Results 31 to 40 of about 5,322 (250)
Journal of Scientific Computing, 2019 Aerodynamic drag can be partially approximated by the entropy flux across fluid domain boundaries with a formula due to Oswatitsch. In this paper, we build the adjoint solution that corresponds to this representation of the drag and investigate its relation to the entropy variables, which are linked to the integrated residual of the entropy transport ...
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Adjoint method in PDE-based image compression
Asymptotic Analysis, 2023 We consider a shape optimization based method for finding the best interpolation data in the compression of images with noise. The aim is to reconstruct missing regions by means of minimizing a data fitting term in an L
Thomas JACUMIN, Zakaria Belhachmi
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Abstract and Applied Analysis, 2014 There are two different approaches on how to formulate adjoint numerical model (ANM). Aiming at the disputes arising from the construction methods of ANM, the differences between nonlinear shallow water equation and its adjoint equation are analyzed; the
Yaodeng Chen +3 more
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Enhancement of Adjoint Design Methods via Optimization of Adjoint Parameters [PDF]
43rd AIAA Aerospace Sciences Meeting and Exhibit, 2005 Three approaches of enhancing the Euler adjoint design methods using a non-linear gradient-based optimization package, SNOPT, have been investigated. First, the convergence of Euler and adjoint solutions was accelerated by optimizing the coecients of the residual smoothing scheme and the CFL number.
Sangho Kim +3 more
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Radial Turbine Thermo-Mechanical Stress Optimization by Multidisciplinary Discrete Adjoint Method
International Journal of Turbomachinery, Propulsion and Power, 2020 This paper addresses the problem of the design optimization of turbomachinery components under thermo-mechanical constraints, with focus on a radial turbine impeller for turbocharger applications.
Alberto Racca +2 more
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THE ADJOINT METHOD APPLIED TO TIME-DISTANCE HELIOSEISMOLOGY [PDF]
The Astrophysical Journal, 2011 23 pages, 9 Figures, accepted by ...
Hanasoge +7 more
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Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI
Advanced Science, EarlyView.ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia +7 more
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Symmetric-adjoint and symplectic-adjoint methods and their applications
, 2018 Symmetric method and symplectic method are classical notions in the theory of Runge-Kutta methods. They can generate numerical flows that respectively preserve the symmetry and symplecticity of the continuous flows in the phase space. Adjoint method is an important way of constructing a new Runge-Kutta method via the symmetrisation of another Runge ...
Sun, Geng +3 more
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Exact Discrete Stochastic Simulation With Deep‐Learning‐Scale Gradient Optimization
Advanced Science, EarlyView.A 203,796‐parameter gene regulatory network classifies handwritten digits with 98.4% accuracy using exact stochastic dynamics. The framework decouples forward simulation from backward differentiation, making continuous‐time Markov chain models compatible with deep‐learning optimization.
Jose M. G. Vilar, Leonor Saiz
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Aerodynamic adjoint-based optimization design method for aircraft based on low-dissipation scheme
Kongqi donglixue xuebaoIn aerodynamic discrete adjoint optimization design systems for aircraft, the accuracy and robustness of the flow field transport equations and adjoint equations are primarily influenced by the numerical discretization schemes used for the inviscid terms.
Yuyang Mu +5 more
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