AIMC Topic: Finite Element Analysis

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The effect of deep learning-based lesion segmentation on failure load calculations of metastatic femurs using finite element analysis.

Bone
Bone ranks as the third most frequent tissue affected by cancer metastases, following the lung and liver. Bone metastases are often painful and may result in pathological fracture, which is a major cause of morbidity and mortality in cancer patients....

Physics-informed UNets for discovering hidden elasticity in heterogeneous materials.

Journal of the mechanical behavior of biomedical materials
Soft biological tissues often have complex mechanical properties due to variation in structural components. In this paper, we develop a novel UNet-based neural network model for inversion in elasticity (El-UNet) to infer the spatial distributions of ...

Predicting trabecular arrangement in the proximal femur: An artificial neural network approach for varied geometries and load cases.

Journal of biomechanics
Machine learning (ML) and deep learning (DL) approaches can solve the same problems as the finite element method (FEM) with a high degree of accuracy in a fraction of the required time, by learning from previously presented data. In this work, the bo...

Crack control optimization of basement concrete structures using the Mask-RCNN and temperature effect analysis.

PloS one
In order to enhance the mitigation of crack occurrence and propagation within basement concrete structures, this research endeavors to propose an optimization methodology grounded in the Mask Region-based Convolutional Neural Network (Mask-RCNN) and ...

Analysis of Friction Noise Mechanism in Lead Screw System of Autonomous Vehicle Seats and Dynamic Instability Prediction Based on Deep Neural Network.

Sensors (Basel, Switzerland)
This study investigated the squeal mechanism induced by friction in a lead screw system. The dynamic instability in the friction noise model of the lead screw was derived through a complex eigenvalue analysis via a finite element model. A two degree ...

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...

Prediction of Bone Healing around Dental Implants in Various Boundary Conditions by Deep Learning Network.

International journal of molecular sciences
Tissue differentiation varies based on patients' conditions, such as occlusal force and bone properties. Thus, the design of the implants needs to take these conditions into account to improve osseointegration. However, the efficiency of the design p...

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...

Historical evolution and new trends for soil-intruder interaction modeling.

Bioinspiration & biomimetics
Soil is a crucial resource for life on Earth. Every activity, whether natural or man-made, that interacts with the sub or deep soil can affect the land at large scales (e.g. geological risks). Understanding such interactions can help identify more su...