Zobrazeno 1 - 10
of 412
pro vyhledávání: '"Sapsis, Themistoklis"'
Chaotic dynamics, commonly seen in weather systems and fluid turbulence, are characterized by their sensitivity to initial conditions, which makes accurate prediction challenging. Despite its sensitivity to initial perturbations, many chaotic systems
Externí odkaz:
http://arxiv.org/abs/2410.00976
Autor:
Sorensen, Benedikt Barthel, Zepeda-Núñez, Leonardo, Lopez-Gomez, Ignacio, Wan, Zhong Yi, Carver, Rob, Sha, Fei, Sapsis, Themistoklis
Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interaction with other, often not fully understood, physics. As a consequence,
Externí odkaz:
http://arxiv.org/abs/2408.02688
Bifurcations mark qualitative changes of long-term behavior in dynamical systems and can often signal sudden ("hard") transitions or catastrophic events (divergences). Accurately locating them is critical not just for deeper understanding of observed
Externí odkaz:
http://arxiv.org/abs/2406.11141
As the global population grows and climate change intensifies, sustainable food production is critical. Marine aquaculture offers a viable solution, providing a sustainable protein source. However, the industry's expansion requires novel technologies
Externí odkaz:
http://arxiv.org/abs/2406.04519
Autor:
Sorensen, Benedikt Barthel, Charalampopoulos, Alexis, Zhang, Shixuan, Harrop, Bryce, Leung, Ruby, Sapsis, Themistoklis
Due to the rapidly changing climate, the frequency and severity of extreme weather is expected to increase over the coming decades. As fully-resolved climate simulations remain computationally intractable, policy makers must rely on coarse-models to
Externí odkaz:
http://arxiv.org/abs/2402.18484
In a multifidelity setting, data are available under the same conditions from two (or more) sources, e.g. computer codes, one being lower-fidelity but computationally cheaper, and the other higher-fidelity and more expensive. This work studies for wh
Externí odkaz:
http://arxiv.org/abs/2402.17984
Machine learning methods for the construction of data-driven reduced order model models are used in an increasing variety of engineering domains, especially as a supplement to expensive computational fluid dynamics for design problems. An important c
Externí odkaz:
http://arxiv.org/abs/2306.15159
Autor:
Charalampopoulos, Alexis-Tzianni, Zhang, Shixuan, Harrop, Bryce, Leung, Lai-yung Ruby, Sapsis, Themistoklis
This work presents a systematic framework for improving the predictions of statistical quantities for turbulent systems, with a focus on correcting climate simulations obtained by coarse-scale models. While high resolution simulations or reanalysis d
Externí odkaz:
http://arxiv.org/abs/2304.02117
This work addresses the data-driven forecasting of extreme events in the airfoil flow. These events may be seen as examples of the kind of unsteady and intermittent dynamics relevant to the flow around airfoils and wings in a variety of laboratory an
Externí odkaz:
http://arxiv.org/abs/2303.07056
Weather extremes are a major societal and economic hazard, claiming thousands of lives and causing billions of dollars in damage every year. Under climate change, their impact and intensity are expected to worsen significantly. Unfortunately, general
Externí odkaz:
http://arxiv.org/abs/2210.12137