Individual Aircraft Research Articles

Impact of operator characteristics on landing gear ground manoeuvre occurrences

Abstract The variability in ground manoeuvre occurrences for aircraft landing gear is intrinsically linked to the airport geometries served by aircraft in-service and consequently, the cyclic loads that landing gear carry are driven by the route network and characteristics of aircraft operators. Currently, assumptions must be made when deriving fatigue load spectra for aircraft landing gear, which may fail to capture the operator characteristics, potentially leading to design conservatism. This paper presents the enhanced characterisation of ground turning manoeuvres within the Automatic Dependent Surveillance-Broadcast (ADS-B) trajectories for six narrow-body aircraft across a full-service carrier (FSC) and a low-cost carrier (LCC) fleet. The methodology presented within this paper employs ADS-B latitude and longitude information to overcome limitations of previous approaches, increasing the rate of correct manoeuvre identification within ADS-B trajectories to 77% of flights from the 50% rate achieved previously. When characterising the ground manoeuvres across 3,000 flights, significant differences in manoeuvre occurrences were observed between individual aircraft within the LCC fleet and between the FSC and LCC fleets. The occurrence of tight and pivot turns were shown to vary across the six aircraft with six and eight fatigue-critical turns being performed by the FSC and LCC fleet for every 10 flights performed. In addition, it was observed that the direction of fatigue critical turns is biased in specific directions, suggesting that individual main landing gear assemblies will accumulate fatigue damage at an increased rate, leading to greater justification for operator-specific spectra and structural health monitoring of aircraft landing gear.

On-line Updated Guided Wave-Based Gaussian Process Method for Damage Evaluation of Aircraft Structure

Accurate damage evaluation for an aircraft by using guided wave-based structural health monitoring (SHM) technology is in critical demand. An aircraft experiences various uncertainties during its service life, such as the time-varying environment, operational conditions, and different flight missions. Additionally, the actual aircraft structure involves complex structural forms such as varied thickness, stiffeners, ribs, and large cutouts, leading to a strong uncertainty of damage initiation and propagation. Consequently, when applied to an individual aircraft structure, the diagnosis model trained by prior data inevitably introduces errors, and the errors accumulate as the damage propagates, which brings challenges in engineering application. To achieve individual aircraft structure’s more accurate damage evaluation, an on-line updated guided wave-based Gaussian process (GP) damage evaluation method is investigated in this paper. Multi-source data from the design, service, and maintenance stages are utilized to continuously update and evolve the GP model, enabling its accurate evaluation throughout the long-term service life.

Cruise altitude patterns for minimizing fuel consumption and emission: A detailed analysis of five prominent aircraft

This study conducts a comprehensive analysis of fuel consumption and emissions associated with the installation of the most commonly used engine combinations currently available on five distinct types of BADA 4 (Base of Aircraft Data), ANP (Aircraft Noise and Performance), and AEM (Advanced Emissions Model) aircraft supplied by two distinct aircraft manufacturers to the civil air transport sector. The comparison spans a total of 18 flight scenarios (90 flights) for each aircraft, ranging in altitude from FL300 to FL385. To achieve this, the research employs a comprehensive approach encompassing data acquisition from EUROCONTROL's Integrated Aircraft Noise and Emissions Modelling Platform (IMPACT), robust data analysis, and advanced statistical techniques. The goal of this study is to investigate variations in fuel consumption and emissions at different cruising altitudes for various commercial aircraft types, assessing the veracity of the commonly assumed decrease in fuel consumption and associated emissions with altitude, and exploring the impact of individual aircraft assessments on the precision and comprehensiveness of environmental impact assessments in civil aviation flight operations. The work seeks to answer the following the main research question: Does every aircraft's fuel consumption and related emissions truly decrease with increasing altitude, according to conventional methodologies and general assumptions?

Exploration of optimal control based surrogate modeling as a basis for fuel efficient 4D aircraft routing on graphs

AbstractFuel efficient coordination of aircraft operations in the Terminal Maneuvering Area of large airports can contribute to the reduction of the environmental impact of air traffic. To exploit the full potential of the air traffic system, coordinated routing in the Terminal Maneuvering Area, runway assignment and scheduling need to be optimized considering detailed models of the aircraft dynamics and performance. Due to the inhomogeneous nature and level of detail of these combined discrete and continuous decision problems, the optimization of the overall operations poses significant challenges. As part of an integrated approach to the solution of this hybrid problem, this work explores the generation of surrogate models for the fuel consumption of individual aircraft using optimal control methods to exploit the physical capability of the aircraft within an operationally permissible envelope. The surrogate models approximate the predicted fuel consumption of a given point-mass aircraft model on short generic trajectory segments. The trade-off between flight duration and fuel consumption on such segments is analyzed, focusing on the influences of initial aircraft mass, altitude, distance, mean climb angle, along-track wind velocity and linear wind shear. An extensive description of the optimal control-based data generation and surrogate modeling methodology is followed by a discussion of the effects of parameter variation. Based on an illustrative case study, the applicability of the approach is critically analyzed.

Stream Life Cycle Assessment Model for Aircraft Preliminary Design

The growing environmental public awareness and the consequential pressure on every industrial field has made environmental impact assessment increasingly important in the last few years. In this scope, the most established tool used in the specialized literature is the life cycle assessment. Applying this method to the life cycle of an aircraft requires it to be broken down into at least four phases: production, operation, maintenance and disposal. In the assessment, the evaluation of the environmental impact of fuel consumption can be performed linearly and has already been studied over many years, while calculating the impact of other life phases is more complicated, and it is still under study. This paper describes a simple and effective method developed to assess the environmental impact of an aircraft at a preliminary design stage and the implemented model that resulted from it. A detailed consideration of all life cycle phases is essential to serve as a reference for the ecological assessment of novel aircraft concepts. Thereby, the developed method is based on some parametric equations that take into account preliminary information, such as the mass breakdown, the technology used and some program considerations. The results obtained have been compared with those of the literature for verification and validation and have proved to be quite reliable. In fact, the comparison with known analyses, conducted on individual aircraft in a very precise manner, has showed that the proposed model is capable of giving results that fell within ±10% of the reference values. This is due to the broad generality of the model, which does not require a large number of specific data as a starting point to obtain reasonably reliable results for use during project development. In the near future, the use of this model can assist the design of aircraft architectures that comply with the European Green Deal of reducing net greenhouse gas emissions by at least 55% by 2030 and of having no net emissions of greenhouse gases by 2050.

Integrated commercial and operations planning model for schedule design, aircraft rotation and crew scheduling in airlines

AbstractThe commercial and operations planning in airlines has traditionally been a hierarchical process starting with flight schedule design, followed by fleet assignment, aircraft rotation planning and finally the crew scheduling. The hierarchical planning approach has a drawback that the optimal solution for a planning phase higher in hierarchy may either be infeasible for the subsequent phase or may lead to a sub‐optimal overall solution. In this paper, we solve a profit‐maximizing integrated planning model for clean‐sheet “rotated” schedule design with flight re‐time option and crew scheduling for a low‐cost carrier (LCC) in an emerging market. While the aircraft rotation problem has been traditionally modeled in the literature as a daily routing of individual aircraft for maintenance requirement, in this work we address the requirement of planned aircraft rotations as part of schedule design for LCCs. The planned aircraft routing is important in our case to create as many via‐flights as possible due to the underserved nature of the emerging market. We solve this large‐scale integer‐programming problem using two approaches – Benders Decomposition and Lagrangian Relaxation. For Lagrangian Relaxation, we exploit the special structure of our problem and intuitive understanding behind the Lagrangian duals to develop a multiplier adjustment approach to find an improved lower bound of integrated model solution. The crew‐pairing sub‐problem is solved using column generation through multi‐label shortest path algorithm followed by branch‐and‐price for integer solution. We test our solution methodology on a flight universe of 378 unique flights for different problem sizes by varying the number of aircraft available for operations. Our computational results show that within a reasonable run time of few hours both the approaches, Benders Decomposition and Lagrangian Relaxation, are successful in finding lower bounds of the integrated model solution, which are higher than the solution of traditional hierarchical approach by 0.5%–2.5%. We find Lagrangian Relaxation methodology to usually attain an improved solution faster than the Benders Decomposition approach, particularly for large‐scale problems.

A whole service time SHM damage quantification model hierarchical evolution mechanism

Accurate damage quantification for an individual aircraft by using structural health monitoring (SHM) technology poses a persistent challenge in practical engineering. Existing damage quantification models typically rely on prior data acquired from ground design and tests. However, an individual aircraft is subject to diverse uncertainties throughout its whole service time, such as time-varying environmental and operational conditions, different flight missions, and different damage morphologies. Consequently, employing a prior trained model for damage quantification inevitably introduces errors, thereby limiting the engineering applicability of SHM. To improve the damage quantification accuracy for individual aircraft under the influence of uncertainty, a new whole lifetime data-based damage quantification model hierarchical evolution mechanism is proposed in this paper. Multi-source data from the design, service, and maintenance stages of individual aircraft are adopted to continuously evolve the probabilistic damage diagnosis model, enabling it to characterize the specific data distribution and track the damage propagation. The proposed method is validated through fatigue tests of a landing gear beam structure, which is an important aircraft load-carrying component, with guided wave monitoring based hidden Markov model quantifying its crack propagation. The validation result demonstrates the effectiveness of the proposed method in ensuring the long-term reliability of the model and achieving more accurate damage quantification for an individual aircraft.

Regarding the Spontaneous Mechanism of Atmospheric Whirlwind Generation in Narrow Mountain Canyons

In a narrow, rather deep mountain canyons, under certain conditions, an irregular thermal mechanism can be activated, leading to the spontaneous convective movement of the air mass. This effect differs from the well-known phenomenon caused by the diurnal variation of the solar heat flux in large, broad valleys, where the regular diurnal variation in the direction of onshore winds is systematically suppressed. A specific hydrodynamic picture corresponds to spontaneous convection. In particular, there is a change of direction (inversion) in the vertical profile of the horizontal movement of air along the slope of the canyon at a certain height. At that time, Ludwig Prandtl developed the theoretical model through which it is possible to analytically determine the level of velocity inversion compared to the base of the valley. At this height, due to the instability of the velocity profile, the formation of atmospheric vortexes of a certain size is likely. It is natural that the dissolution (dissipation) of such vortexes will affect the temperature field.Therefore, the breakup of whirlwinds is related to the violation of thermodynamic equilibrium, meaning that there will be an impulsive change in the meteorological regime in the local area due to the spontaneous turbulence of air masses in the areas of velocity inversion. The characteristic time of this event will depend on the duration of the temperature field disturbance. It is likely that such a location will become a dangerous opportunity for hang gliding or paragliding enthusiasts. It should be noted that this type of sport has become an important component of tourism in Georgia, particularly in the mountainous regions of the country. Therefore, there is a need to focus on ensuring the safe flight conditions of individual aircraft in narrow valleys. Their formation, among other measures, requires an assessment of the probability of the operation of a thermal mechanism causing stochastic atmospheric disturbances in narrow canyons. This task can be carried out only as a result of a special investigation, based on the monitoring of seasonal and short-term hourly indicators of the mentioned physical event in a specially selected canyon, which can be considered typical for the mountainous regions of Georgia.

A multi-layer ML model evolutionary paradigm for high-accuracy individual aircraft SHM

Evolutionary Machine Learning (EML) has emerged as a novel direction for providing robust methodologies for effectively tackling complex problems. However, most current research focuses on multi-objective optimization problems in machine learning (ML). There is limited research on the EML mechanism along the temporal application process, where a fixed machine learning model trained with the prior dataset will inevitably be not representative of the target problem with time. Taking the Structural Health Monitoring (SHM)-ML damage diagnosis model as an example, this paper proposes a novel multi-layer ML model evolutionary paradigm with multi-source data for high-accuracy individual aircraft SHM. The proposed paradigm considers three interconnected layers for the SHM-ML damage diagnosis model, including the dataset to establish the diagnosis model, the model structure and its parameter training, and mapping relationship used in the model to give the damage size. Besides, for a specific model of aircraft, there exist multiple stages from design to service, where multi-source of data is fused for the multi-layer evolution, enabling continuous improvement of damage diagnosis accuracy. Experimental validation is conducted on critical connection structures of aircraft, specifically the attachment lug structure, using the active guided wave SHM method. The results demonstrate the effectiveness of the proposed multi-layer ML model evolutionary paradigm.

Effect of Rinsing on Atmospheric Corrosion Environment of KT-1 Aircraft

Corrosion is difficult to predict and manage. Thus, understanding the characteristics of the atmospheric corrosion environment inside and outside the aircraft is necessary. A series of corrosion defects were found inside the KT-1 aircraft; hence, an atmospheric corrosion monitoring set was mounted inside the aircraft to measure the effect of external rinsing on the internal corrosion according to location (fuselage and wing). The effect of external rinsing was analyzed through surface analysis of the specimens and corrosion rate estimation using internal environmental parameters. Steel specimens within the monitoring set exhibited complete corrosion, while Ag specimens showed discoloration. External rinsing reduced the rate of chloride build-up inside the wing. Additionally, time of wetness (TOW) tended to increase with external rinsing regardless of location. Estimated and measured corrosion rates were positively correlated with TOW but negatively correlated with chloride accumulation rate. These results indicate the mixed effect of rinsing and require corrosion control for individual aircraft when deciding whether to apply cleaning for corrosion control.

Aircraft fleet availability optimisation: a reinforcement learning approach

AbstractA fleet of aircraft can be seen as a set of degrading systems that undergo variable loads as they fly missions and require maintenance throughout their lifetime. Optimal fleet management aims to maximise fleet availability while minimising overall maintenance costs. To achieve this goal, individual aircraft, with variable age and degradation paths, need to operate cooperatively to maintain high fleet availability while avoiding mechanical failure by scheduling preventive maintenance actions. In recent years, reinforcement learning (RL) has emerged as an effective method to optimise complex sequential decision-making problems. In this paper, an RL framework to optimise the operation and maintenance of a fleet of aircraft is developed. Three cases studies, with varying number of aircraft in the fleet, are used to demonstrate the ability of the RL policies to outperform traditional operation/maintenance strategies. As more aircraft are added to the fleet, the combinatorial explosion of the number of possible actions is identified as a main computational limitation. We conclude that the RL policy has potential to support fleet management operators and call for greater research on the application of multi-agent RL for fleet availability optimisation.

Utilisation of semantic technologies for the realisation of data-driven process improvements in the maintenance, repair and overhaul of aircraft components

AbstractAircraft components are subject to numerous, complex and often manual maintenance, repair and overhaul (MRO) procedures to ensure long operating cycles. In order to remain competitive in the long term, in spite of increased cost pressure, MRO service providers must improve the efficiency of their processes through the targeted use of internal knowledge sources. Techniques from the fields of Artificial Intelligence (AI) and Data Mining (DM) have already proven their potential in diverse domains. However, the application of such data-driven approaches is also associated with some hurdles that need to be eliminated in advance. Data are generated at the business process level, known as Information Technology (IT, e.g. Enterprise Resource Planning (ERP) systems), as well as at the equipment level, known as Operational Technology (OT, e.g. test equipment). The integration of both forms the basis for improving the maintenance activities of diagnostics and maintenance scheduling. However, creating a unified view and understanding of the manifold data related to the maintenance process is a major problem due to the heterogeneous data sources and formats included. In this context, the use of Semantic Technologies (ST) can be helpful to overcome these challenges and provide the foundation for improved data management. The objective of this contribution is to introduce an ontology that delineates fundamental domain concepts, facilitating the augmentation of maintenance process data for individual aircraft components with pertinent contextual information. The result is being applied within the scope of a proof of concept aimed at supporting the coherent digital services diagnostics and short-term maintenance planning.

A Novel Individual Aircraft Life Monitoring Method Based on Reliable Life Consumption Assessment

Individual life monitoring is crucial for ensuring aircraft flight safety. Conventional life-consumption-based monitoring methods ignore reliability, thus disjoining them from the aircraft’s reliable life determination and extension, where high confidence and reliability are required. Therefore, this paper proposes a reliable life consumption and individual life monitoring method for aircraft structure fatigue. In the paper, the P-S-N curve, i.e., the relationship between the aircraft structure’s life (N) and fatigue load (S) under a certain probability (P), is established, by which the lower confidence limit of the aircraft structure’s reliable life can be evaluated under any fatigue loads. Based on that and the aircraft’s monitored fatigue loads, the indexes of reliable life consumption and remaining reliable life percentages are proposed and assessed in real time for individual aircraft life monitoring and online life management. Case studies indicate that the proposed method can guarantee high confidence and reliability requirements in individual life monitoring, consistent with the aircraft’s life determination and extension, which are widely accepted nowadays in engineering practice.

Effects of Aircraft Noise on Sleep: Federal Aviation Administration National Sleep Study Protocol.

Aircraft noise can disrupt sleep and impair recuperation. The last U.S. investigation into the effects of aircraft noise on sleep dates back more than 20 years. Since then, traffic patterns and the noise levels produced by single aircraft have changed substantially. It is therefore important to acquire current data on sleep disturbance relative to varying degrees of aircraft noise exposure in the U.S. that can be used to check and potentially update the existing noise policy. This manuscript describes the design, procedures, and analytical approaches of the FAA's National Sleep Study. Seventy-seven U.S. airports with relevant nighttime air traffic from 39 states are included in the sampling frame. Based on simulation-based power calculations, the field study aims to recruit 400 participants from four noise strata and record an electrocardiogram (ECG), body movement, and sound pressure levels in the bedroom for five consecutive nights. The primary outcome of the study is an exposure-response function between the instantaneous, maximum A-weighted sound pressure levels (dBA) of individual aircraft measured in the bedroom and awakening probability inferred from changes in heart rate and body movement. Self-reported sleep disturbance due to aircraft noise is the secondary outcome that will be associated with long-term average noise exposure metrics such as the Day-Night Average Sound Level (DNL) and the Nighttime Equivalent Sound Level (Lnight). The effect of aircraft noise on several other physiological and self-report outcomes will also be investigated. This study will provide key insights into the effects of aircraft noise on objectively and subjectively assessed sleep disturbance.

Towards a resilience assessment framework for the airport passenger terminal operations

Airport terminals can generate and intensify the undesired phenomena that take place on transportation networks in the wake of disruptive events. The more resilient a terminal is, the more easily it will bounce back to the desired state, causing less nuisance to the users. In this study, we expand the state-of-the-art airport terminal resilience assessment through fast-time simulation and tailored resilience metrics. From the point of view of simulation, we establish delay management strategies based on flight schedule alterations as a response to a disruptive event. In the baseline scenario, no disruption is set, whereas passenger arrival to the airport is blocked for 1 or 2 h in the disrupted scenarios. A previously verified and validated simulation model of a Brazilian domestic airport was used to represent the passenger departing flow, encompassing check-in and security screening. From the resilience perspective, a systematic assessment procedure for new resilience metrics is unveiled, providing means for exploring the metrics’ formulations and their relationship to the operational strategies. Following the simulation runs, resilience metrics for individual passenger and aircraft delays were investigated, something yet scarcely explored in the literature. The results show that the proposed metrics deliver significantly different outcomes from those associated with the current literature. Consequently, we can conclude that a resilience assessment concerning the airport terminal that disregards individual delays may be missing important information. The systematic approach we propose is a contribution in that sense, even though this topic requires more research, considering the vast nature of the possible disruptive events and their subsequent operational impacts.

Aircraft routing clusters and their impact on airline delays

Airlines operate thousands of aircraft routings every day with a multitude of options to connect single flights integrated in a routing. Since airline delays entail significant costs for airlines and to societies, we aim to identify how far individual aircraft routings differ in on-time performance. We apply a novel approach to cluster aircraft routings and compute the routing strength to quantify the structure of aircraft routings. We then develop an econometric model to analyze the impact different routing clusters have on airline delays. As a key finding, routings with higher strengths tend to cause more delays. Our clustering of routings shows that hybrid routing structures and intense shuttling of flights between a few airports in a routing increases delays compared to routings structured star- or string-like. We also find major differences across airlines in the way routings are structured.

Emissions of ultrafine particles from civil aircraft: dependence upon aircraft type and passenger load

Very high concentrations of ultrafine particles (UFP) were measured at Heathrow Airport London. Exposure to UFP is strongly linked to adverse health effects and guidance for exposure limits has recently been provided by the World Health Organization (WHO). Using 1 s resolution UFP measurements and aircraft GPS data, measurements were assigned to individual aircraft and their operating mode, and this information was used to model UFP emission rates. In all cases, the highest emission rates were associated with departing aircraft, with rates for larger aircraft higher than smaller aircraft. Emission rates per passenger is influenced by the number of passengers carried, especially for arriving aircraft. Calculated emission rates are significantly higher than stated literature values, due to the inclusion of condensable particles in the measurements. These condensable particles are specifically not included in the regulated emission rates. Measured UFP concentrations within the airport boundary (and therefore not accessible to the general public) exceed the WHO guidance, indicating that UFP concentrations outside of the airport boundary could also be of concern. Assessing population exposure close to airports will be of increasing importance in future.

From passenger itineraries to climate impact: Analyzing the implications of a new mid-range aircraft on the global air transportation system

Aircraft design usually focuses on utilizing new technologies to improve mission performance of individual aircraft and, thus, reduce cost, emissions and climate impact of the global air transportation system (ATS). However, efficiency gains in the ATS can also be achieved by improving the alignment of payload–range capabilities and aircraft–route assignment of the overall fleet. Therefore, this article analyzes the implications—from passenger itineraries to climate impact—of a new mid-range aircraft (NMRA), which addresses the current lack of modern, designated mid-range aircraft in commercial production. The analysis is based on simulating and comparing two future scenarios with similar technology levels: one with and one without a NMRA. The core of the applied novel simulation framework is highly integrated models for passenger itinerary preferences, fleet development and aircraft–route assignment. Models for passenger demand as well as aircraft trajectories, emissions and climate impact complement the simulation framework. The results show that introducing a NMRA to the ATS improves the quality of travel for passengers and the alignment of payload–range capabilities and aircraft–route assignment for the overall aircraft fleet. As a consequence, the NMRA reduces the fuel consumption, emissions and climate impact of the ATS in our future scenarios by up to 1.4% (pessimistic) and 2.1% (optimistic). We conclude that a higher fleet diversification and a better alignment of payload–range capabilities and aircraft–route assignment through introducing a NMRA can marginally improve the fuel efficiency and climate impact of the ATS.

Aircraft noise exposure and risk for recurrent cardiovascular events after acute coronary syndrome: A prospective patient cohort study

In several population based cohort studies associations between aircraft noise and various diagnoses of cardiovascular disease were observed. However, no study has yet addressed the risk of recurrences in relation to transportation noise in patients with acute coronary heart disease.We conducted a prospective patient cohort study of 737 individuals recruited from eleven cardiac centers in the Rhine-Main region in the vicinity of Frankfurt Airport. All patients had an angiographically confirmed acute coronary syndrome diagnosed between July 2013 and November 2018. Individual aircraft noise exposure at the place of residence was calculated using Soundplan software, and exposure to road traffic and railway noise was obtained from noise maps provided by the Hessian State Agency. Data was analyzed by means of Cox regression adjusted for relevant confounders. Recurrent event as non-fatal endpoint was defined as myocardial infarction, stroke, bypass surgery or percutaneous coronary intervention with stent implantation. In addition, all-cause mortality was evaluated.Follow-up data including socioeconomic and confounder information was obtained from 663 (90%) patients covering a mean follow-up period of 42 (range: 1–80) months. Mean Lden aircraft noise exposure was 48.1 dB. Adjusted hazard ratio (HR) for recurrence was 1.24 (95%-CI: 0.97–1.58) per 10 dB increase in Lden aircraft noise exposure. A combined analysis of recurrence and all-cause mortality yielded a HR of 1.31 (95%-CI: 1.03–1.66). Similar HRs were found for Lday and Lnight aircraft noise exposure. HRs for road traffic and railway noise were above unity but less pronounced and not significant.Observed exposure-response associations for aircraft noise were more pronounced than previously observed in population-based cohort studies suggesting that acute coronary heart disease patients are particularly vulnerable to effects from transportation noise. Measures to reduce environmental noise exposure may thus be helpful in improving clinical outcome of patients with coronary heart disease.

Optimized Escape Path Planning for Commercial Aircraft Formations

There is growing interest in commercial aircraft formation flight as a means of reducing both airspace congestion and the carbon footprint of air transportation. Wake vortex surfing has been proven to have significant fuel-saving benefits; however, commercial air transportation has yet to take advantage of these formation benefits due to understandable safety concerns. The realization of these formations requires serious consideration of safety contingencies during closer-in maneuvering of large commercial aircraft. Formation contingency scenarios are much more complex than those of individual aircraft and have not yet been studied in depth. This paper investigates the utility of an optimization modeling approach in generating maneuvering and escape paths for commercial formation aircraft by comparing model-generated paths with pilot-generated escape plans. Three high-altitude commercial aircraft formation scenarios are presented: formation join, formation emergency exit, and formation escape. The model-generated paths are evaluated and compared with pilot-generated escape plans using the author’s pilot expertise. Model results compare well with pilot intuition and are useful in presenting solutions not previously considered, in evaluating separation requirements for improvement of escape path planning, and in confirming the viability of the pilot-generated plans. The novel optimization model formulation presented in this paper is the first model capable of generating exit and escape paths comparable to pilot-generated plans. It is also the first model to incorporate path avoidance of persistent and drifting wake turbulence.