Mohit Pundir

Last Name

Pundir

First Name

Mohit

ORCID

0000-0001-7244-7416

Organisational unit

09650 - Kammer, David / Kammer, David

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Publications 1 - 10 of 29

Transonic and Supershear Crack Propagation Driven by Geometric Nonlinearities
Pundir, Mohit; Adda-Bedia, Mokhtar; Kammer, David S. (2024)
Physical Review Letters
Linear elastic fracture mechanics theory predicts that the speed of crack growth is limited by the Rayleigh wave speed. Although many experimental observations and numerical simulations have supported this prediction, some exceptions have raised questions about its validity. The underlying reasons for these discrepancies and the precise limiting speed of dynamic cracks remain unknown. Here, we demonstrate that tensile (mode I) cracks can exceed the Rayleigh wave speed and propagate at supershear speeds. We show that taking into account geometric nonlinearities, inherent in most materials, is sufficient to enable such propagation modes. These geometric nonlinearities modify the crack-tip singularity, resulting in different crack-tip opening displacements, cohesive zone behavior, and energy flows towards the crack tip.
Learning physics-consistent material behavior from dynamic displacements
Han, Zhichao; Pundir, Mohit; Fink, Olga; et al. (2025)
Computer Methods in Applied Mechanics and Engineering
Accurately modeling the mechanical behavior of materials is crucial for numerous engineering applications. The quality of these models depends directly on the accuracy of the constitutive law that defines the stress–strain relation. However, discovering these constitutive material laws remains a significant challenge, in particular when only material deformation data is available. To address this challenge, unsupervised machine learning methods have been proposed to learn the constitutive law from deformation data. Nonetheless, existing approaches have several limitations: they either fail to ensure that the learned constitutive relations are consistent with physical principles, or they rely on boundary force data for training which are unavailable in many in-situ scenarios. Here, we introduce a machine learning approach to learn physics-consistent constitutive relations solely from material deformation without boundary force information. This is achieved by considering a dynamic formulation rather than static equilibrium data and applying an input convex neural network (ICNN). We validate the effectiveness of the proposed method on a diverse range of hyperelastic material laws. We demonstrate that it is robust to a significant level of noise and that it converges to the ground truth with increasing data resolution. We also show that the model can be effectively trained using a displacement field from a subdomain of the test specimen and that the learned constitutive relation from one material sample is transferable to other samples with different geometries. The developed methodology provides an effective tool for discovering constitutive relations. It is, due to its design based on dynamics, particularly suited for applications to strain-rate-dependent materials and situations where constitutive laws need to be inferred from in-situ measurements without access to global force data.
Frictional Contact in an Eulerian Phase-Field Framework
Lorez, Flavio; Pundir, Mohit; Kammer, David S. (2025)
Corrosion-induced concrete cracking - a poromechanical, multi-scale approach
Pundir, Mohit; Kammer, David S.; Angst, Ueli (2022)
Effect of stochastic nature of pore structure on corrosion-driven mechanisms in concrete
Pundir, Mohit; Angst, Ueli; Kammer, David S. (2022)
Modeling solid-solid contact in a fully Eulerian phase-field framework
Lorez, Flavio; Pundir, Mohit; Kammer, David S. (2024)
On the failure of beam-like topologically interlocked structures
Koureas, Ioannis; Pundir, Mohit; Feldfogel, Shai; et al. (2022)
International Journal of Solids and Structures
Topologically interlocked structures are architectured by fitting together blocks that are constrained geometrically through contact and friction by their neighboring blocks. As long as the frictional strength is nowhere exceeded, the blocks stick against each other, allowing for large rotations. Once the interfacial stresses exceed the frictional strength, relative sliding between the blocks alters the structure’s mechanical response. Improving the structural performance, precisely the strength and the toughness, has been one of the main focal points in the literature. However, many fundamental questions regarding the role and effect of the interface mechanisms (stick and slip) and rotation of the blocks have not been addressed yet. Here, we carry out a parametric analysis to understand the effect of Young’s modulus, friction coefficient, and geometry of the blocks on the dominance of the stick or slip-governed mechanism. We combine analytical and computational tools to analyze the failure mechanisms and the response capacities of beam-like topologically interlocked structures. This is achieved using the finite element method coupled with a penalty-based approach for enforcing contact constraints along interfaces. We show that the combination of the structure’s height and the friction coefficient controls whether the failure mechanism is slip-governed or stick-governed. Furthermore, we demonstrate that the sticking mechanism across all interfaces along with the rotation of the blocks dictates a saturation level to the mechanical performance of a given structure irrespective of geometric and material properties. This provides a theoretical upper bound for the structural response of topologically interlocked structures and establishes a theoretical benchmark of achievable performance.
Precipitation of corrosion products in macroscopic voids at the steel–concrete interface: observations, mechanisms and research needs
Mundra, Shishir; Rossi, Emanuele; Malenica, Luka; et al. (2025)
Materials and Structures
Macroscopic voids at the steel–concrete interface and their degree of saturation with an aqueous electrolyte are known to play an important role in the corrosion of steel in reinforced concrete. Irrespective of the exposure conditions and testing parameters, in the majority of studies corrosion products have been reported to consistently precipitate in a unique pattern within these macroscopic voids, preferentially along the void walls and growing inward. The underlying mechanisms governing corrosion product precipitation in macroscopic voids and their effects on long-term durability remain unclear. Through in-situ X-ray computed tomography observations, thermodynamic and kinetic considerations, and numerical modelling of water transport within macroscopic voids, here, we provide plausible hypotheses of the processes responsible for the precipitation of corrosion products along the walls of the voids. Understanding the mechanisms of corrosion product precipitation can offer insights into the development of stresses in and around the macroscopic interfacial void and the durability of reinforced concrete structures. This contribution also discusses opportunities for different avenues for research to elucidate several multiscale processes that influence the durability of reinforced concrete.
Exploring dynamic contact of soft solids with an Eulerian phase-field approach
Lorez , Flavio; Pundir, Mohit (2025)
International Journal of Solids and Structures
Dynamic contact of soft solids plays a role in many applications, from biomechanical impacts to manufacturing processes. Traditional Lagrangian methods often struggle with large deformations and rapidly evolving contact interfaces. Fully Eulerian approaches for solid–solid contact have remained few and contributions are mostly from the fluid–structure interaction community. In this work, we extend our previous Eulerian phase-field framework for static contact to solid dynamics. Our formulation employs multiple Eulerian fields – a phase-field for interface capturing, a reference map to model elasticity, and separate velocity fields for each body – to describe the state of different solids on a fixed mesh. Contact is resolved implicitly through a penalty-based approach that uses the overlap of phase-fields. Temporal integration is performed using the generalized-α method. Numerical examples demonstrate that translating the contact formulation to the dynamic case is straight-forward and that the total energy is well-conserved.
Simplifying FFT-based methods for solid mechanics with automatic differentiation
Pundir, Mohit; Kammer, David S. (2025)
Computer Methods in Applied Mechanics and Engineering
Fast-Fourier Transform (FFT) methods have been widely used in solid mechanics to address complex homogenization problems. However, current FFT-based methods face challenges that limit their applicability to intricate material models or complex mechanical problems. These challenges include the manual implementation of constitutive laws and the use of computationally expensive and complex algorithms to couple microscale mechanisms to macroscale material behavior. Here, we incorporate automatic differentiation (AD) within the FFT framework to mitigate these challenges. We demonstrate that AD-enhanced FFT-based methods can derive stress and tangent stiffness directly from energy density functionals, facilitating the extension of FFT-based methods to more intricate material models. Additionally, automatic differentiation simplifies the calculation of homogenized tangent stiffness for microstructures with complex architectures and constitutive properties. This enhancement renders current FFT-based methods more modular, enabling them to tackle homogenization in complex multiscale systems, especially those involving multiphysics processes. Furthermore, we illustrate the use of the AD-enhanced FFT method for problems that extend beyond homogenization, such as uncertainty quantification and topology optimization where automatic differentiation simplifies the computation of sensitivities. Our work will simplify the numerical implementation of FFT-based methods for complex solid mechanics problems.

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Mohit Pundir

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