Article
Materials Science, Multidisciplinary
G. Girard, M. Martiny, S. Mercier
Summary: This paper investigates the mechanical analysis of peel tests for a ductile film on an elastic substrate, proposing a new contribution by considering elastic-plastic behavior with combined kinematic-isotropic hardening. The validation of the theoretical work is established via finite element simulations of 90 degrees peel test, comparing materials with isotropic hardening and only kinematic hardening to quantify the role of kinematic hardening in predicting the interface fracture energy.
INTERNATIONAL JOURNAL OF FRACTURE
(2021)
Article
Engineering, Mechanical
Peter Zobec, Jernej Klemenc
Summary: This research highlights the importance of considering residual stress in the fatigue analysis of formed products, and demonstrates the differences in predicting residual stress state and strain accumulation through experimental observations and model comparisons.
INTERNATIONAL JOURNAL OF FATIGUE
(2021)
Article
Computer Science, Interdisciplinary Applications
K. Krabbenhoft, J. Krabbenhoft
Summary: A simplified kinematic hardening plasticity framework for constitutive modeling of soils is proposed, where yield surfaces are used to compute effective hardening modulus for efficient numerical implementation. The framework is detailed for total and effective stress analysis, and illustrated with a simple model for undrained total stress analysis of clays.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Engineering, Mechanical
Jianqiang Zhou, Kun Cui, Zhiyuan Xu, Zhidan Sun, Bruno Guelorget, Delphine Retraint
Summary: In this study, residual stress and coupled residual work hardening were investigated in a surface mechanical attrition treatment (SMAT) on a cylindrical structure using the discrete element method (DEM) and finite element method (FEM). The results showed that the generation of residual stress is influenced by both isotropic hardening and kinematic hardening of the target material.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2022)
Article
Nanoscience & Nanotechnology
Olivier Bouaziz, Jongun Moon, Hyoung Seop Kim, Yuri Estrin
Summary: The contribution of kinematic hardening to the overall strain hardening of a high entropy alloy was investigated for the first time. The observed occurrence of high back stresses signifies substantial kinematic hardening, attributed to the low probability of cross-slip in the alloy. A model capturing these effects was proposed and validated.
SCRIPTA MATERIALIA
(2021)
Article
Materials Science, Multidisciplinary
Shuyan Zhang, Zhuozhi Fan, Jun Li, Shuwen Wen, Sanjooram Paddea, Lili Lu, Shiyi Li
Summary: This study investigated the weld residual stresses in a mock-up of a nuclear safe-end dissimilar metal weld (DMW) joint using neutron diffraction, the contour method, and finite element (FE) modelling. The results showed high levels of tensile residual stresses in the hoop direction of the weld joint, with reasonable consistency between the experimental and numerical results.
Article
Engineering, Mechanical
Philip Crone, Peter Gudmundson, Jonas Faleskog
Summary: The influence of small, spherical, elastic particles dispersed within a matrix on macroscopic work hardening is studied. A proposed analytical solution based on an initial yield strength model is validated numerically and calibrated against experimental data.
INTERNATIONAL JOURNAL OF PLASTICITY
(2022)
Article
Engineering, Geological
Andrea Panteghini, Rocco Lagioia
Summary: In this paper, a finite element (FE) procedure based on a fully implicit backward Euler predictor/corrector scheme for the Cosserat continuum is presented. The integration algorithm makes use of the spectral decomposition of the stress tensor, and the choice of invariants as independent variables enables mathematical simplifications and rigorous handling of discontinuities. The algorithm is capable of handling various classical failure criteria and has been validated through numerical analyses.
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
(2022)
Article
Materials Science, Multidisciplinary
Dilip K. Banerjee, William E. Luecke, Mark A. Iadicola, Evan Rust
Summary: This paper evaluates the performance of the Manual and Optimization methods for determining the values of the constitutive-model parameters for the Yoshida-Uemori isotropic-kinematic hardening model. The results show that the Optimization Method produces the best results, especially for dual-phase steel tests. The authors also suggest that using a finite element model to determine the parameters is more reliable than the manual methods.
MATERIALS TODAY COMMUNICATIONS
(2022)
Article
Chemistry, Physical
Stanislav Strashnov, Sergei Alexandrov, Lihui Lang
Summary: This paper provides a semi-analytic solution for finite plane strain bending under tension of an incompressible elastic/plastic sheet. A combined material model of isotropic and kinematic hardening is used, with numerical treatment necessary to solve transcendental equations and evaluate ordinary integrals. The solution's validity and the effects of parameters on the constitutive equations are analyzed in detail.
Article
Mechanics
Sumit Kumar, Badri Prasad Patel
Summary: This paper introduces the requirement of a multi-invariants dependent isotropic yield function for accurate plasticity description in polycrystalline solids. It compares two integration schemes (IS-1 and IS-2) in terms of computational costs. IS-1 is fully-implicit and requires iterative updates of principal Kirchhoff stresses, equivalent plastic strain, and plastic Lagrange multiplier. IS-2 is semi-implicit and only requires iterative updates of the plastic Lagrange multiplier. For J2 dependent plasticity, the computational time is almost the same for both schemes, while for multi-invariants dependent plasticity, IS-1 has significantly greater computation time compared to J2 dependent plasticity, whereas IS-2 has similar computation time to J2 dependent plasticity, making it more computationally cost-effective.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2023)
Article
Engineering, Civil
Yulin Luo, Carol A. Featherston, David Kennedy
Summary: Damage modelling is crucial for preliminary structural design and non-destructive damage detection. This paper proposes a novel hybrid method that combines an exact strip model with a finite element model to analyze changes in natural frequencies of plates caused by arbitrarily aligned cracks. The crack is represented as a rotational spring with additional rotational freedoms. The method is validated by comparing with published results and used to investigate the effects of varying crack parameters.
THIN-WALLED STRUCTURES
(2023)
Article
Materials Science, Multidisciplinary
Seongyong Yoon, Frederic Barlat
Summary: This paper proposes a fully explicit non-iterative stress projection method for instant stress integration of advanced plasticity models considering history-dependent deformation. The stress increment is directly determined based on the elastoplastic constitutive law in this method. Generalized formulations of the elastoplastic tangent moduli for anisotropic hardening models are discussed, considering morphological changes in the yield surface. The precision integration of stress tensor, effective plastic strain, and other state variables are accomplished for kinematic and distortional hardening models. The implemented plasticity hardening models are validated through non-proportional loadings and sheet metal forming simulations, reducing the computational cost by up to 50%.
MECHANICS OF MATERIALS
(2023)
Proceedings Paper
Materials Science, Multidisciplinary
Rajeswara R. Resapu, Lohit Raj Perumahanthi
Summary: This paper investigates the low-cycle elastic-plastic response of metals and alloys under uniaxial tension-compression loading using finite element analysis. The study reveals significant differences in stress-strain relationships between kinematic hardening and isotropic hardening, with the latter exhibiting stress accumulation in constant strain cycles.
MATERIALS TODAY-PROCEEDINGS
(2021)
Article
Crystallography
Petr Sivtsev, Piotr Smarzewski
Summary: Numerical modeling of stress-strain states in composite materials, such as fiber-reinforced concrete, is a significant computational challenge. The method of numerical homogenization is actively used to address the complexity of calculations, particularly when considering plastic deformations. This work proposes a novel approach for describing the anisotropic hardening of composite materials and conducting numerical homogenization for J2 flow with isotropic hardening to solve the computational challenges effectively.
Article
Engineering, Mechanical
Michael Saleh, Alan Xu, Christopher Hurt, Mihail Ionescu, John Daniels, Paul Munroe, Lyndon Edwards, Dhriti Bhattacharyya
INTERNATIONAL JOURNAL OF PLASTICITY
(2019)
Article
Engineering, Multidisciplinary
Qingrong Xiong, M. C. Smith, O. Muransky, J. Mathew
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2019)
Article
Chemistry, Inorganic & Nuclear
Gabriel L. Murphy, Chun-Hai Wang, Zhaoming Zhang, Piotr M. Kowalski, George Beridze, Maxim Avdeev, Ondrej Muransky, Helen E. A. Brand, Qin-Fen Gu, Brendan J. Kennedy
INORGANIC CHEMISTRY
(2019)
Article
Materials Science, Multidisciplinary
O. Muransky, C. Yang, H. Zhu, I. Karatchevtseva, P. Slama, Z. Novy, L. Edwards
Article
Materials Science, Multidisciplinary
Dengshan Zhou, Hao Wang, Ondrej Muransky, Charlie Kong, Chao Yang, Deliang Zhang
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE
(2019)
Article
Materials Science, Multidisciplinary
Dengshan Zhou, Hao Wang, David W. Saxey, Ondrej Muransky, Hongwei Geng, William D. A. Rickard, Zakaria Quadir, Chao Yang, Steven M. Reddy, Deliang Zhang
METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE
(2019)
Article
Materials Science, Multidisciplinary
O. Muransky, L. Balogh, M. Tran, C. J. Hamelin, J. -S. Park, M. R. Daymond
Article
Engineering, Multidisciplinary
Kevin Kan, Ondrej Muransky, Philip J. Bendeich, Richard N. Wright, Jamie J. Kruzic, Warwick Payten
INTERNATIONAL JOURNAL OF PRESSURE VESSELS AND PIPING
(2019)
Article
Materials Science, Multidisciplinary
A. E. Danon, O. Muransky, I. Karatchevtseva, Z. Zhang, Z. J. Li, N. Scales, J. J. Kruzic, L. Edwards
Article
Energy & Fuels
Madjid Sarvghad, Ondrej Muransky, Theodore A. Steinberg, James Hester, Michael R. Hill, Geoffrey Will
SOLAR ENERGY MATERIALS AND SOLAR CELLS
(2019)
Article
Nanoscience & Nanotechnology
Hao Wang, Hongwei Geng, Dengshan Zhou, Kodai Niitsu, Ondrej Muransky, Deliang Zhang
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2020)
Article
Materials Science, Multidisciplinary
Zhiyang Wang, Ondrej Muransky, Hanliang Zhu, Tao Wei, Anna Sokolova, Ken Short, Richard N. Wright
Article
Materials Science, Multidisciplinary
O. Muransky, H. Zhu, S-L Lim, K. Short, J. Cairney, M. Drew
Correction
Materials Science, Multidisciplinary
A. D. Boccardo, M. Tong, S. B. Leen, D. Tourret, J. Segurado
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Tao Li, Qing Hou, Jie-chao Cui, Jia-hui Yang, Ben Xu, Min Li, Jun Wang, Bao-qin Fu
Summary: This study investigates the thermal and defect properties of AlN using molecular dynamics simulation, and proposes a new method for selecting interatomic potentials, developing a new model. The developed model demonstrates high computational accuracy, providing an important tool for modeling thermal transport and defect evolution in AlN-based devices.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Shin-Pon Ju, Chao-Chuan Huang, Hsing-Yin Chen
Summary: Amorphous boron nitride (a-BN) is a promising ultralow-dielectric-constant material for interconnect isolation in integrated circuits. This study establishes a deep learning potential (DLP) for different forms of boron nitride and uses molecular dynamics simulations to investigate the mechanical behaviors of a-BN. The results reveal the structure-property relationships of a-BN, providing useful insights for integrating it in device applications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
M. Salman, S. Schmauder
Summary: Shape memory polymer foams (SMPFs) are lightweight cellular materials that can recover their undeformed shape through external stimulation. Reinforcing the material with nano-clay filler improves its physical properties. Multiscale modeling techniques can be used to study the thermomechanical response of SMPFs and show good agreement with experimental results.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Laura Gueci, Francesco Ferrante, Marco Bertini, Chiara Nania, Dario Duca
Summary: This study investigates the acidity of 30 Bronsted sites in the beta-zeolite framework and compares three computational methods. The results show a wide range of deprotonation energy values, and the proposed best method provides accurate calculations.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
K. A. Lopes Lima, L. A. Ribeiro Junior
Summary: Advancements in nanomaterial synthesis and characterization have led to the discovery of new carbon allotropes, including biphenylene network (BPN). The study finds that BPN lattices with a single-atom vacancy exhibit higher CO2 adsorption energies than pristine BPN. Unlike other 2D carbon allotropes, BPN does not exhibit precise CO2 sensing and selectivity by altering its band structure configuration.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Jay Kumar Sharma, Arpita Dhamija, Anand Pal, Jagdish Kumar
Summary: In this study, the quaternary Heusler alloys LiAEFeSb were investigated for their crystal structure, electronic properties, and magnetic behavior. Density functional theory calculations revealed that LiSrFeSb and LiBaFeSb exhibit half-metallic band structure and 100% spin polarization, making them excellent choices for spintronic applications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Roman A. Eremin, Innokentiy S. Humonen, Alexey A. Kazakov, Vladimir D. Lazarev, Anatoly P. Pushkarev, Semen A. Budennyy
Summary: Computational modeling of disordered crystal structures is essential for studying composition-structure-property relations. In this work, the effects of Cd and Zn substitutions on the structural stability of CsPbI3 were investigated using DFT calculations and GNN models. The study achieved accurate energy predictions for structures with high substitution contents, and the impact of data subsampling on prediction quality was comprehensively studied. Transfer learning routines were also tested, providing new perspectives for data-driven research of disordered materials.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Zhixin Sun, Hang Dong, Yaohui Yin, Ai Wang, Zhen Fan, Guangyong Jin, Chao Xin
Summary: In this study, the crystal structure, electronic structure, and optical properties of KH2PO4: KDP crystals under different pressures were investigated using the generalized gradient approximate. It was found that high pressure caused a phase transition in KDP and greatly increased the band gap. The results suggest that high pressure enhances the compactness of KDP and improves the laser damage threshold.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Tingting Yu
Summary: This study presents atomistic simulations revealing that an increase in driving force may result in slower grain boundary movement and switches in the mode of grain boundary shear coupling migration. Shear coupling behavior is found to effectively alleviate stress and holds potential for stress relaxation and microstructure manipulation in materials.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Y. Zhang, X. Q. Deng, Q. Jing, Z. S. Zhang
Summary: The electronic properties of C2N/antimonene van der Waals heterostructure are investigated using density functional theory. The results show that by applying horizontal strain, vertical strain, electric field, and interlayer twist, the electronic structure can be adjusted. Additionally, the band alignment and energy states of the heterostructure can be significantly changed by applying vertical strain on the twisted structure. These findings are important for controlling the electronic properties of heterostructures.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Chad E. Junkermeier, Evan Larmand, Jean-Charles Morais, Jedediah Kobebel, Kat Lavarez, R. Martin Adra, Jirui Yang, Valeria Aparicio Diaz, Ricardo Paupitz, George Psofogiannakis
Summary: This study investigates the adsorption properties of carbon dioxide (CO2), methane (CH4), and dihydrogen (H2) in carbophenes functionalized with different groups. The results show that carbophenes can be promising adsorbents for these gases, with high adsorption energies and low desorption temperatures. The design and combination of functional groups can further enhance their adsorption performance.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Y. Borges, L. Huber, H. Zapolsky, R. Patte, G. Demange
Summary: Grain boundary structure is closely related to solute atom segregation, and machine learning can predict the segregation energy density. The study provides a fresh perspective on the relationship between grain boundary structure and segregation properties.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
M. R. Jones, L. T. W. Fey, I. J. Beyerlein
Summary: In this work, a three-dimensional ab-initio informed phase-field-dislocation dynamics model combined with Langevin dynamics is used to investigate glide mechanisms of edge and screw dislocations in Nb at finite temperatures. It is found that the screw dislocation changes its mode of glide at two distinct temperatures, which coincides with the thermal insensitivity and athermal behavior of Nb yield strengths.
COMPUTATIONAL MATERIALS SCIENCE
(2024)
Article
Materials Science, Multidisciplinary
Joshua A. Vita, Dallas R. Trinkle
Summary: This study introduces a new machine learning model framework that combines the simplicity of spline-based potentials with the flexibility of neural network architectures. The simplified version of the neural network potential can efficiently describe complex datasets and explore the boundary between classical and machine learning models. Using spline filters for encoding atomic environments results in interpretable embedding layers that can incorporate expected physical behaviors and improve interpretability through neural network modifications.
COMPUTATIONAL MATERIALS SCIENCE
(2024)