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Machine-learning models have demonstrated a great ability to learn complex patterns and make predictions. In high-dimensional nonlinear problems of fluid dynamics, data representation often greatly affects the performance and…

Fluid Dynamics · Physics 2022-07-29 Runze Li , Yufei Zhang , Haixin Chen

A new form of aerostat wind generation system which contains an array of interacting turbines is proposed. The design of the balloon turbine components is undertaken through the combination of artificial intelligence and rapid prototyping…

Neural and Evolutionary Computing · Computer Science 2018-11-14 Larry Bull , Neil Phillips

Finding new superconductors with a high critical temperature ($T_c$) has been a challenging task due to computational and experimental costs. We present a diffusion model inspired by the computer vision community to generate new…

Superconductivity · Physics 2023-07-28 Daniel Wines , Tian Xie , Kamal Choudhary

Laminated composite materials are widely used in most fields of engineering. Wave propagation analysis plays an essential role in understanding the short-duration transient response of composite structures. The forward physics-based models…

Signal Processing · Electrical Eng. & Systems 2022-12-14 Mahindra Rautela , J. Senthilnath , Armin Huber , S. Gopalakrishnan

We introduce the vine copula autoencoder (VCAE), a flexible generative model for high-dimensional distributions built in a straightforward three-step procedure. First, an autoencoder (AE) compresses the data into a lower dimensional…

Machine Learning · Statistics 2019-11-28 Natasa Tagasovska , Damien Ackerer , Thibault Vatter

Background. This paper study statistical data gathered from wind turbines located on the territory of the Republic of Poland. The research is aimed to construct the stochastic model that predicts the change of wind speed with time. Purpose.…

Computational Engineering, Finance, and Science · Computer Science 2017-11-15 M. N. Gevorkyan , A. V. Demidova , Robert A. Sobolewski , I. S. Zaryadov , A. V. Korolkova , D. S. Kulyabov , L. A. Sevastianov

To what extent is the success of deep visualization due to the training? Could we do deep visualization using untrained, random weight networks? To address this issue, we explore new and powerful generative models for three popular deep…

Computer Vision and Pattern Recognition · Computer Science 2016-06-17 Kun He , Yan Wang , John Hopcroft

Generative dynamic texture models (GDTMs) are widely used for dynamic texture (DT) segmentation in the video sequences. GDTMs represent DTs as a set of linear dynamical systems (LDSs). A major limitation of these models concerns the…

Graphics · Computer Science 2019-01-15 Sahar Yousefi , M. T. Manzuri Shalmani , Antoni B. Chan

Vortex is a central concept in the understanding of turbulent dynamics. Objective algorithms for the detection and extraction of vortex structures can facilitate the physical understanding of turbulence regeneration dynamics by enabling…

Fluid Dynamics · Physics 2019-12-06 Lu Zhu , Li Xi

Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply try a limited number of hand-designed shapes or restrict…

Computational Engineering, Finance, and Science · Computer Science 2018-02-13 Pierre Baqué , Edoardo Remelli , François Fleuret , Pascal Fua

The generation of ocean surface waves by wind is a classic fluid mechanics problem whose theoretical study dates back to 1957, when the two seminal papers by Phillips and Miles were published in the incipient Journal of Fluid Mechanics.…

Fluid Dynamics · Physics 2023-02-17 Tianyi Li , Lian Shen

The ever-growing use of wind energy makes necessary the optimization of turbine operations through pitch angle controllers and their maintenance with early fault detection. It is crucial to have accurate and robust models imitating the…

Machine Learning · Computer Science 2023-07-28 Alfonso Gijón , Ainhoa Pujana-Goitia , Eugenio Perea , Miguel Molina-Solana , Juan Gómez-Romero

Recent laboratory experiments have revealed that important insights into the physical processes involved in the wind-driven generation of surface waves may be obtained by varying the viscosity of the carrying liquid over several orders of…

Fluid Dynamics · Physics 2023-04-12 Florent Burdairon , Jacques Magnaudet

Metamaterials are emerging as a new paradigmatic material system to render unprecedented and tailorable properties for a wide variety of engineering applications. However, the inverse design of metamaterial and its multiscale system is…

Computational Engineering, Finance, and Science · Computer Science 2020-09-17 Liwei Wang , Yu-Chin Chan , Faez Ahmed , Zhao Liu , Ping Zhu , Wei Chen

We present a data-driven optimization framework that aims to address online adaptation of the flight path shape for an airborne wind energy system (AWE) that follows a repetitive path to generate power. Specifically, Bayesian optimization,…

Systems and Control · Electrical Eng. & Systems 2020-11-18 Ali Baheri , Chris Vermillion

Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it…

Computer Vision and Pattern Recognition · Computer Science 2021-05-14 Zerong Zheng , Tao Yu , Qionghai Dai , Yebin Liu

Wind farm flow control aims to improve wind turbine performance by reducing aerodynamic wake interaction between turbines. Dynamic, physics-based models of wind farm flows have been essential for exploring control strategies such as wake…

Systems and Control · Electrical Eng. & Systems 2022-11-15 Maarten J. van den Broek , Delphine De Tavernier , Benjamin Sanderse , Jan-Willem van Wingerden

Generating high-quality 3D assets from text and images has long been challenging, primarily due to the absence of scalable 3D representations capable of capturing intricate geometry distributions. In this work, we introduce Direct3D, a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Shuang Wu , Youtian Lin , Feihu Zhang , Yifei Zeng , Jingxi Xu , Philip Torr , Xun Cao , Yao Yao

We present a novel approach for designing complex approximate arithmetic circuits that trade correctness for power consumption and play important role in many energy-aware applications. Our approach integrates in a unique way formal methods…

Neural and Evolutionary Computing · Computer Science 2020-07-03 Milan Ceska , Jiri Matyas , Vojtech Mrazek , Lukas Sekanina , Zdenek Vasicek , Tomas Vojnar

This paper solves an approximate form of conservation of mass and momentum for a turbine in a wind farm array. The solution is a fairly simple explicit relationship that predicts the streamwise velocity distribution within a wind farm with…