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defects

Defect-based Physics-Informed Machine Learning Framework for Fatigue Prediction

Submitted by enrico.salvati1 on

I would like to draw your attention to our recently proposed predictive method based on a semi-empirical model (LEFM) and Neural Network, exploiting the Physics-informed Machine Learning concept. We show how the accuracy of state-of-the-art fatigue predictive models, based on defects present in materials, can be significantly boosted by accounting for additional morphological features via Physics-Informed Machine Learning.

Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks

Submitted by Nuwan Dewapriya on

Abstract: Advanced machine learning methods could be useful to obtain novel insights into some challenging nanomechanical problems. In this work, we employed artificial neural networks to predict the fracture stress of defective graphene samples. First, shallow neural networks were used to predict the fracture stress, which depends on the temperature, vacancy concentration, strain rate, and loading direction.

Postdoctoral vacancy (3 years) on high-frequency vibration techniques for non-destructive inspection of 3D printed metal parts

Submitted by wvpaepeg on

 

The use of 3D printed metal structures is taking a very fast ramp-up in industry. General Electric has demonstrated the possibility of printing titanium fuel injectors for their LEAP engine, EADS has printed a nacelle hinge bracket for the Airbus A320, Boeing is printing plastic inlet ducts for high-altitude aircrafts, hip implants and other prosthetics are exploiting the design freedom of additive manufacturing (AM),...

On Weingarten-Volterra defects

Submitted by Amit Acharya on

Amit Acharya

(in Journal of Elasticity)

The kinematic theory of Weingarten-Volterra line defects is revisited, both at small and fi nite deformations. Existing results are clari fied and corrected as needed, and new results are obtained. The primary focus is to understand the relationship between the disclination strength and Burgers vector of deformations containing a Weingarten-Volterra defect corresponding to di fferent cut-surfaces.

Small-on-Large Geometric Anelasticity

Submitted by arash_yavari on

In this paper we are concerned with finding exact solutions for the stress fields of nonlinear solids with non-symmetric distributions of defects (or more generally finite eigenstrains) that are small perturbations of symmetric distributions of defects with known exact solutions. In the language of geometric mechanics this corresponds to finding a deformation that is a result of a perturbation of the metric of the Riemannian material manifold. We present a general framework that can be used for a systematic analysis of this class of anelasticity problems.

"Imperfection" in graphene oxide invites surprising properties in a mechano-chemical way

Submitted by Xiaoding Wei on

In an article published in the August 20 issue of Nature Communications, we report a mechanochemical phenomenon in graphene oxide membranes, covalent epoxide-to-ether functional group transformations that deviate from epoxide ring-opening reactions, discovered through nanomechanical experiments and density functional-based tight binding calculations.