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Journal article(2022)
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Michael J. Scott, W.J.C. Verhagen, M.T. Bieber, Pier Marzocca
In recent decades, the increased use of sensor technologies, as well as the increase in digitalisation of aircraft sustainment and operations, have enabled capabilities to detect, diagnose, and predict the health of aircraft structures, systems, and components. Predictive maintenance and closely related concepts, such as prognostics and health management (PHM) have attracted increasing attention from a research perspective, encompassing a growing range of original research papers as well as review papers. When considering the latter, several limitations remain, including a lack of research methodology definition, and a lack of review papers on predictive maintenance which focus on military applications within a defence context. This review paper aims to address these gaps by providing a systematic two-stage review of predictive maintenance focused on a defence domain context, with particular focus on the operations and sustainment of fixed-wing defence aircraft. While defence aircraft share similarities with civil aviation platforms, defence aircraft exhibit significant variation in operations and environment and have different performance objectives and constraints. The review utilises a systematic methodology incorporating bibliometric analysis of the considered domain, as well as text processing and clustering of a set of aligned review papers to position the core topics for subsequent discussion. This discussion highlights state-of-the-art applications and associated success factors in predictive maintenance and decision support, followed by an identification of practical and research challenges. The scope is primarily confined to fixed-wing defence aircraft, including legacy and emerging aircraft platforms. It highlights that challenges in predictive maintenance and PHM for researchers and practitioners alike do not necessarily revolve solely on what can be monitored, but also covers how robust decisions can be made with the quality of data available.
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In recent decades, the increased use of sensor technologies, as well as the increase in digitalisation of aircraft sustainment and operations, have enabled capabilities to detect, diagnose, and predict the health of aircraft structures, systems, and components. Predictive maintenance and closely related concepts, such as prognostics and health management (PHM) have attracted increasing attention from a research perspective, encompassing a growing range of original research papers as well as review papers. When considering the latter, several limitations remain, including a lack of research methodology definition, and a lack of review papers on predictive maintenance which focus on military applications within a defence context. This review paper aims to address these gaps by providing a systematic two-stage review of predictive maintenance focused on a defence domain context, with particular focus on the operations and sustainment of fixed-wing defence aircraft. While defence aircraft share similarities with civil aviation platforms, defence aircraft exhibit significant variation in operations and environment and have different performance objectives and constraints. The review utilises a systematic methodology incorporating bibliometric analysis of the considered domain, as well as text processing and clustering of a set of aligned review papers to position the core topics for subsequent discussion. This discussion highlights state-of-the-art applications and associated success factors in predictive maintenance and decision support, followed by an identification of practical and research challenges. The scope is primarily confined to fixed-wing defence aircraft, including legacy and emerging aircraft platforms. It highlights that challenges in predictive maintenance and PHM for researchers and practitioners alike do not necessarily revolve solely on what can be monitored, but also covers how robust decisions can be made with the quality of data available.
Low-fidelity fluid–structure interaction model of flexible propeller blades is assessed by means of comparison with high-fidelity aeroelastic results. The low-fidelity model is based on a coupled extended blade-element momentum model and non-linear beam theory which were both implemented in Matlab. High-fidelity fluid–structure interaction analysis is based on coupling commercial computational fluid dynamics and computational structural dynamics codes. For this purpose, Ansys CFX® and Ansys Mechanical® were used. Three different flexible propeller blade geometries are considered in this study: straight, backward swept, and forward swept. The specific backward and forward swept blades are chosen due to their aeroelastic response and its influence on the propulsive performance of the blade while a straight blade was selected in order to serve as a reference. First, the high-fidelity method is validated against experimental data available for the selected blade geometries. Then the high- and low-fidelity methods are compared in terms of integral thrust and breaking power as well as their respective distributions along the blades are compared for different advancing ratios. In a structural sense, the comparison is performed by analyzing the blade bending and torsional deformation. Based on the obtained results, given the simplicity of the low-fidelity method, it can be concluded that the agreement between the two methods is reasonably good. Moreover, an important result of the comparison study is an observation that the advance ratio is no longer a valid measure of similarity in the case of flexible propeller blades and the behavior of such blades can change significantly with changing operating conditions while keeping the advance ratio constant. This observation is supported by both high- and low-fidelity methods.
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Low-fidelity fluid–structure interaction model of flexible propeller blades is assessed by means of comparison with high-fidelity aeroelastic results. The low-fidelity model is based on a coupled extended blade-element momentum model and non-linear beam theory which were both implemented in Matlab. High-fidelity fluid–structure interaction analysis is based on coupling commercial computational fluid dynamics and computational structural dynamics codes. For this purpose, Ansys CFX® and Ansys Mechanical® were used. Three different flexible propeller blade geometries are considered in this study: straight, backward swept, and forward swept. The specific backward and forward swept blades are chosen due to their aeroelastic response and its influence on the propulsive performance of the blade while a straight blade was selected in order to serve as a reference. First, the high-fidelity method is validated against experimental data available for the selected blade geometries. Then the high- and low-fidelity methods are compared in terms of integral thrust and breaking power as well as their respective distributions along the blades are compared for different advancing ratios. In a structural sense, the comparison is performed by analyzing the blade bending and torsional deformation. Based on the obtained results, given the simplicity of the low-fidelity method, it can be concluded that the agreement between the two methods is reasonably good. Moreover, an important result of the comparison study is an observation that the advance ratio is no longer a valid measure of similarity in the case of flexible propeller blades and the behavior of such blades can change significantly with changing operating conditions while keeping the advance ratio constant. This observation is supported by both high- and low-fidelity methods.
