aircraft, the definition of the optimal positioning for stability and efficiency. In conclusion, it analyses the expected performances of the resulting aircraft architecture. Outstanding results allows verifying an effective possibility of implementing the ACHEON Coanda effect thrust and vector propulsion system on real aircraft.

CFD Modelling of the Coanda Based Thrust Vectoring Nozzle

The paper presents the CFD study of a Coanda-effect based nozzle, developed within the European FP7 project ACHEON. The ACHEON nozzle is able to provide a directional thrust without any movement of mechanical parts, by utilizing the Coanda effect to divert a jet from the symmetry axis. The deviation of the jet produces an oriented thrust vector due to the existence of a perpendicular component to the main propulsive direction. The studied nozzle is envisaged to be applied to UAVs. The directional thrust control—its deviation from the symmetry axis—is achieved by the relative mass flow variations between the two inlet jets. The geometry of the nozzle forces the resulting jet to follow the desired trajectory, thus by controlling in this way the thrust direction exerted by the nozzle. The influence of the selected parameters on the control of the thrust direction has been studied using CFD. In particular, the dependency of the thrust change in respect to the inlet conditions is analysed for different scenarios, with special focus on the thrust magnitude and its direction. The following parameters affecting the flow field of the nozzle have been studied: (a) the ratio of inlet velocities, (b) the Reynolds number at the throat and (c) the geometrical ratio throat/cylinder. Significant dependences between the identified parameters have been observed.

Monochrome Multitone Image Approximation on Lowered Dimension Palette with Sub-optimization Method Based on Genetic Algorithm

The problem of sub-optimum approximation of monochrome multitone images (MMI) by a palette with reduced amount of tones, called support palette (SP), is solved. The SP palette tones are defined with the images analysis, which arise in related scientific topics as: technical sight, recognition of images, etc. In this work the research objective was to assess the opportunity of using efficiently such analysis, by applying the genetic algorithms (GA) for sub-optimum approximation of MMI, considering the original big size tones palette [1]. The proposed approximation consists in replacing the original MMI pixels with the approximated pixels from a smaller size tone palette. This procedure is of importance in the synthetic vision approach, where image recognition procedures are expected to define the main contours within the image. The developed method reduces the amount of tones used to display an image, whose approximation approach is presented in this paper. In order to solve it, two alternative problems are considered: (1) minimization of losses in such image transformation, and (2) minimization of the SP size (for example, to simplify the image recognition process). The approximated MMI quality is defined as the mean square deviation of pixels brightness (original to approximated). The chromosome in GA is SP, where tones are represented as genes. Such approximations are resulting from the mutational variation of the MMI palette tones, within gene alleles, which are formed by applying the original palette tones. The palette is iteratively changing from generation to generation, where the reduction of the stop risks is done on the local extremum. This fact increases the available search opportunities, as provided by the multi-point crossing-over algorithm, whose parameters are able to mutate during such an evolution process. In addition, to demonstrate the result of this work, an appropriate software has been developed, having an easy-to-use user interface, enabling to show the highly efficient processing of the investigated algorithm. The presented solutions are validated with photo examples of several technical objects, on which the sub-optimum method has been applied.

Robot Path Planning Based on Ant Colony Optimization Algorithm for Environments with Obstacles

In modern industrial processes, robotic equipment is widely used, and one of the most pressing problems is to have to have navigation available for mobile robots. In this paper, the ant algorithm for laying and optimizing the robots paths in 2-dimensional environments with obstacles, is described and shown on construction site examples. The most important requirement is to be able to plan the shortest or permissible robot navigation route in such a complex environment with obstacles. It is well known that one of the most effective solutions to resolve such optimization problems of route seals is provided by the ant colony optimization (ACO) algorithm. The exploratory nature of the ant colony behaviour requires a classical partition of the search space, which is incomparably smaller, when compared to the obstacles fragments, as considered within this paper. The ant’s agents use the traditional logic of selecting the transition from fragment to fragment: the memory of the most popular routes based on pheromone are investigated, and formulated within the task elements, adopting appropriate tactics and situational awareness, and based on the random decisions. In addition, the new elements of the decision-making tactics are formulated for each task. For example, “feeling” of targeted routes by laying points is added to the algorithm. The natural analogue of this mechanism is similar to sensing the odors by the mustaches of real ants. The special software tool “Path Planning Optimization with Obstacle Avoidances by Ant Algorithm” is designed as the research test bed. A comprehensive study of the proposed algorithm, which shows superior performance, is done by utilizing the developed software. The examples, of the construction site with different complexity, are provided to explain the finding of the suboptimal routes for the specially designed test tracks, with defined obstacles in the simulated construction site landscape. The analysis of the results confirms the relevance and effectiveness of the developed software, which is based on the ant algorithm for the robot path planning, and validated for the environments containing complex obstacles.