WL
Wim Lammen
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6 records found
1
Conference paper
(2022)
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Johan Kos, John Posada-Duque, Bram Peerlings, Nora ben Salah, Nanette Lim, Wim Lammen, Inna Stepchuk, Elisabeth van der Sman, Mar Palmeros-Parada
This paper investigates green hydrogen and bio-based sustainable aviation fuels, including their production technology and feedstock, in combination with Clean Sky 2 propulsion technologies and novel hydrogen-powered propulsion technologies. The impact that these alternative aviation fuels and propulsion technologies can have on greenhouse gas emissions is identified and the demand for alternative aviation fuels is compared with their expected availability, both until 2050.
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This paper investigates green hydrogen and bio-based sustainable aviation fuels, including their production technology and feedstock, in combination with Clean Sky 2 propulsion technologies and novel hydrogen-powered propulsion technologies. The impact that these alternative aviation fuels and propulsion technologies can have on greenhouse gas emissions is identified and the demand for alternative aviation fuels is compared with their expected availability, both until 2050.
Journal article
(2020)
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Mengmeng Zhang, Nathalie Bartoli, Aidan Jungo, Wim Lammen, Erik Baalbergen, Mark Voskuijl
In the modern aircraft design process numerical simulation is one of the key enablers. However, computational time increases exponentially with the level of fidelity of the simulation. In the EU Horizon2020 project AGILE different aircraft design analysis tools relative to different levels of fidelity are used. One of the challenges is to reduce the computational time - e.g. to facilitate an efficient optimization process - by processing the analysis data of various fidelity levels in a global surrogate model. This paper focuses on fusion of data sets via an automatic iterative process embedded in the collaborative multidisciplinary analysis (MDA) chains as applied in AGILE. Surrogate modeling techniques are applied, taking into account the optimal sampling and the corresponding fidelities of the samples. This paper will detail the different steps of the proposed collaborative approach. As a test case handling qualities analysis of the AGILE reference conventional aircraft is performed, by fusing the computed aerodynamic coefficients and derivatives. A full set of aerodynamic data computed either with different levels of fidelity or with only a low-fidelity tool has been derived and evaluated. The data set with multiple levels of fidelity significantly improved the accuracy of the flight performance analysis, especially for the transonic region in which the low fidelity aerodynamic method is not reliable. Moreover, the test case shows that by combining a collaborative surrogate modeling approach with fusion of the data sets, the fidelity of the analysis data can be significantly improved giving maximum relative prediction error less than 5% with minimal computing efforts.
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In the modern aircraft design process numerical simulation is one of the key enablers. However, computational time increases exponentially with the level of fidelity of the simulation. In the EU Horizon2020 project AGILE different aircraft design analysis tools relative to different levels of fidelity are used. One of the challenges is to reduce the computational time - e.g. to facilitate an efficient optimization process - by processing the analysis data of various fidelity levels in a global surrogate model. This paper focuses on fusion of data sets via an automatic iterative process embedded in the collaborative multidisciplinary analysis (MDA) chains as applied in AGILE. Surrogate modeling techniques are applied, taking into account the optimal sampling and the corresponding fidelities of the samples. This paper will detail the different steps of the proposed collaborative approach. As a test case handling qualities analysis of the AGILE reference conventional aircraft is performed, by fusing the computed aerodynamic coefficients and derivatives. A full set of aerodynamic data computed either with different levels of fidelity or with only a low-fidelity tool has been derived and evaluated. The data set with multiple levels of fidelity significantly improved the accuracy of the flight performance analysis, especially for the transonic region in which the low fidelity aerodynamic method is not reliable. Moreover, the test case shows that by combining a collaborative surrogate modeling approach with fusion of the data sets, the fidelity of the analysis data can be significantly improved giving maximum relative prediction error less than 5% with minimal computing efforts.
Conference paper
(2020)
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Thomas Zill, Michael Iwanizki, Peter Schmollgruber, Sebastien Defoort, Carsten Döll, M.F.M. Hoogreef, R. de Vries, Jos Vankan, Wim Lammen
In the Clean Sky 2 Large Passenger Aircraft (LPA) program the potential of innovative hybrid electric propulsion (HEP) air vehicle concepts has been investigated by the projects ADEC (Advanced Engine and Aircraft Configuration) and NOVAIR (Novel Aircraft Configurations and Scaled Flight Testing Instrumentation). In a combined effort the members of the two projects worked closely together to identify promising technologies for air vehicle concepts that utilize hybrid electric powertrains. The vehicle design studies were divided onto the three distinct teams of DLR, TU Delft/NLR (NOVAIR), and ONERA. This paper will summarize the design efforts and the results obtained from the HEP design space exploration.
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In the Clean Sky 2 Large Passenger Aircraft (LPA) program the potential of innovative hybrid electric propulsion (HEP) air vehicle concepts has been investigated by the projects ADEC (Advanced Engine and Aircraft Configuration) and NOVAIR (Novel Aircraft Configurations and Scaled Flight Testing Instrumentation). In a combined effort the members of the two projects worked closely together to identify promising technologies for air vehicle concepts that utilize hybrid electric powertrains. The vehicle design studies were divided onto the three distinct teams of DLR, TU Delft/NLR (NOVAIR), and ONERA. This paper will summarize the design efforts and the results obtained from the HEP design space exploration.
Conference paper
(2018)
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Thierry Lefebvre, Nathalie Bartoli, Sylvain Dubreuil, Marco Panzeri, Riccardo Lombardi, Wim Lammen, Mengmeng Zhang, Imco van Gent, Pier Davide Ciampa
In this paper methodological investigations regarding an innovative Multidisciplinary Design and Optimization (MDO) approach for conceptual aircraft design are presented. These research activities are part of the ongoing EU-funded research project AGILE. The next generation of aircraft MDO processes is developed in AGILE, which targets significant reductions in aircraft development cost and time to market, leading to cheaper and greener aircraft solutions. The paper introduces the AGILE project structure and recalls the achievements of the first year of activities where a reference distributed MDO system has been formulated, deployed and applied to the design and optimization of a reference conventional aircraft configuration. Then, investigations conducted in the second year are presented, all aiming at making the complex optimization workflows easier to handle, characterized by a high degree of discipline interdependencies, multi-level processes and multi-partner collaborative engineering activities. The paper focuses on an innovative approach in which knowledge-based engineering and collaborative engineering techniques are used to handle a complex aircraft design workflow. Surrogate models replacing clusters of analysis disciplines have been developed and applied to make workflow execution more efficient. The paper details the different steps of the developed approach to set up and operate this test case, involving a team of aircraft design and surrogate modelling specialists, and taking advantage of the AGILE MDO framework. To validate the approach, different executable workflows were generated automatically and used to efficiently compare different MDO formulations. The use of surrogate models for clusters of design competences have been proved to be efficient approach not only to decrease the computational time but also to benchmark different MDO formulations on a complex optimization problem.
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In this paper methodological investigations regarding an innovative Multidisciplinary Design and Optimization (MDO) approach for conceptual aircraft design are presented. These research activities are part of the ongoing EU-funded research project AGILE. The next generation of aircraft MDO processes is developed in AGILE, which targets significant reductions in aircraft development cost and time to market, leading to cheaper and greener aircraft solutions. The paper introduces the AGILE project structure and recalls the achievements of the first year of activities where a reference distributed MDO system has been formulated, deployed and applied to the design and optimization of a reference conventional aircraft configuration. Then, investigations conducted in the second year are presented, all aiming at making the complex optimization workflows easier to handle, characterized by a high degree of discipline interdependencies, multi-level processes and multi-partner collaborative engineering activities. The paper focuses on an innovative approach in which knowledge-based engineering and collaborative engineering techniques are used to handle a complex aircraft design workflow. Surrogate models replacing clusters of analysis disciplines have been developed and applied to make workflow execution more efficient. The paper details the different steps of the developed approach to set up and operate this test case, involving a team of aircraft design and surrogate modelling specialists, and taking advantage of the AGILE MDO framework. To validate the approach, different executable workflows were generated automatically and used to efficiently compare different MDO formulations. The use of surrogate models for clusters of design competences have been proved to be efficient approach not only to decrease the computational time but also to benchmark different MDO formulations on a complex optimization problem.
With civil aviation growing at around 4.7% per annum, the environmental footprint of aviation is increasing. Moreover, the use of kerosene as a fuel accelerates the depletion of non-renewable fossil fuels and increases global warming. Hence, the aviation industry has to come up with new technologies to reduce its environmental impact and make aviation more sustainable. An electrically assisted propulsion system can combine the benefits of an electrical power source with a conventional turbofan engine. However, the additional electrical system increases the weight of the aircraft and complexity of the power management system. The objective of this research is to analyze the effect of an assistive electrical system on the performance of a turbofan engine for an A320 class aircraft on a short-range mission. The developed simulation model consists of an aircraft performance model combined with a propulsion model. The power management strategy is integrated within the simulation model. With the proposed propulsion system and power management strategy, the electrically assisted propulsion system would be able to reduce fuel burn, total energy consumption, and emissions for short-range missions of around 1000 km.
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With civil aviation growing at around 4.7% per annum, the environmental footprint of aviation is increasing. Moreover, the use of kerosene as a fuel accelerates the depletion of non-renewable fossil fuels and increases global warming. Hence, the aviation industry has to come up with new technologies to reduce its environmental impact and make aviation more sustainable. An electrically assisted propulsion system can combine the benefits of an electrical power source with a conventional turbofan engine. However, the additional electrical system increases the weight of the aircraft and complexity of the power management system. The objective of this research is to analyze the effect of an assistive electrical system on the performance of a turbofan engine for an A320 class aircraft on a short-range mission. The developed simulation model consists of an aircraft performance model combined with a propulsion model. The power management strategy is integrated within the simulation model. With the proposed propulsion system and power management strategy, the electrically assisted propulsion system would be able to reduce fuel burn, total energy consumption, and emissions for short-range missions of around 1000 km.
Conference paper
(2018)
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Darwin Rajpal, Roeland De Breuker, H Timmermans, Wim Lammen, F. Torrigiani
High aspect ratio strut braced aircraft can significantly reduce the induced drag. The inherent anisotropic behaviour of the composite material along with their weight saving potential can improve the performance of the aircraft during the flight. Thus, a composite strut braced aircraft is one of the promising candidates to achieve the targets set by European commission in Flightpath 2050 report. In this paper, multidisciplinary design analysis and optimization framework for strut braced aircrafts, is set-up involving tools provided by AGILE partners distributed worldwide. In the workflow, composite aeroelastic analysis and tailoring capability has been integrated with use of surrogate modelling. A design of experiment of the workflow with wing planform parameters as design variables is performed and a surrogate model is build. The optimization with an objective to reduce the fuel mass is performed using the surrogate of the workflow.
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High aspect ratio strut braced aircraft can significantly reduce the induced drag. The inherent anisotropic behaviour of the composite material along with their weight saving potential can improve the performance of the aircraft during the flight. Thus, a composite strut braced aircraft is one of the promising candidates to achieve the targets set by European commission in Flightpath 2050 report. In this paper, multidisciplinary design analysis and optimization framework for strut braced aircrafts, is set-up involving tools provided by AGILE partners distributed worldwide. In the workflow, composite aeroelastic analysis and tailoring capability has been integrated with use of surrogate modelling. A design of experiment of the workflow with wing planform parameters as design variables is performed and a surrogate model is build. The optimization with an objective to reduce the fuel mass is performed using the surrogate of the workflow.