Separable shape tensors for aerodynamic design

Grey, Zachary; Доронина, О. Б.; Glaws, Andrew

doi:10.1093/jcde/qwac140

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…G2Aero implements the novel separable tensor framework outlined in detail in Grey et al (2023). It is designed to learn matrix-submanifolds, generate novel shapes localized to data, control shape undulations by truncating an ordered basis of deforming modes, and enable a novel notion of "consistent deformations" as an approach to regularized surface design.…”

Section: Methodsmentioning

confidence: 99%

G2Aero: A Python package for separable shape tensors

Doronina,

Grey,

Glaws

2023

JOSS

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G2Aero is a Python package for the design and deformation of discrete planar curves and tubular surfaces using a geometric data-driven approach. G2Aero utilizes a topology of product manifolds: the Grassmannian, 𝒢(𝑛, 2)-the set of 2-dimensional subspaces in ℝ 𝑛 -and the symmetric positive-definite (SPD) manifold, 𝑆 2 ++ -the set of 2×2 SPD matrices. The package provides a novel framework for representing separable deformations to shapes, which consist of stretching, scaling, rotating, and translating-also known as affine deformations-and a set of complementary deformations-which we refer to as undulation-type deformations.

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Section: Methodsmentioning

confidence: 99%

G2Aero: A Python package for separable shape tensors

Doronina,

Grey,

Glaws

2023

JOSS

Self Cite

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“…The left side of Figure 1 showed that a six-rotor drone and air flows are augmented in an office room shown by an MR device, and the right side demonstrates that an extracted wing section called airfoil which is very critical in the wing performance produces aerodynamic lifting and drag forces. Although airfoil shape design is a classical subject in engineering and manufacturing, it is still being studied by many researchers such as Grey et al [20] and Wang et al [21]. Wing design analysis is generally accompanied by CFD simulation around the airfoils belonging to the given wing.…”

Section: Introductionmentioning

confidence: 99%

Development of a Digital Twin Pipeline for Interactive Scientific Simulation and Mixed Reality Visualization

Shin,

Park,

Kim

et al. 2023

IEEE Access

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An interactive scientific simulation and visualization pipeline in mixed reality was developed to explore how scientific simulation could proceed in coming workplace. The main technical concern is fast scientific simulator and visualizer in mixed reality with hand gesture. Framework for scientific simulation and visualization was implemented on the server side based on deep learning based fast simulation model and open source visualization toolkit, VTK, respectively. Airfoil aerodynamics was selected as a target scientific simulation task since it is a representative and critical problem in scientific fluid simulation determining the whole aero-product's performance and shows highly nonlinear physics even by small shape deviation and so high computational cost. Therefore, the fast simulator was firstly developed by carefully developing convolutional neural network-based model, using U-net, which learned corresponding high accuracy simulation dataset. All scenes which are supposed to be seen on the mobile device side were authored in a widely used content development tool called Unity3D with a mixed reality toolkit, MRTK for Microsoft Hololens 2. User interface and user experience were created based on a scenario of a drone rotor which demonstrates running and analyzing the simulation results using designed interaction gestures. Finally, several discussions were derived through the implemented digital twin pipeline. It was concluded, with an adequately implemented mixed reality tools, that scientific researchers or industrial engineers will be helped not only in individual analysis works due to the delicacy of hands and fingers and real time interaction in mixed reality, but also, as a future study, in cooperative analysis works. INDEX TERMSComputational fluid dynamics, Computer simulation, Convolutional neural network, Digital twin, Extended reality, Mixed realityTABLE I NOMENCLATURE Symbols or Abbreviations Meanings ρ Density p Pressure t, x, y Time and spatial axis u, v Velocity on x, y-axis 2D or 3D Two-dimensional or three-dimensional AI Artificial intelligence AR Augmented reality CFD Computational fluid dynamics CNN Convolution neural network ELU Exponential linear unit I/O Input and output LiDAR Light detection and ranging MR Mixed reality MRO Maintenance, repair, and operation MRTK Mixed reality toolkit PDE Partial differential equation This article has been accepted for publication in IEEE Access.

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Data-driven surrogate model for aerodynamic design using separable shape tensor method

PANG,

ZHANG,

et al. 2024

Chinese Journal of Aeronautics

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Separable shape tensors for aerodynamic design

Cited by 5 publications

References 44 publications

G2Aero: A Python package for separable shape tensors

G2Aero: A Python package for separable shape tensors

Development of a Digital Twin Pipeline for Interactive Scientific Simulation and Mixed Reality Visualization

Data-driven surrogate model for aerodynamic design using separable shape tensor method

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