Paul C. Roling

Modeling the effect of night time penalties on commercial and business flights for regional airport noise and economics: Rotterdam Airport case study

Noise is one of the main concerns of airports around the world. Several measures have been taken by regulators to reduce noise at airports. Some of these measures are meant to control noise at major or busy airports; however, certain operational restrictions (quota, curfew, and budget) are also implemented throughout the whole country regardless of the role and the size of the airports. An empirical example, using the Rotterdam Airport, a regional airport in the Netherlands, illustrates how regional airport should determine its night surcharges policies, especially with different type of aircraft categories. In this research, the night surcharges received from Business Jet category and Commercial aircraft category are being compared. The results indicate that the night surcharges did not compensate for the number of day time flight movements and potential revenues losses. Regional airport may need to be more selective in setting the night surcharges in order to maximise its revenues.

Airport surface traffic planning optimization: a case study of Amsterdam Airport Schiphol

Adding runways and taxiways is a way of solving capacity problems at major airport. As this also increases the intensity of airport ground operations, safety and efficiency might be compromised which is why significant amounts of research has been done in this field, such as research with respect to Advanced Surface Movement Guidance and Control Systems. A taxi planning model developed at the TU Delft uses MILP techniques, combined with pre and processing to allow simulation and optimization of the routing of aircraft on taxiways for major airports, such as Amsterdam Airport Schiphol.

Electric Taxi Systems: An operations and value estimation

This research is based on Value Operation Methodology (VOM) and the current progress in aircraft electric taxi operations. In addition to fuel and emissions, the impact of electric taxiing on several other value drivers is investigated, including maintenance, time benefits and ground operations. Furthermore the taxi standard operating procedures (SOP’s) are evaluated and an initial design of ETS operating procedures is stated. For the creation of new ETS operating procedures a thorough data research is carried out on KLM Royal Dutch Airlines taxi operations data. It is concluded that the system design can have big influence on the taxi performance, which in turn influences the taxi operations and time. Moreover the maintenance costs, specifically for engines and ground services cost are important ETS value drivers. Finally the operating times of ETS taxi play a crucial role in the ETS utilization. This utilization is the main driver for the ETS value.

Calculating capacity of dependent runway configurations: A discrete-event simulation approach for analysing the effect of aircraft sequencing

Different projects and tools exist to prepare the air transport industry with the expected growth in the coming 20 years. An important Key Performance Indicator (KPI) in these projects and tools is runway capacity. Existing analytical models to approximate runway capacity cannot take into account all dependencies that exist between multiple runways. Extensive simulation models form an alternative, but are often too complex and time consuming to be used by airport operators themselves. This paper proposes a discrete-event simulation model that is able to determine the runway capacity, by defining a set of standard dependencies between runways that can be adjusted to local circumstances using a limited number of parameters. The model is furthermore able to analyse the benefits in runway capacity that can be achieved by the optimal sequencing of aircraft and has been validated against realised capacity data, and shows realistic results.

Effects of Pushback Accuracy On Static Apron Capacity

The static apron capacity for aircraft with a wingspan higher than 65m is limited at Amsterdam Airport Schiphol (AMS). With the introduction of new large aircraft with increasing wingspan, such as the B777-9X, Schiphol is faced with the challenge of realizing larger gates. Currently, the taxi wingtip clearance is used for pushback and towing and the goal of this research is to see if it is possible to decrease the wingtip clearance there. Using aircraft transponder data and reproducing the pushback tracks for five gates, it is shown that some room is available to limit clearance and thus increase capacity at some gates, but more capacity could be gained by providing tug drivers with extra guidance through Differential GPS or a ‘Follow the Greens’ system.

Flexible runway use modeling using pairwise RECAT-EU separation minima

If we would take fuel consumption and noise annoyance into account in the runway allocation process,runway allocation can take place more efficiently, both in terms of fuel cost as well as noise annoyance. In this research, the focus is on the further development of a model in order to make the calculationsmore refined. Moreover, the improvements conducted in this research relate to the methodologies to compute the cost of the decision variables and the level of complexity of specific linear programming constraints in the optimization model. Consequently, the aim of this research is to answer the following research question: Can the performance of Standard Flex be further optimized by applying pairwise flight dependencies, while ensuring and contributing to a valid trade-off between runway capacity, noise emission, fuel burn and safety. By means of this research, the flexible runway allocation model has been improved on many aspects. The computation strategy of both objectives has moved from a reference aircraft based computation strategy to an analysis based on each unique aircraft on its own. This refined computational approach has resulted in a better understanding and modeling strategy of the operations that take place at an airport. Finally, the implementation of RECAT-EU separation minima has resulted in a reduction of 5-10% in overall separation times with respect to the regular ICAO WTC strategy, based on multiple air traffic demand mixture scenarios, based on a specific demand of flights?.

Flexible Arrival & Departure Runway Allocation Using Mixed-Integer Linear Programming

Runway capacity of a complex runways system can be limited by several factors. Currently, the runway usage at Amsterdam Airport Schiphol (AAS) is described by a preference list established by multiple stakeholders. It makes an important trade-off between minimizing noise exposure to the environment and maximizing capacity. The existing model does not take into account fuel burn and the ensued emissions for the current and future demand in flights. This study tries to address this issue. A model has been developed using Mixed-Integer Linear Programming (MILP) by which flights can be allocated to runways, while optimizing for fuel and noise. The research has the following research question: Can fuel burn be significantly reduced for aircraft operating at Amsterdam Airport by utilizing a novel flexible arrival and departure runway allocation model, using a predefined set of variables and rules, accounting for noise annoyance, runway capacity and the current and future demand of flights? The runway allocation model developed for this study is able to assign aircraft to runways based upon an optimization trade-off between fuel usage and noise exposure to the environment. Selecting a shorter flight- or taxi route may result in lower fuel burn and emissions, while separation- and noise regulations are maintained. A multitude of scenarios is simulated using the allocation model. Different runway configurations are tested. Additionally, different peak moments varying during the day are compared to see when flexible allocation is feasible and most profitable. A set of Pareto optimal solutions can be evaluated in order to determine the most optimal runway allocation distribution. The conclusion that can be drawn from this research is that flexible allocation can have significant impact on both fuel usage and emissions, while adhering to the current regulations. Depending on the flexibility of available runways, mainly restricted by separation- and noise regulations, runway demand, local conditions and maintenance, savings are possible. For scenarios where there is room for flexibility, savings are evident. For restricted scenarios, due to wind- or visibility conditions, potential savings exist, although to a lesser extend. The level of runway demand plays a role, as most flexibility and potential savings are obtainable during off-peaks. Annual savings can amount to significant fuel and emission reduction. The described runway allocation tool has the generic abilities of being scalable to wide variety of airports and their characteristics. Other airports, a larger set of aircraft and aircraft types, different arrival and departure operations can all be added to the model due to the generic characteristics. This aids further research and eventual application of flexible arrival and departure runway allocation in the aviation industry.

Evaluation of a Dynamic Taxi-time Estimation Model Using Process-based Segmentation in an A-CDM Environment

In order to meet the high increase in traffic demands, many are looking for solutions to improve the aircraft turn-around process without changing the current airport infrastructure, predicting taxi times is a vital step. The primary goal of this project is to create a dynamic taxi-time estimation model that can predict the taxi-time for both the arriving and departing flights with more accuracy than current static estimation models. Where the static models only use certain historical averages, the dynamic model uses a combination of historic as well as short-term traffic predictions to estimate each taxi time individually in smaller process divisions. Using approximately 2 months of historical data of two airports, both the most successful static and dynamic models reduced the standard deviation between the actual and predicted accuracy by approximately 22% from a global average. The dynamic model resulted in a ±5 min accurate arrival prediction made for 93% and 98% of the times as well as 82% and 93% ±7 min accuracy for departures. There was little direct distinction in the results between the two types of models yet the dynamic model showed to be only very slightly inferior to the static.

TPMagic, a universal airport surface traffic planning analysis and optimization tool

Adding runways and taxiways is a way of solving capacity problems at major airport. As this also increases the intensity of airport ground operations, safety and efficiency might be compromised. This is one of the main reasons why a significant amount of research has been done in this field, such as research with respect to Advanced Surface Movement Guidance and Control Systems. A taxi planning model developed at the TU Delft uses MILP techniques, combined with pre and processing to allow simulation and optimization of the routing of aircraft on taxiways for major airports. A study of Hartsfield–Jackson Atlanta International Airport shows the benefits an Advanced Surface Movement Guidance and Control Systems can have.