YL
Y. Luan
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1
In studies of wind plant designs, wake dynamics are of great interests as wakes affect downstream turbine loading that impacts wind plant efficiency. Recent developments of Tensor Basis Decision Tree (TBDT) based machine learning (ML) models in reconstructing the turbulence anisotropy fields of simple flow cases prompt the motivation in applying such models to the more complex wind plant simulations. A significantly more efficient TBDT framework has been developed to tackle large scale flow domains. By training on the Large Eddy Simulation data of a one-turbine case, the ML models can reconstruct the free shear layers in wind plants of various turbine layouts and atmospheric conditions while predicting the correct shape and orientation of turbine wakes. Subsequently, a data-driven augmentation to Reynolds-averaged Navier-Stokes simulations of wind plants has been employed that results in more accurate turbulent fields and turbine outputs, which demonstrates the potential of efficient wind plant simulations of tomorrow.
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In studies of wind plant designs, wake dynamics are of great interests as wakes affect downstream turbine loading that impacts wind plant efficiency. Recent developments of Tensor Basis Decision Tree (TBDT) based machine learning (ML) models in reconstructing the turbulence anisotropy fields of simple flow cases prompt the motivation in applying such models to the more complex wind plant simulations. A significantly more efficient TBDT framework has been developed to tackle large scale flow domains. By training on the Large Eddy Simulation data of a one-turbine case, the ML models can reconstruct the free shear layers in wind plants of various turbine layouts and atmospheric conditions while predicting the correct shape and orientation of turbine wakes. Subsequently, a data-driven augmentation to Reynolds-averaged Navier-Stokes simulations of wind plants has been employed that results in more accurate turbulent fields and turbine outputs, which demonstrates the potential of efficient wind plant simulations of tomorrow.
Finding Venusian Volcanoes
Project Matryoshka
Bachelor thesis
(2016)
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M.P. den Boer, A.J.D. de Bruin, C.S. Ganani, A.A. Gunessee, S.F.M. Harmsen, M. Henger, J.J.X. Huang, T.C. Kroes, Y. Luan, J.N. Weinmiller, D.M. Stam, S. Teixeira De Freitas, Z. Hong
This report details the design of a mission aimed to find and analyse active Venusian volcanoes, if they exist. These volcanoes are interesting because active volcanism would significantly contribute to the understanding of the Venusian atmosphere, its extreme climate and geological processes. This knowledge would in turn help us understand Earth better. The design is based on the concept selected previously in the Midterm report and consists of five vehicles: a spacecraft, an aeroshell, an aircraft and two landers. The spacecraft with aeroshell will be launched into a Hohmann transfer orbit to Venus in 2023. Upon arrival, the satellite will map the surface, and find the most promising region for volcanic activity. It will then deploy the aeroshell containing the aircraft and landers. The satellite then changes its orbit to one that allows for it to act as a relay between the Venusian vehicles and Earth. After entry and having slowed down sufficiently to deploy a parachute, the first lander will be dropped. This lander will act as a reference for the lander inside the aircraft. Next, the aircraft is deployed after which it will start following flight tracks that allow for it to stay in the Sunlight. These tracks are designed by taking into consideration the power systems, thermal system and propulsion system, and then optimising such that the electronics do not overheat and that the battery size is reasonable. While flying, the aircraft will take measurements to locate volcanoes. Once a very promising location is found, the aircraft will deploy the second lander from an altitude of about 32 km. This lander will then descend further down and land on the surface where it will perform measurements. Combining the measurements of all vehicles it is expected that the mission can also complete a number of secondary objectives to further improve the knowledge of Venus...
...
This report details the design of a mission aimed to find and analyse active Venusian volcanoes, if they exist. These volcanoes are interesting because active volcanism would significantly contribute to the understanding of the Venusian atmosphere, its extreme climate and geological processes. This knowledge would in turn help us understand Earth better. The design is based on the concept selected previously in the Midterm report and consists of five vehicles: a spacecraft, an aeroshell, an aircraft and two landers. The spacecraft with aeroshell will be launched into a Hohmann transfer orbit to Venus in 2023. Upon arrival, the satellite will map the surface, and find the most promising region for volcanic activity. It will then deploy the aeroshell containing the aircraft and landers. The satellite then changes its orbit to one that allows for it to act as a relay between the Venusian vehicles and Earth. After entry and having slowed down sufficiently to deploy a parachute, the first lander will be dropped. This lander will act as a reference for the lander inside the aircraft. Next, the aircraft is deployed after which it will start following flight tracks that allow for it to stay in the Sunlight. These tracks are designed by taking into consideration the power systems, thermal system and propulsion system, and then optimising such that the electronics do not overheat and that the battery size is reasonable. While flying, the aircraft will take measurements to locate volcanoes. Once a very promising location is found, the aircraft will deploy the second lander from an altitude of about 32 km. This lander will then descend further down and land on the surface where it will perform measurements. Combining the measurements of all vehicles it is expected that the mission can also complete a number of secondary objectives to further improve the knowledge of Venus...