A generative modeling framework for inferring families of biomechanical constitutive laws in data-sparse regimes
Quantifying biomechanical properties of the human vasculature could deepen our
understanding of cardiovascular diseases. Standard nonlinear regression in constitutive …
understanding of cardiovascular diseases. Standard nonlinear regression in constitutive …
Polyconvex neural networks for hyperelastic constitutive models: A rectification approach
A simple approach to rectify unconstrained neural networks for hyperelastic constitutive
models is proposed with the aim of ensuring both mathematical well-posedness (in terms of …
models is proposed with the aim of ensuring both mathematical well-posedness (in terms of …
Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach
Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for
its environmental disposal. To reduce the number of laboratory experiments, this study …
its environmental disposal. To reduce the number of laboratory experiments, this study …
Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites
In this paper, we investigate the construction and identification of a new random field model
for representing the constitutive behavior of laminated composites. Here, the material is …
for representing the constitutive behavior of laminated composites. Here, the material is …
Quantification of uncertainties on the critical buckling load of columns under axial compression with uncertain random materials
This study is devoted to the modeling and simulation of uncertainties in the constitutive
elastic properties of material constituting a circular column under axial compression. To this …
elastic properties of material constituting a circular column under axial compression. To this …
Stochastic analysis of geometrically imperfect thin cylindrical shells using topology-aware uncertainty models
Buckling of thin-shell structures is one of the most canonical problems in mechanics. In
practice, the buckling load and its deviation from theoretical prediction is often handled …
practice, the buckling load and its deviation from theoretical prediction is often handled …
Random field simulation over curved surfaces: Applications to computational structural mechanics
It is important to account for inherent variability in the material properties in the design and
analysis of engineering structures. These properties are typically not homogeneous, but vary …
analysis of engineering structures. These properties are typically not homogeneous, but vary …
Concurrent multiscale simulations of nonlinear random materials using probabilistic learning
This work is concerned with the construction of statistical surrogates for concurrent
multiscale modeling in structures comprising nonlinear random materials. The development …
multiscale modeling in structures comprising nonlinear random materials. The development …
Stochastic modeling and identification of material parameters on structures produced by additive manufacturing
A methodology enabling the representation, sampling, and identification of spatially-
dependent stochastic material parameters on complex structures produced by additive …
dependent stochastic material parameters on complex structures produced by additive …
Stochastic modeling of geometrical uncertainties on complex domains, with application to additive manufacturing and brain interface geometries
We present a stochastic modeling framework to represent and simulate spatially-dependent
geometrical uncertainties on complex geometries. While the consideration of random …
geometrical uncertainties on complex geometries. While the consideration of random …