On the Potential of Extending Aircraft Service Time Using Load Monitoring

The entire aircraft industry is facing major challenges due to the formulated targets to reduce environmental emissions. For decision-makers, it is therefore of great importance to be able to compare the environmental impact of aircrafts. This includes the impact assessment of different aircraft-cabin configurations. Based on this motivation, this paper proposes a dynamic method for calculating those environmental impacts. To ensure a straightforward application, the method allows for the cabin configuration with the main cabin components. In addition, a specific mission profile can be defined and is considered in the calculations. The method follows the standardized life-cycle assessment framework. The first application of the method showed that there were large differences in the environmental impacts depending on the cabin configuration and that airlines can contribute to the achievement of sustainability goals with optimized cabin layouts.

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“…The total flight hours (t Li f e ) are further set by the user. For this purpose, reference values of 60,000 flight hours can be used [68].…”

Section: Calculation Of Fuel Consumption and Massmentioning

confidence: 99%

Method to Model the Environmental Impacts of Aircraft Cabin Configurations during the Operational Phase

et al. 2023

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“…The research showed that an average of 100 aircraft accidents occur annually due to material fatigue, of which 18 are a direct consequence of the material fatigue of metal parts. Pfingstl et al [17] proposed a fatigue damage index as a motivation for predicting aircraft decommissioning; they chose material fatigue based on the IATA's best industry practices for aircraft decommissioning [18]. Material fatigue is primarily dictated by the amplitude and frequency of the load acting on the observed part and environmental conditions.…”

Section: The Problem With Implementing Phm In Light Aircraft Maintenancementioning

confidence: 99%

Predicting the Remaining Useful Life of Light Aircraft Structural Parts: An Expert System Approach

Gerhardinger,

Domitrović,

Krajček Nikolić

et al. 2023

Aerospace

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This paper introduces an expert system approach for predicting the remaining useful life (RUL) of light aircraft structural components by analyzing operational and maintenance records. The expert system consists of four modules: knowledge acquisition, knowledge base, inference, and explanation. The knowledge acquisition module retrieves data from mandatory records, such as aircraft logbooks and mass and balance sheets. The knowledge base stores specific remaining useful lives (SRULs) for different load profiles that are determined using numerical strength analysis. The inference module utilizes the Palmgren-Miner rule to estimate the accumulated fatigue damage of the structural component based on the input data and the knowledge base. Lastly, the explanation module links the accumulated damage to the maintenance program and suggests the appropriate maintenance action. The Cessna 172R main landing gear leg is utilized as a case study, demonstrating the variance of RUL depending on the operating conditions. The objective of this approach is to enhance light aircraft maintenance decision making and advance operational safety.

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“…The integration of advanced digital tools, notably sophisticated simulation and analysis techniques, has bolstered the aviation industry's capacity to develop and implement damage-tolerant designs. This transformative shift empowers engineers and decision makers to conduct improved assessments of structural responses to diverse stress scenarios, enabling the creation of aircraft that can resiliently manage potential damage while upholding stringent airworthiness standards [6]. In this context of airworthiness, the impact of the LOV rule has been substantial.…”

Section: Introductionmentioning

confidence: 99%

“…The continuous stream of data from embedded sensors within the aircraft structure allows for ongoing monitoring, enabling precise and responsive adjustments to LOV parameters. This real-time adaptability ensures that operational limits are not only accurately defined but also continually refined based on the actual structural conditions of the aircraft, thereby optimizing safety margins and contributing to sustained airworthiness throughout the aircraft's operational life [6].…”

Section: Introductionmentioning

confidence: 99%

Aircraft Structural Design and Life-Cycle Assessment through Digital Twins

Tavares,

Ribeiro,

Ribeiro

et al. 2024

Designs

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Numerical modeling tools are essential in aircraft structural design, yet they face challenges in accurately reflecting real-world behavior due to factors like material properties scatter and manufacturing-induced deviations. This article addresses the potential impact of digital twins on overcoming these limitations and enhancing model reliability through advanced updating techniques based on machine learning. Digital twins, which are virtual replicas of physical systems, offer a promising solution by integrating sensor data, operational inputs, and historical records. Machine learning techniques enable the calibration and validation of models, combining experimental inputs with simulations through continuous updating processes that refine digital twins, improving their accuracy in predicting structural behavior and performance throughout an aircraft’s life cycle. These refined models enable real-time monitoring and precise damage assessment, supporting decision making in diverse contexts. By integrating sensor data and updating techniques, digital twins contribute to improved design and maintenance operations by providing valuable insights into structural health, safety, and reliability. Ultimately, this approach leads to more efficient and safer aviation operations, demonstrating the potential of digital twins to revolutionize aircraft structural analysis and design. This article explores various advancements and methodologies applicable to structural assessment, leveraging machine learning tools. These include the utilization of physics-informed neural networks, which enable the handling of diverse uncertainties. Such approaches empower a more informed and adaptive strategy, contributing to the assurance of structural integrity and safety in aircraft structures throughout their operational life.

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On the Potential of Extending Aircraft Service Time Using Load Monitoring

Cited by 8 publications

References 23 publications

Method to Model the Environmental Impacts of Aircraft Cabin Configurations during the Operational Phase

Method to Model the Environmental Impacts of Aircraft Cabin Configurations during the Operational Phase

Predicting the Remaining Useful Life of Light Aircraft Structural Parts: An Expert System Approach

Aircraft Structural Design and Life-Cycle Assessment through Digital Twins

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