Ground Operations Research Articles

Study on the ground attenuation of engine run-up and APU noise for developing the airport noise model in Japan

The correction for ground effect around airports is modeled based on the results of numerical analysis in order to make it possible to estimate the propagation of noise caused by ground operations in airports such as engine run-ups and APU to the vicinity of airports. The excess attenuation due to ground effects on sound caused by engine run-ups and APU is calculated using a PE method for typical jet aircraft and propeller aircraft, respectively. On the assumption that the ground around an airport consists of asphalt-paved surface and grass-covered surface in a certain ratio, the excess attenuation for the mixed impedance ground is calculated with the Fresnel-zone method using the results of PE calculation. The composition ratio of ground surface is assumed based on the composition ratio of asphalt-paved surface and grass-covered surface along the propagation path from the engine run-up spot to the airport site boundary of six major airports in Japan. In this paper, we introduce the excess attenuation calculated with the PE method and the correction model for ground effects on noise of engine run-ups and APU is discussed to implement it in the airport noise prediction model used in Japan.

Solar energy for the airport ground support equipment – a quantitative study

PurposeThis paper aims to evaluate the hypothetical situation in a resembling airport to Esenboga Airport and analyzes the condition of all ground support equipment (GSE) equipment to be supplied by electricity produced by solar panels mounted on the rooftop of the terminal building. The case is discussed using environmental emissions and economic feasibility. The results of the resembling case can be generalized to all airports for the reduction of emissions caused by ground operations of aviation.Design/methodology/approachGSE fleet data which has been prepared by TGS operated in the Esenboğa Airport have been used to calculate emissions, and equivalent electricity consumption. A hypothetical solar panel construction on the rooftop of the terminal building and also the electricity production case was analyzed. Based on the calculations, both fuel and electricity use cases are compared by means of emissions and production costs using real data.FindingsThe electricity production and transmission pose a high value of emissions. Thus, electrification of GSE in the airport need a new approach such as producing the electric energy in the site. This research analyzes the case that the electricity is produced on the rooftop of terminal building and consumed by the GSE fleet. The authors discussed that it is both feasible and possible to electrify all the GSE except a shortage of two cold months with high fuel demand by using electric storage options.Practical implicationsGround handling is performed by using GSE which is historically powered by diesel and such internal combustion engines which are well known for their high emission rates. As most of the airports reside in populated areas, GSE emissions need to be evaluated for reduction. However the electric energy could be an alternative for GSE emissions reductionOriginality/valueAviation is a system of many subsystems in which the performance of each unit plays a crucial role in the final success of the system. Concerns on environmental protection make the aviation industry focus on reducing emissions produced during operations. Although aircraft emissions are widely discussed in the literature, ground handling systems which are an integral part of the whole aviation system, also need to be studied regarding the environmental issues. Besides, the European Union has set out targets of reducing emissions at the airports during ground operations to zero. This paper discusses the possibility of the target by comparing various scenarios

Reduction in Ground Times in Passenger Air Transport: A First Approach to Evaluate Mechanisms and Challenges

Rising air travel demand, airport capacity issues, and schedule disruptions form part of the challenges that aviation stakeholders have to face in the upcoming decades. Minimizing ground times is one of their recent objectives as extended ground times induce operational, economic, and environmental risks. The flow of ground operations has a high impact on the overall air transportation system. Therefore, the impact and risks of extended ground times in passenger air transport were thoroughly compared, weighed, and compared based on pre-selected individual literature sources. Several studies deliver solution approaches to reduce ground times. The turnaround especially is a key element of any flight operation and impacts the competitive advantage of airlines and airports. Next to infrastructural changes, technological advancements, and operational performance improvements, the cooperation of stakeholders is a measure to shorten ground times. Special focus lies on the improvement of boarding procedures. They are essential for passenger air transport and reducing ground times.

A New Strategy of Satellite Autonomy with Machine Learning for Efficient Resource Utilization of a Standard Performance CubeSat

A mega constellation of Nano/microsatellites is the contemporary solution for global-level Earth observation demands. However, as most of the images taken by Earth-observing satellites are covered by clouds, storing and downlinking these images results in inefficient utilization of scarce onboard resources and bandwidth. In addition, the trend of making satellite task execution plans by ground operators demands the efforts of experts or simulators to predict the real-time situation of satellites and to decide which tasks should be executed next. Granting controlled autonomy to satellites to perform onboard tasks will boost mission effectiveness. We experimented with granting controlled autonomy for satellites in performing onboard image classification and task scheduling. We designed a convolutional neural network-based binary image classification model with more than 99% accuracy in classifying clear and cloudy images. The model is configured to perform inference in low-performance computers of ordinary Cubesats. Moreover, we designed an autonomous satellite task scheduling mechanism based on reinforcement learning. It performs better than a custom heuristic-based method in scheduling onboard tasks. As a result, the proposed classification and scheduling techniques with machine learning ensured efficient utilization of onboard memory, power, and bandwidth in the highly resource-constrained CubeSat platforms and mission accomplishment of Nano/microsatellite constellations.

Mathematical model of the UAV landing approach system on the example of the course-glide path system

A mathematical model of the landing approach system for an unmanned aerial vehicle (UAV) on the example of a course-glide path system (СGS) is presented. The proposed mathematical model includes an information model of the ground and airborne segments operation for the approach system. The mathematical model of the ground segment implements the calculation of the CGS radio signals power level at a given point in space — the position of the UAV. The mathematical model of the onboard segment implements the determination of the UAV getting into the radio beacon coverage area and the calculation of the UAV deviation angles from the glide path line. The UAV dynamics model is considered as a set of pre-obtained trajectory points. The carried out computational experiments showed the fundamental adequacy of the mathematical model and its application possibility for checkout automatic control systems for aircraft-type UAVs during landing approach. Keywords UAV, landing approach system, course-glide path system, localizer, glide path radio beacon, marker beacon, mathematical model, UAV landing

Тепловое состояние малого спутника при различной плотности расположения электронных плат

To reduce the cost of CubeSat satellites, an industrial level of performance for radio-electronic components designed for ground operations is applied. A specific tem-perature range should be maintained for such electronic components to operate under space flight conditions. Since the CubeSat spacecraft does not have an active temperature regulation system, the thermal conditions are determined by the balance between inactive absorbed and radiated energy flows, including internal heat release. This paper considers the effect of heat release from circuit boards of different packing density in the electronic equipment on the 1U CubeSat thermal conditions. Both the absorbed radiation from ex-ternal sources, the radiation from the CubeSat external surfaces, the inner heat release, and the re-radiation between the surfaces within the spacecraft are taken into account. The formulated problem is solved numerically. The results show the effect of circuit board packing density on the amplitudes of temperature oscillations and on the average temperatures of satellite structural elements.

Regenerative Electric Aircraft Taxi System

Electrification is the rising trend within the sector of transportation. It is happening not solely within the automotive business as it conjointly spreads wide into alternative industry. The airline business is a different field that is targeted underneath fast change into electrification stage. In the mere future there will be marketed new systems for ground maneuvering of aircrafts. Main reason why these new devices are to maximize the effort to decrease prices and environmental impacts of aviation. Airline operations mainly ground operation is one among the important source of emissions within the airports as taxing is performed by using jet engines inefficient idle thrust. Standard aircraft transportation consumes nearly to some percentage of the world’s complete fossil fuels, that equals to nearly 13% of the whole usage of fuel for transportation. Particularly in the billowing increment from evolving countries, the consumption rate of fuel is anticipated to extend quickly. Our approach of solving this problem is by implementing electrical motors which will be integrated within the main landing gears to alter electrical drive of the airplane to perform ground operations whereas they are off main engines throughout the taxiing method thereby increasing aircraft potency, decreasing fuel consumption, value reduction, reducing emission and reduced noise.

A Study on Airline Operations and Corporate Social Responsibilities of Air Italy

The world is becoming more connected, with the internet bringing us closer together, 24- hour news allowing us to see what is happening around the world, and more efficient planes allowing us to travel from place to place. Over the next decade, China will overtake the US as the highest source of passengers, flying to, from, and within the country, potentially rising to over 1 billion. Even if there is a downturn in productivity and restrictions in trade agreements, globally there should still be more than 6 billion passengers every year by the end of the next decade, significantly higher than today. Passengers numbering in the billions will continue to use planes, and many millions of new fliers will experience it for the first time, eventually becoming loyal customers. Job Growth: Job growth is also increasing Aviation industry growth. An increase in passengers will have a knock-on effect of stimulating more jobs in the Aviation industry. There are already 65 million jobs supported by the industry, but even more, will be needed to handle the volume of new flights. The IATA surveyed growth in the Aviation sector and found that the majority of respondents predict growth in ground operations, cabin crew, and customer service personnel jobs over the next two years, which will allow the industry to maintain its high standards. The 10 million jobs directly in the Aviation sector are around 4.4 times more productive than the average job around the world, and there will be millions more Aviation jobs created over the next decade. Supersonic Flight: New Aviation technology is emerging all the time, making flights faster, more efficient, and a more enjoyable experience for customers.

Detailed simulations of an aircraft fuel system by means of Simulink

The fuel system is one of the most important and complex parts of aircraft, being tasked with suppling the correct quantity of fuel to the aircraft engine during all operative conditions, from flight to ground operation. It must operate efficiently in any condition to guarantee safety and reliability. A fuel system for kerosene-based fuels (i.e., jet fuels) is a combination of hydraulic components, namely, tanks, pumps, bypass valves, safety valves, servovalves. The aim of this paper is to provide an accurate simulation model of an entire fuel system for gas turbine (turboprop and turbofan) engines, which can be used by manufacturers and researchers to evaluate the performance of the fuel system under different operating conditions for given components or to select the geometries of the components to obtain specific performance levels. The numerical code is developed in the Simulink environment, which is a software package widely used in industry. A detailed description of the model is provided in this paper, and results under specific operating conditions are shown and discussed. The power consumption of the system is assessed as well, with indication of the main sources of losses, which will be useful for current EU projects aimed at reducing the power consumption of aircraft.

Non-Road Mobile Machinery Emissions and Regulations: A Review

Non-Road Mobile Machinery (NRMM) incorporate a wide range of machinery, with or without bodywork and wheels, and are installed with a combustion engine and not intended for carrying passengers or goods on the road. These are used in many different sectors including construction, agriculture, forestry, mining, local authorities, airport and port ground operations, railways, inland waterways and within the household and gardening sector. This article presents a review of the state of knowledge with regard to non-road mobile machinery, particularly focusing on their regulation and the atmospheric emissions associated with them. This was undertaken as there is currently a lack of this information available in the literature, which is an oversight due to the potential for Non-Road Mobile Machinery to form a greater part of atmospheric emissions in the future, as other areas of emissions are tackled by regulations, as is outlined in the article. Emissions such as particulate matter (PM), carbon oxide (CO), carbon dioxide (CO2), hydrocarbons (HC), nitrogen oxides (NOx) and sulphur oxides (SOx) from NRMM contribute considerably to total emissions released into the air. NRMM are diverse in application, engine type and fuel use, and are therefore difficult to categorise. This leads to numerous issues when it comes to the control and regulation of their emissions. The most recent European and international regulations are outlined in this article. Due to the divergent nature of NRMM, their emissions profiles are highly varied, and in-use emissions monitoring is challenging. This has led to a lack of data and inaccuracies in the estimation of total emissions and emission inventories. It was assumed in the past that emissions from non-road sources did not contribute as significantly to total emissions as those from on-road sources. This assumption was partly due to the difficulty in gathering relevant data, and it was disproven in the 1990s by studies in The Netherlands, Finland and Sweden. It is now understood that NRMM will eventually surpass on-road vehicles as the leading source of mobile pollution due to the continuing efforts to reduce emissions from other sources. Many states worldwide gather emissions data from NRMM, and EU member states are required to report their emissions. As of January 2017, a new European regulation establishing limits for gaseous and particulate pollutants from NRMM applies, and this regulation also defines administrative and technical requirements for EU approval. The exact number of NRMM and the total amount of fuel they use is currently not known. In Ireland, for example, their fuel use has been reported under stationary boilers and engines. However, this results in the underestimation of emissions of some pollutants (NOx in particular) because emissions of air pollutants tend to be higher in mobile than in stationary machinery.

Evaluating AERMOD with measurements from a major U.S. airport located on a shoreline

The impact of airport operations on air quality is a key public health concern for the population surrounding an airport. Air pollution regulations require the assessment of this impact using dispersion models. Modeling dispersion of aircraft-related sources poses challenges because of the large number and variety of airport sources, which include aircraft, ground operation vehicles, and traffic in and out of the airport, most of which are mobile. Emissions from aircraft sources are transient, buoyant, and occur at different heights from the ground. Quantifying these emissions as well as modeling the governing processes is challenging. An added complexity occurs when the airport is situated near a shoreline where meteorological conditions are far from being spatially uniform. These features that characterize the dispersion of airport emissions are being incorporated into the AERMOD model in this paper. This paper examines the impact of shoreline meteorology and urban effects on dispersion by comparing model estimates of SO2 with corresponding measurements made during a field study conducted at the Los Angeles International Airport (LAX) during winter and summer of 2012 at all the four core sites (AQ, CN, CE, and CS) as a part of the LAX Air Quality Source Apportionment Study (AQSAS). We modified outputs from AERMOD's meteorological preprocessor AERMET to account for 1) the formation of the internal boundary layer that is formed when stable air from the ocean flows onto the warmer land surface of the airport, and 2) urban roughness effects on winds flowing from Los Angeles, east of the airport. Simulations with unmodified AERMET yielded concentrations that were substantially higher than the concentrations at AQ and CS and much lower than those at CN and CE. Model performance improved when AERMOD used the modified meteorology. The fraction of model estimates within a factor of two of the observations improved from 34 to 84% at the CS site and CE site, by up to 79% in winter season whereas in summer, FAC2 values are almost comparable at all the sites. The ratio of robust highest modeled values to measured values improved from 7.72 to 2.53 and 4.92 to 1.94 in winter and summer seasons respectively.

Heart rate variability in student pilots during the flight training: a preliminary report

Heart rate (HR) indicates the number of beats per minute (bpm) of the heart, while heart rate variability (HRV) indicates the temporal fluctuation of the intervals between adjacent beats (NN). HRV expresses neuro-cardiac activity and is generated by heart-brain interactions and dynamics related to the function of the Autonomous Nervous System (ANS) and other components (body and ambient temperature, respiration, hormones, blood pressure). The flight activity, especially during training, provides for a prolonged state of alert of the student pilot, as well as careful management of the flight and simultaneous planning of the next steps, with attention to the unusual conditions and emergencies that may occur during all various stages. HRV can provide a good reference index for estimating the degree of evolution of the training process of student pilots and a valid tool for some indications of a physiological as well as clinical nature. To investigate this issue, we started a series of experiments, still ongoing, by coupling the flight task times of student pilots with changes in their HRV. Before each experimental session, the participating pilot student was equipped with five electrodes, three-channel Holter (ECG BIOMEDICAL, BI9100). For this purpose, we have defined three-time phases: ground flight operations (bfo), in-flight operations (dfo) and post-flight ground operations (afo). The HRV analysis was carried out using the time domain and frequency domain parameters. As regards the mean of the RR intervals in the dfo, an increase was observed in 29% of the sample, while a decrease was observed in the remaining 71%, compared to that in the bfo. The analysis of the data relating to very low frequencies (VLF), low frequencies (LF) and high frequencies (HF) in the sample highlighted the values indicated below. In dfo, an increase in VLF values in 18% of the sample and a decrease in 82% in the remaining 71% compared to what was observed in bfo. LF values in dfo increased in 29% of the sample and decreased in the remaining 71%, compared to bfo. Finally, the HF, in dfo increased in 29% and decreased in 71% of cases, compared to the values of the bfo. Additional significant differences were found between the cases in which the RR intervals decreased in the dfo compared to the bfo, and those in which the RR intervals increased in the dfo compared to the bfo. In conclusion, the observed data lead to reconsider some physiological correlates of the different components involved in the determinism of HRV of a subject who carries out intense psychophysical activity for a certain period. In fact, it is necessary to evaluate the role of the ANS, in its various divisions (parasympathetic, sympathetic, and enteric), as well as the activity of the baroreceptors, the respiratory cycle (respiratory sinus arrhythmia), the thermoregulatory and hormonal factors within the short and medium tasks term.

Impact Assessment of The Covid-19 Pandemic on Service Performance of Sofia Airport

The main objective of the research presented in the paper is to examine the impact of the COVID pandemic on the volume of passenger and freight traffic and the quality of the services provided by Sofia Airport, as well as to examine the factors influencing the demand for air freight transport and the extent of their impact. The authors focus on using two approaches, namely SERVPERF and SERVQUAL, in studying factors influencing the demand for transport. The study analyses a system of indicators with independent influences on the demand for air transport, but they are all related to the development of macroeconomic indicators at the national level under the influence of the COVID pandemic. The study of the impact of the pandemic on the service performance and quality of services provided by Sofia Airport allows us to predict the volume of transport activity and to plan the activities of airlines and ground operators, their transport capacity, as well as the need for adopting measures for recovery of the airport from the negative impacts of the pandemic and the necessary investments in airport facilities. The authors argue that evaluating the service performance and the quality of services could contribute to developing appropriate measures for recovery. They summarized appropriate measures based on the leading quality indicators for air transport services. 
 Keywords: Air Transport, Impact Assessment, COVID pandemic, Service Performance, Service Quality.

Research on fault detection and principal component analysis for spacecraft feature extraction based on kernel methods

Abstract Satellite anomaly is a process of evolution. Detecting this evolution and the underlying feature changes is critical to satellite health prediction, fault early warning, and response. Analyzing the correlation between telemetry parameters is more convincing than detecting single-point anomalies. In this article, principal component analysis method was adopted to downscale the multivariate probability model, T 2 {T}^{2} statistic was checked to determine the data anomaly, without the trouble of threshold setting. After an anomaly was detected, time-domain visualization and dimension reduction methods were introduced to visualize the satellite anomaly evolution, where the dimensions of telemetry or features were reduced and presented in two- or three-dimensional coordinates. Engineering practice shows that this method facilitates the early detection of satellite anomalies, and helps ground operators to respond in the early stages of an anomaly.

Realistic solution of fuzzy critical path problems, case study: the airport’s cargo ground operation systems

Realistic solution of fuzzy critical path problems, case study: the airport’s cargo ground operation systems

MICROSCOPE mission scenario, ground segment and data processing

Testing the weak equivalence principle to a precision of 10−15 requires a quantity of data that give enough confidence on the final result: ideally, the longer the measurement the better the rejection of the statistical noise. The science sessions had a duration of 120 orbits maximum and were regularly repeated and spaced out to accommodate operational constraints but also in order to repeat the experiment in different conditions and to allow time to calibrate the instrument. Several science sessions were performed over the 2.5 years duration of the experiment. This paper aims to describe how the data have been produced on the basis of a mission scenario and a data flow process, driven by a tradeoff between the science objectives and the operational constraints. The mission was led by the Centre National d’Etudes Spatiales (CNES) which provided the satellite, the launch and the ground operations. The ground segment was distributed between CNES and Office National d’Etudes et de Recherches Aérospatiales (ONERA). CNES provided the raw data through the Centre d’Expertise de Compensation de Traînée (CECT: drag-free expertise centre). The science was led by the Observatoire de la Côte d’Azur (OCA) and ONERA was in charge of the data process. The latter also provided the instrument and the Science Mission Centre of MICROSCOPE (CMSM).

An Enhanced Drone Technology for Detecting the Human Object in the Dense Areas Using a Deep Learning Model

During the recent decade, emerging technological and dramatic uses for drones were devised and accomplished, including rescue operations, monitoring, vehicle tracking, forest fire monitoring, and environmental monitoring, among others. Wildfires are one of the most significant environmental threats to wild areas and forest management. Traditional firefighting methods, which rely on ground operation inspections, have major limits and may threaten firefighters’ lives. As a result, remote sensing techniques, particularly UAV-based remotely sensed techniques, are currently among the most sought-after wildfire-fighting approaches. Current improvements in drone technology have resulted in significant breakthroughs that allow drones to perform a wide range of more sophisticated jobs. Rescue operations and forest monitoring, for example, demand a large security camera, making the drone a perfect tool for executing intricate responsibilities. Meanwhile, growing movement of the deep learning techniques in computer vision offers an interesting perspective into the project’s objective. They were used to identify forest fires in their beginning stages before they become out of control. This research describes a methodology for recognizing the presence of humans in a forest setting utilizing a deep learning framework and a human object detection method. The goal of identifying human presence in forestry areas is to prevent illicit forestry operations like illegal access into forbidden areas and illegal logging. In recent years, a lot of interest in automated wildfire identification utilizes UAV-based visual information and various deep learning techniques. This study focused on detecting wildfires at the beginning stages in forest and wilderness areas, utilizing deep learning-based computer vision algorithms that control and then mitigate massive damages to human life and forest management.

Applying digital twins for the management of information in turnaround event operations in commercial airports

The aerospace sector is one of the many sectors in which large amounts of data are generated. Thanks to the evolution of technology, these data can be exploited in several ways to improve the operation and management of industrial processes. However, to achieve this goal, it is necessary to define architectures and data models that allow to manage and homogenise the heterogeneous data collected. In this paper, we present an Airport Digital Twin Reference Conceptualisation’s and data model based on FIWARE Generic Enablers and the Next Generation Service Interfaces-Linked Data standard. Concretely, we particularise the Airport Digital Twin to improve the efficiency of flight turnaround events. The architecture proposed is validated in the Aberdeen International Airport with the aim of reducing delays in commercial flights. The implementation includes an application that shows the real state of the airport, combining two-dimensional and three-dimensional virtual reality representations of the stands, and a mobile application that helps ground operators to schedule departure and arrival flights.

Evolution of inverter ground impedances for PV modules with various backsheet types

AbstractHerein, we present results that emphasize the importance of retaining high insulation resistance in polymer backsheets for the reliable operation of photovoltaic installations. By correlating inverter monitoring data, meteorological data, and spectroscopic information from backsheet materials of photovoltaic modules, we derive performance and degradation rates for inverters connected to photovoltaic modules with several backsheet types. The feasibility of evaluating the degradation status of photovoltaic modules in the field through spectroscopic analysis of the water content in backsheet and encapsulant is demonstrated. We show that an increase in water content is a sign for reduced leakage resistance. Ground impedance was measured alongside relative humidity and temperature for three specific backsheet types. Inverters with polyamide and fluorinated coating/polyethylene terephthalate backsheets showed a significant drop in ground impedance at high humidity, RH > 70%. A loss rate of −2 kΩ/day in ground impedance was found for inverters connected to modules with certain fluorinated backsheets. This value is twice as high as for inverters connected to modules with polyamide backsheets. Time series show that the sensitivity to moisture and water ingress increases with time, especially for modules with polyamide and certain fluorinated backsheets. The worst degradation scenario observed had an annual yield loss of 27% due to inverter outages on humid days. About 25% of inverter trip alerts after 8 years of operation included modules with the specific fluorinated backsheet. In general, the study revealed a distinct backsheet impact on ground impedance and operation of inverters and the resulting yield showing an important role of the choice of polymers for reliable and long‐lasting photovoltaic systems.

Identification and orientation patterns relative to the type of information provided, and the accuracy of alerts: an operational use case with infantry ground military operators

With the increased use of unmanned aerial and ground systems in the military environment, the question of what information to distribute to ground military operators arises. Generally, ground operators prefer ground views over aerial ones. Aerial views can generate broader understanding of the environment and increase comprehension of the situation but, also, cause overload and confusion. Alert systems can push information to operators to increase attending to critical events. But alerts are not perfect; accuracy depends on the rate of misses and false alerts of irrelevant events. In an experimental setup, we examined how information sources (with or without aerial view) and alert accuracy interact to affect ground operators’ performance in an Intelligence gathering identification and orientation mission. We collected performance, subjective and eye-tracking data and present here the ground operators’ sensitivity and response bias using signal detection theory (SDT) measures. Participants performed better with ground views, and we report an interaction between the presence of aerial view and the accuracy of the alerting system for the orientation task. Participants benefited more from alerts with ground views alone.