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AI-based exhaust gas temperature

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM) strategies have emerged over recent years and aim at minimizing the aviation maintenance costs and environmental impact by the diagnosis and prognosis of aircraft systems. As the use of data and relevant algorithms is essential to AI-based gas turbine diagnostics, there are different technical, operational, and regulatory challenges that need to be tackled in order for the aeronautical industry to be able to exploit their full potential. In this work, the machine learning (ML) method of the generalised additive model (GAM) is used in order to predict the evolution of an aero engine’s exhaust gas temperature (EGT). Three different continuous synthetic data sets developed by NASA are employed, known as New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS), with increasing complexity in engine deterioration. The results show that the GAM can be predict the evolution of the EGT with high accuracy when using several input features that resemble the types of physical sensors installed in aero gas turbines currently in operation. As the GAM offers good interpretability, this case study is used to discuss the different data attributes a data set needs to have in order to build trust and move towards certifiable models in the future.

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Using simulation to estimate critical paths and survival functions in aircraft turnaround processes

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Electric flight operations for interisland mobility

Several studies have shown that flying electric between the so-called ABC-islands in the Caribbean (i.e., Aruba, Bonaire and Curaçao) is feasible with the upcoming first generation of battery-electric aircraft. This paper presents a real-world case study that deals with the technical and operational characteristics of electric flight in that region. With that purpose, the Aruba Airport Authority (AAA) commissioned this investigation, which involved numerous local stakeholders, such as airlines, energy providers and navigation services. This study involves two commuter electric aircraft under development, aiming to investigate how they fit in the current operational scheme of three local airlines and three conventional aircraft types in terms of technology, capacity, schedule, performance, CO2 emissions and fuel costs. Conclusions indicate that a transition to batter-electric aircraft is feasible with regards to the aforementioned criteria and with the current technology and energy density of batteries.

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Electric flight operations for interisland mobility

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Using STPA in the evaluation of fighter pilots training programs

This paper presents how the application of the STPA method might support the evaluation of fighter pilots training programs and trigger procedural and technological changes. We applied the STPA method by considering the safety constraints documented in the Standard Operating Procedures (SOPs) of a South European Air Force and regard a flight of a two F-16 aircraft formation. In this context, we derived the control actions and feedback mechanisms that are available to the leader pilot during an Aircraft Combat Maneuver (ACM) mission, and we developed the control flow diagram based on the aircraft manuals. We compared the results of each analysis step with the respective flight training program, which is based on a mixed skill and rule-based decision-making, and we examined the role of the feedback mechanisms during multiple safety constraints violations. The analysis showed that: the flight training program under study does not structurally include cases of infringement of multiple safety constraints; the maintenance of some safety constraints are not supported by alerts, or rely on only one human sense; the existing procedures do not refer to the prioritization of pilot actions in cases of violation of multiple safety constraints; operation manuals do not address the cases of possible human performance deterioration when simultaneous information from feedback mechanisms is received. The results demonstrated the benefits of the STPA method, the application of which uncovered various inadequacies in the flight training program studied, some of them related to the F-16 cockpit ergonomics. The analysis lead to recommendations in regard to the amendment of the corresponding fighter pilots training program, and the conduction of further research regarding the aircraft – pilot interaction when multiple safety constraints are violated. The approach presented in this paper can be also followed for the (re)evaluation of flight training schemes in military, civil and general aviation, as well by any human-machine interface intensive domain.

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Using STPA in the evaluation of fighter pilots training programs

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Data mining for aircraft maintenance repair and overhaul (MRO) process optimization

Presentation.

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Data mining for aircraft maintenance repair and overhaul (MRO) process optimization

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From Full Freighters to Belly Cargo Aircraft: Stochastic Analysis of Alternatives for Freight in Schiphol Airport

KLM has revealed the plan to downsize the full-freight cargo fleet in Schiphol Airport, for that reason the company requires to explore the consequences of moving the cargo transported by the full freighters into the bellies of the passenger flights. In this study, the authors analyze the implications of this decision by considering the variability of the load factors and the impact that replacing old aircraft might have. The study addresses how the transition towards the belly operation should impact the current operation of KLM at Schiphol. Our study shows that the replacement of old aircraft with new 787s and 777s will have significant effect on the cargo capacity of the company. The results rise the discussion on future problems to be faced and how to make the transition from full freighter to belly operation.

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From Full Freighters to Belly Cargo Aircraft: Stochastic Analysis of Alternatives for Freight in Schiphol Airport

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The balance between safety and productivity and its relationship with human factors and safety awareness and communication in aircraft manufacturing

Background: This paper presents the findings of a pilot research survey which assessed the degree of balance between safety and productivity, and its relationship with awareness and communication of human factors and safety rules in the aircraft manufacturing environment.Methods: The study was carried out at two Australian aircraft manufacturing facilities where a Likertscale questionnaire was administered to a representative sample. The research instrument included topics relevant to the safety and human factors training provided to the target workforce. The answers were processed in overall, and against demographic characteristics of the sample population.Results: The workers were sufficiently aware of how human factors and safety rules influence their performance and acknowledged that supervisors had adequately communicated such topics. Safety and productivity seemed equally balanced across the sample. A preference for the former over the latter wasassociated with a higher awareness about human factors and safety rules, but not linked with safety communication. The size of the facility and the length and type of employment were occasionally correlated with responses to some communication and human factors topics and the equilibrium between productivity and safety.Conclusion: Although human factors training had been provided and sufficient bidirectional communication was present across the sample, it seems that quality and complexity factors might have influencedthe effects of those safety related practices on the safety-productivity balance for specific parts of the population studied. Customization of safety training and communication to specific characteristics of employees may be necessary to achieve the desired outcomes.

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CPN-simulation methodology for the boarding process of aircraft

The boarding process of an aircraft is one of the identified bottlenecks in the turnaround when aircraft arrives to an airport.

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CPN-simulation methodology for the boarding process of aircraft

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An End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines

Estimating the remaining useful life (RUL) of an asset lies at the heart of prognostics and health management (PHM) of many operations-critical industries such as aviation. Mod- ern methods of RUL estimation adopt techniques from deep learning (DL). However, most of these contemporary tech- niques deliver only single-point estimates for the RUL without reporting on the confidence of the prediction. This practice usually provides overly confident predictions that can have severe consequences in operational disruptions or even safety. To address this issue, we propose a technique for uncertainty quantification (UQ) based on Bayesian deep learning (BDL). The hyperparameters of the framework are tuned using a novel bi-objective Bayesian optimization method with objectives the predictive performance and predictive uncertainty. The method also integrates the data pre-processing steps into the hyperparameter optimization (HPO) stage, models the RUL as a Weibull distribution, and returns the survival curves of the monitored assets to allow informed decision-making. We vali- date this method on the widely used C-MAPSS dataset against a single-objective HPO baseline that aggregates the two ob- jectives through the harmonic mean (HM). We demonstrate the existence of trade-offs between the predictive performance and the predictive uncertainty and observe that the bi-objective HPO returns a larger number of hyperparameter configurations compared to the single-objective baseline. Furthermore, we see that with the proposed approach, it is possible to configure models for RUL estimation that exhibit better or comparable performance to the single-objective baseline when validated on the test sets.

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Search results

Products 127

AI-based exhaust gas temperature

Using simulation to estimate critical paths and survival functions in aircraft turnaround processes

Electric flight operations for interisland mobility

Using STPA in the evaluation of fighter pilots training programs

Data mining for aircraft maintenance repair and overhaul (MRO) process optimization

From Full Freighters to Belly Cargo Aircraft: Stochastic Analysis of Alternatives for Freight in Schiphol Airport

The balance between safety and productivity and its relationship with human factors and safety awareness and communication in aircraft manufacturing

CPN-simulation methodology for the boarding process of aircraft

An End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines

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Products 127

AI-based exhaust gas temperature

Using simulation to estimate critical paths and survival functions in aircraft turnaround processes

Electric flight operations for interisland mobility

Using STPA in the evaluation of fighter pilots training programs

Data mining for aircraft maintenance repair and overhaul (MRO) process optimization

From Full Freighters to Belly Cargo Aircraft: Stochastic Analysis of Alternatives for Freight in Schiphol Airport

The balance between safety and productivity and its relationship with human factors and safety awareness and communication in aircraft manufacturing

CPN-simulation methodology for the boarding process of aircraft

An End-to-End Pipeline for Uncertainty Quantification and Remaining Useful Life Estimation: An Application on Aircraft Engines