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Consolidating the Network Carrier Business Model in the European Airline Industry
Published in Werner Delfmann, Herbert Baum, Stefan Auerbach, Sascha Albers, Strategie Management in the Aviation Industry, 2017
Stefan Auerbach, Werner Delfmann
Within Europe, network carriers offer connecting services between city pairs via the hub when the passenger demand is not sufficient to justify direct flights. The same flights are booked by passengers, whose final destination is the hub city as well as by passengers originating at the hub city and with a spoke destination within Europe. Furthermore, the same physical flights to the hub may be used by passengers traveling from an intercontinental point of origin and connect to a European destination and vice versa. In the European major hubs like Frankfurt, Munich, Paris Charles-de-Gaulle or London Heathrow passengers can connect on continental flights as well. European Airlines not only offer air services via the hub. The so-called non-hub traffic is served by direct flights bypassing the hub. Generally speaking, passengers prefer direct flights between two cities without the inconvenience of changing aircraft at the hub. For direct flights airlines are able to charge higher ticket prices than for connecting flights.
Airlines
Published in Milica Kalić, Slavica Dožić, Danica Babić, Introduction to the Air Transport System, 2022
Milica Kalić, Slavica Dožić, Danica Babić
The network design of cargo airlines is predominantly linear, hub-and-spoke and point-to-point. The hub-and-spoke network structure enables the efficient development of a global network coverage by maximizing the number of destinations under the restrictions of the airline’s capacity. The point-to-point network connects the airports with direct flights. Direct flights offer the reduced total travel time and thus are less sensitive to the occurrence of flight delays. The flights are evenly distributed among the airports, no airport has a large number of concentrated flights, which reduces the possibility of disruption and the spread of disruption to other flights in the network.
Air combat manoeuvre strategy algorithm based on two-layer game decision-making and the distributed MCTS method with double game trees
Published in Systems Science & Control Engineering, 2022
Qiuni Li, Fawei Wang, Zongcheng Liu, Yuqin Li
If an air combat game is considered as playing chess in three-dimensional space, then the game strategies can be considered as an optional position on the chessboard and choosing different game strategies will result in different payoffs. Referring to Ji et al. (2020), all the manoeuvres of fighters can usually be divided into 11 kinds of basic manoeuvres in the tactical action planning layer in the three-dimensional space. The basic manoeuvre library can combine most tactical manoeuvres in air combat, and different combinations of manoeuvreing sequences correspond to different tactical manoeuvres in air combat as expounded in Ji et al. (2020), Du et al. (2018). As shown in Figure 2, generally speaking, the possible manoeuvres of a fighter mainly include: 1. direct flight without any manoeuvre, 2. Climb, 3. Dive, 4. Turn left, 5. Climb to the left, 6. Dive to the left, 7. Turn right, 8. Climb to the right, 9. Dive to the right, 10. Flying with an acceleration. 11. Flying with a deceleration. The inclination angle can reach −60°, 0° and 60°, corresponding to the climbing, direct flight without any manoeuvre and dive in the manoeuvre decision, respectively, and the roll angle can reach −30°, 0° and 30°, corresponding to the turn left, direct flight without any manoeuvre and turn right in the manoeuvre decision, respectively.
Design of a distributed compliant mechanism using spring-lever model and topology optimization for piezoelectrically actuated flapping wings
Published in Mechanics of Advanced Materials and Structures, 2021
Nilanjan Chattaraj, G. K. Ananthasuresh, Ranjan Ganguli
Flapping-wing micro air vehicle (MAV) is one of the most challenging micro-engineering systems. Considering the complexity of modeling flapping wing aerodynamics, researchers adopted bio-mimicking approach for designing flapping wing MAVs [1] and [2]. There are two types of flapping-wing mechanism available in biological spices: (a) active-wing actuation and (b) passive-wing actuation. All birds and bat inherit active-wing actuation as their wings are composed of distributed muscles. Whereas, all insects inherit passive-wing actuation as their wings are muscleless and are controlled from their thorax. Therefore, construction wise insects’ wings are less complex compared to the birds’ wings. The flapping of insect-wing can be further classified into two categories: (a) direct flight and (b) indirect flight. In direct flight mechanism, the flight muscles, which reside inside the thorax, are directly attached to the wings. This provides the advantage of individual wing control. Whereas, in indirect flight mechanism, the flight muscles are not directly attached to the wings, but the thorax itself expands and contracts to cause wing flapping indirectly. This makes the mechanism least complex. However, individual wing control is not possible in indirect flight mechanism. This draws a conclusion that the indirect insect flight mechanism is considered to be the best choice for bio-mimicking as it is the simplest flight mechanism among all natural flyers [3]. Therefore, motivation of this research is associated to the bio-mimicking of indirect flight mechanism for flapping-wing applications.
Transporting COVID-19 testing specimens by routing unmanned aerial vehicles with range and payload constraints: the case of Istanbul
Published in Transportation Letters, 2021
In the model, there are ‘u’ numbers of UAVs (U = 1 … u), ‘h’ numbers of hospitals (H = 1 … h), and ‘l’ numbers of laboratories (L = 1 ... l). Therefore, there are ‘h + l = n’ numbers of nodes, and the edges are direct flight paths between nodes. The dij is the Euclidean flight distance between nodes i and j. The decision variables xijk represent the used edges between nodes, if xijk is 1 then the edge between i and j is used by UAV k, otherwise, xijk is 0. The yijk presents the total carried testing samples via UAV k between nodes i and j. The tijk is the loaded amount of testing specimens to UAV k when i is a hospital. That means tijk covers the number of testing specimens that should be received from hospital i via UAV k when k is flying from i to any j. The pi and pj are the positions of nodes i and j in the path that are embedded to the model to avoid sub-tours. Rk is the flight distance range, Wk is the payload weight capacity, and Vk is the payload volume capacity of UAV k. The w is the unit weight of the testing sample and v is the unit volume of the testing sample. M1 and M2 are sufficiently big numbers for the model. TSj is the total test capacity of laboratory j and TDi is the total test sample amounts done in hospital i in a day.