Johann Guilleminot

Journal article Theoretical and Applied Fracture Mechanics · July 1, 2026 This work develops a unified framework for inferring, representing, and statistically characterizing an anisotropic strength surface directly from molecular dynamics data. Large-scale tensile loading simulations are used to generate failure data across all ... Full text Cite

When model-form and parametric uncertainties matter: A unified stochastic representation for propagation and sensitivity analysis

Journal article Computer Methods in Applied Mechanics and Engineering · April 1, 2026 This work develops a new probabilistic framework for uncertainty quantification and sensitivity analysis in computational engineering, focusing on the case of mixed uncertainties arising from both parametric and model-form sources. We introduce a stochasti ... Full text Cite

Data generation with optimal experimental design for operator learning

Journal article Computer Methods in Applied Mechanics and Engineering · March 1, 2026 Partial differential equations (PDEs) are fundamental to modeling complex physical phenomena across scientific disciplines. While operator learning offers a promising alternative to conventional PDE solvers, it generally requires substantial high-fidelity ... Full text Cite

Examining crack nucleation under spatially uniform stress states with a complete phase-field model for fracture

Journal article Theoretical and Applied Fracture Mechanics · December 1, 2025 This work concerns crack nucleation problems in elastic brittle materials subjected to stress states that are spatially uniform or nearly so. Such conditions arise under a wide range of settings, including standard tests of material strength. This class of ... Full text Cite

Neural operators from the Cole–Hopf transformation: Leveraging relations between PDEs for efficient operator learning

Journal article Computer Methods in Applied Mechanics and Engineering · September 1, 2025 Partial differential equations (PDEs) constitute the primary theoretical tool to model complex physical phenomena across diverse scientific disciplines, from materials science to fluid dynamics. While (physics-informed) operator learning approaches have em ... Full text Cite

Enhancing robustness in machine-learning-accelerated molecular dynamics: A multi-model nonparametric probabilistic approach

Journal article Mechanics of Materials · March 1, 2025 In this work, we present a system-agnostic probabilistic framework to quantify model-form uncertainties in molecular dynamics (MD) simulations based on machine-learned (ML) interatomic potentials. Such uncertainties arise from the design and selection of M ... Full text Cite

Learning latent space dynamics with model-form uncertainties: A stochastic reduced-order modeling approach

Journal article Computer Methods in Applied Mechanics and Engineering · February 15, 2025 This paper presents a probabilistic approach to represent and quantify model-form uncertainties in the reduced-order modeling of complex systems using operator inference techniques. Such uncertainties can arise in the selection of an appropriate state–spac ... Full text Cite

Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects

Journal article Computers and Structures · December 1, 2024 Acoustic metamaterials are a subject of increasing study and utility. Through designed combinations of geometries with material properties, acoustic metamaterials can be built to arbitrarily manipulate acoustic waves for various applications. Despite the t ... Full text Cite

Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles

Journal article Computer Methods in Applied Mechanics and Engineering · November 1, 2024 This work focuses on the representation of model-form uncertainties in molecular dynamics simulations in various statistical ensembles. In prior contributions, the modeling of such uncertainties was formalized and applied to quantify the impact of, and the ... Full text Cite

Approximating Fracture Paths in Random Heterogeneous Materials: A Probabilistic Learning Perspective

Journal article Journal of Engineering Mechanics · August 1, 2024 Approximation frameworks for phase-field models of brittle fracture are presented and compared in this work. Such methods aim to address the computational cost associated with conducting full-scale simulations of brittle fracture in heterogeneous materials ... Full text Cite

Microstructurally-informed stochastic inhomogeneity of material properties and material symmetries in 3D-printed 316 L stainless steel

Journal article Computational Mechanics · July 1, 2024 Stochastic mesoscale inhomogeneity of material properties and material symmetries are investigated in a 3D-printed material. The analysis involves a spatially-dependent characterization of the microstructure in 316 L stainless steel, obtained through elect ... Full text Cite

Operator learning for homogenizing hyperelastic materials, without PDE data

Journal article Mechanics Research Communications · June 1, 2024 In this work, we address operator learning for stochastic homogenization in nonlinear elasticity. A Fourier neural operator is employed to learn the map between the input field describing the material at fine scale and the deformation map. We propose a var ... Full text Cite

Effect of pore size polydispersity on the acoustic properties of high-porosity solid foams

Journal article Physics of Fluids · April 1, 2024 This study investigates the influence of pore size polydispersity on the acoustic behavior of high-porosity solid foams using numerical simulations. The effect of the size of the periodic unit cell (PUC) on the transport parameters is first examined. It is ... Full text Cite

Concurrent multiscale simulations of nonlinear random materials using probabilistic learning

Journal article Computer Methods in Applied Mechanics and Engineering · March 15, 2024 This work is concerned with the construction of statistical surrogates for concurrent multiscale modeling in structures comprising nonlinear random materials. The development of surrogates approximating a homogenization operator is a fairly classical topic ... Full text Cite

A nonlinear-manifold reduced-order model and operator learning for partial differential equations with sharp solution gradients

Journal article Computer Methods in Applied Mechanics and Engineering · February 1, 2024 Traditional linear subspace-based reduced order models (LS-ROMs) can be used to significantly accelerate simulations in which the solution space of the discretized system has a small dimension (with a fast decaying Kolmogorov n-width). However, LS-ROMs str ... Full text Cite

Representing model uncertainties in brittle fracture simulations

Journal article Computer Methods in Applied Mechanics and Engineering · January 5, 2024 This work focuses on the representation of model-form uncertainties in phase-field models of brittle fracture. Such uncertainties can arise from the choice of the degradation function for instance, and their consideration has been unaddressed to date. The ... Full text Cite

Stochastic modeling of spatially-dependent elastoplastic parameters in 316L stainless steel produced by direct energy deposition

Journal article Mechanics of Materials · December 1, 2023 The stochastic modeling and calibration of an anisotropic elasto-plastic model for additive manufacturing materials are addressed in this work. We specifically focus on 316L stainless steel, produced by directed energy deposition. Tensile specimens machine ... Full text Cite

A Riemannian stochastic representation for quantifying model uncertainties in molecular dynamics simulations

Journal article Computer Methods in Applied Mechanics and Engineering · January 1, 2023 A Riemannian stochastic representation of model uncertainties in molecular dynamics is proposed. The approach relies on a reduced-order model, the projection basis of which is randomized on a subset of the Stiefel manifold characterized by a set of linear ... Full text Cite

Polyconvex neural networks for hyperelastic constitutive models: A rectification approach

Journal article Mechanics Research Communications · October 1, 2022 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 existence theorems) and physical consistency. The surrogate involves neural n ... Full text Cite

Polydisperse solid foams: Multiscale modeling and simulations of elasto-acoustic properties including thin membrane effects

Journal article International Journal of Solids and Structures · August 1, 2022 This work is concerned with the prediction of the elasto-acoustic properties of polydisperse solid foam structures. A highly polydisperse foam sample is first characterized using microtomography and scanning electron microscopy. Relevant geometrical proper ... Full text Cite

Spatially-dependent material uncertainties in anisotropic nonlinear elasticity: Stochastic modeling, identification, and propagation

Journal article Computer Methods in Applied Mechanics and Engineering · May 1, 2022 This paper develops a stochastic model for the spatially-dependent material parameters parameterizing anisotropic strain energy density functions. The construction is cast within the framework of information theory, which is invoked to derive a least-infor ... Full text Cite

Stochastic analysis of geometrically imperfect thin cylindrical shells using topology-aware uncertainty models

Journal article Computer Methods in Applied Mechanics and Engineering · April 1, 2022 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 through the development of knock-down factors in shell structure design. Unc ... Full text Cite

Learning acoustic responses from experiments: A multiscale-informed transfer learning approach.

Journal article The Journal of the Acoustical Society of America · April 2022 A methodology to learn acoustical responses based on limited experimental datasets is presented. From a methodological standpoint, the approach involves a multiscale-informed encoder used to cast the learning task in a finite-dimensional setting. A neural ... Full text Cite

Uncertainty quantification of TMS simulations considering MRI segmentation errors.

Journal article Journal of neural engineering · March 2022 Objective.Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation method that is used to study brain function and conduct neuropsychiatric therapy. Computational methods that are commonly used for electric field (E-field) dosimet ... Full text Cite

Permeability of polydisperse solid foams.

Journal article Physical review. E · January 2022 The effect of polydispersity on foam permeability is investigated by numerical simulations. Foam structures are first generated by Laguerre tessellations via the Neper software and relaxed to minimize the surface energy via the Surface Evolver software. Th ... Full text Cite

Stochastic Modeling and identification of material parameters on structures produced by additive manufacturing

Journal article Computer Methods in Applied Mechanics and Engineering · December 15, 2021 A methodology enabling the representation, sampling, and identification of spatially-dependent stochastic material parameters on complex structures produced by additive manufacturing is presented. The modeling component builds upon earlier works by the aut ... Full text Cite

Desiccation cracking of heterogeneous clayey soil: Experiments, modeling and simulations

Journal article Engineering Fracture Mechanics · December 1, 2021 Experimental results for the cracking of heterogeneous clay samples during desiccation are reported, and an associated numerical model is developed for comparison. The clay samples contain embedded rigid inclusions to induce heterogeneous strain fields dur ... Full text Cite

On the sensitivity of the design of composite sound absorbing structures

Journal article Materials and Design · November 15, 2021 The acoustic properties of composite structures made of a perforated panel, an air gap, and a porous layer, can be studied numerically by a combined use of ad hoc optimization and sensitivity analysis methods. The methodology is briefly described and is sy ... Full text Cite

Stochastic modeling of geometrical uncertainties on complex domains, with application to additive manufacturing and brain interface geometries.

Journal article Computer methods in applied mechanics and engineering · November 2021 We present a stochastic modeling framework to represent and simulate spatially-dependent geometrical uncertainties on complex geometries. While the consideration of random geometrical perturbations has long been a subject of interest in computational engin ... Full text Cite

Nematic liquid crystalline elastomers are aeolotropic materials.

Journal article Proceedings. Mathematical, physical, and engineering sciences · September 2021 Continuum models describing ideal nematic solids are widely used in theoretical studies of liquid crystal elastomers. However, experiments on nematic elastomers show a type of anisotropic response that is not predicted by the ideal models. Therefore, their ... Full text Cite

A phase-field model of fracture with frictionless contact and random fracture properties: Application to thin-film fracture and soil desiccation

Journal article Computer Methods in Applied Mechanics and Engineering · August 15, 2020 We present a new derivation for a phase-field model of cohesive fracture that allows for fully-damaged surfaces to properly transmit tractions under frictionless contact conditions. The model is derived from an energy minimization standpoint, and the gover ... Full text Cite

Data-driven enhancement of fracture paths in random composites

Journal article Mechanics Research Communications · January 1, 2020 A data-driven framework for the enhancement of fracture paths in random heterogeneous microstructures is presented. The approach relies on the combination of manifold learning, introduced to explore the geometrical structure exhibited by crack patterns and ... Full text Cite

Stochastic multiscale modeling of crack propagation in random heterogeneous media

Journal article International Journal for Numerical Methods in Engineering · September 28, 2019 A stochastic approach to model crack propagation in random heterogeneous media, using mesoscopic representations of elastic and fracture properties, is presented. In order to obtain reference results, Monte-Carlo simulations are first conducted on microstr ... Full text Cite

Topology optimization under topologically dependent material uncertainties

Journal article Structural and Multidisciplinary Optimization · September 15, 2019 A methodology allowing for the algorithmic integration of topologically dependent random fields of material parameters in topology optimization processes is presented. A detailed example is provided to illustrate the methodology step by step. ... Full text Cite

Modeling uncertainties in molecular dynamics simulations using a stochastic reduced-order basis

Journal article Computer Methods in Applied Mechanics and Engineering · September 1, 2019 A methodology enabling the robust treatment of model-form uncertainties in molecular dynamics simulations is proposed. The approach consists in properly randomizing a reduced-order basis, obtained by the method of snapshots in the configuration space. A mu ... Full text Cite

Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites

Journal article Computer Methods in Applied Mechanics and Engineering · April 15, 2019 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 modeled as a random hyperelastic medium characterized by a spatially dep ... Full text Cite

Stochastic multiscale modeling with random fields of material properties defined on nonconvex domains

Journal article Mechanics Research Communications · April 1, 2019 A methodology to model and generate spatially dependent material uncertainties in stochastic multiscale analysis is proposed. The approach consists in defining non-Gaussian random fields through transport maps acting on Gaussian fields, defined by appropri ... Full text Cite

Tuning membrane content of sound absorbing cellular foams: Fabrication, experimental evidence and multiscale numerical simulations

Journal article Materials and Design · January 15, 2019 This work is focused on tailoring cellular foam membranes for sound absorption. Several foam configurations with a constant porosity and varying membrane content were first fabricated by using milli-fluidic techniques. This approach allows transport and so ... Full text Cite

On the robustness of variational multiscale error estimators for the forward propagation of uncertainty

Journal article Computer Methods in Applied Mechanics and Engineering · December 1, 2018 The numerical simulation of physical phenomena and engineering problems can be affected by numerical errors and various types of uncertainties. Characterizing the former in computational frameworks involving system parameter uncertainties becomes a key iss ... Full text Cite

Mori–Tanaka estimates of the effective elastic properties of stress-gradient composites

Journal article International Journal of Solids and Structures · August 1, 2018 A stress-gradient material model was recently proposed by Forest and Sab (Mech. Res. Comm. 40, 16–25, 2012) as an alternative to the well-known strain-gradient model introduced in the mid 60s. We propose a theoretical framework for the homogenization of st ... Full text Cite

A random field model for anisotropic strain energy functions and its application for uncertainty quantification in vascular mechanics

Journal article Computer Methods in Applied Mechanics and Engineering · May 1, 2018 This paper deals with the construction of random field models for spatially-dependent anisotropic strain energy functions indexed by complex geometries. The approach relies on information theory and the principle of maximum entropy, which are invoked in or ... Full text Cite

On the construction of multiscale surrogates for design optimization of acoustical materials

Journal article Acta Acustica United with Acustica · January 1, 2018 This paper is concerned with the use of polynomial metamodels for the design of acoustical materials, considered as equivalent fluids. Polynomial series in microstructural parameters are considered, and allow us to approximate the multiscale solution map i ... Full text Cite

Stochastic multiscale analysis in hydrodynamic lubrication

Journal article International Journal for Numerical Methods in Engineering · November 23, 2017 A stochastic multiscale analysis framework is developed for hydrodynamic lubrication problems with random surface roughness. The approach is based on a multi-resolution computational strategy wherein the deterministic solution of the multiscale problem for ... Full text Cite

Stochastic modeling and generation of random fields of elasticity tensors: A unified information-theoretic approach

Journal article Comptes Rendus Mecanique · June 1, 2017 Featured Publication In this Note, we present a unified approach to the information-theoretic modeling and simulation of a class of elasticity random fields, for all physical symmetry classes. The new stochastic representation builds upon a Walpole tensor decomposition, which ... Full text Cite

Stochastic modeling of the Ogden class of stored energy functions for hyperelastic materials: the compressible case

Journal article ZAMM Zeitschrift Fur Angewandte Mathematik Und Mechanik · March 1, 2017 Featured Publication This paper is devoted to the modeling of compressible hyperelastic materials whose response functions exhibit uncertainties at some scale of interest. The construction of parametric probabilistic representations for the Ogden class of stored energy functio ... Full text Cite

Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability.

Journal article Journal of the mechanical behavior of biomedical materials · January 2017 Featured Publication In this work, we address the constitutive modeling, in a probabilistic framework, of the hyperelastic response of soft biological tissues. The aim is on the one hand to mimic the mean behavior and variability that are typically encountered in the experimen ... Full text Cite

Functional approximation and projection of stored energy functions in computational homogenization of hyperelastic materials: A probabilistic perspective

Journal article Computer Methods in Applied Mechanics and Engineering · January 1, 2017 Featured Publication This work is concerned with the construction of a surrogate model for the homogenized stored energy functions defining the effective behavior of nonlinear elastic microstructures. Here, a probabilistic standpoint is adopted and allows for the definition of ... Full text Cite

Stochastic continuum modeling of random interphases from atomistic simulations. Application to a polymer nanocomposite

Journal article Computer Methods in Applied Mechanics and Engineering · May 1, 2016 Featured Publication This paper is concerned with the probabilistic multiscale analysis of polymeric materials reinforced by nanoscopic fillers. More precisely, this work is devoted to the stochastic modeling and inverse identification of the random field associated with the e ... Full text Cite

Stochastic modeling of mesoscopic elasticity random field

Journal article Mechanics of Materials · February 1, 2016 In the homogenization setting, the effective properties of a heterogeneous material can be retrieved from the solution of the so-called corrector problem. In some cases of practical interest, obtaining such a solution remains a challenging computational ta ... Full text Cite

Stochastic modeling of a class of stored energy functions for incompressible hyperelastic materials with uncertainties

Journal article Comptes Rendus Mecanique · September 1, 2015 In this Note, we address the construction of a class of stochastic Ogden's stored energy functions associated with incompressible hyperelastic materials. The methodology relies on the maximum entropy principle, which is formulated under constraints arising ... Full text Cite

Approximate solutions of lagrange multipliers for information-theoretic random field models

Journal article SIAM Asa Journal on Uncertainty Quantification · January 1, 2015 This work is concerned with the construction of approximate solutions for the Lagrange multipliers involved in information-theoretic non-Gaussian random field models. Specifically, representations of physical fields with invariance properties under some or ... Full text Cite

Kinetic modeling of multiple scattering of elastic waves in heterogeneous anisotropic media

Journal article Wave Motion · January 1, 2014 In this paper we develop a multiple scattering model for elastic waves in random anisotropic media. It relies on a kinetic approach of wave propagation phenomena pertaining to the situation whereby the wavelength is comparable to the correlation length of ... Full text Cite

Itô SDE-based generator for a class of non-Gaussian vector-valued random fields in uncertainty quantification

Journal article SIAM Journal on Scientific Computing · January 1, 2014 Featured Publication This paper is concerned with the derivation of a generic sampling technique for a class of non-Gaussian vector-valued random fields. Such an issue typically arises in uncertainty quantification for complex systems, where the input coefficients associated w ... Full text Cite

Stochastic framework for modeling the linear apparent behavior of complex materials: Application to random porous materials with interphases

Journal article Acta Mechanica Sinica Lixue Xuebao · December 1, 2013 This paper is concerned with the modeling of randomness in multiscale analysis of heterogeneous materials. More specifically, a framework dedicated to the stochastic modeling of random properties is first introduced. A probabilistic model for matrix-valued ... Full text Cite

On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties

Journal article Journal of Elasticity · April 1, 2013 This work is concerned with the characterization of the statistical dependence between the components of random elasticity tensors that exhibit some given material symmetries. Such an issue has historically been addressed with no particular reliance on pro ... Full text Cite

Stochastic model and generator for random fields with symmetry properties: Application to the mesoscopic modeling of elastic random media

Journal article Multiscale Modeling and Simulation · January 1, 2013 This paper is concerned with the construction of a new class of generalized nonparametric probabilistic models for matrix-valued non-Gaussian random fields. More specifically, we consider the case where the random field may take its values in some subset o ... Full text Cite

VALIDATION OF A PROBABILISTIC MODEL FOR MESOSCALE ELASTICITY TENSOR OF RANDOM POLYCRYSTALS

Journal article International Journal for Uncertainty Quantification · 2013 Full text Cite

Stochastic representation for anisotropic permeability tensor random fields

Journal article International Journal for Numerical and Analytical Methods in Geomechanics · September 1, 2012 In this paper, we introduce a novel stochastic model for the permeability tensor associated with stationary random porous media. In the light of recent works on mesoscale modeling of permeability, we first discuss the physical interpretation of the permeab ... Full text Cite

Generalized stochastic approach for constitutive equation in linear elasticity: A random matrix model

Journal article International Journal for Numerical Methods in Engineering · May 4, 2012 This work is concerned with the construction of stochastic models for random elasticity matrices, allowing either for the generation of elasticity tensors exhibiting some material symmetry properties almost surely (integrating the statistical dependence be ... Full text Cite

Stochastic modeling of anisotropy in multiscale analysis of heterogeneous materials: A comprehensive overview on random matrix approaches

Journal article Mechanics of Materials · January 1, 2012 The aim of this paper is to provide a general overview on random matrix ensembles for modeling stochastic elasticity tensors that exhibit uncertainties on material symmetries. Such an issue is of primal importance in many practical situations involving eit ... Full text Cite

Non-Gaussian positive-definite matrix-valued random fields with constrained eigenvalues: Application to random elasticity tensors with uncertain material symmetries

Journal article International Journal for Numerical Methods in Engineering · December 16, 2011 This paper is devoted to the construction of a class of prior stochastic models for non-Gaussian positive-definite matrix-valued random fields. The proposed class allows the variances of selected random eigenvalues to be specified and exhibits a larger num ... Full text Cite

A probabilistic model for bounded elasticity tensor random fields with application to polycrystalline microstructures

Journal article Computer Methods in Applied Mechanics and Engineering · April 1, 2011 In this paper, we address the construction of a prior stochastic model for non-Gaussian deterministically-bounded positive-definite matrix-valued random fields in the context of mesoscale modeling of heterogeneous elastic microstructures. We first introduc ... Full text Cite

A stochastic model for elasticity tensors with uncertain material symmetries

Journal article International Journal of Solids and Structures · November 1, 2010 In this paper, we consider the probabilistic modeling of media exhibiting uncertainties on material symmetries. More specifically, we address both the construction of a stochastic model and the definition of a methodology allowing the numerical simulation ... Full text Cite

Mesoscale probabilistic models for the elasticity tensor of fiber reinforced composites: Experimental identification and numerical aspects

Journal article Mechanics of Materials · December 1, 2009 This work deals with the computational and experimental identification of two probabilistic models. The first one was recently proposed in the literature and provides a direct stochastic representation of the mesoscopic elasticity tensor random field for a ... Full text Cite

Computational and experimental analysis of fusion bonding in thermoplastic composites: Influence of process parameters

Journal article Journal of Materials Processing Technology · June 21, 2009 A fundamental characteristic of composite materials is that the initial choice of fiber and matrix type together with the selected manufacturing process controls the properties of the final part. As the manufacturing process creates simultaneously the comp ... Full text Cite

Theoretical framework and experimental procedure for modelling mesoscopic volume fraction stochastic fluctuations in fiber reinforced composites

Journal article International Journal of Solids and Structures · October 15, 2008 Many engineering materials exhibit fluctuations and uncertainties on their macroscopic mechanical properties. This randomness results from random fluctuations observed at a lower scale, especially at the meso-scale where microstructural uncertainties gener ... Full text Cite

Multiscale modelling of the composite reinforced foam core of a 3D sandwich structure

Journal article Composites Science and Technology · January 1, 2008 A key objective dealing with 3D sandwich structures is to maximize the through-thickness stiffness, the strength of the core and the core to faces adhesion. The Napco® technology was especially designed for improving such material properties and ... Full text Cite

Stochastic model identification of fibre-reinforced composites at the mesoscale

Journal article JEC Composites Magazine · January 1, 2008 This paper introduces an approach that can be used to model the mechanical behaviour of fibre-reinforced composites exhibiting stochastic fluctuations in local volume fractions. In particular, a relevant theoretical framework is briefly introduced and a fe ... Cite

Stochastic model identification of fibre-reinforced composites at the mesoscale

A micromechanical analysis of a local failure criterion for particle-reinforced composites

Journal article Composites Science and Technology · September 1, 2007 The present paper aims at predicting the ultimate mechanical properties of a particle-reinforced polymer using a micromechanical approach of a local failure criterion. The considered criterion includes both normal and shear stresses at the interface betwee ... Full text Cite

Experimental and ultrastructural study of the control of ovulation and parturition in the tsetse fly Glossina fuscipes (Diptera)

Journal article Journal of Insect Physiology · January 1984 Full text Cite