Johann Guilleminot

Research Themes

Computational Mechanics & Scientific Computing, Geomechanics & Geophysics for Energy and the Environment, Risk & Resilient Systems

Research Interests

Computational mechanics, mechanics of heterogeneous materials, molecular dynamics simulations and atomistic-to-continuum coupling, stochastic solvers, statistical inverse problem and model validation, stochastic analysis, uncertainty quantification in science and engineering

Bio

JohaGuilleminot is the Paul Ruffin Scarborough Associate Professor of Engineering and an Associate Professor of Civil and Environmental Engineering at Duke University. He joined Duke on July 1, 2017.

Prior to that, he held a Maître de Conférences position in the Multiscale Modeling and Simulation Laboratory at Université Paris-Est in France.

He earned an MS (2005) and PhD (2008) in Theoretical Mechanics from the University of Lille 1 Science and Technology (France), and received his Habilitation (2014) in Mechanics from Université Paris-Est. Habilitation is the highest academic degree in France.

Dr. Guilleminot’s research focuses on uncertainty quantification, computational mechanics and materials science, as well as on topics at the interface between these fields. He is particularly interested in the multiscale analysis of linear/nonlinear heterogeneous materials (including biological and engineered ones), homogenization theory, scientific machine learning, statistical inverse problems and stochastic modeling with applications for computational science and engineering.

Education

• M.S. Lille University of Science and Technology (France), 2005
• Ph.D. Lille University of Science and Technology (France), 2008

Positions

• Paul Ruffin Scarborough Associate Professor of Engineering
• Associate Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science

Courses Taught

• MENG 551: Master of Engineering Internship/Project Assessment
• MENG 550: Master of Engineering Internship/Project
• ME 758S: Curricular Practical Training
• ME 582: Applications in Data and Materials Science
• ME 524: Introduction to the Finite Element Method
• EGR 393: Research Projects in Engineering
• COMPSCI 583: Applications in Data and Materials Science
• CEE 780: Internship
• CEE 628: Uncertainty Quantification in Computational Science and Engineering
• CEE 530: Introduction to the Finite Element Method
• CEE 421L: Matrix Structural Analysis
• CEE 394: Research Independent Study in Civil and Environmental Engineering

Publications

• Zhang H, Mahabadi RK, Rudin C, Guilleminot J, Brinson LC. Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects (Accepted). Computers and Structures. 2024 Dec 1;305.
• Kounouho S, Dingreville R, Guilleminot J. Stochastic symplectic reduced-order modeling for model-form uncertainty quantification in molecular dynamics simulations in various statistical ensembles. Computer Methods in Applied Mechanics and Engineering. 2024 Nov 1;431.
• Quek A, Yi Yong J, Guilleminot J. Approximating Fracture Paths in Random Heterogeneous Materials: A Probabilistic Learning Perspective. Journal of Engineering Mechanics. 2024 Aug 1;150(8).
• Chu S, Iliopoulos A, Michopoulos J, Birnbaum A, Steuben J, Stewart C, et al. Microstructurally-informed stochastic inhomogeneity of material properties and material symmetries in 3D-printed 316 L stainless steel. Computational Mechanics. 2024 Jul 1;74(1):85–111.
• Zhang H, Guilleminot J. Operator learning for homogenizing hyperelastic materials, without PDE data. Mechanics Research Communications. 2024 Jun 1;138.
• Nguyen CT, Langlois V, Guilleminot J, Duval A, Perrot C. Effect of pore size polydispersity on the acoustic properties of high-porosity solid foams. Physics of Fluids. 2024 Apr 1;36(4).
• Chen P, Guilleminot J, Soize C. Concurrent multiscale simulations of nonlinear random materials using probabilistic learning. Computer Methods in Applied Mechanics and Engineering. 2024 Mar 15;422.
• Chen P, Hu T, Guilleminot J. A nonlinear-manifold reduced-order model and operator learning for partial differential equations with sharp solution gradients. Computer Methods in Applied Mechanics and Engineering. 2024 Feb 1;419.
• Zhang H, Dolbow JE, Guilleminot J. Representing model uncertainties in brittle fracture simulations. Computer Methods in Applied Mechanics and Engineering. 2024 Jan 5;418.
• Chu S, Iliopoulos A, Michopoulos J, Steuben J, Thomas J, Guilleminot J. Stochastic modeling of spatially-dependent elastoplastic parameters in 316L stainless steel produced by direct energy deposition. Mechanics of Materials. 2023 Dec 1;187.
• Zhang H, Guilleminot J. A Riemannian stochastic representation for quantifying model uncertainties in molecular dynamics simulations. Computer Methods in Applied Mechanics and Engineering. 2023 Jan 1;403.
• Chen P, Guilleminot J. Polyconvex neural networks for hyperelastic constitutive models: A rectification approach. Mechanics Research Communications. 2022 Oct 1;125.
• Nguyen CT, Langlois V, Guilleminot J, Detrez F, Duval A, Bornert M, et al. Polydisperse solid foams: Multiscale modeling and simulations of elasto-acoustic properties including thin membrane effects. International Journal of Solids and Structures. 2022 Aug 1;249.
• Chen P, Guilleminot J. Spatially-dependent material uncertainties in anisotropic nonlinear elasticity: Stochastic modeling, identification, and propagation. Computer Methods in Applied Mechanics and Engineering. 2022 May 1;394.
• Trinh VH, Guilleminot J, Perrot C, Vu VD. Learning acoustic responses from experiments: A multiscale-informed transfer learning approach. The Journal of the Acoustical Society of America. 2022 Apr;151(4):2587.
• Wang H, Guilleminot J, Schafer BW, Tootkaboni M. Stochastic analysis of geometrically imperfect thin cylindrical shells using topology-aware uncertainty models. Computer Methods in Applied Mechanics and Engineering. 2022 Apr 1;393.
• Zhang H, Gomez LJ, Guilleminot J. Uncertainty quantification of TMS simulations considering MRI segmentation errors. Journal of neural engineering. 2022 Mar;19(2).
• Langlois V, Nguyen CT, Detrez F, Guilleminot J, Perrot C. Permeability of polydisperse solid foams. Physical review E. 2022 Jan;105(1–2):015101.
• Chu S, Guilleminot J, Kelly C, Abar B, Gall K. Stochastic Modeling and identification of material parameters on structures produced by additive manufacturing. Computer Methods in Applied Mechanics and Engineering. 2021 Dec 15;387.
• Hun DA, Yvonnet J, Guilleminot J, Dadda A, Tang AM, Bornert M. Desiccation cracking of heterogeneous clayey soil: Experiments, modeling and simulations. Engineering Fracture Mechanics. 2021 Dec 1;258.
• Trinh VH, Guilleminot J, Perrot C. On the sensitivity of the design of composite sound absorbing structures. Materials and Design. 2021 Nov 15;210.
• Zhang H, Guilleminot J, Gomez LJ. Stochastic modeling of geometrical uncertainties on complex domains, with application to additive manufacturing and brain interface geometries. Computer Methods in Applied Mechanics and Engineering. 2021 Nov 1;385.
• Mihai LA, Wang H, Guilleminot J, Goriely A. Nematic liquid crystalline elastomers are aeolotropic materials. Proceedings Mathematical, physical, and engineering sciences. 2021 Sep;477(2253):20210259.
• Nguyen CT, Guilleminot J, Detrez F, Langlois V, Bornert M, Duval A, et al. Micro-Macro Acoustic Modeling of Heterogeneous Foams with Nucleation Perturbation. In: SAE Technical Papers. 2020.
• Hu T, Guilleminot J, Dolbow JE. A phase-field model of fracture with frictionless contact and random fracture properties: Application to thin-film fracture and soil desiccation. Computer Methods in Applied Mechanics and Engineering. 2020 Aug 15;368.
• Guilleminot J, Dolbow JE. Data-driven enhancement of fracture paths in random composites. Mechanics Research Communications. 2020 Jan 1;103.
• Guilleminot J. Modeling non-Gaussian random fields of material properties in multiscale mechanics of materials. In: Uncertainty Quantification in Multiscale Materials Modeling. 2020. p. 385–420.
• Hun DA, Guilleminot J, Yvonnet J, Bornert M. Stochastic multiscale modeling of crack propagation in random heterogeneous media. International Journal for Numerical Methods in Engineering. 2019 Sep 28;119(13):1325–44.
• Guilleminot J, Asadpoure A, Tootkaboni M. Topology optimization under topologically dependent material uncertainties. Structural and Multidisciplinary Optimization. 2019 Sep 15;60(3):1283–7.
• Wang H, Guilleminot J, Soize C. Modeling uncertainties in molecular dynamics simulations using a stochastic reduced-order basis. Computer Methods in Applied Mechanics and Engineering. 2019 Sep 1;354:37–55.
• Staber B, Guilleminot J, Soize C, Michopoulos J, Iliopoulos A. Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites. Computer Methods in Applied Mechanics and Engineering. 2019 Apr 15;347:425–44.
• Chu S, Guilleminot J. Stochastic multiscale modeling with random fields of material properties defined on nonconvex domains. Mechanics Research Communications. 2019 Apr 1;97:39–45.
• Trinh VH, Langlois V, Guilleminot J, Perrot C, Khidas Y, Pitois O. Tuning membrane content of sound absorbing cellular foams: Fabrication, experimental evidence and multiscale numerical simulations. Materials and Design. 2019 Jan 15;162:345–61.
• Colomés O, Scovazzi G, Guilleminot J. On the robustness of variational multiscale error estimators for the forward propagation of uncertainty. Computer Methods in Applied Mechanics and Engineering. 2018 Dec 1;342:384–413.
• Tran VP, Brisard S, Guilleminot J, Sab K. Mori–Tanaka estimates of the effective elastic properties of stress-gradient composites. International Journal of Solids and Structures. 2018 Aug 1;146:55–68.
• He M, Perrot C, Guilleminot J, Leroy P, Jacqus G. Multiscale prediction of acoustic properties for glass wools: Computational study and experimental validation. In: The Journal of the Acoustical Society of America. 2018. p. 3283.
• Staber B, Guilleminot J. A random field model for anisotropic strain energy functions and its application for uncertainty quantification in vascular mechanics. Computer Methods in Applied Mechanics and Engineering. 2018 May 1;333:94–113.
• Trinh VH, Guilleminot J, Perrot C. On the construction of multiscale surrogates for design optimization of acoustical materials. Acta Acustica united with Acustica. 2018 Jan 1;104(1):1–4.
• Waseem A, Guilleminot J, Temizer. Stochastic multiscale analysis in hydrodynamic lubrication. International Journal for Numerical Methods in Engineering. 2017 Nov 23;112(8):1070–93.
• Staber B, Guilleminot J. Stochastic modeling and generation of random fields of elasticity tensors: A unified information-theoretic approach. Comptes Rendus - Mecanique. 2017 Jun 1;345(6):399–416.
• Staber B, Guilleminot J. Stochastic modeling of the Ogden class of stored energy functions for hyperelastic materials: the compressible case. ZAMM Zeitschrift fur Angewandte Mathematik und Mechanik. 2017 Mar 1;97(3):273–95.
• Staber B, Guilleminot J. Functional approximation and projection of stored energy functions in computational homogenization of hyperelastic materials: A probabilistic perspective. Computer Methods in Applied Mechanics and Engineering. 2017 Jan 1;313:1–27.
• Staber B, Guilleminot J. Stochastic hyperelastic constitutive laws and identification procedure for soft biological tissues with intrinsic variability. Journal of the mechanical behavior of biomedical materials. 2017 Jan;65:743–52.
• Le TT, Guilleminot J, Soize C. Stochastic continuum modeling of random interphases from atomistic simulations. Application to a polymer nanocomposite. Computer Methods in Applied Mechanics and Engineering. 2016 May 1;303:430–49.
• Tran VP, Guilleminot J, Brisard S, Sab K. Stochastic modeling of mesoscopic elasticity random field. Mechanics of Materials. 2016 Feb 1;93:1–12.
• Staber B, Guilleminot J. Stochastic modeling of a class of stored energy functions for incompressible hyperelastic materials with uncertainties. Comptes Rendus - Mecanique. 2015 Sep 1;343(9):503–14.
• Soize C, Desceliers C, Guilleminot J, Le TT, Nguyen MT, Perrin G, et al. Stochastic representations and statistical inverse identification for uncertainty quantification in computational mechanics. In: UNCECOMP 2015 - 1st ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and Engineering. 2015. p. 1–26.
• Staber B, Guilleminot J. Approximate solutions of lagrange multipliers for information-theoretic random field models. SIAM-ASA Journal on Uncertainty Quantification. 2015 Jan 1;3(1):599–621.
• Guilleminot J, Soize C. Itô SDE-based generator for a class of non-Gaussian vector-valued random fields in uncertainty quantification. SIAM Journal on Scientific Computing. 2014 Jan 1;36(6):A2763–86.
• Baydoun I, Savin, Cottereau R, Clouteau D, Guilleminot J. Kinetic modeling of multiple scattering of elastic waves in heterogeneous anisotropic media. Wave Motion. 2014 Jan 1;51(8):1325–48.
• Guilleminot J, Soize C. Generation of non-gaussian tensor-valued random fields using an isde-based algorithm. In: Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013. 2013. p. 2793–8.
• Guilleminot J, Le TT, Soize C. Stochastic framework for modeling the linear apparent behavior of complex materials: Application to random porous materials with interphases. Acta Mechanica Sinica/Lixue Xuebao. 2013 Dec 1;29(6):773–82.
• Guilleminot J, Soize C. On the statistical dependence for the components of random elasticity tensors exhibiting material symmetry properties. Journal of Elasticity. 2013 Apr 1;111(2):109–30.
• Noshadravan A, Ghanem R, Guilleminot J, Atodaria I, Peralta P. VALIDATION OF A PROBABILISTIC MODEL FOR MESOSCALE ELASTICITY TENSOR OF RANDOM POLYCRYSTALS. International Journal for Uncertainty Quantification. 2013;3(1):73–100.
• Guilleminot J, Soize C. Prior representations of random fields for stochastic multiscale modeling. In: Procedia IUTAM. 2013. p. 44–9.
• Guilleminot J, Soize C. Stochastic model and generator for random fields with symmetry properties: Application to the mesoscopic modeling of elastic random media. Multiscale Modeling and Simulation. 2013 Jan 1;11(3):840–70.
• Guilleminot J, Soize C, Ghanem RG. Stochastic representation for anisotropic permeability tensor random fields. International Journal for Numerical and Analytical Methods in Geomechanics. 2012 Sep 1;36(13):1592–608.
• Guilleminot J, Soize C. Generalized stochastic approach for constitutive equation in linear elasticity: A random matrix model. International Journal for Numerical Methods in Engineering. 2012 May 4;90(5):613–35.
• Guilleminot J, Soize C. Probabilistic modeling of apparent tensors in elastostatics: A MaxEnt approach under material symmetry and stochastic boundedness constraints. In: Probabilistic Engineering Mechanics. 2012. p. 118–24.
• Guilleminot J, Soize C. Stochastic modeling of anisotropy in multiscale analysis of heterogeneous materials: A comprehensive overview on random matrix approaches. Mechanics of Materials. 2012 Jan 1;44:35–46.
• Guilleminot J, Soize C. Non-Gaussian positive-definite matrix-valued random fields with constrained eigenvalues: Application to random elasticity tensors with uncertain material symmetries. International Journal for Numerical Methods in Engineering. 2011 Dec 16;88(11):1128–51.
• Guilleminot J, Noshadravan A, Soize C, Ghanem RG. A probabilistic model for bounded elasticity tensor random fields with application to polycrystalline microstructures. Computer Methods in Applied Mechanics and Engineering. 2011 Apr 1;200(17–20):1637–48.
• Guilleminot J, Soize C. A stochastic model for elasticity tensors with uncertain material symmetries. International Journal of Solids and Structures. 2010 Nov 1;47(22–23):3121–30.
• Guilleminot J, Soize C, Kondo D. Mesoscale probabilistic models for the elasticity tensor of fiber reinforced composites: Experimental identification and numerical aspects. Mechanics of Materials. 2009 Dec 1;41(12):1309–22.
• Guilleminot J, Soize C, Kondo D, Binétruy C. Stochastic modeling of the mesoscopic elasticity tensor random field for composite materials. In: ICCM International Conferences on Composite Materials. 2009.
• Schell JSU, Guilleminot J, Binetruy C, Krawczak P. Computational and experimental analysis of fusion bonding in thermoplastic composites: Influence of process parameters. Journal of Materials Processing Technology. 2009 Jun 21;209(11):5211–9.
• Guilleminot J, Soize C, Kondo D, Binétruy C. Stochastic modeling of the mesoscopic elasticity tensor random field for composite materials. In: ICCM International Conferences on Composite Materials. 2009.
• Guilleminot J, Soize C, Kondo D, Binetruy C. Theoretical framework and experimental procedure for modelling mesoscopic volume fraction stochastic fluctuations in fiber reinforced composites. International Journal of Solids and Structures. 2008 Oct 15;45(21):5567–83.
• Guilleminot J, Soize C, Kondo D, Binetruy C. Stochastic model identification of fibre-reinforced composites at the mesoscale. JEC Composites Magazine. 2008 Jan 1;45(45):73–4.
• Guilleminot J, Soize C, Kondo D, Binetruy C. Stochastic model identification of fibre-reinforced composites at the mesoscale. JEC Composites Magazine. 2008 Jan 1;45(45):73–4.
• Guilleminot J, Comas-Cardona S, Kondo D, Binetruy C, Krawczak P. Multiscale modelling of the composite reinforced foam core of a 3D sandwich structure. Composites Science and Technology. 2008 Jan 1;68(7–8):1777–86.
• Guilleminot J, Deléglise M, Binétruy C, Krawczak P. Stochastic modeling of resin flow in fibrous media in liquid composite molding. In: ICCM International Conferences on Composite Materials. 2007.
• Guilleminot J, Kondo D, Binetruy C, Panier S, Hariri S, Krawczak P. A micromechanical analysis of a local failure criterion for particle-reinforced composites. Composites Science and Technology. 2007 Sep 1;67(11–12):2384–9.
• Guilleminot J, Deléglise M, Binétruy C, Krawczak P. Stochastic modeling of resin flow in fibrous media in liquid composite molding. In: ICCM International Conferences on Composite Materials. 2007.
• Robert A, Grillot JP, Guilleminot J, Raabe M. Experimental and ultrastructural study of the control of ovulation and parturition in the tsetse fly Glossina fuscipes (Diptera). Journal of Insect Physiology. 1984 Jan;30(8):671–84.