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

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.

Optimal Asset Allocation for CRRA and CARA Insurers under the Vasicek Interest Rate Model

This paper considers the reinsurance-investment problem with interest rate risks under constant relative risk aversion and constant absolute risk aversion preferences, respectively. Stochastic control theory and dynamic programming principle are applied to investigate the optimal proportional reinsurance-investment strategy for an insurer under the Vasicek stochastic interest rate model. Solving the corresponding Hamilton-Jacobi-Bellman equation via the Legendre transform approach, the optimal premium allocation strategies maximizing the expected utilities of terminal wealth are derived. In addition, several sensitivity analyses and numerical illustrations are given to analyze the impacts of different risk preferences and interest rate fluctuation on the optimal strategies. We find that the asset allocation and reinsurance ratio of the insurer are correlated with risk preference coefficient and interest rate fluctuation, and the insurance company may adjust the reinsurance-investment strategy to deal with interest rate risk.

Principle and structure of a multi-chamber piezoelectric pump with large flow rate integrated into printed circuit board

Parametric simulation of multi-chamber piezoelectric pump proposed by authors shows that its flow rate is positively correlated with chamber compression ratio when height of chamber wall is not less than central deflection of circular piezoelectric unimorph actuator (CPUA). Therefore, in this paper, principle and structure of multi-chamber piezoelectric pump with novel CPUAs with three-layer structure are proposed and realized, so as to improve its chamber compression ratio, and then improve its flow rate. Its processing technology compatible with PCB processing technology is studied and its flow rate model is established. Central deflection of CPUA with three-layer structure and the flow rate characteristics are tested. Experimental results show that when the central deflection of CPUA with three-layer structure reaches the maximum value of 106.8 μm, the chamber compression ratio and flow rate of multi-chamber piezoelectric pump reach the maximum value of 50% and 3.11 mL/min, respectively. The maximum flow rate is increased by 622% compared to unimproved pump. By comparing experimental results with numerical and finite element simulation results, the realized multi-chamber piezoelectric pump has large flow rate and the established flow rate model can predict its flow rate.

Lévy Interest Rate Models with a Long Memory

This article proposes an interest rate model ruled by mean reverting Lévy processes with a sub-exponential memory of their sample path. This feature is achieved by considering an Ornstein–Uhlenbeck process in which the exponential decaying kernel is replaced by a Mittag–Leffler function. Based on a representation in term of an infinite dimensional Markov processes, we present the main characteristics of bonds and short-term rates in this setting. Their dynamics under risk neutral and forward measures are studied. Finally, bond options are valued with a discretization scheme and a discrete Fourier’s transform.

The Influences of Oxygen Concentration and External Heating on Carbon Nanotube Growth in Diffusion Flame

Tight control of the carbon nanotube (CNT) synthesis process in flames remains a challenge due to the highly non-uniform gradient of flame thermochemical properties. The present study aims to establish a baseline model for flame-enhanced chemical vapor deposition (FECVD) synthesis of CNT and to analyze the CNT growth region at varying flame and furnace conditions. The numerical model comprises a computational fluid dynamics (CFD) simulation that is coupled with the CNT growth rate model to simulate the flow field within the furnace and the CNT growth respectively. Validation of the flame shape, flame length, and temperature profile are carried with a reasonable comparison to experimental measurements. A parametric study on the effects of furnace heating capacity and oxidizer concentration is conducted. The results of the CNT growth rate model reveal that there is a positive correlation between the heater power and CNT length. Supplying a higher concentration oxidizer at a fixed furnace power is predicted to result in further improvement in CNT length and high yield region. Flame structure analysis showed that with the heater turned on at 750 W (corresponding to heat flux of 21,713W/m2), the growth region expands twofold when oxygen concentration is increased from 19% to 24%. However, the growth region shrinks when the oxygen concentration is further increased to 27% which indicates depletion of carbon source for CNT growth due to excess oxygen. The finding of this research could guide and optimize the experiment of the flame-assisted CNT production in the future.

Reliability Study of Parameter Uncertainty Based on Time-Varying Failure Rates with an Application to Subsea Oil and Gas Production Emergency Shutdown Systems

The failure rate of equipment during long-term operation in severe environment is time-varying. Most studies regard the failure rate as a constant, ignoring the reliability evaluation error caused by the constant. While studying failure data that are few and easily missing, it is common to focus only on the uncertainty of reliability index rather than parameter of failure rate. In this study, a new time-varying failure rate model containing time-varying scale factor is established, and a statistical-fuzzy model of failure rate cumulated parameter is established by using statistical and fuzzy knowledge, which is used to modify the time-varying failure rate model. Subsequently, the theorem of the upper boundary existence for the failure rate region is proposed and proved to provide the failure rate cumulated parameter when the failure rate changes the fastest. The proposed model and theorem are applied to analyze the reliability of subsea emergency shutdown system in the marine environment for a long time. The comparison of system reliability under time-varying failure rate and constant failure rate shows that the time-varying failure rate model can eliminate the evaluation error and is consistent with engineering. The reliability intervals based on the failure rate model before and after modification are compared to analyze differences in uncertainty, which confirm that the modified model is more accurate and more practical for engineering.