Search Results (13)

Long landings can reduce runway utilization and increase the probability of runway incursions and excursions. Previous studies on long landings often lacked support from actual operational data and primarily relied on event-triggering logic established by airlines for parameter exceedance detection and retrospective analysis. In response, a comprehensive risk prediction framework for aircraft long landings, supported by Quick Access Recorder (QAR) data, was constructed. The framework includes a data analysis pipeline, a sequence prediction model, and performance evaluation metrics for accident warning efficiency. Specifically, approximately 3 million rows of real QAR data were collected, and reasonable landing intervals were extracted based on pilots’ correct landing sightlines, attention allocation, and actual visual scenarios at departure heights. Gradient Boosting Decision Trees (GBDT) were employed to develop a method for extracting landing interval feature data, based on monitored parameters and ranges of landing distance. Additionally, the GBDT-Informer long-sequence time series prediction model was developed to forecast landing distance, accompanied by the construction of effective metrics for evaluating prediction performance. The results indicate that the GBDT-Informer model effectively models the temporal dimensions of landing intervals, accurately predicting ground speed (GS), radio altitude (RALT), and landing distance sequences. Compared to other prediction models, the GBDT-Informer model consistently achieved the smallest RMSE, MAE, and MAPE values, demonstrating high prediction accuracy. This predictive framework allows for the analysis of the coupling relationships among multiple parameters in flight data and their interrelations with exceedance anomalies. The findings can be applied in actual flight landings to promptly assess whether landing distances exceed limits, providing quick references for flight crews during landing or go-around decisions, thereby enhancing operational safety margins during the landing phase. Full article

Runway skid resistance is crucial for the safety of aircrafts. Despite being internationally regulated, investigation reports published by the Australian Transport Safety Bureau and the US National Transportation Safety Board indicate that 4.9–22% of runway excursion accidents are related to insufficient friction, or to friction overestimation. Consequently, based on this review of friction physics, aircraft accident reports, international runway surface regulation, and aircraft braking performance regulation, it was concluded that significant improvement in the management of runway surface characteristics can be achieved. Areas for potential improvement in the current systems for aircraft skid resistance include gaps in the operational reporting of prevailing runway contamination, as well as friction and surface texture measurement and interpretation protocols. Furthermore, aircraft braking performance regulations are not related to actual runway surface friction levels, resulting in reportedly good runways being found to provide inadequate aircraft skid resistance in certain conditions. Recommendations include improvements in the management of runway friction and texture measurement and analysis during pavement design, and through the service life of the pavement surfaces. Finally, the basis of an improved international runway surface engineering design and management system is outlined. Recommendations can reduce the risk of aircraft skidding accidents in the future. Full article

Runway Safety Assistant Foreseeing Excursions (RUNSAFE) is a complete embedded system solution, that predicts a potential runway overrun of a civil aviation aircraft during takeoff and landing. This work examines the feasibility of such a system, through the algorithms and computations that predict the overruns. The system executes both static and dynamic calculations, with the former being dependent on and the latter independent to the user’s inputs. Their outcomes and the runway’s length are compared in real time to assess if the process will end up in an overrun. All inputs are specifically selected to either be available to the pilots or be retrieved from the existing avionics systems of the cockpit. A performance evaluation is conducted on both static and dynamic calculations, and metrics unveil the accuracy of the predictions and the time needed to converge to a reliable result. The solution is adapted for a Boeing 737-800 aircraft with CFM56-7B engines, but the calculations also apply for similar aircraft equipped with tricycle landing gear and turbofan engines, namely the whole Boeing 737 family, the Airbus A320 family, etc. The system is aligned with current standards and certification specifications, where applicable. Full article

The Quick Access Recorder (QAR), as an onboard device used for monitoring and recording flight parameters, has been extensively installed on various types of aircraft. Recently, there has been a significant focus on studying the typical flight safety event of runway excursions based on QAR data. However, there is limited research that combines the analysis of runway excursion risks with flight operations, and there is also a scarcity of studies that divide the investigation of the landing phase into multiple key stages. In this paper, we propose a comparative analysis of operational characteristics and risks associated with runway excursions from the perspective of operational styles. A total of 2087 flights were classified on the basis of touchdown distance, taxiing distance, and magnetic heading changes and were divided into three styles based on these indicators. Subsequently, we analyze flight operations and attitudes at five key stages: runway threshold, flare, speed brake deployment, touchdown, and reverse thrust activation. Furthermore, we employ the selection criteria of pilot proficiency levels to filter out standard operational curves. The curve similarity is used to compare the difference between the actual operating curves and the standard curves. Finally, we employ typical correlation analysis to explore the relationship between touchdown distance and operational variances. The findings indicate that Style 1 pilots exhibit the lowest probability of runway excursions, yet their maneuvers potentially elevate the risk of hard landing events. Full article

Over the years, Global Reporting Format (GRF) was the first major change in the approach to evaluate runway conditions. The greatest impulse for this new regulation were incidents and accidents related mainly to runway excursions that occurred because of unfavorable weather conditions, when not only aircraft and different airport facilities but also human health and lives suffered. To better understand these changes, their advantages and their disadvantages, as well as the challenges that arose, an expert survey was carried out with duty officers of Polish airports, who directly made an assessment of runway conditions. Beside strengths of the GRF approach, research results show its weaknesses and uncertainties, especially when using the Runway Condition Assessment Matrix. In addition, in the article are presented a brief GRF description together with comparison with the previous reporting system and a discussion about air accident statistics related to a runway excursion, as well as a description and discussion of one selected air incident that took place in Poland. Full article

Pilots typically implement the go-around protocol to avoid landings that are hazardous due to wind shear, runway excursions, or unstable approaches. Despite its rarity, it is essential for safety. First, in this study, we present three Dynamic Ensemble Selection (DES) frameworks: Meta-Learning for Dynamic Ensemble Selection (META-DES), Dynamic Ensemble Selection Performance (DES-P), and K-Nearest Oracle Elimination (KNORAE), with homogeneous and heterogeneous pools of machine learning classifiers as base estimators for the prediction of aircraft go-around in wind shear (WS) events. When generating a prediction, the DES approach automatically selects the subset of machine learning classifiers which is most probable to perform well for each new test instance to be classified, thereby making it more effective and adaptable. In terms of Precision (86%), Recall (83%), and F1-Score (84%), the META-DES model employing a pool of Random Forest (RF) classifiers outperforms other models. Environmental and situational factors are subsequently assessed using SHapley Additive exPlanations (SHAP). The wind shear magnitude, corridor, time of day, and WS altitude had the greatest effect on SHAP estimation. When a strong tailwind was present at low altitude, runways 07R and 07C were highly susceptible to go-arounds. The proposed META-DES with a pool of RF classifiers and SHAP for predicting aircraft go-around in WS events may be of interest to researchers in the field of air traffic safety. Full article

Poor braking performance on runways during winter is one of the most significant factors causing runway excursions. The International Civil Aviation Organization (ICAO) proposed a standardized method, named the Global Reporting Format (GRF), to establish runway surface conditions based on human observers. The GRF includes the description of most winter conditions. This work aimed at reproducing the GRF winter conditions in the laboratory, and to monitor the effect of the surface conditions, both without surface treatment and with surface treatment using liquid runway de-icing products (RDP) in both de-icing and anti-icing modes, using the British Pendulum Tester (BPT). The reproduction of the GRF winter conditions was possible in the laboratory since the BPT results correlated well with the GRF ratings. The worst conditions retained snow on ice. Wet conditions obtained with water and RDPs (potassium formate KFO, potassium acetate KAC and hybrid glycol-KAC HYB) behave similarly, indicating that RDPs alone on a runway for prevention are not any more dangerous than just water. The range from wet to dry, equivalent to a British Pendulum Number (BPN) from ~40 to ~50, was considered as good conditions on the runway. All the RDPs tested in the study improved the BPN from untreated conditions. In most of the conditions, the RDPs improved the BPN to values in the range of favorable conditions. KFO and KAC reacted almost in the same way for each condition. However, the HYB was better in conditions with ice. The obtained results demonstrated that simulated laboratory winter conditions could be used to determine the efficiency of RDPs in both de-icing and anti-icing modes. Full article

Radar measurements are inherently affected by various meteorological and non-meteorological factors that may lead to a degradation of their quality, and the unwanted effects are also transferred into composites, i.e., overlapping images from different radars. The paper was aimed at answering the research question whether we could create ‘cleaner’ radar composites without disturbing features, and if yes, how the operational practice could take advantage of the improved results. To achieve these goals, the qRad and qPrec software packages, based on the concept of quality indices, were used. The qRad package estimates the true quality of the C-band radar volume data using various quality indices and attempts to correct some of the adverse effects on the measurements. The qPrec package uses a probabilistic approach to estimate precipitation intensity, based on heterogeneous input data and quality-based outputs of the qRad software. The advantages of the qRad software are improved radar composites, which offer benefits, among others, for aviation meteorology. At the same time, the advantages of the qPrec software are manifested through improved quantitative precipitation estimation, which can be translated into hydrological modeling or climatological precipitation mapping. Beyond this, the developed software indirectly contributes to sustainability and environmental protection—for instance, by enabling fuel savings due to the more effective planning of flight routes or avoiding runway excursions due to information on the increased risk of aquaplaning. Full article

Rapid exit taxiways enhance runway operational capacities by means of reducing the runway occupancy times of aircraft. The selection of rapid exit taxiway locations is important to achieve the optimum runway capacity. This paper presents a methodology for locating rapid exits based on excursion risk. Considering the level of severity and frequency of historical runway-related accidents and emerging use of rapid exit taxiways in the future, this study explores the associated veer-off risk at rapid exits. The proposed methodology estimates veer-off risk using three successive steps such as event probability, location probability, and severity estimation. An existing logistic regression model developed for landing overrun probability estimation is adapted for the exit taxiway facility to estimate event probability. Aircraft touchdown speed, deceleration, and runway criticality factor are the important operational parameters of this model adaptation. The aircraft turn path radius and kinetic energy at the time of veer-off are used to estimate the respective location probabilities and accident severities. As the sample analysis proves, the associated veer-off risk increases when the exits are closer to the runway threshold. The paper recommends wider taxiways and larger taxiway radii to compensate for increasing veer risks. The methodology helps for planning risk-based rapid exit taxiways for varying design, operational, and weather conditions. Full article

Runway excursions are the main risk for runway safety: operational protection areas mitigate the effects of events classified as veer-off, overrun, and undershoot. This paper presents a methodology for the quantitative risk assessment of runway veer-off in an international airport whose name will not be revealed for privacy reasons. The proposed methodology is based on similar principles adopted in other aviation risk analyses. The Real Level of Safety (RLS) related to the veer-off accident was calculated through the implementation of a retrospective analysis that permits to define a frequency model, a location model and a consequence model. Instead, Target Level of Safety (TLS) was defined through the risk matrix and acceptability criteria present in the International Civil Aviation Organization (ICAO) Safety Management Manual. Finally, the risk of veer-off accidents in the airport under evaluation was determined by using primary data provided by the airport management body. Risk values were calculated in more than 1300 points around the runway and they were used to assess the current level of safety. The authors present a risk map that allows identifying the areas in the strip with the highest risk of a veer-off accident. The obtained results demonstrate that the developed methodology represents a useful tool to define TLS and to assess whether infrastructural and operational modification need to obtain the required level of safety. Full article

The exponential increase in aviation activity and air traffic in recent decades has raised several public health issues. One of the critical public health concerns is runway safety and the increasing demand for airports without accidents. In addition to threatening human lives, runway accidents are often associated with severe environmental and pollution consequences. In this study, a three-step approach is used for runway risk assessment considering probability, location, and consequences of accidents through advanced statistical methods. This study proposes novel models for the implementation of these three steps in Iran. Data on runway excursion accidents were collected from several countries with similar air accident rates. The proposed models empower engineers to advance an accurate assessment of the accident probability and safety assessment of airports. For in-service airports, it is possible to assess existing runways to remove obstacles close to runways if necessary. Also, the proposed models can be used for preliminary evaluations of developing existing airports and the construction of new runways. Full article

Aircraft maintenance has been identified as a key point of concern within many high-risk areas of aviation; still being a casual/contributory factor in a number of accidents and serious incidents in commercial air transport industry. The purpose of this study is to review and analyse the aircraft maintenance-related accidents and serious incidents which occurred between 2003 and 2017, to provide a better understanding of the causal and contributory factors. To achieve this, a dataset of maintenance-related accidents and serious incidents was compiled and then qualitatively analysed by thematic analysis method. Coding these events by using NVivo software enabled the development of a taxonomy, MxFACS. The coded output was then evaluated by subject matter experts, and an inter-rater concordance value determined to demonstrate the rigour of the research process. Subsequently, the events were evaluated in terms of their relationship to known accident categories such as loss of control, runway excursions. The most frequent maintenance event consequences were found to be runway excursions and air turnbacks, with the second level categories being related to failures in engine and landing gear systems. The greatest maintenance factor issues were ‘inadequate maintenance procedures’ and ‘inspections not identifying defects’. In terms of fatalities, ‘collision events’ were the most prominent consequence, ‘engine-related events’ were the most significant event, and ‘inadequate maintenance procedures’ were the most concerning maintenance factor. The study’s findings may be used in conjunction with existing risk analysis methodologies and enable the stakeholders to develop generic or customised bowties. This may identify the existing barriers in the system as well as weaknesses which will enable the development of mitigation strategies on both organisational and industry-wide levels. Full article

The Single Europe Sky Air Traffic Management Research (SESAR) program develops and implements innovative technological and operational solutions to modernize European air traffic management and to eliminate the negative environmental impacts of aviation activity. This article presents our developments within the SESAR Solution “Safety Support Tools for Avoiding Runway Excursions”. This SESAR Solution aims to mitigate the risk of runway excursion, to optimize airport operation management by decreasing the number of runway inspections, to make chemical treatment effective with respect to the environment, and to increase resilience, efficiency and safety in adverse weather situations. The proposed approach is based on the enhancement of runway surface condition awareness by integrating data from various sources. Dangerous windy conditions based on Lidar measurements are also discussed as another relevant factor in relation to runway excursions. The paper aims to explore four different data mining methods to obtain runway conditions from the available input data sources, examines their performance and discusses their pros and cons in comparison with a rule-based algorithm approach. The output of the SESAR Solution is developed in compliance with the new Global Reporting Format of the International Civil Aviation Organization for runway condition description to be valid from 2020. This standard is expected to provide concerned stakeholders with more precise information to enhance flight safety and environmental protection. Full article