AIMC Topic: Stress, Mechanical

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Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics-Informed Neural Networks.

Small methods
The heterogeneous micromechanical properties of biological tissues have profound implications across diverse medical and engineering domains. However, identifying full-field heterogeneous elastic properties of soft materials using traditional enginee...

Assessing screw length impact on bone strain in proximal humerus fracture fixation via surrogate modelling.

International journal for numerical methods in biomedical engineering
A high failure rate is associated with fracture plates in proximal humerus fractures. The causes of failure remain unclear due to the complexity of the problem including the number and position of the screws, their length and orientation in the space...

Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.

Journal of the mechanical behavior of biomedical materials
The study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquire...

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering.

Biomechanics and modeling in mechanobiology
Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mecha...

Mechanochemical Degradation of Biopolymers.

Molecules (Basel, Switzerland)
Mechanochemical treatment of various organic molecules is an emerging technology of green processes in biofuel, fine chemicals, or food production. Many biopolymers are involved in isolating, derivating, or modifying molecules of natural origin. Mech...

A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation.

Biophysical journal
Mechanical stresses generated at the cell-cell level and cell-substrate level have been suggested to be important in a host of physiological and pathological processes. However, the influence various chemical compounds have on the mechanical stresses...

Tendon Stress Estimation from Strain Data of a Bridge Girder Using Machine Learning-Based Surrogate Model.

Sensors (Basel, Switzerland)
Prestressed girders reduce cracking and allow for long spans, but their construction requires complex equipment and strict quality control. Their accurate design depends on a precise knowledge of tensioning force and stresses, as well as monitoring t...

A strategy to formulate data-driven constitutive models from random multiaxial experiments.

Scientific reports
We present a test technique and an accompanying computational framework to obtain data-driven, surrogate constitutive models that capture the response of isotropic, elastic-plastic materials loaded in-plane stress by combined normal and shear stresse...

Elasticity imaging using physics-informed neural networks: Spatial discovery of elastic modulus and Poisson's ratio.

Acta biomaterialia
Elasticity imaging is a technique that discovers the spatial distribution of mechanical properties of tissue using deformation and force measurements under various loading conditions. Given the complexity of this discovery, most existing methods appr...

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

Acta biomaterialia
Microstructural features and mechanical properties are closely related in all soft biological tissues. Both yet exhibit considerable inter-individual differences and are affected by factors such as aging and disease and its progression. Histological ...