Zobrazeno 1 - 10
of 117
pro vyhledávání: '"András Sóbester"'
Publikováno v:
Journal of Open Research Software, Vol 5, Iss 1 (2017)
Teetool is a Python package which models and visualises motion patterns found in two- and three-dimensional trajectory data. It models the trajectories as a Gaussian process and uses the mean and covariance of the trajectory data to produce a confide
Externí odkaz:
https://doaj.org/article/8044497f704f4aabaac900213fad42ec
Publikováno v:
Journal of Open Research Software, Vol 5, Iss 1 (2017)
The Cambridge Rocketry Simulator can be used to simulate the flight of unguided rockets for both design and operational applications. The software consists of three parts: The first part is a GUI that enables the user to design a rocket. The second p
Externí odkaz:
https://doaj.org/article/d92f815924824eac89df2de3b59055d6
Publikováno v:
Journal of Aerospace Information Systems. 20:126-139
In this paper we propose the use of spatiotemporal population density data in the analysis of ground risk posed by uncrewed aircraft system (UAS) operations. The spatiotemporal population density maps are generated through the combination of authorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9d3f37c7390ae8354f7cafaccf6d4f4
https://doi.org/10.2514/1.i011113
https://doi.org/10.2514/1.i011113
Publikováno v:
AIAA SCITECH 2023 Forum.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2fd5a5f399c4efc5be9e5e72c3ab70e
https://doi.org/10.2514/6.2023-2601
https://doi.org/10.2514/6.2023-2601
Autor:
András Sóbester
Publikováno v:
Journal of Aircraft. 58:1216-1228
A Monte Carlo model designed for fixed-wing aircraft takeoff performance uncertainty quantification is benchmarked. The uses of an efficient takeoff simulator of this type range from rapid design variable and constraint sensitivity studies and large-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e880087c6c8695543364b7b41c2da4d5
https://doi.org/10.2514/1.c036180
https://doi.org/10.2514/1.c036180
Statistical analysis of control parameters in evolutionary map L-systems-based topology optimization
Autor:
András Sóbester, Teemu J. Ikonen
Publikováno v:
Structural and Multidisciplinary Optimization. 58:997-1013
Map L-systems-based parametrization, also referred to as the cellular division method, is a generative encoding, suitable for topology optimization. The parametrization is compact due to its ability to reuse its elements, and therefore capable of cov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daa6e98afca7cefb4db1922a6e76af27
https://doi.org/10.1007/s00158-018-1943-1
https://doi.org/10.1007/s00158-018-1943-1
Autor:
Timothy T. Takahashi, András Sóbester
Publikováno v:
AIAA Aviation 2019 Forum.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4e553e7de6f94582b64160a51406b76e
https://doi.org/10.2514/6.2019-3271
https://doi.org/10.2514/6.2019-3271
Publikováno v:
Journal of Guidance, Control, and Dynamics. 39:2661-2672
This work investigates the application of Gaussian processes to capturing the probability distribution of a set of aircraft trajectories from historical measurement data. To achieve this, all data are assumed to be generated from a probabilistic mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0860a490c63b4150bcdb965bf2cf929
https://doi.org/10.2514/1.g000537
https://doi.org/10.2514/1.g000537
Publikováno v:
Journal of Aircraft. 54:2010-2012
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6fc7d5a63b4842e6eba98dd691296a4
https://doi.org/10.2514/1.c034358
https://doi.org/10.2514/1.c034358
Generative encodings have the potential of improving the performance of evolutionary algorithms. In this work we apply parametric L-systems, which can be described as developmental recipes, to evolutionary topology optimization of widely studied two-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::afc9b6536941737ea024ea1d4370ae9a
https://eprints.soton.ac.uk/422930/
https://eprints.soton.ac.uk/422930/
