Results 131 to 140 of about 5,322 (250)
Enhancing hydrodynamic efficiency in Autonomous Underwater Vehicles (AUVs) utilizing adjoint method and proper orthogonal decomposition. [PDF]
Bhuiyan SA, Hasan MJ, Hoque MA.
europepmc +1 more source
AEROSTRUCTURAL OPTIMIZATION WITH THE ADJOINT METHOD
This paper presents the current developments performed at ONERA to extend the aeroelastic adjoint method in the CFD software elsA towards an aerostructural adjoint. Because multiobjective and multipoint optimizations require an aerostructural design space, a tool for fully-flexible wings is created utilizing Python and Fortran.
Ghazlane, Imane +4 more
openaire +1 more source
Deep‐Learning‐Based Image Reconstruction to Improve End‐Diastolic and Systolic Cardiac T1 Mapping
ABSTRACT Purpose To develop an image reconstruction method that enables increased spatial resolution cardiac T1 mapping in both the end‐diastolic and systolic phase, that shows high T1 agreement with the clinical standard. The resolution gain is achieved by increasing the acceleration rate of MOLLI single‐shot images to R = 4, while maintaining a ...
Daniel Amsel +10 more
wiley +1 more source
Adjoint method-based Fourier neural operator surrogate solver for wavefront shaping in tunable metasurfaces. [PDF]
Kang C, Seo J, Jang I, Chung H.
europepmc +1 more source
Persistent sheaf Laplacian analysis of protein stability and solubility changes upon mutation
Abstract Genetic mutations frequently disrupt protein structure, stability, and solubility, acting as primary drivers for a wide spectrum of diseases. Despite the critical importance of these molecular alterations, existing computational models often lack interpretability and fail to integrate essential physicochemical interactions.
Yiming Ren +4 more
wiley +1 more source
ABSTRACT We analytically construct initial data for binary black hole systems by solving the Einstein constraint equations within the Bowen–York framework. Allowing for arbitrarily oriented linear momenta and spins, we obtain a perturbative solution of the vacuum Hamiltonian constraint up to third order in the source parameters. Our solution explicitly
Leyla Ogurol, Tore Boybeyi, Bayram Tekin
wiley +1 more source
Gradient‐Free Online Learning of Subgrid‐Scale Dynamics With Neural Emulators
Abstract In this paper, we propose a generic algorithm to train machine learning‐based subgrid parametrizations online, that is, with a posteriori loss functions, but for non‐differentiable numerical solvers. The proposed approach leverages a neural emulator to approximate the reduced state‐space solver, which is then used to allow gradient propagation
H. Frezat +3 more
wiley +1 more source
Abstract Seismic attenuation provides sensitivity to fracture density, fluid saturation, and pore geometry that complements velocity, enabling quantitative imaging of fracture architecture and associated fluid‐pathways in near‐surface bedrock. Yet high‐resolution attenuation models remain rare in refraction studies due to amplitude‐fidelity and ...
Donggeon Kim, Guangchi Xing, Tieyuan Zhu
wiley +1 more source
The ASTE‐BGC Data‐Assimilative Regional Ocean Biogeochemical Model
Abstract We present a data‐assimilative regional ocean biogeochemical model, ASTE‐BGC, which simulates the physical and biogeochemical state of the North Atlantic Ocean from 2002 to 2017. Model physics are provided by a physical state estimate (ASTE), which assimilates O(109) in situ and satellite‐based observations over the model domain and time ...
L. A. Moseley +5 more
wiley +1 more source

