Suchergebnis | Hamburg Open Science

Facetten

42 Einträge gefunden

Peridynamic elastic waves in two-dimensional unbounded domains: construction of nonlocal Dirichlet-type absorbing boundary conditions
2023 - TUHH Open Research
Ultrasound shear wave elasticity imaging with spatio-temporal deep learning
2022 - TUHH Open Research - frei zugänglich
Training deep neural networks to reconstruct nanoporous structures from FIB tomography images using synthetic training data
2022 - TUHH Open Research - frei zugänglich
A hybrid meshfree discretization to improve the numerical performance of peridynamic models
2022 - TUHH Open Research
Training deep neural networks to reconstruct nanoporous structures from FIB tomography images using synthetic training data
2022 - TUHH Open Research - frei zugänglich
A versatile SPH modeling framework for coupled microfluid-powder dynamics in additive manufacturing: binder jetting, material jetting, directed energy deposition and powder bed fusion
2022 - TUHH Open Research - frei zugänglich
Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning
2022 - TUHH Open Research - frei zugänglich
Accelerating the distance-minimizing method for data-driven elasticity with adaptive hyperparameters
2022 - TUHH Open Research - frei zugänglich
Combining peridynamic and finite element simulations to capture the corrosion of degradable bone implants and to predict their residual strength
2022 - TUHH Open Research
Comment on “Tensional homeostasis at different length scales” by D. Stamenović and M. L. Smith,
1. Humphrey, Jay Dowell
2. Cyron, Christian J.
2022 - TUHH Open Research
Global sensitivity analysis of a homogenized constrained mixture model of arterial growth and remodeling
2021 - TUHH Open Research - frei zugänglich
Mechanical homeostasis in tissue equivalents: a review
2021 - TUHH Open Research - frei zugänglich
Identification of the concentration‐dependent viscoelastic constitutive parameters of gelatin by combining computational mechanics and machine learning
2021 - TUHH Open Research - frei zugänglich
The Brain–Bladder Axis in Tissue Growth and Remodelling
1. Miftahof, Roustem
2. Cyron, Christian J.
2021 - TUHH Open Research
Unraveling the local relation between tissue composition and human brain mechanics through machine learning
2021 - TUHH Open Research - frei zugänglich
Constitutive artificial neural networks : a fast and general approach to predictive data-driven constitutive modeling by deep learning
2021 - TUHH Open Research - frei zugänglich
Neural network surgery: combining training with topology optimization
2021 - TUHH Open Research - frei zugänglich
An SPH framework for fluid–solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions
2021 - TUHH Open Research - frei zugänglich
Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition
2021 - TUHH Open Research
A novel smoothed particle hydrodynamics and finite element coupling scheme for fluid-structure interaction: the sliding boundary particle approach
2021 - TUHH Open Research

Aktive Facetten

Facetten

Zugriff

Einrichtung

Medientyp

Karte

Erscheinungsjahr

Autor/in

Sprache

Peridynamic elastic waves in two-dimensional unbounded domains: construction of nonlocal Dirichlet-type absorbing boundary conditions

Ultrasound shear wave elasticity imaging with spatio-temporal deep learning

Training deep neural networks to reconstruct nanoporous structures from FIB tomography images using synthetic training data

A hybrid meshfree discretization to improve the numerical performance of peridynamic models

Training deep neural networks to reconstruct nanoporous structures from FIB tomography images using synthetic training data

A versatile SPH modeling framework for coupled microfluid-powder dynamics in additive manufacturing: binder jetting, material jetting, directed energy deposition and powder bed fusion

Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning

Accelerating the distance-minimizing method for data-driven elasticity with adaptive hyperparameters

Combining peridynamic and finite element simulations to capture the corrosion of degradable bone implants and to predict their residual strength

Comment on “Tensional homeostasis at different length scales” by D. Stamenović and M. L. Smith,

Global sensitivity analysis of a homogenized constrained mixture model of arterial growth and remodeling

Mechanical homeostasis in tissue equivalents: a review

Identification of the concentration‐dependent viscoelastic constitutive parameters of gelatin by combining computational mechanics and machine learning

The Brain–Bladder Axis in Tissue Growth and Remodelling

Unraveling the local relation between tissue composition and human brain mechanics through machine learning

Constitutive artificial neural networks : a fast and general approach to predictive data-driven constitutive modeling by deep learning

Neural network surgery: combining training with topology optimization

An SPH framework for fluid–solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions

Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition

A novel smoothed particle hydrodynamics and finite element coupling scheme for fluid-structure interaction: the sliding boundary particle approach