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Iwona Jasiuk

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Dr. Iwona Jasiuk is a professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign. Dr. Jasiuk’s research interests focus on the mechanics of materials for medical, aerospace, energy, and other technological applications. Her projects address the design, manufacture, characterization, and modeling of composite and nanocomposite materials, architectured materials, and studies of biological and bioinspired materials.

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Papers by Iwona Jasiuk

On Stiffness, Strength, Anisotropy, and Buckling of 30 Strut‐Based Lattices with Cubic Crystal Structures

Advanced Engineering Materials, 2021

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads

arXiv (Cornell University), Jun 6, 2023

Cracking of Plates With Randomly Distributed Holes by a Maximum Entropy Method

It has recently been shown [1] that fracture response of nominally identical elastic-brittle (epo... more It has recently been shown [1] that fracture response of nominally identical elastic-brittle (epoxy) as well as ductile (aluminum) sheets, each containing randomly distributed circular holes, is non-unique. This non-uniqueness pertains, in particular, to the resulting fracture patterns and effective stress-strain curves, whereby both of these characteristics display considerable scatter. This result points to the significant influence which microscale random noise in material parameters may have on the global, macroscopic behavior. In this paper we formulate, on the basis of a maximum entropy method [2], a stochastic fracture mechanics model for this class of problems. The method is based on the statistics of experimental data, obtained for a number of specimens, involving the inter-hole crack lengths and their angles. It allows prediction of probability distributions of damage responses and patterns of Gibbs ensembles of random hole systems such as, for example, porous materials with millions of voids.

Effect of filler alignment on percolation in polymer nanocomposites using tunneling-percolation model

Journal of Applied Physics, Jul 27, 2016

Tunneling-percolation model of multicomponent nanocomposites

Journal of Applied Physics, Feb 28, 2018

Scale and boundary conditions effects in elasticity and damage mechanics of random composites

Studies in Applied Mechanics, 1998

Spatial randomness, as opposed to periodic geometries, may have a significant effect on damage fo... more Spatial randomness, as opposed to periodic geometries, may have a significant effect on damage formation in composite materials. This issue was studied extensively over the last few years [1, 2, 3, 4], and in this paper we report new results on effects of scale and boundary conditions in the determination of meso-scale continuum-type models for elasticity and fracture. These models are formulated on scales larger than the single inclusion, yet smaller than the conventional continuum limit. The latter corresponds to the classical concept of aRepresentative Volume Element (RVE) which presupposes the presence representation of the microstructure with all the typical microheterogeneities, and thus calls for relatively large volumes. Indeed, according to Hill [5], an RVE should be such that the relations between volume average stress and strain should be the same regardless of whether kinematic or stress boundary conditions have been used.

Acoustic band gaps and elastic stiffness of PMMA cellular solids based on triply periodic minimal surfaces

Materials & Design, May 1, 2018

Nanofiller Geometry Effects on Electrical Properties of Composites

Nanofillers with highly anisotropic shapes, such as carbon nanotubes, graphene nanoplatelets, car... more Nanofillers with highly anisotropic shapes, such as carbon nanotubes, graphene nanoplatelets, carbon black, and metallic nanowires are used as inclusions in polymer matrix materials to generate nanocomposites with superior electrical, mechanical, and thermal properties. In this paper, we report on our recent and ongoing studies focusing on the enhanced effective electrical conductivity of such composites. First, we report on Monte Carlo simulations of systems of polydisperse prolate and oblate ellipsoids using the critical path-based tunneling-percolation mode. For polydisperse prolate ellipsoids, the critical percolation volume fraction, c  , is shown to have a quasi-universal dependence on the weight-averaged aspect ratio. For polydisperse oblate ellipsoids, c  is shown to have a quasi-universal dependence on the apparent aspect ratio, which is a function of up to fourth moment of the size distribution, as given by percolation theory. In both cases, the function approaches the theoretical predictions for higher volume fractions and higher aspect ratios. The model predictions are then compared with experimental data to estimate the tunneling length scale which is found to be within the expected range. Next, we examine the effect of filler alignment on percolation behavior of nanocomposites using Monte Carlo simulations of monodisperse prolate and oblate hard-core soft-shell ellipsoids representing carbon nanotubes and graphene nanoplatelets, respectively. As expected, the percolation threshold is observed to increase with increasing extent of alignment. For a highly aligned system of rod-like fillers, the simulation results are shown to be in good agreement with the second virial approximation-based predictions. However, for a highly aligned system of disk-like fillers, the second virial approximation-based results are observed to significantly deviate from the simulations, even for higher aspect ratios. The anisotropy in percolation threshold is found to vanish with increasing system size even for highly aligned systems of fillers.

LatticeOPT: a heuristic topology optimization framework for thin-walled, 2D extruded lattices

Structural and Multidisciplinary Optimization, Oct 20, 2022

Optimizing Hyperparameters and Architecture of Deep Energy Method

Compression and buckling of microarchitectured Neovius-lattice

Extreme Mechanics Letters, May 1, 2020

Couple-stress moduli and characteristics length of a two-phase composite

Mechanics Research Communications, Jul 1, 1999

An Overview on Additive Manufacturing of Polymers

JOM, Jan 25, 2018

Improving the Accuracy of the Deep Energy Method

On the use of graph neural networks and shape-function-based gradient computation in the deep energy method

arXiv (Cornell University), Jul 14, 2022

Direct Numerical Simulation of Bone Plasticity and Strength

Bioinspired Architectured Materials with Interpenetrating Phases

Micropolar model of trabecular bone

1999 Bioengineering Conference, Dec 1, 1999

Modeling of Stiffness and Strength of Bone at Nanoscale

Journal of biomechanical engineering, Apr 6, 2017

Effect of the cross-section architecture on the impact resistance of bio-inspired low-porosity structures using neural networks

arXiv (Cornell University), Jul 3, 2023

On Stiffness, Strength, Anisotropy, and Buckling of 30 Strut‐Based Lattices with Cubic Crystal Structures

Advanced Engineering Materials, 2021

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads

arXiv (Cornell University), Jun 6, 2023

Cracking of Plates With Randomly Distributed Holes by a Maximum Entropy Method

It has recently been shown [1] that fracture response of nominally identical elastic-brittle (epo... more It has recently been shown [1] that fracture response of nominally identical elastic-brittle (epoxy) as well as ductile (aluminum) sheets, each containing randomly distributed circular holes, is non-unique. This non-uniqueness pertains, in particular, to the resulting fracture patterns and effective stress-strain curves, whereby both of these characteristics display considerable scatter. This result points to the significant influence which microscale random noise in material parameters may have on the global, macroscopic behavior. In this paper we formulate, on the basis of a maximum entropy method [2], a stochastic fracture mechanics model for this class of problems. The method is based on the statistics of experimental data, obtained for a number of specimens, involving the inter-hole crack lengths and their angles. It allows prediction of probability distributions of damage responses and patterns of Gibbs ensembles of random hole systems such as, for example, porous materials with millions of voids.

Effect of filler alignment on percolation in polymer nanocomposites using tunneling-percolation model

Journal of Applied Physics, Jul 27, 2016

Tunneling-percolation model of multicomponent nanocomposites

Journal of Applied Physics, Feb 28, 2018

Scale and boundary conditions effects in elasticity and damage mechanics of random composites

Studies in Applied Mechanics, 1998

Spatial randomness, as opposed to periodic geometries, may have a significant effect on damage fo... more Spatial randomness, as opposed to periodic geometries, may have a significant effect on damage formation in composite materials. This issue was studied extensively over the last few years [1, 2, 3, 4], and in this paper we report new results on effects of scale and boundary conditions in the determination of meso-scale continuum-type models for elasticity and fracture. These models are formulated on scales larger than the single inclusion, yet smaller than the conventional continuum limit. The latter corresponds to the classical concept of aRepresentative Volume Element (RVE) which presupposes the presence representation of the microstructure with all the typical microheterogeneities, and thus calls for relatively large volumes. Indeed, according to Hill [5], an RVE should be such that the relations between volume average stress and strain should be the same regardless of whether kinematic or stress boundary conditions have been used.

Acoustic band gaps and elastic stiffness of PMMA cellular solids based on triply periodic minimal surfaces

Materials & Design, May 1, 2018

Nanofiller Geometry Effects on Electrical Properties of Composites

Nanofillers with highly anisotropic shapes, such as carbon nanotubes, graphene nanoplatelets, car... more Nanofillers with highly anisotropic shapes, such as carbon nanotubes, graphene nanoplatelets, carbon black, and metallic nanowires are used as inclusions in polymer matrix materials to generate nanocomposites with superior electrical, mechanical, and thermal properties. In this paper, we report on our recent and ongoing studies focusing on the enhanced effective electrical conductivity of such composites. First, we report on Monte Carlo simulations of systems of polydisperse prolate and oblate ellipsoids using the critical path-based tunneling-percolation mode. For polydisperse prolate ellipsoids, the critical percolation volume fraction, c  , is shown to have a quasi-universal dependence on the weight-averaged aspect ratio. For polydisperse oblate ellipsoids, c  is shown to have a quasi-universal dependence on the apparent aspect ratio, which is a function of up to fourth moment of the size distribution, as given by percolation theory. In both cases, the function approaches the theoretical predictions for higher volume fractions and higher aspect ratios. The model predictions are then compared with experimental data to estimate the tunneling length scale which is found to be within the expected range. Next, we examine the effect of filler alignment on percolation behavior of nanocomposites using Monte Carlo simulations of monodisperse prolate and oblate hard-core soft-shell ellipsoids representing carbon nanotubes and graphene nanoplatelets, respectively. As expected, the percolation threshold is observed to increase with increasing extent of alignment. For a highly aligned system of rod-like fillers, the simulation results are shown to be in good agreement with the second virial approximation-based predictions. However, for a highly aligned system of disk-like fillers, the second virial approximation-based results are observed to significantly deviate from the simulations, even for higher aspect ratios. The anisotropy in percolation threshold is found to vanish with increasing system size even for highly aligned systems of fillers.

LatticeOPT: a heuristic topology optimization framework for thin-walled, 2D extruded lattices

Structural and Multidisciplinary Optimization, Oct 20, 2022

Optimizing Hyperparameters and Architecture of Deep Energy Method

Compression and buckling of microarchitectured Neovius-lattice

Extreme Mechanics Letters, May 1, 2020

Couple-stress moduli and characteristics length of a two-phase composite

Mechanics Research Communications, Jul 1, 1999

An Overview on Additive Manufacturing of Polymers

JOM, Jan 25, 2018

Improving the Accuracy of the Deep Energy Method

On the use of graph neural networks and shape-function-based gradient computation in the deep energy method

arXiv (Cornell University), Jul 14, 2022

Direct Numerical Simulation of Bone Plasticity and Strength

Bioinspired Architectured Materials with Interpenetrating Phases

Micropolar model of trabecular bone

1999 Bioengineering Conference, Dec 1, 1999

Modeling of Stiffness and Strength of Bone at Nanoscale

Journal of biomechanical engineering, Apr 6, 2017

Effect of the cross-section architecture on the impact resistance of bio-inspired low-porosity structures using neural networks

arXiv (Cornell University), Jul 3, 2023