Fuel flow rate modeling for descent using cuckoo search algorithm: a case study for point merge system procedure at Istanbul airport

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ridvan Oruc ◽  
Ozlem Sahin ◽  
Tolga Baklacioglu
Keyword(s):  
Fuel Consumption ◽  
Flow Rate ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
High Accuracy ◽  
Cuckoo Search Algorithm ◽  
Rate Model ◽  
Fuel Flow Rate ◽  
Content Type ◽  
Fuel Flow

Purpose The purpose of this paper is to create a new fuel flow rate model using cuckoo search algorithm (CSA) for the descending stage of the flight. Design/methodology/approach Using the actual flight data record data of the B737-800 aircraft, a new fuel flow rate model has been developed for this aircraft type. The created model is to predict the fuel flow rate with high accuracy depending on the altitude and true airspeed. In addition, the CSA fuel flow rate model was used to calculate the fuel consumption for the point merge system, which is used for combining the initial approach to the final approach at Istanbul Airport, the largest airport of Turkey. Findings As a result of the analysis, the correlation coefficient value is found as 0.996858 for Flight 1, 0.998548 for Flight 2, 0.995363 and 0.997351 for Flight 3 and Flight 4, respectively. The values that are so close to 1 indicate that the model predicts the real fuel flow rate data with high accuracy. Practical implications This model is considered to be useful in air traffic management decision support systems, aircraft performance models, models used for trajectory prediction and strategies used by the aviation community to reduce fuel consumption and related emissions. Originality/value The importance of this study lies in the fact that to the best of the authors’ knowledge, it is the first fuel flow rate model developed using CSA for the descent stage in the existing literature; the data set used is real values.

Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm

2020 ◽  
Vol 92 (3) ◽  
pp. 495-501
Author(s):  
Ridvan Oruc ◽  
Tolga Baklacioglu
Keyword(s):  
Flow Rate ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
High Accuracy ◽  
Cuckoo Search Algorithm ◽  
Rate Model ◽  
Fuel Flow Rate ◽  
Content Type ◽  
Flight Data ◽  
Fuel Flow

Purpose The purpose of this study is to create a new fuel flow rate model adopting cuckoo search algorithm (CSA) for the climbing phase of the flight. Design/methodology/approach Using the real flight data records (FDRs) of B737-800 passenger aircraft, a new fuel flow rate model for the climbing phase of the flight was developed by incorporating CSA. In the model, fuel flow rate is given as a function of altitude and true airspeed. The aim is to create a model that yields results that are closest to the real fuel flow rate values obtained from flight data records. Various error analysis methods were used to test the accuracy of the obtained values. Finally, the effect of change of some CSA parameters on the model was investigated. Findings It was observed that the derived model is able to predict real fuel flow rate values with high accuracy. It has been deduced that increasing the number of nest (n) and discovery rate of alien nests (pa) values of CSA parameters to a certain value gradually decreases the model’s accuracy. Practical implications This model is considered to be useful in air traffic management decision support systems, simulation applications, aircraft trajectory prediction models and aircraft performance modelling studies because of the high accuracy accomplished by the CSA model. Originality/value The originality of this study is the development of a new fuel flow rate model using CSA as a first attempt in the literature. The use of real flight data is important for the originality and reliability of the model.

Modeling of fuel flow-rate of commercial aircraft for the descent flight using particle swarm optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ridvan Oruc ◽  
Tolga Baklacioglu
Keyword(s):  
Particle Swarm Optimization ◽  
Fuel Consumption ◽  
Flow Rate ◽  
Particle Swarm ◽  
Management Decision ◽  
Rate Model ◽  
Fuel Flow Rate ◽  
Swarm Optimization ◽  
Content Type ◽  
Fuel Flow

Purpose The purpose of this paper is to create a new fuel flow rate model for the descent phase of the flight using particle swarm optimization (PSO). Design/methodology/approach A new fuel flow rate model was developed for the descent phase of the B737-800 aircraft, which is frequently used in commercial air transport using PSO method. For the analysis, the actual flight data records (FDRs) data containing the fuel flow rate, speed, altitude, engine speed, time and many more data were used. In this regard, an empirical formula has been created that gives real fuel flow rate values as a function of altitude and true airspeed. In addition, in the fuel flow rate predictions made for the descent phase of the specified aircraft, a different model has been created that can be used without any optimization process when FDR data are not available for a specific aircraft take-off weight condition. Findings The error analysis applied to the models showed that both models predict real fuel flow rate values with high precision. Practical implications Because of the high accuracy of the PSO model, it is thought to be useful in air traffic management, decision support systems, models used for trajectory prediction, aircraft performance models, strategies used to reduce fuel consumption and emissions because of fuel consumption. Originality/value This study is the first fuel flow rate model for descent flight using PSO algorithm. The use of real FDR data in the analysis shows the originality of this study.

Multi-path selection based on fractional cuckoo search algorithm for QoS aware routing in MANET

Sensor Review ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 218-232 ◽  
Author(s):  
Rama Rao A. ◽  
Satyananda Reddy ◽  
Valli Kumari V.
Keyword(s):  
Ad Hoc ◽  
Search Algorithm ◽  
Life Time ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Path Selection ◽  
Content Type ◽  
Time Distance ◽  
Multiple Qos Constraints ◽  
Multiple Qos

Purpose Multimedia applications such as digital audio and video have stringent quality of service (QoS) requirement in mobile ad hoc network. To support wide range of QoS, complex routing protocols with multiple QoS constraints are necessary. In QoS routing, the basic problem is to find a path that satisfies multiple QoS constraints. Moreover, mobility, congestion and packet loss in dynamic topology of network also leads to QoS performance degradation of protocol. Design/methodology/approach In this paper, the authors proposed a multi-path selection scheme for QoS aware routing in mobile ad hoc network based on fractional cuckoo search algorithm (FCS-MQARP). Here, multiple QoS constraints energy, link life time, distance and delay are considered for path selection. Findings The experimentation of proposed FCS-MQARP is performed over existing QoS aware routing protocols AOMDV, MMQARP, CS-MQARP using measures such as normalized delay, energy and throughput. The extensive simulation study of the proposed FCS-based multipath selection shows that the proposed QoS aware routing protocol performs better than the existing routing protocol with maximal energy of 99.1501 and minimal delay of 0.0554. Originality/value This paper presents a hybrid optimization algorithm called the FCS algorithm for the multi-path selection. Also, a new fitness function is developed by considering the QoS constraints such as energy, link life time, distance and delay.

Enhanced packet reordering procedure to improve TCP communication

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sai Prasanthi Kasimsetti ◽  
Asdaque Hussain
Keyword(s):  
Wireless Network ◽  
Search Algorithm ◽  
Research Work ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Support Vector ◽  
Linear Network ◽  
Content Type ◽  
Packet Reordering ◽  
Linear Network Coding

Purpose The research work is attained by Spurious Transmission–based Enhanced Packet Reordering Method (ST-EPRM). The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss. Design/methodology/approach Based on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission. Findings The research work which is attained by ST-EPRM. The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss. Originality/value Based on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission.

scholarly journals A Mathematical Model for the Analysis of Jet Engine Fuel Consumption during Aircraft Cruise

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3649
Author(s):  
Francisco Velásquez-SanMartín ◽  
Xabier Insausti ◽  
Marta Zárraga-Rodríguez ◽  
Jesús Gutiérrez-Gutiérrez
Keyword(s):  
Mathematical Model ◽  
Closed Form ◽  
Fuel Consumption ◽  
Flow Rate ◽  
Carbon Dioxide Emissions ◽  
Closed Form Expression ◽  
Engine Fuel ◽  
Fuel Flow Rate ◽  
Fuel Flow ◽  
Closed Form Formula

In this paper we propose a mathematical model for the fuel consumption analysis during aircraft cruise. A closed-form formula that expresses the aircraft’s weight variation over time, and hence, the fuel flow rate, is obtained as a result. Furthermore, a closed-form expression of the aircraft’s main performance parameters is also obtained. We compare the values of such parameters computed by using the Piano-X software and computed by using our mathematical model. Simulation results confirm that our mathematical model provides results very close to reality. Finally, the closed-form formula of the fuel flow rate provided by our model is used to improve the calculation of the carbon dioxide emissions for four example routes, which, unlike here, are usually obtained under the assumption of a constant value of the fuel flow rate.

Fuel flow-rate modelling of transport aircraft for the climb flight using genetic algorithms

2015 ◽  
Vol 119 (1212) ◽  
pp. 173-183 ◽  
Author(s):  
T. Baklacioglu
Keyword(s):  
Flow Rate ◽  
Rate Model ◽  
Fuel Flow Rate ◽  
Transport Aircraft ◽  
Fuel Flow ◽  
True Airspeed ◽  
The Relationship ◽  
Medium Weight ◽  
Study Development ◽  
Modelling Approaches

AbstractIn this study, development of a new fuel flow rate model for the climbing phase of flight was achieved using a genetic algorithm (GA) method. Two modelling approaches were performed using real flight data records (FDRs) from a medium-weight transport-category aircraft. The first model considered the dependency of fuel consumption only with respect to altitude, whereas the effects of both altitude and true airspeed (TAS) were included in the second model. The proposed models are improvements on existing models because the relationship between fuel flow rate, flight altitude, and TAS can be deduced using the derived formulations. Both modelling approaches were found to provide accurate results after performing an error analysis for fuel flow rate values. It was clear that incorporating the TAS effect into the second model enhanced the accuracy of the model, but the first model was also found to be appropriate for practical usage.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

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