fuel flow
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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.

This paper presents the design and simulation of air-fuel percentage sensors in drone engine control using Matlab. The applications of sensor engineering system have been pioneer in technology development and advancement of automated machine as complex systems. The integration of drone fuel sensor system is the major series components such as injector, pumps and switches. The suggested model is tuned to interface drone fuel system with fuel flow in order to optimize efficient monitoring. The sensor system is improved and virtualized in Simulink block set by varying the parameters with high range to observe the fuel utilization curves and extract the validated results. The obtained results show that the possibility of engine operation in critical conditions such as takeoff, landing, sharp maneuver and performance is applicable to turn off the system in case of break down in the sensor to ensure the safety of drone engine. HIGHLIGHTS The drone engine fuel rate sensor is designed and examined to determine the air-to-fuel ratio The suggested model is tuned to interface drone fuel system with fuel flow in order to optimize efficient monitoring The obtained results show that the possibility of using engine with different failure mode and fault considerations The represented control structure is simple, efficient and provides the required air-to-fuel ratio

Fuel flowrate control system and fuel thermal management are very important for aeroengine and the overall aircraft, and it has been researched for several decades. This survey paper makes a comprehensive and systematic overview on the exiting fuel flowrate regulation methods, thermal load of fuel metering units, fuel-based thermal management, and the fuel tank’s thermal management topology network with drain and recirculation. This paper firstly reviews the mechanism, technical advantages, and technical challenges of the fuel metering unit with flowrate control valve and constant pressure difference valve compensator, flowrate control valve and variable displacement pump-based pressure difference compensator, and motor-based flowrate regulation. Then, the technical characteristics of above fuel flowrate control methods related to thermal management are discussed and compared. Meanwhile, the behaviors of recirculated fuel flow within single tank system and dual tank system are explored. Thirdly, the paper discusses the future directions of fuel flowrate control and thermal management. The survey is significant to the fuel flowrate control and fuel thermal management of the aircraft.

This work presents the numerical simulation of biogas and LPG fuelled diffusion flames in an axisymmetric chamber to study in-depth, the formation mechanism of soot and carbon nanostructures in these flames. The simulation is formulated on the set of transport equations that involve the equations for conservation of mass (the continuity equation), momentum (Navier-Stokes equation), energy, and chemical species. The governing equations are solved using ANSYS FLUENT, which is centered on the finite volume method. To predict the soot formation, one step soot model has been incorporated. The solution of these equations permits the estimation of temperature field and species concentrations inside the flame. Simulation is conducted at fixed fuel flow rate and varied oxygen flow rates. The results reveal that the formation of soot and carbon nanostructures is strongly dependent on peak flame temperature and concentration of precursor species formed in the flame. Since two fuels produce an exclusive chemical environment in the flame, the flame temperature and CO concentration that is conducive to the growth of carbon nanostructures is higher for LPG fuel as compared to that for biogas. Hence, the nucleation process of carbon nanostructures is faster for LPG than biogas. Moreover, the reactions taking place inside the flame at different locations can also be predicted from flame temperature and species concentration at that location. Pyrolysis of fuel occur near the burner exit, followed by the nucleation and surface growth of carbon nanostructures in the nearby region and oxidation of formed carbon nanostructures near the flame tip.

The quality of power supply and reliability play a vital role in the smooth operation and maintenance of commercial use. These requirements have significant applications when dealing with residential areas, hospitals, industries, educational sectors, banks and airports, etc. In this regard, backup diesel generators are considered the most important source for an uninterrupted supply of electricity. However, there is an emergent need to avoid sudden shutdown of generators in the events of overload, shortage of fuel flow, service interval and lagging of power factor. These common problems can be addressed through monitoring of power generator parameters, for instance, real time remote monitoring to measure the health of the generator, the problem of load management due to high demand of power during peak hours and power factor improvement due to exceeding inductive load. In this paper, our proposed architecture—based on an IOT solution—consists of different sensors, namely a current transformer for measuring load, fuel gauge for fuel level monitoring, and temperature measurement with the energy module to determine the power factor of the system. Our proposed system is operated and tested on a real trolley-mounted 25 KVA generator.

A common way of measuring heavy fuel oil consumption on board a vessel is to use volumetric fuel flow meters installed at fuel systems inlets for each of the major fuel consumers. At each stage of the fuel processing cycle, certain mass fuel losses or deviations and calculation errors occur that are not counted accurately into fuel consumption figures. The goal of this paper is to identify those fuel mass losses and measuring/calculating errors and perform their quantitative numerical analysis based on actual data. Fuel mass losses defined as deviations identified during the fuel preparation process are evaporation of volatile organic compounds, water drainage, fuel separation, and leakages while errors identified are flow meter accuracy and volumetric/mass flow conversion accuracy. By utilizing statistical analysis of obtained data from engine logbook extracts from three different ships numerical models were generated for each fuel mass loss point. Measuring errors and volumetric/mass conversion errors are numerically analyzed based on actual equipment and models used onboard example vessels. By computational analysis of the obtained models, approximate percentage losses and errors are presented as a fraction of fuel quantity on board or as a fraction of fuel consumed. Those losses and errors present between 0,001% and 5% of fuel stock or fuel consumption figures for each identified loss/error point. This paper presents a contribution for more accurate heavy fuel oil consumption calculation and consequently accurate declaration of remaining fuel stock onboard. It also presents a base for possible further research on the possible influence of fuel grade, fuel water content on the accuracy of consumption calculation.

Microturbines can be used not only in models and education but also to propel UAVs. However, their wider adoption is limited by their relatively low efficiency and durability. Validated simulation models are required to monitor their performance, improve their lifetime, and design engine control systems. This study aims at developing a numerical model of a micro gas turbine for prediction and prognostics of engine performance. To build a reliable zero-dimensional model, the available compressor and turbine maps were scaled to the available test bench data with the least squares method, to meet the performance of the engine achieved during bench and flight tests. A steady-state aeroengine model was implemented in GSP and compared with experimental operating points. The selected flight data was then used as input for the transient engine model. The exhaust gas temperature (EGT) and fuel flow were chosen as the two key parameters to validate the model, comparing the numerical predicted values with the experimental ones. The observed difference between the model and the flight data was lower than 3% for both EGT and fuel flow.

This paper presents a method and results, which studies influences of the fuel flow mode on the pressure oscillation in the volumes of the accumulator fuel system. The fuel is supplied through nozzle holes into a constant volume chamber, which is installed a jet for fuel discharge into the low-pressure line. Results show that the increase in the base pressure value of the fuel accumulator leads to the rise in the slope of the leading edge of the differential characteristics and the maximum dQ/dt value changes closer to the beginning moment of the fuel injection process. At the same time, the control pressure value is a significant parameter that greatly influences the shape of the injection characteristic. In addition, when using the drain orifices with different diameters, received values and differential characteristics vary during the fuel supply process. The differential characteristics of the study are the basis for implementing fuel injection control solutions.

This research presents a system to use natural gas to meet electricity, freshwater and cooling needs for a residential building in Bandar Abbas. The system includes a gas turbine, absorption chiller and multi-effect desalination (MED) plant. The energy produced in the gas turbine is used to generate electricity, and the excess energy is used to produce cooling and freshwater. Finally, an exergoeconomic evaluation of the system is performed. The effects of ambient temperature on the output power as well as the exergy current have been investigated. The COP of the absorption cycle has been investigated, and the results show that at an operating temperature of 150∘C compared to 90∘C, the efficiency rate increases to 20%. The highest exergoeconomic cost rate is related to absorption chiller, and the lowest is related to heat recovery steam generation. The results show that if the ambient temperature increases, the production capacity decreases. Increasing the fuel flow rate increases the power. Evaluation of two different solutions to reduce the ambient temperature and increase the fuel flow shows that increasing the fuel flow is a better solution, considering the exergy cost of the absorption chiller, which is 10 times higher than that of the gas turbine.

The fuel flow pattern in the fuel injection nozzle of diesel engine is a complex and changeable phenomenon, which is easily affected by various factors, bringing the differences of flow patterns between multiple injection cycles. To solve the above problem, a visual experimental platform of fuel injection nozzle was built, in which the 100 injection cycles of diesel engine on the same working condition were photographed via shadowgraphy to study the difference in fuel flow pattern in the nozzle by ensemble average processing method. The cyclic variation rate K of fuel flow pattern is defined. Results demonstrate that the fuel flow pattern tends to be the same in multiple fuel injection cycles, but there is a strong randomness at the starting of injection and after ending of injection; the K can be reduced by decreasing the injection pressure and the inclination angle of orifice, so that the fuel flow pattern in the nozzle tends to be consistent.