ICARUS - Intelligent Communications and Avionics for Robust Unmanned Aerial Systems
http://hdl.handle.net/2117/1077
2024-03-19T06:24:29Z
2024-03-19T06:24:29Z
ATC human factors involved in RPAS contingency management in non-segregated airspace
Reyes Muñoz, María Angélica
Barrado Muxí, Cristina
Pastor Llorens, Enric
Royo Chic, Pablo
http://hdl.handle.net/2117/402118
2024-02-18T21:57:50Z
2024-02-16T15:00:03Z
ATC human factors involved in RPAS contingency management in non-segregated airspace
Reyes Muñoz, María Angélica; Barrado Muxí, Cristina; Pastor Llorens, Enric; Royo Chic, Pablo
The overall approach towards Remotely Piloted Aerial System integration into a non-segregated airspace is that the unmanned vehicles should be able to fit into the current air traffic management system, thus meeting all the technical and regulatory requirements to be treated similar to any other airspace user. Such a requirement implies that unmanned aircraft operations should behave as close as possible to manned aviation or at least generate the most negligible possible negative impact on the system. From the air traffic management point of view, this implies that air traffic controllers should be capable of effectively handling different types of RPAS operating in a nominal state but also when suffering a potential contingency. This paper aims to analyse how air traffic controllers involved in managing unmanned aircraft integration into non-segregated airspace are impacted when an unmanned vehicle suffers a contingency. Participants: Six air traffic controllers were the test subjects, complemented by one RPAS pilot and several pseudo-pilots controlling the simulated manned traffic. The project collected real-time simulation data to develop specific indicators to determine how the controllers’ workload increases while managing complex traffic scenarios, including a single RPAS. Study Method: We conducted exhaustive traffic flight simulations, recreating complex airspace scenarios, including various RPAS types and mission-oriented trajectories. The involved RPAS were subjected to two of the most relevant contingencies: loss of the command-and-control link and engine failure. The experiments were evaluated in different operational scenarios, including using autonomous communication technologies to help air traffic controllers track the RPAS operation. Findings: The results indicate that the air traffic controller’s perception and workload are not affected beyond reason by the introduction of an unmanned aircraft as a new element into the non-segregated airspace, even when that aircraft suffers a contingency. The flight-intent technology increases situational awareness, leading to more efficient and safe airspace management. Additional simulations may need to be performed to evaluate the impact on airspace capacity, safety, and workload when various unmanned vehicles are simultaneously inserted.
2024-02-16T15:00:03Z
Reyes Muñoz, María Angélica
Barrado Muxí, Cristina
Pastor Llorens, Enric
Royo Chic, Pablo
The overall approach towards Remotely Piloted Aerial System integration into a non-segregated airspace is that the unmanned vehicles should be able to fit into the current air traffic management system, thus meeting all the technical and regulatory requirements to be treated similar to any other airspace user. Such a requirement implies that unmanned aircraft operations should behave as close as possible to manned aviation or at least generate the most negligible possible negative impact on the system. From the air traffic management point of view, this implies that air traffic controllers should be capable of effectively handling different types of RPAS operating in a nominal state but also when suffering a potential contingency. This paper aims to analyse how air traffic controllers involved in managing unmanned aircraft integration into non-segregated airspace are impacted when an unmanned vehicle suffers a contingency. Participants: Six air traffic controllers were the test subjects, complemented by one RPAS pilot and several pseudo-pilots controlling the simulated manned traffic. The project collected real-time simulation data to develop specific indicators to determine how the controllers’ workload increases while managing complex traffic scenarios, including a single RPAS. Study Method: We conducted exhaustive traffic flight simulations, recreating complex airspace scenarios, including various RPAS types and mission-oriented trajectories. The involved RPAS were subjected to two of the most relevant contingencies: loss of the command-and-control link and engine failure. The experiments were evaluated in different operational scenarios, including using autonomous communication technologies to help air traffic controllers track the RPAS operation. Findings: The results indicate that the air traffic controller’s perception and workload are not affected beyond reason by the introduction of an unmanned aircraft as a new element into the non-segregated airspace, even when that aircraft suffers a contingency. The flight-intent technology increases situational awareness, leading to more efficient and safe airspace management. Additional simulations may need to be performed to evaluate the impact on airspace capacity, safety, and workload when various unmanned vehicles are simultaneously inserted.
Assistive self-driving car networks to provide safe road ecosystems for disabled road users
Guerrero Ibañez, Juan Antonio
Contreras Castillo,, Juan José
Amezcua Valdovinos, Ismael
Reyes Muñoz, María Angélica
http://hdl.handle.net/2117/402116
2024-02-18T21:57:33Z
2024-02-16T14:52:15Z
Assistive self-driving car networks to provide safe road ecosystems for disabled road users
Guerrero Ibañez, Juan Antonio; Contreras Castillo,, Juan José; Amezcua Valdovinos, Ismael; Reyes Muñoz, María Angélica
Disabled pedestrians are among the most vulnerable groups in road traffic. Using technology to assist this vulnerable group could be instrumental in reducing the mobility challenges they face daily. On the one hand, the automotive industry is focusing its efforts on car automation. On the other hand, in recent years, assistive technology has been promoted as a tool for consolidating the functional independence of people with disabilities. However, the success of these technologies depends on how well they help self-driving cars interact with disabled pedestrians. This paper proposes an architecture to facilitate interaction between disabled pedestrians and self-driving cars based on deep learning and 802.11p wireless technology. Through the application of assistive technology, we can locate the pedestrian with a disability within the road traffic ecosystem, and we define a set of functionalities for the identification of hand gestures of people with disabilities. These functions enable pedestrians with disabilities to express their intentions, improving their confidence and safety level in tasks within the road ecosystem, such as crossing the street.
2024-02-16T14:52:15Z
Guerrero Ibañez, Juan Antonio
Contreras Castillo,, Juan José
Amezcua Valdovinos, Ismael
Reyes Muñoz, María Angélica
Disabled pedestrians are among the most vulnerable groups in road traffic. Using technology to assist this vulnerable group could be instrumental in reducing the mobility challenges they face daily. On the one hand, the automotive industry is focusing its efforts on car automation. On the other hand, in recent years, assistive technology has been promoted as a tool for consolidating the functional independence of people with disabilities. However, the success of these technologies depends on how well they help self-driving cars interact with disabled pedestrians. This paper proposes an architecture to facilitate interaction between disabled pedestrians and self-driving cars based on deep learning and 802.11p wireless technology. Through the application of assistive technology, we can locate the pedestrian with a disability within the road traffic ecosystem, and we define a set of functionalities for the identification of hand gestures of people with disabilities. These functions enable pedestrians with disabilities to express their intentions, improving their confidence and safety level in tasks within the road ecosystem, such as crossing the street.
Domain-driven multiple-criteria decision-making for flight crew decision support tool
Villardi de Montlaur, Adeline de
Delgado Muñoz, Luis
Prats Menéndez, Xavier
http://hdl.handle.net/2117/399665
2024-01-21T19:31:58Z
2024-01-17T10:55:20Z
Domain-driven multiple-criteria decision-making for flight crew decision support tool
Villardi de Montlaur, Adeline de; Delgado Muñoz, Luis; Prats Menéndez, Xavier
During the flight, the crew might consider modifying their planned trajectory, taking into account currently available information, such as an updated weather forecast report or the already accrued amount of delay. This modified planned trajectory translates into changes on expected fuel and flying time, which will impact the airline’s relevant performance indicators leading to a complex multiple-criteria decision-making problem. Pilot3, a project from the Clean Sky Joint Undertaking 2 under European Union’s Horizon 2020 research and innovation programme, aims to develop an objective optimisation engine to assist the crew on this process. This article presents a domain-driven approach for the selection of the most suitable multiple-criteria decision-making methods to be used for this optimisation framework. The most relevant performance indicators, based on airline’s objectives and policies, are identified as: meeting on-time performance, leading to a binary value in a deterministic scenario; and total cost, which can be disaggregated into sub-cost components. The optimisation process consists of two phases: first, Pareto optimal solutions are generated with a multi-objective optimisation method (lexicographic ordering); second, alternative trajectories are filtered and ranked using a combination of multi-criteria decision analysis methods (analytic hierarchy process and VIKOR). A realistic example of use shows the applicability of the process and studies the sensibility of the optimisation framework.
2024-01-17T10:55:20Z
Villardi de Montlaur, Adeline de
Delgado Muñoz, Luis
Prats Menéndez, Xavier
During the flight, the crew might consider modifying their planned trajectory, taking into account currently available information, such as an updated weather forecast report or the already accrued amount of delay. This modified planned trajectory translates into changes on expected fuel and flying time, which will impact the airline’s relevant performance indicators leading to a complex multiple-criteria decision-making problem. Pilot3, a project from the Clean Sky Joint Undertaking 2 under European Union’s Horizon 2020 research and innovation programme, aims to develop an objective optimisation engine to assist the crew on this process. This article presents a domain-driven approach for the selection of the most suitable multiple-criteria decision-making methods to be used for this optimisation framework. The most relevant performance indicators, based on airline’s objectives and policies, are identified as: meeting on-time performance, leading to a binary value in a deterministic scenario; and total cost, which can be disaggregated into sub-cost components. The optimisation process consists of two phases: first, Pareto optimal solutions are generated with a multi-objective optimisation method (lexicographic ordering); second, alternative trajectories are filtered and ranked using a combination of multi-criteria decision analysis methods (analytic hierarchy process and VIKOR). A realistic example of use shows the applicability of the process and studies the sensibility of the optimisation framework.
Explainability of deep reinforcement learning method with drones
Çetin, Ender
Barrado Muxí, Cristina
Pastor Llorens, Enric
http://hdl.handle.net/2117/399125
2024-01-28T04:55:27Z
2024-01-11T09:05:26Z
Explainability of deep reinforcement learning method with drones
Çetin, Ender; Barrado Muxí, Cristina; Pastor Llorens, Enric
Recent advances in artificial intelligence (AI) technology demonstrated that AI algorithms are very powerful as AI models become more complex. As a result, the users and also the engineers who developed the AI algorithms have a hard time explaining how the AI model gives the specific result. This phenomenon is known as "black box" and affects end-users’ confidence in these AI systems. In this research, explainability of deep reinforcement learning is investigated for counter-drone systems. To counter a drone, a deep reinforcement learning method such as double deep Q-network with dueling architecture and prioritized experience replay is proposed. In counter-drone systems, catching the target as soon as possible is expected. Otherwise, the target can be gone in a short time. To understand how the agent performs more quickly and accurately, figures representing rewards, drone locations, crash positions, and the distribution of actions are analyzed and compared. For example, the positions of the drones in a successful episode during training can be analyzed by the actions the agent performed and the rewards in this episode. In addition, the actions agent took in episodes are compared with action frequencies during training and it is seen that at the end of the training, the agent selects the dominant actions throughout the training. However, at the beginning of the training, the distribution of actions is not correlated with the actions selected at the end. The results showed that the agent uses different flight paths by using different actions to catch the target drone in different episodes and different models. Finally, the generation of a saliency map is investigated to identify the critical regions in an input image which influences the predictions made by the DQN agent by evaluating the gradients of the model’s output with respect to both the image and scalar inputs.
2024-01-11T09:05:26Z
Çetin, Ender
Barrado Muxí, Cristina
Pastor Llorens, Enric
Recent advances in artificial intelligence (AI) technology demonstrated that AI algorithms are very powerful as AI models become more complex. As a result, the users and also the engineers who developed the AI algorithms have a hard time explaining how the AI model gives the specific result. This phenomenon is known as "black box" and affects end-users’ confidence in these AI systems. In this research, explainability of deep reinforcement learning is investigated for counter-drone systems. To counter a drone, a deep reinforcement learning method such as double deep Q-network with dueling architecture and prioritized experience replay is proposed. In counter-drone systems, catching the target as soon as possible is expected. Otherwise, the target can be gone in a short time. To understand how the agent performs more quickly and accurately, figures representing rewards, drone locations, crash positions, and the distribution of actions are analyzed and compared. For example, the positions of the drones in a successful episode during training can be analyzed by the actions the agent performed and the rewards in this episode. In addition, the actions agent took in episodes are compared with action frequencies during training and it is seen that at the end of the training, the agent selects the dominant actions throughout the training. However, at the beginning of the training, the distribution of actions is not correlated with the actions selected at the end. The results showed that the agent uses different flight paths by using different actions to catch the target drone in different episodes and different models. Finally, the generation of a saliency map is investigated to identify the critical regions in an input image which influences the predictions made by the DQN agent by evaluating the gradients of the model’s output with respect to both the image and scalar inputs.
Generation of RNP approach flight procedures with an RRT* path-planning algorithm
Sáez García, Raúl
Toratani, Daichi
Mori, Ryota
Prats Menéndez, Xavier
http://hdl.handle.net/2117/398432
2023-12-20T18:31:40Z
2023-12-20T18:26:51Z
Generation of RNP approach flight procedures with an RRT* path-planning algorithm
Sáez García, Raúl; Toratani, Daichi; Mori, Ryota; Prats Menéndez, Xavier
We present a framework capable of generating required navigation performance authorization required approach (RNP AR APCH) procedures by using a combination of the optimal version of the path-planning rapidly-exploring random tree (RRT*) algorithm and Dubins paths. Procedures are generated by taking into account design constraints defined by the international civil aviation organization (ICAO) procedures for air navigation services - aircraft operations (PANS-OPS). The framework is used to compute several approach procedures for two airports in Japan, Kumamoto and Kitakyushu airports. Several feasible procedures are successfully obtained in a low amount of computational time, many of them resembling the actual procedures published in the selected airports. The output of our framework represents a valuable input for procedure designers, who could later refine the obtained results with specific flight-procedure-design software.
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
2023-12-20T18:26:51Z
Sáez García, Raúl
Toratani, Daichi
Mori, Ryota
Prats Menéndez, Xavier
We present a framework capable of generating required navigation performance authorization required approach (RNP AR APCH) procedures by using a combination of the optimal version of the path-planning rapidly-exploring random tree (RRT*) algorithm and Dubins paths. Procedures are generated by taking into account design constraints defined by the international civil aviation organization (ICAO) procedures for air navigation services - aircraft operations (PANS-OPS). The framework is used to compute several approach procedures for two airports in Japan, Kumamoto and Kitakyushu airports. Several feasible procedures are successfully obtained in a low amount of computational time, many of them resembling the actual procedures published in the selected airports. The output of our framework represents a valuable input for procedure designers, who could later refine the obtained results with specific flight-procedure-design software.
Enriched finite element approach for modeling discontinuous electric field in multi-material problems
Narváez Muñoz, Christian
Hashemi, Mohammad Reza
Ryzhakov, Pavel
Pons Prats, Jordi
Owen, Herbert
http://hdl.handle.net/2117/393476
2023-09-17T22:43:01Z
2023-09-14T08:06:44Z
Enriched finite element approach for modeling discontinuous electric field in multi-material problems
Narváez Muñoz, Christian; Hashemi, Mohammad Reza; Ryzhakov, Pavel; Pons Prats, Jordi; Owen, Herbert
This work is devoted to developing an efficient and robust technique for accurately capturing the electric field in multi-material problems. The formulation is based on the finite element method enriched by the introduction of hat-type shape function within the elements crossed by the material interface. The peculiar feature of the proposed method consists of direct employment of the hat-function that requires solely one additional degree-of-freedom per cut element for capturing the discontinuity in the electric potential gradient and, thus, the electric field. This additional degree-of-freedom is subsequently statically condensed element-wise prior to the assembly of the discrete global system. As a consequence, the graph of the system matrix remains the same as that of the standard finite element method. In order to guarantee the robust performance of the proposed method for a wide range of electrical material property ratios, it also accounts for the possible discontinuities among the neighboring cut elements that arise due to employing additional degrees-of-freedom fully local to the element. The method is tested using several examples solved on structured and unstructured grids. The proposed approach constitutes a basis for enriched FEM applicable to a wide range of electromagnetic problems.
2023-09-14T08:06:44Z
Narváez Muñoz, Christian
Hashemi, Mohammad Reza
Ryzhakov, Pavel
Pons Prats, Jordi
Owen, Herbert
This work is devoted to developing an efficient and robust technique for accurately capturing the electric field in multi-material problems. The formulation is based on the finite element method enriched by the introduction of hat-type shape function within the elements crossed by the material interface. The peculiar feature of the proposed method consists of direct employment of the hat-function that requires solely one additional degree-of-freedom per cut element for capturing the discontinuity in the electric potential gradient and, thus, the electric field. This additional degree-of-freedom is subsequently statically condensed element-wise prior to the assembly of the discrete global system. As a consequence, the graph of the system matrix remains the same as that of the standard finite element method. In order to guarantee the robust performance of the proposed method for a wide range of electrical material property ratios, it also accounts for the possible discontinuities among the neighboring cut elements that arise due to employing additional degrees-of-freedom fully local to the element. The method is tested using several examples solved on structured and unstructured grids. The proposed approach constitutes a basis for enriched FEM applicable to a wide range of electromagnetic problems.
CO2 and non-CO2 balanced environmental scores module for flight performance evaluation and optimisation
Middel, Jan
Sutopo, Kinanthi
Heesbeen, Bart
Verbeek, René
van den Dungen, Nick
Sáez García, Raúl
Prats Menéndez, Xavier
Riccio, Angelo
http://hdl.handle.net/2117/390836
2023-09-10T09:41:02Z
2023-07-14T08:26:24Z
CO2 and non-CO2 balanced environmental scores module for flight performance evaluation and optimisation
Middel, Jan; Sutopo, Kinanthi; Heesbeen, Bart; Verbeek, René; van den Dungen, Nick; Sáez García, Raúl; Prats Menéndez, Xavier; Riccio, Angelo
The SESAR2020 exploratory research (ER4) programme CREATE (Grant 890898) developed a climate and weather aware Concept of Operations (ConOps) which encompasses a multi-aircraft 4D trajectory optimisation framework, which utilises a CO2 and non-CO2 balanced Environmental Scores Module (ESM) for the en-route flight phase. The ESM provides a computational method to evaluate the “greenness” of aircraft trajectories. Some components related to the internal ESM scoring are based on expert judgement, which is in line with the technology readiness level (TRL) 1 of the solution. Fast-time simulations were performed to demonstrate the proof-of-concept of the ESM in a multi-aircraft tactical optimisation scenario in the North-Atlantic region. The results show that, because of the simplicity of the metric, the ESM could be well used for trajectory optimisation and tactical replanning, and most likely as well as flight and ATC sector environmental performance evaluations.
2023-07-14T08:26:24Z
Middel, Jan
Sutopo, Kinanthi
Heesbeen, Bart
Verbeek, René
van den Dungen, Nick
Sáez García, Raúl
Prats Menéndez, Xavier
Riccio, Angelo
The SESAR2020 exploratory research (ER4) programme CREATE (Grant 890898) developed a climate and weather aware Concept of Operations (ConOps) which encompasses a multi-aircraft 4D trajectory optimisation framework, which utilises a CO2 and non-CO2 balanced Environmental Scores Module (ESM) for the en-route flight phase. The ESM provides a computational method to evaluate the “greenness” of aircraft trajectories. Some components related to the internal ESM scoring are based on expert judgement, which is in line with the technology readiness level (TRL) 1 of the solution. Fast-time simulations were performed to demonstrate the proof-of-concept of the ESM in a multi-aircraft tactical optimisation scenario in the North-Atlantic region. The results show that, because of the simplicity of the metric, the ESM could be well used for trajectory optimisation and tactical replanning, and most likely as well as flight and ATC sector environmental performance evaluations.
CREATE - D5.2: Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions - Exercise Results
Sáez García, Raúl
Cabrera Ramírez, Bryan Gustavo
Melgosa Farrés, Marc
Prats Menéndez, Xavier
http://hdl.handle.net/2117/390834
2023-09-10T01:27:32Z
2023-07-14T08:12:59Z
CREATE - D5.2: Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions - Exercise Results
Sáez García, Raúl; Cabrera Ramírez, Bryan Gustavo; Melgosa Farrés, Marc; Prats Menéndez, Xavier
This report is the deliverable “D5.2 - Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions” of the H2020 SESAR CREATE project. The purpose of this document is to provide the exercise results of the “proof-of-concept” exercise of the CREATE concept of operations (CONOPS) and its solutions (SOL) developed under the previous work packages: • CREATE-SOL-1: Multi-scale multi-pollutant air quality system (AQS); • CREATE-SOL-2: Framework for multi-aircraft environmentally-scored weather-resilient optimized 4D-trajectories in the flight execution phase, WAAP = Weather Avoidance for extended air traffic control (ATC) planning. • CREATE-SOL-3: CO2 and non-CO2 balanced environmental scores module. The main exercise objective was to test the integrated concept of the various computational modules related to the CREATE solutions, and to investigate if the solutions provide operational benefits for the following use-cases; • TMA Naples ¿ reduced local air quality (LAQ) impacts and efficient thunderstorm evasion; • En-Route North-Atlantic tracks extending into the European Civil Aviation Conference (ECAC) area ¿ reduced environmental impacts in terms of CO2 and non-CO2 combined metric in climate sensitive areas (CSA) related to contrail formation regions (CFR), and efficient contrail and thunderstorm evasion. The methodology for the exercise was provided in the exercise plan, i.e. “D5.1 - software design for validation scenarios execution”.[4] The exercises were set up to assess the solutions for maturity level TRL1.
2023-07-14T08:12:59Z
Sáez García, Raúl
Cabrera Ramírez, Bryan Gustavo
Melgosa Farrés, Marc
Prats Menéndez, Xavier
This report is the deliverable “D5.2 - Procedures validation identifying potential benefits and risks and stakeholders implementation suggestions” of the H2020 SESAR CREATE project. The purpose of this document is to provide the exercise results of the “proof-of-concept” exercise of the CREATE concept of operations (CONOPS) and its solutions (SOL) developed under the previous work packages: • CREATE-SOL-1: Multi-scale multi-pollutant air quality system (AQS); • CREATE-SOL-2: Framework for multi-aircraft environmentally-scored weather-resilient optimized 4D-trajectories in the flight execution phase, WAAP = Weather Avoidance for extended air traffic control (ATC) planning. • CREATE-SOL-3: CO2 and non-CO2 balanced environmental scores module. The main exercise objective was to test the integrated concept of the various computational modules related to the CREATE solutions, and to investigate if the solutions provide operational benefits for the following use-cases; • TMA Naples ¿ reduced local air quality (LAQ) impacts and efficient thunderstorm evasion; • En-Route North-Atlantic tracks extending into the European Civil Aviation Conference (ECAC) area ¿ reduced environmental impacts in terms of CO2 and non-CO2 combined metric in climate sensitive areas (CSA) related to contrail formation regions (CFR), and efficient contrail and thunderstorm evasion. The methodology for the exercise was provided in the exercise plan, i.e. “D5.1 - software design for validation scenarios execution”.[4] The exercises were set up to assess the solutions for maturity level TRL1.
Methodological framework for a deeper understanding of airline profit cycles in the context of disruptive exogenous impacts
Renold, Manuel
Vollenweider, Janik
Mijovic, Nemanja
Kuljanin, Jovana
Kalic, Milica
http://hdl.handle.net/2117/389769
2023-07-02T22:31:14Z
2023-06-27T08:02:37Z
Methodological framework for a deeper understanding of airline profit cycles in the context of disruptive exogenous impacts
Renold, Manuel; Vollenweider, Janik; Mijovic, Nemanja; Kuljanin, Jovana; Kalic, Milica
This paper combines the k-means clustering method in combination with PCA and the system dynamic modeling approach to derive a better insight into the behavior of airline profitability during the time span of 1995 until 2020. The model includes various explanatory variables that capture different aspects of airline economic and operational metrics, whose fluctuations may affect the airline profitability. By forecasting these exogenous variables, the system dynamic model is used to predict airline profitability through 2025 and answer the question of whether the US airline industry will return to its pre-COVID 19 pandemic state. The latter research question can be agreed with, as the effect of introducing a fourth dimension derived from Principal Component Analysis (PCA) to sufficiently cover the variation within the dataset during the years of COVID-19 pandemic diminishes towards the end of the forecast period. Furthermore, the key measures from PCA imply that under the assumption of continuous growth and a non-exogenous shock, future years will not cluster in past years. The six different clusters from 2019 to 2025 showed how the system stays in a certain state for a few years and then drifts further to a new state. There are only a few variables that change to transfer from one cluster to the next.
2023-06-27T08:02:37Z
Renold, Manuel
Vollenweider, Janik
Mijovic, Nemanja
Kuljanin, Jovana
Kalic, Milica
This paper combines the k-means clustering method in combination with PCA and the system dynamic modeling approach to derive a better insight into the behavior of airline profitability during the time span of 1995 until 2020. The model includes various explanatory variables that capture different aspects of airline economic and operational metrics, whose fluctuations may affect the airline profitability. By forecasting these exogenous variables, the system dynamic model is used to predict airline profitability through 2025 and answer the question of whether the US airline industry will return to its pre-COVID 19 pandemic state. The latter research question can be agreed with, as the effect of introducing a fourth dimension derived from Principal Component Analysis (PCA) to sufficiently cover the variation within the dataset during the years of COVID-19 pandemic diminishes towards the end of the forecast period. Furthermore, the key measures from PCA imply that under the assumption of continuous growth and a non-exogenous shock, future years will not cluster in past years. The six different clusters from 2019 to 2025 showed how the system stays in a certain state for a few years and then drifts further to a new state. There are only a few variables that change to transfer from one cluster to the next.
An enriched finite elements approach for multi-phase microsystems
Narváez Muñoz, Christian
Hashemi, Mohammad Reza
Ryzhakov, Pavel
Pons Prats, Jordi
Martí, Julio Marcelo
http://hdl.handle.net/2117/389728
2023-09-10T12:20:39Z
2023-06-23T16:27:47Z
An enriched finite elements approach for multi-phase microsystems
Narváez Muñoz, Christian; Hashemi, Mohammad Reza; Ryzhakov, Pavel; Pons Prats, Jordi; Martí, Julio Marcelo
This study presents an E-FEM/L-S approach for modeling fluid-fluid inter-face deformation in microsystems under electric fields. The approach treats the interface as a zero-thickness boundary and precisely models discontinuities in pressure and elec-tric fields. Numerical results show improved accuracy on coarser meshes compared to conventional methods. The proposed model is useful for problems without guaranteed symmetry of revolution and can efficiently analyze fundamental aspects of multi-phase microsystems.
2023-06-23T16:27:47Z
Narváez Muñoz, Christian
Hashemi, Mohammad Reza
Ryzhakov, Pavel
Pons Prats, Jordi
Martí, Julio Marcelo
This study presents an E-FEM/L-S approach for modeling fluid-fluid inter-face deformation in microsystems under electric fields. The approach treats the interface as a zero-thickness boundary and precisely models discontinuities in pressure and elec-tric fields. Numerical results show improved accuracy on coarser meshes compared to conventional methods. The proposed model is useful for problems without guaranteed symmetry of revolution and can efficiently analyze fundamental aspects of multi-phase microsystems.