Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Nguyen Anh Khoa Doan"'
Publikováno v:
Data-Centric Engineering, Vol 4 (2023)
Modeling complex dynamical systems with only partial knowledge of their physical mechanisms is a crucial problem across all scientific and engineering disciplines. Purely data-driven approaches, which only make use of an artificial neural network and
Externí odkaz:
https://doaj.org/article/f82937f97a8d4cb080d70f9379313e72
Autor:
Mathias Lesjak, Nguyen Anh Khoa Doan
Publikováno v:
Data-Centric Engineering, Vol 2 (2021)
We explore the possibility of combining a knowledge-based reduced order model (ROM) with a reservoir computing approach to learn and predict the dynamics of chaotic systems. The ROM is based on proper orthogonal decomposition (POD) with Galerkin proj
Externí odkaz:
https://doaj.org/article/621e1f5a415643f09fa392ee5d06b28c
Autor:
Camilo Fernando Silva Garzon, Philip Bonnaire, Nguyen Anh Khoa Doan, Korbinian Niebler, Camilo Fernando Silva
Publikováno v:
INTER-NOISE and NOISE-CON Congress and Conference Proceedings. 265:4773-4782
Acoustic measurements, obtained by microphones positioned at strategic places, are of great utility for the monitoring of a given acoustic system and for its protection in case large pressure fluctuations are measured. Such strategies are reliable as
Publikováno v:
INTER-NOISE and NOISE-CON Congress and Conference Proceedings. 265:1645-1656
Performing measurements in reacting flows is a challenging task due to the complexity of measuring all quantities of interest simultaneously or limitations in the optical access. To compensate for this, recent advances in deep learning have shown a s
Publikováno v:
INTER-NOISE & NOISE-CON Congress & Conference Proceedings; 2023, Vol. 265 Issue 6, p647-658, 12p
Autor:
Nguyen Anh Khoa Doan, Yuki Minamoto, Tianfeng Lu, Nedunchezhian Swaminathan, Jacqueline H. Chen, S. Bansude, Kosuke Osawa
Publikováno v:
Proceedings of the Combustion Institute. 38:5415-5422
Direct Numerical Simulations (DNS) data of Moderate or Intense Low-oxygen Dilution (MILD) combustion are analysed to identify the contributions of the autoignition and flame modes. This is performed using an extended Chemical Explosive Mode Analysis
Publikováno v:
Proceedings of the Combustion Institute
This paper demonstrates the ability of neural networks to reliably learn the nonlinear flame response of a laminar premixed flame, while carrying out only one unsteady CFD simulation. The system is excited with a broadband, low-pass filtered velocity
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Publikováno v:
Proceedings of the Combustion Institute, 39(4)
A neural network (NN) aided model is proposed for the filtered reaction rate in moderate or intense low-oxygen dilution (MILD) combustion. The framework of the present model is based on the partially stirred reactor (PaSR) approach, and the fraction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ba018ba31a9b992e13be06eca1461e0
http://resolver.tudelft.nl/uuid:114095b4-39da-47bf-af1c-9504f88cd84f
http://resolver.tudelft.nl/uuid:114095b4-39da-47bf-af1c-9504f88cd84f
Publikováno v:
Physics of Fluids, 34(8)
Pool fires are canonical representations of many accidental fires which can exhibit an unstable unsteady behavior, known as puffing, which involves a strong coupling between the temperature and velocity fields. Despite their practical relevance to fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac9187f5a0f19e375e9171ece1ec8d0a
http://resolver.tudelft.nl/uuid:1fb03542-82fd-4e2d-901d-c745b4bff8b7
http://resolver.tudelft.nl/uuid:1fb03542-82fd-4e2d-901d-c745b4bff8b7