Pub Date : 2025-03-09DOI: 10.1016/j.mechmat.2025.105314
Predrag Andric , Sebastián Echeverri Restrepo , Francesco Maresca
Screw dislocations control the yield strength of low-alloyed body-centered-cubic (e.g. steels). Interstitials such as C and N play a key role in the strengthening mechanisms, yet a mechanistic theory that enables the prediction of strength of alloys over a broad range of compositions and interstitial contents is not available. Here, we provide such a theory and apply it to screw dislocations with C and N in iron, from dilute to larger concentrations. The theory, which accounts for interstitial solute segregation by Cottrell atmospheres, is validated with respect to atomistic simulations and used to predict the yield strength of a broad range of alloys, including fully ferritic, martensitic and precipitation-strengthened microstructures. By using a recent model developed by the authors to predict the dislocation density of martensite as a function of the interstitials content, we find a new scaling of the yield strength with the dislocation density, which matches experiments and differs from the commonly used Taylor equation. The demonstrated predictive power of the theory paves the way for theory-guided alloy design, based on reduced and hence more sustainable testing.
{"title":"Mechanism and prediction of screw dislocation strengthening by interstitials in advanced high-strength steels: Application to Fe–C and Fe–N alloys","authors":"Predrag Andric , Sebastián Echeverri Restrepo , Francesco Maresca","doi":"10.1016/j.mechmat.2025.105314","DOIUrl":"10.1016/j.mechmat.2025.105314","url":null,"abstract":"<div><div>Screw dislocations control the yield strength of low-alloyed body-centered-cubic (e.g. steels). Interstitials such as C and N play a key role in the strengthening mechanisms, yet a mechanistic theory that enables the prediction of strength of alloys over a broad range of compositions and interstitial contents is not available. Here, we provide such a theory and apply it to screw dislocations with C and N in iron, from dilute to larger concentrations. The theory, which accounts for interstitial solute segregation by Cottrell atmospheres, is validated with respect to atomistic simulations and used to predict the yield strength of a broad range of alloys, including fully ferritic, martensitic and precipitation-strengthened microstructures. By using a recent model developed by the authors to predict the dislocation density of martensite as a function of the interstitials content, we find a new scaling of the yield strength with the dislocation density, which matches experiments and differs from the commonly used Taylor equation. The demonstrated predictive power of the theory paves the way for theory-guided alloy design, based on reduced and hence more sustainable testing.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105314"},"PeriodicalIF":3.4,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The extensive emergence and frequent interaction of shear bands play a pivotal role in the behavior of ductile polymers under large deformations. This paper employs the finite element method to analyze the emergence and evolution of shear bands in polymer tubes under internal pressure. Assuming the tube is sufficiently long, plane strain conditions prevail in the axial direction. The behavior of polymers is represented by the classical elastic-viscoplastic constitutive model, which incorporates influences of pressure, strain rate and temperature on yielding and encompasses intrinsic softening and consequent orientation hardening. Simulations indicate that shear bands initially propagate in a spiral pattern, followed by widening, multiplication, and annihilation indications. These phenomena collectively contribute to the onset and expansion of necks. The competition between the propagation and multiplication of shear bands governs the unpredictability in the initiation sites of necking. Particular attention is paid to four interesting interactions between shear bands (i.e., “detour”, bifurcation, obstruction, “repulsion”) and their genesis mechanisms. The effects of material parameters, initial geometric imperfections, specimen thickness and loading method are systematically discussed. It is demonstrated that intrinsic softening facilitates the emergence and propagation of bands, while orientation hardening contributes to the widening of bands and the expansion of necks. The synergistic effect of intrinsic softening and orientational hardening modulates shear bands’ morphology, multiplication, competition and interaction. The initial imperfection wave number significantly affects the number of shear bands. Periodic symmetric imperfections result in a comparable number of clockwise and counterclockwise shear bands, followed by necks propagating bi-directionally along the specimen. Conversely, periodic asymmetric imperfections induce a unidirectional spiral configuration of shear bands, followed by necks propagating unidirectionally along the specimen. Compared with experiments, it is demonstrated that the constitutive model can qualitatively depict the onset and propagation of necks. The multiplication, bifurcation, “detour”, and obstruction of shear bands frequently observed in experiments can also be predicted well qualitatively.
{"title":"Shear bands in polymer tubes under internal pressure","authors":"Tianxiang Lan , Yaodong Jiang , Peidong Wu , Yueguang Wei","doi":"10.1016/j.mechmat.2025.105315","DOIUrl":"10.1016/j.mechmat.2025.105315","url":null,"abstract":"<div><div>The extensive emergence and frequent interaction of shear bands play a pivotal role in the behavior of ductile polymers under large deformations. This paper employs the finite element method to analyze the emergence and evolution of shear bands in polymer tubes under internal pressure. Assuming the tube is sufficiently long, plane strain conditions prevail in the axial direction. The behavior of polymers is represented by the classical elastic-viscoplastic constitutive model, which incorporates influences of pressure, strain rate and temperature on yielding and encompasses intrinsic softening and consequent orientation hardening. Simulations indicate that shear bands initially propagate in a spiral pattern, followed by widening, multiplication, and annihilation indications. These phenomena collectively contribute to the onset and expansion of necks. The competition between the propagation and multiplication of shear bands governs the unpredictability in the initiation sites of necking. Particular attention is paid to four interesting interactions between shear bands (i.e., “detour”, bifurcation, obstruction, “repulsion”) and their genesis mechanisms. The effects of material parameters, initial geometric imperfections, specimen thickness and loading method are systematically discussed. It is demonstrated that intrinsic softening facilitates the emergence and propagation of bands, while orientation hardening contributes to the widening of bands and the expansion of necks. The synergistic effect of intrinsic softening and orientational hardening modulates shear bands’ morphology, multiplication, competition and interaction. The initial imperfection wave number significantly affects the number of shear bands. Periodic symmetric imperfections result in a comparable number of clockwise and counterclockwise shear bands, followed by necks propagating bi-directionally along the specimen. Conversely, periodic asymmetric imperfections induce a unidirectional spiral configuration of shear bands, followed by necks propagating unidirectionally along the specimen. Compared with experiments, it is demonstrated that the constitutive model can qualitatively depict the onset and propagation of necks. The multiplication, bifurcation, “detour”, and obstruction of shear bands frequently observed in experiments can also be predicted well qualitatively.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105315"},"PeriodicalIF":3.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-02DOI: 10.1016/j.mechmat.2025.105308
Ozge Ozbayram , Daniel Olsen , Maruthi Annamaraju , Andreas E. Robertson , Aditya Venkatraman , Surya R. Kalidindi , Min Zhou , Lori Graham-Brady
Polymer-bonded explosives (PBX) exhibit complex microstructure–property relationships, particularly in their shock-to-detonation transition (SDT) behavior. Traditionally physics-based simulations to explore these relationships are computationally expensive and time-consuming for a number of reasons. We present a material informatics framework that leverages batch active learning to efficiently investigate the intricate microstructure-macroscopic property relationships for PBX, significantly reducing simulation time. Our framework integrates multi-output Gaussian Process Regression (MOGPR) to capture complex relationships between microstructural features (including void volume fraction, shape, and distribution) and reaction response (characterized by shock pressure and run-to-detonation distance). The batch active learning component efficiently traverses the microstructure space by strategically selecting the most informative microstructures for additional simulations, maximizing information gain while minimizing computational costs. By iteratively refining the MOGPR model with the most informative samples, we accelerate the learning process and improve the predictive accuracy of the microstructure–property relationships. Our results demonstrate rapid model convergence and high predictive accuracy, with scores of 0.97 for both pressure and run distance predictions in leave-one-out cross-validation after only eight iterations. This approach efficiently navigates the diverse microstructure space, uncovering key factors governing the SDT behavior in PBX. It also has the potential to significantly improve the design and optimization of PBX materials, enabling the development of tailored explosives with enhanced performance and safety characteristics.
{"title":"Batch active learning for microstructure–property relations in energetic materials","authors":"Ozge Ozbayram , Daniel Olsen , Maruthi Annamaraju , Andreas E. Robertson , Aditya Venkatraman , Surya R. Kalidindi , Min Zhou , Lori Graham-Brady","doi":"10.1016/j.mechmat.2025.105308","DOIUrl":"10.1016/j.mechmat.2025.105308","url":null,"abstract":"<div><div>Polymer-bonded explosives (PBX) exhibit complex microstructure–property relationships, particularly in their shock-to-detonation transition (SDT) behavior. Traditionally physics-based simulations to explore these relationships are computationally expensive and time-consuming for a number of reasons. We present a material informatics framework that leverages batch active learning to efficiently investigate the intricate microstructure-macroscopic property relationships for PBX, significantly reducing simulation time. Our framework integrates multi-output Gaussian Process Regression (MOGPR) to capture complex relationships between microstructural features (including void volume fraction, shape, and distribution) and reaction response (characterized by shock pressure and run-to-detonation distance). The batch active learning component efficiently traverses the microstructure space by strategically selecting the most informative microstructures for additional simulations, maximizing information gain while minimizing computational costs. By iteratively refining the MOGPR model with the most informative samples, we accelerate the learning process and improve the predictive accuracy of the microstructure–property relationships. Our results demonstrate rapid model convergence and high predictive accuracy, with <span><math><msup><mrow><mi>r</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> scores of 0.97 for both pressure and run distance predictions in leave-one-out cross-validation after only eight iterations. This approach efficiently navigates the diverse microstructure space, uncovering key factors governing the SDT behavior in PBX. It also has the potential to significantly improve the design and optimization of PBX materials, enabling the development of tailored explosives with enhanced performance and safety characteristics.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105308"},"PeriodicalIF":3.4,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143550930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-27DOI: 10.1016/j.mechmat.2025.105311
Zhouyu Zheng, Hui-Shen Shen, Bai-Wei Na, Yin Fan, Xiuhua Chen, Hai Wang
In current engineering applications, there is a lack of a complete set of material properties for graphene platelets (GPLs). In this paper, we predict the material properties of GPLs through atomistic structural mechanics and molecular dynamics (MD) simulations. A novel spring beam-based finite element model is designed and implemented for the analysis of material properties. Numerical results of the atomistic structural mechanics model are compared with those of the MD model. In the present proposed model, the interlayer distance of GPL is varied as the number of layer increases, and the numerical results show that the varying of interlayer distance has a significant influence on the Young's moduli E11 and E22, and shear modulus G12 of GPLs under AIREBO potential. The simulation results reveal that the material properties of GPLs are slightly anisotropic and in most cases GPLs have auxetic properties. The temperature-dependent material properties, including Young's moduli, shear modulus and thermal expansion coefficients of GPLs with in-plane positive and negative Poisson's ratios are obtained for the first time.
{"title":"Predictions of temperature-dependent material properties and auxeticity of graphene platelets","authors":"Zhouyu Zheng, Hui-Shen Shen, Bai-Wei Na, Yin Fan, Xiuhua Chen, Hai Wang","doi":"10.1016/j.mechmat.2025.105311","DOIUrl":"10.1016/j.mechmat.2025.105311","url":null,"abstract":"<div><div>In current engineering applications, there is a lack of a complete set of material properties for graphene platelets (GPLs). In this paper, we predict the material properties of GPLs through atomistic structural mechanics and molecular dynamics (MD) simulations. A novel spring beam-based finite element model is designed and implemented for the analysis of material properties. Numerical results of the atomistic structural mechanics model are compared with those of the MD model. In the present proposed model, the interlayer distance of GPL is varied as the number of layer increases, and the numerical results show that the varying of interlayer distance has a significant influence on the Young's moduli <em>E</em><sub>11</sub> and <em>E</em><sub>22</sub>, and shear modulus <em>G</em><sub>12</sub> of GPLs under AIREBO potential. The simulation results reveal that the material properties of GPLs are slightly anisotropic and in most cases GPLs have auxetic properties. The temperature-dependent material properties, including Young's moduli, shear modulus and thermal expansion coefficients of GPLs with in-plane positive and negative Poisson's ratios are obtained for the first time.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105311"},"PeriodicalIF":3.4,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-25DOI: 10.1016/j.mechmat.2025.105312
Bin Xie , Jing Wang , Yongsheng Fan , Ruizhi Li
Ni-based single crystal superalloys, as crucial materials in the aviation and aerospace industry, frequently encounter fatigue failure induced by cyclic loading, which is one of the primary failure modes. In this study, molecular dynamics (MD) simulations are utilized to explore the cyclic strengthening mechanisms of Ni-based single crystal superalloys, with a focus on dislocation evolution under cyclic loading. Two typical feature atomistic models of the alloys are constructed and dislocations are introduced under cyclic loading, investigating the interactions between dislocations and the γ/γ′ interface. The results highlight the excellent capacity of the interfacial dislocation network for dislocation deposition, particularly for those attempting to penetrate the γ′ phase, and capture a transition in emission dislocations slip plane from the plane to the plane. The dislocation absorption is driven by two primary mechanisms: the formation of stable link points at the γ/γ′ interface and the obstructive effect of the γ′ phase. Additionally, a stress stratification phenomenon at the γ/γ′ interface is observed, hindering dislocation movement during loading and leading to dislocation trapping through cross-slip during unloading. Furthermore, the simulations reveal two distinct forms of dislocation barriers pile-up within the γ phase: one arising from the decomposition of the interfacial dislocation network, which leads to the emergence of stacking faults (SFs) bands and Lomer-Cottrell lock; the other stemming from the formation of SFs bands due to the decomposition of the emission dislocations within the γ phase channel. These findings provide meaningful insights into the cyclic hardening behavior of Ni-based superalloys.
{"title":"A molecular dynamic investigation of cyclic strengthening mechanism of Ni-based single crystal superalloy","authors":"Bin Xie , Jing Wang , Yongsheng Fan , Ruizhi Li","doi":"10.1016/j.mechmat.2025.105312","DOIUrl":"10.1016/j.mechmat.2025.105312","url":null,"abstract":"<div><div>Ni-based single crystal superalloys, as crucial materials in the aviation and aerospace industry, frequently encounter fatigue failure induced by cyclic loading, which is one of the primary failure modes. In this study, molecular dynamics (MD) simulations are utilized to explore the cyclic strengthening mechanisms of Ni-based single crystal superalloys, with a focus on dislocation evolution under cyclic loading. Two typical feature atomistic models of the alloys are constructed and dislocations are introduced under cyclic loading, investigating the interactions between dislocations and the γ/γ′ interface. The results highlight the excellent capacity of the interfacial dislocation network for dislocation deposition, particularly for those attempting to penetrate the γ′ phase, and capture a transition in emission dislocations slip plane from the <span><math><mrow><mo>{</mo><mn>111</mn><mo>}</mo></mrow></math></span> plane to the <span><math><mrow><mo>{</mo><mn>100</mn><mo>}</mo></mrow></math></span> plane. The dislocation absorption is driven by two primary mechanisms: the formation of stable link points at the γ/γ′ interface and the obstructive effect of the γ′ phase. Additionally, a stress stratification phenomenon at the γ/γ′ interface is observed, hindering dislocation movement during loading and leading to dislocation trapping through cross-slip during unloading. Furthermore, the simulations reveal two distinct forms of dislocation barriers pile-up within the γ phase: one arising from the decomposition of the interfacial dislocation network, which leads to the emergence of stacking faults (SFs) bands and Lomer-Cottrell lock; the other stemming from the formation of SFs bands due to the decomposition of the emission dislocations within the γ phase channel. These findings provide meaningful insights into the cyclic hardening behavior of Ni-based superalloys.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105312"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-23DOI: 10.1016/j.mechmat.2025.105295
Fani Derveni, Florian Choquart, Arefeh Abbasi , Dong Yan, Pedro M. Reis
We perform a probabilistic investigation on the effect of systematically removing imperfections on the buckling behavior of pressurized thin, elastic, hemispherical shells containing a distribution of defects. We employ finite element simulations, which were previously validated against experiments, to assess the maximum buckling pressure, as measured by the knockdown factor, of these multi-defect shells. Specifically, we remove fractions of either the least or the most severe imperfections to quantify their influence on the buckling onset. We consider shells with a random distribution of defects whose mean amplitude and standard deviation are systematically explored while, for simplicity, fixing the width of the defect to a characteristic value. Our primary finding is that the most severe imperfection of a multi-defect shell dictates its buckling onset. Notably, shells containing a single imperfection corresponding to the maximum amplitude (the most severe) defect of shells with a distribution of imperfections exhibit an identical knockdown factor to the latter case. Our results suggest a simplified approach to studying the buckling of more realistic multi-defect shells, once their most severe defect has been identified, using a well-characterized single-defect description, akin to the weakest-link setting in extreme-value probabilistic problems.
{"title":"The most severe imperfection governs the buckling strength of pressurized multi-defect hemispherical shells","authors":"Fani Derveni, Florian Choquart, Arefeh Abbasi , Dong Yan, Pedro M. Reis","doi":"10.1016/j.mechmat.2025.105295","DOIUrl":"10.1016/j.mechmat.2025.105295","url":null,"abstract":"<div><div>We perform a probabilistic investigation on the effect of systematically removing imperfections on the buckling behavior of pressurized thin, elastic, hemispherical shells containing a distribution of defects. We employ finite element simulations, which were previously validated against experiments, to assess the maximum buckling pressure, as measured by the knockdown factor, of these multi-defect shells. Specifically, we remove fractions of either the least or the most severe imperfections to quantify their influence on the buckling onset. We consider shells with a random distribution of defects whose mean amplitude and standard deviation are systematically explored while, for simplicity, fixing the width of the defect to a characteristic value. Our primary finding is that the most severe imperfection of a multi-defect shell dictates its buckling onset. Notably, shells containing a single imperfection corresponding to the maximum amplitude (the most severe) defect of shells with a distribution of imperfections exhibit an identical knockdown factor to the latter case. Our results suggest a simplified approach to studying the buckling of more realistic multi-defect shells, once their most severe defect has been identified, using a well-characterized single-defect description, akin to the weakest-link setting in extreme-value probabilistic problems.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"204 ","pages":"Article 105295"},"PeriodicalIF":3.4,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-21DOI: 10.1016/j.mechmat.2025.105294
Zhichao Wei , Steffen Gerke , Michael Brünig
This paper discusses the calibration and verification of material parameters based on novel one-axis and biaxial reverse loading experiments. The uniaxially loaded tension–compression (TC-), one-axis-loaded shear, and biaxially loaded HC-specimens are designed to perform different cyclic experiments, covering a wide range of stress triaxialities. Special anti-buckling clamping jaws and a newly designed downholder are used during the experiments to avoid buckling under compression loads. During the experiments, strain fields are recorded and analyzed using the digital image correlation (DIC) technique. A combination of direct and indirect fitting approaches is employed to identify the essential elastic–plastic material parameters for the proposed advanced elastic–plastic-damage constitutive model. The characterization of damage parameters is not discussed in this paper. A quantitative error analysis method is introduced to check the quality of the numerical simulation using the obtained material parameters. The comparison between experimental and numerical results demonstrates that the proposed damage model with identified parameters can predict global load–displacement curves and local strain fields with good accuracy.
{"title":"Novel uniaxial and biaxial reverse experiments for material parameter identification in an advanced anisotropic cyclic plastic-damage model","authors":"Zhichao Wei , Steffen Gerke , Michael Brünig","doi":"10.1016/j.mechmat.2025.105294","DOIUrl":"10.1016/j.mechmat.2025.105294","url":null,"abstract":"<div><div>This paper discusses the calibration and verification of material parameters based on novel one-axis and biaxial reverse loading experiments. The uniaxially loaded tension–compression (TC-), one-axis-loaded shear, and biaxially loaded HC-specimens are designed to perform different cyclic experiments, covering a wide range of stress triaxialities. Special anti-buckling clamping jaws and a newly designed downholder are used during the experiments to avoid buckling under compression loads. During the experiments, strain fields are recorded and analyzed using the digital image correlation (DIC) technique. A combination of direct and indirect fitting approaches is employed to identify the essential elastic–plastic material parameters for the proposed advanced elastic–plastic-damage constitutive model. The characterization of damage parameters is not discussed in this paper. A quantitative error analysis method is introduced to check the quality of the numerical simulation using the obtained material parameters. The comparison between experimental and numerical results demonstrates that the proposed damage model with identified parameters can predict global load–displacement curves and local strain fields with good accuracy.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105294"},"PeriodicalIF":3.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-21DOI: 10.1016/j.mechmat.2025.105299
Denis Kucherenko , Arina Korneva
The structure of the optic nerve resembles a cylindrical composite where the pia mater surrounds the nervous tissue which is saturated with interstitial fluid. This interstitial fluid is necessary for effective nerve conduction of visual signals. The reaction of the optic nerve to physiological loads remains unknown. Current computational and material models do not fully capture the complexities of this tissue's structure, particularly the biofluid has not yet been considered as a load-supporting material. We developed a microstructurally motivated analytical model of a cylindrical composite with a poroelastic core and an elastic outer layer subjected to an axial load. We examined the effect of the geometry and the material parameters of the composite on the stress distribution across the composite. We found physiologically relevant conditions when the outer layer and the biofluid support most of the applied stress relative to the solid constituents of the core. The model shows that the fluid pressure can be as large as one third of the applied stress. The model makes possible the fluid pressure injuring nerve fibers. This scenario is missing in studies modeling the optic nerve as an elastic solid. We examined how variations in outer layer thickness and compressibility of animal nerves or materials stiffen the stress-strain response. This study provides guidelines for measuring and comparing the material parameters between diseased, aged, and healthy nerves and similar biomaterials. The model can be used to analyze mechanics of similar composites.
{"title":"A poroelastic model of the optic nerve shows a significant effect of fluid pressure on the nerve fibers","authors":"Denis Kucherenko , Arina Korneva","doi":"10.1016/j.mechmat.2025.105299","DOIUrl":"10.1016/j.mechmat.2025.105299","url":null,"abstract":"<div><div>The structure of the optic nerve resembles a cylindrical composite where the pia mater surrounds the nervous tissue which is saturated with interstitial fluid. This interstitial fluid is necessary for effective nerve conduction of visual signals. The reaction of the optic nerve to physiological loads remains unknown. Current computational and material models do not fully capture the complexities of this tissue's structure, particularly the biofluid has not yet been considered as a load-supporting material. We developed a microstructurally motivated analytical model of a cylindrical composite with a poroelastic core and an elastic outer layer subjected to an axial load. We examined the effect of the geometry and the material parameters of the composite on the stress distribution across the composite. We found physiologically relevant conditions when the outer layer and the biofluid support most of the applied stress relative to the solid constituents of the core. The model shows that the fluid pressure can be as large as one third of the applied stress. The model makes possible the fluid pressure injuring nerve fibers. This scenario is missing in studies modeling the optic nerve as an elastic solid. We examined how variations in outer layer thickness and compressibility of animal nerves or materials stiffen the stress-strain response. This study provides guidelines for measuring and comparing the material parameters between diseased, aged, and healthy nerves and similar biomaterials. The model can be used to analyze mechanics of similar composites.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"204 ","pages":"Article 105299"},"PeriodicalIF":3.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143511637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-19DOI: 10.1016/j.mechmat.2025.105307
Ronghai Wu , Yuxin Zhang , Zichao Peng , Di Song , Heng Li
Predicting multiple fatigue properties of metals under a wide range of conditions is still a challenge, as massive high-dimension inputs and multiple outputs are involved. We systematically conduct fatigue experiments on TWIP steel under various conditions, including different preloading methods, temperatures, strain amplitudes and mean strains. Using experimental data, we propose both black-box and white-box machine learning models to predict the fatigue performance of TWIP steel. The black-box model employs dimensionality reduction, clustering and regression techniques to achieve simultaneous predictions for fatigue life and maximum stress amplitude. The predicted fatigue lives are 100% within 3✕ error band and 88.31% within 2✕ error band. The predicted maximum stress amplitudes are all within 1.51✕ error band. The white-box model utilizes symbolic regression and matching analysis to automatically discover several predictive formulas for fatigue life and maximum stress amplitude, without any predefined equations. The three optimal fatigue life prediction formulas yield 100% predicted values within 3✕ error band and 98% within 2✕ error band. The two optimal maximum stress amplitude prediction formulas yield predicted values all within 1.09✕ error band. Based on the results, we discuss the applicability of our models and propose suggestions for future developments in machine learning fatigue performance predictions.
{"title":"Predicting multiple fatigue properties of twinning-induced plasticity steels by black-box and white-box machine learning","authors":"Ronghai Wu , Yuxin Zhang , Zichao Peng , Di Song , Heng Li","doi":"10.1016/j.mechmat.2025.105307","DOIUrl":"10.1016/j.mechmat.2025.105307","url":null,"abstract":"<div><div>Predicting multiple fatigue properties of metals under a wide range of conditions is still a challenge, as massive high-dimension inputs and multiple outputs are involved. We systematically conduct fatigue experiments on TWIP steel under various conditions, including different preloading methods, temperatures, strain amplitudes and mean strains. Using experimental data, we propose both black-box and white-box machine learning models to predict the fatigue performance of TWIP steel. The black-box model employs dimensionality reduction, clustering and regression techniques to achieve simultaneous predictions for fatigue life and maximum stress amplitude. The predicted fatigue lives are 100% within 3✕ error band and 88.31% within 2✕ error band. The predicted maximum stress amplitudes are all within 1.51✕ error band. The white-box model utilizes symbolic regression and matching analysis to automatically discover several predictive formulas for fatigue life and maximum stress amplitude, without any predefined equations. The three optimal fatigue life prediction formulas yield 100% predicted values within 3✕ error band and 98% within 2✕ error band. The two optimal maximum stress amplitude prediction formulas yield predicted values all within 1.09✕ error band. Based on the results, we discuss the applicability of our models and propose suggestions for future developments in machine learning fatigue performance predictions.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"205 ","pages":"Article 105307"},"PeriodicalIF":3.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143526564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-18DOI: 10.1016/j.mechmat.2025.105298
Chuan He , Yuanming Lai , Enlong Liu , Siming He , Jianhai Zhang , Yunming Yang
This study proposes a higher-order framework for half-space indentation based on mixture unified gradient theory (MUGT) with surface elasticity (SE). MUGT, a well-posed theory that captures both nonlocal and strain gradient properties, is essential for understanding size effects in nano/micro-scale materials and structures. However, indentation problems considering MUGT remain unexplored. We develop efficient analytical and numerical methods to address the problem. In the 3D context, the stress components are analytically determined using 2D Fourier transform applied to constitutive relations that incorporate stress gradient elasticity. Regarding the contact pressure, the problem results in integral equations whose kernel is challenging to obtain explicitly. These are numerically solved using the sum of independent functions, rather than relying on discrete point values as done in previous studies on singular integral equations. Our findings demonstrate that stress gradient elasticity leads to greater surface vertical displacement, whereas strain gradient and surface elasticity result in smaller surface vertical displacement, highlighting the softening and hardening behaviors respectively. Drastically different contact pressure distributions and surface vertical displacements can be obtained compared to existing theories. Particularly, both hardening and softening of size-dependent indentation hardness are intrinsically captured, aligning with available experimental observations. These behaviors, however, are challenging to simultaneously reflect in existing indentation theories due to the exclusion of stress gradient elasticity. The study enhances the understanding of contact mechanics and is of practically significance for nano/micro-scale materials and structures.
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