Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.039
João E. Ribeiro , Hernani Lopes , João Rocha
The increasing demand for sustainable materials has fostered the development of natural fiber-reinforced composites as eco-friendly alternatives to petroleum-based systems. This work investigates the mechanical performance of GreenPoxy resin reinforced with coir fibers through a comprehensive experimental program. Fiber properties were first characterized by density and tensile tests, while the resin was evaluated under tensile and flexural loading. Composite laminates were then fabricated by hand lay-up using 3% and 6% fiber volume fractions, with both untreated and retted fibers. Mechanical behavior was analyzed using Taguchi design and ANOVA to assess the effects of fiber treatment and content. Untreated fibers displayed slightly higher intrinsic strength, while mercerization enhanced fiber–matrix adhesion, particularly at higher fractions. The composites exhibited promising properties, confirming the potential of coir/GreenPoxy systems for sustainable structural applications.
{"title":"Mechanical Characterization of Eco-Friendly Composites: Green Epoxy Resin Reinforced with Coir Fibers","authors":"João E. Ribeiro , Hernani Lopes , João Rocha","doi":"10.1016/j.prostr.2026.01.039","DOIUrl":"10.1016/j.prostr.2026.01.039","url":null,"abstract":"<div><div>The increasing demand for sustainable materials has fostered the development of natural fiber-reinforced composites as eco-friendly alternatives to petroleum-based systems. This work investigates the mechanical performance of GreenPoxy resin reinforced with coir fibers through a comprehensive experimental program. Fiber properties were first characterized by density and tensile tests, while the resin was evaluated under tensile and flexural loading. Composite laminates were then fabricated by hand lay-up using 3% and 6% fiber volume fractions, with both untreated and retted fibers. Mechanical behavior was analyzed using Taguchi design and ANOVA to assess the effects of fiber treatment and content. Untreated fibers displayed slightly higher intrinsic strength, while mercerization enhanced fiber–matrix adhesion, particularly at higher fractions. The composites exhibited promising properties, confirming the potential of coir/GreenPoxy systems for sustainable structural applications.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 300-307"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.042
Pawel Madejski , Isyna Izzal Muna , Tomasz Machniewicz
Additive manufacturing (AM) techniques are increasingly popular across various industries due to their capability of producing complex shapes with minimal waste. Fused Deposition Modeling (FDM) is the most widely used method for creating these reinforced structures. The printed materials are intended for various applications, such as prototypes for the covers of thermal sensors or components in thermal storage systems. The paper presents the results of experimental activities related to 3D-printed samples, which aim to determine the thermal effects and strength of thermoplastic materials, such as polylactic acid (PLA). During the tensile tests, five different infill patterns were investigated: cubic pattern, lines pattern, triangle pattern, octet pattern, and quarter cubic pattern. The comparison of stress-strain curves, Poisson’s ratio, Young’s Modulus, etc., allows for evaluating the range of operating conditions and the application of selected printed samples. The novelty of the presented study is the analysis of thermal effects and comparison with mechanical effects during the tensile test of analyzed samples using thermal imaging results. The values of average temperature change during force increases and rapid temperature changes in the region close to the place of failure can be used in thermo-mechanical characterization of materials. Analysis of thermo-mechanical effects can help investigate the material fracture mechanisms produced by the FDM additive manufacturing technique.
{"title":"Thermo-mechanical characterization of 3D printed samples with different infill patterns produced by FDM additive manufacturing technique","authors":"Pawel Madejski , Isyna Izzal Muna , Tomasz Machniewicz","doi":"10.1016/j.prostr.2026.01.042","DOIUrl":"10.1016/j.prostr.2026.01.042","url":null,"abstract":"<div><div>Additive manufacturing (AM) techniques are increasingly popular across various industries due to their capability of producing complex shapes with minimal waste. Fused Deposition Modeling (FDM) is the most widely used method for creating these reinforced structures. The printed materials are intended for various applications, such as prototypes for the covers of thermal sensors or components in thermal storage systems. The paper presents the results of experimental activities related to 3D-printed samples, which aim to determine the thermal effects and strength of thermoplastic materials, such as polylactic acid (PLA). During the tensile tests, five different infill patterns were investigated: cubic pattern, lines pattern, triangle pattern, octet pattern, and quarter cubic pattern. The comparison of stress-strain curves, Poisson’s ratio, Young’s Modulus, etc., allows for evaluating the range of operating conditions and the application of selected printed samples. The novelty of the presented study is the analysis of thermal effects and comparison with mechanical effects during the tensile test of analyzed samples using thermal imaging results. The values of average temperature change during force increases and rapid temperature changes in the region close to the place of failure can be used in thermo-mechanical characterization of materials. Analysis of thermo-mechanical effects can help investigate the material fracture mechanisms produced by the FDM additive manufacturing technique.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 323-330"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.004
Andrzej Katunin , Jafar Amraei , Dominik Wachla
The self-heating based vibrothermography (SHVT) is a promising non-destructive testing (NDT) technique for polymer-matrix composites, which is based on inducing resonant vibrations of a tested structure. Vibrations serve as a thermal excitation for NDT inspection due to the hysteretic heating of a polymer matrix, known as the self-heating effect. In previous studies, it was validated that the controlled self-heating temperature rise ensures proper thermal excitation of tested composite structures and has a non-destructive and non-invasive character for such structures. It was shown that the increase in temperature usually below 5°C from the ambient temperature is enough to provide appropriate thermal excitation of a tested structure for identifying structural damage. The following study focuses on methods for processing of thermographic images acquired from NDT inspections using SHVT to enable accurate quantification of damage. The results of inspections of two-dimensional glass fiber-reinforced composite specimens with introduced artificial damage were used for a case study to quantify the damage and assess the accuracy of the determination of its spatial position and characteristic dimensions. The results of the processing demonstrated significant enhancement in identification of the introduced damage and allowed its precise quantification, which creates a potential for practical applications, especially during inspection of structures with single-side access or in the cases where external thermal excitation typical for most of classical thermographic techniques cannot be applied.
{"title":"Damage quantification in composites using self-heating based vibrothermography and dedicated image processing","authors":"Andrzej Katunin , Jafar Amraei , Dominik Wachla","doi":"10.1016/j.prostr.2026.01.004","DOIUrl":"10.1016/j.prostr.2026.01.004","url":null,"abstract":"<div><div>The self-heating based vibrothermography (SHVT) is a promising non-destructive testing (NDT) technique for polymer-matrix composites, which is based on inducing resonant vibrations of a tested structure. Vibrations serve as a thermal excitation for NDT inspection due to the hysteretic heating of a polymer matrix, known as the self-heating effect. In previous studies, it was validated that the controlled self-heating temperature rise ensures proper thermal excitation of tested composite structures and has a non-destructive and non-invasive character for such structures. It was shown that the increase in temperature usually below 5°C from the ambient temperature is enough to provide appropriate thermal excitation of a tested structure for identifying structural damage. The following study focuses on methods for processing of thermographic images acquired from NDT inspections using SHVT to enable accurate quantification of damage. The results of inspections of two-dimensional glass fiber-reinforced composite specimens with introduced artificial damage were used for a case study to quantify the damage and assess the accuracy of the determination of its spatial position and characteristic dimensions. The results of the processing demonstrated significant enhancement in identification of the introduced damage and allowed its precise quantification, which creates a potential for practical applications, especially during inspection of structures with single-side access or in the cases where external thermal excitation typical for most of classical thermographic techniques cannot be applied.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 18-25"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.017
Bastian Roidl , Martin Matušů , Jan Papuga , Jakub Rosenthal , Lorenzo Pagliari , Franco Concli , Vladimír Mára , Jan Šimota , Libor Beránek
This study investigates the fatigue behavior of additively manufactured AlSi10Mg under cyclic loading using Laser Powder Bed Fusion (L-PBF) technology. The research addresses two key aspects: the size effect across three distinct geometries, and the influence of mean stress on one geometry under both push-pull and tension-tension loading conditions. The findings provide valuable insights into how geometry and mean stress affect the fatigue resistance of L-PBF AlSi10Mg, contributing to the optimization of additive manufacturing processes for high-performance applications.
{"title":"Fatigue Behavior of Additively Manufactured AlSi10Mg: Influence of Size Effect and Mean Stress","authors":"Bastian Roidl , Martin Matušů , Jan Papuga , Jakub Rosenthal , Lorenzo Pagliari , Franco Concli , Vladimír Mára , Jan Šimota , Libor Beránek","doi":"10.1016/j.prostr.2026.01.017","DOIUrl":"10.1016/j.prostr.2026.01.017","url":null,"abstract":"<div><div>This study investigates the fatigue behavior of additively manufactured AlSi10Mg under cyclic loading using Laser Powder Bed Fusion (L-PBF) technology. The research addresses two key aspects: the size effect across three distinct geometries, and the influence of mean stress on one geometry under both push-pull and tension-tension loading conditions. The findings provide valuable insights into how geometry and mean stress affect the fatigue resistance of L-PBF AlSi10Mg, contributing to the optimization of additive manufacturing processes for high-performance applications.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 119-126"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.021
Douaa Benhaddouche , Vincent Barra , Alaa Chateauneuf
Data-driven structural health monitoring (SHM) systems are designed to assess the structural health conditions and to detect any potential damage, ensuring both structural safety and functionality. These systems rely on machine learning-based methods to process and analyze structural response data. The key step of these methods is damage sensitive feature extraction. Signal processing techniques, statistical modeling and neural networks were widely used in this step. However, these techniques presents limitations as information loss and computational complexity. Additionally, machine learning methods that use these techniques are supervised, which make them impractical because of damage and undamaged labels lack. To overcome these limitations, an unsupervised deep learning method based on spatio-temporel graph neural network is proposed in this paper. The method doesn’t require any preprocessing step to extract damage sensitive features. It integrates three key steps: First, Dynamic Time Warping (DTW) is used to construct a graph that captures the interactions among sensor measurements by assessing similarities between signals data. Second, a hybrid neural network architecture combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) layers is established to automatically capture the spatio-temporal dependencies from the historical sensor data of the undamaged structure. This combination enables accurate forecasting of expected sensor responses under normal conditions. Finally, the model prediction errors are analyzed to identify potential damage under unknown conditions; significant deviations between predicted and actual sensor data suggest damage presence. To quantify these deviations, the Kolmogorov–Smirnov test is employed, measuring the differences between the error distributions for undamaged and damaged scenarios. The proposed method is applied on the full-scale Tianjin bridge in order to demonstrate its efficiency in identifying the presence of damage and assessing the global structural condition of the bridge.
{"title":"Spatio-temporal graph neural network for damage detection and global structural condition assessment","authors":"Douaa Benhaddouche , Vincent Barra , Alaa Chateauneuf","doi":"10.1016/j.prostr.2026.01.021","DOIUrl":"10.1016/j.prostr.2026.01.021","url":null,"abstract":"<div><div>Data-driven structural health monitoring (SHM) systems are designed to assess the structural health conditions and to detect any potential damage, ensuring both structural safety and functionality. These systems rely on machine learning-based methods to process and analyze structural response data. The key step of these methods is damage sensitive feature extraction. Signal processing techniques, statistical modeling and neural networks were widely used in this step. However, these techniques presents limitations as information loss and computational complexity. Additionally, machine learning methods that use these techniques are supervised, which make them impractical because of damage and undamaged labels lack. To overcome these limitations, an unsupervised deep learning method based on spatio-temporel graph neural network is proposed in this paper. The method doesn’t require any preprocessing step to extract damage sensitive features. It integrates three key steps: First, Dynamic Time Warping (DTW) is used to construct a graph that captures the interactions among sensor measurements by assessing similarities between signals data. Second, a hybrid neural network architecture combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) layers is established to automatically capture the spatio-temporal dependencies from the historical sensor data of the undamaged structure. This combination enables accurate forecasting of expected sensor responses under normal conditions. Finally, the model prediction errors are analyzed to identify potential damage under unknown conditions; significant deviations between predicted and actual sensor data suggest damage presence. To quantify these deviations, the Kolmogorov–Smirnov test is employed, measuring the differences between the error distributions for undamaged and damaged scenarios. The proposed method is applied on the full-scale Tianjin bridge in order to demonstrate its efficiency in identifying the presence of damage and assessing the global structural condition of the bridge.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 152-160"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.023
Nikola Čajová Kantová , Alexander Backa , Alexander Čaja , Patrik Nemec
Particulate matter adversely affects human health, causing respiratory and other diseases that substantially reduce both quality of life and life expectancy. Electrostatic precipitation offers a promising solution to enhance the capture efficiency of particulate matter. This study investigates a novel approach to improve the efficiency of electrostatic precipitation by expanding tubes from one to four and incorporating a screw construction into a four-tubular precipitator. The increased collection area of this configuration leads to enhanced particle capture efficiency. However, uniform flue gas distribution across all tubes is important for high efficiency. Computational Fluid Dynamics simulations were employed to analyze the flow behavior within the electrostatic precipitator with and without the screw construction. Based on simulations, velocity profiles of flue gas and particles were created, and velocities in the individual tubes were also compared with each other. The results demonstrated that the screw construction effectively induces a more uniform flue gas flow, leading to improved particle capture. By optimizing the design and operation of the screw-augmented electrostatic precipitators, it is possible to significantly reduce particulate matter from small-scale combustion systems. Moreover, ensuring the structural integrity of the screw construction and the precipitator framework is essential for maintaining long-term performance and reliability under thermal and mechanical stresses.
{"title":"Flue gases flowing in the four-tubular electrostatic precipitator with an inserted screw construction based on CFD simulations","authors":"Nikola Čajová Kantová , Alexander Backa , Alexander Čaja , Patrik Nemec","doi":"10.1016/j.prostr.2026.01.023","DOIUrl":"10.1016/j.prostr.2026.01.023","url":null,"abstract":"<div><div>Particulate matter adversely affects human health, causing respiratory and other diseases that substantially reduce both quality of life and life expectancy. Electrostatic precipitation offers a promising solution to enhance the capture efficiency of particulate matter. This study investigates a novel approach to improve the efficiency of electrostatic precipitation by expanding tubes from one to four and incorporating a screw construction into a four-tubular precipitator. The increased collection area of this configuration leads to enhanced particle capture efficiency. However, uniform flue gas distribution across all tubes is important for high efficiency. Computational Fluid Dynamics simulations were employed to analyze the flow behavior within the electrostatic precipitator with and without the screw construction. Based on simulations, velocity profiles of flue gas and particles were created, and velocities in the individual tubes were also compared with each other. The results demonstrated that the screw construction effectively induces a more uniform flue gas flow, leading to improved particle capture. By optimizing the design and operation of the screw-augmented electrostatic precipitators, it is possible to significantly reduce particulate matter from small-scale combustion systems. Moreover, ensuring the structural integrity of the screw construction and the precipitator framework is essential for maintaining long-term performance and reliability under thermal and mechanical stresses.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 170-176"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.028
Jafar Amraei , Andrzej Katunin , Dominik Wachla
Fatigue testing of polymer-matrix composites (PMCs) is traditionally conducted at low frequency range (below10 Hz), resulting in long testing durations and increased expenses. A viable strategy is to accelerate fatigue testing at higher frequencies within a feasible time duration. However, at higher frequencies, the self-heating effect becomes a critical factor, affecting the structural response and potentially altering the fatigue behaviour. The entropy-based thermodynamic framework effectively captures the impact of self-heating and improves fatigue response analysis by incorporating the correlation among heat dissipation rate, applied stress, and loading frequency. Unlike the conventional S-N curve methods, which may skip the self-heating effect, entropy-based models provide a rapid and more general assessment of fatigue behaviour under arbitrary applied stresses and frequencies. This study focuses on the application of entropy-based modelling to capture the complex interplay between stress, frequency, and temperature rise. This allows for predicting the life of a fatigue-loaded PMC specimen by accounting for the interplay between mechanical loading and thermal effects. The proposed framework provides a rapid methodology for characterizing the fatigue performance of PMCs, playing a key role in refining the structural integrity assessment of PMCs.
{"title":"Fatigue life prediction of polymer-matrix composites using fracture fatigue entropy concept","authors":"Jafar Amraei , Andrzej Katunin , Dominik Wachla","doi":"10.1016/j.prostr.2026.01.028","DOIUrl":"10.1016/j.prostr.2026.01.028","url":null,"abstract":"<div><div>Fatigue testing of polymer-matrix composites (PMCs) is traditionally conducted at low frequency range (below10 Hz), resulting in long testing durations and increased expenses. A viable strategy is to accelerate fatigue testing at higher frequencies within a feasible time duration. However, at higher frequencies, the self-heating effect becomes a critical factor, affecting the structural response and potentially altering the fatigue behaviour. The entropy-based thermodynamic framework effectively captures the impact of self-heating and improves fatigue response analysis by incorporating the correlation among heat dissipation rate, applied stress, and loading frequency. Unlike the conventional <em>S-N</em> curve methods, which may skip the self-heating effect, entropy-based models provide a rapid and more general assessment of fatigue behaviour under arbitrary applied stresses and frequencies. This study focuses on the application of entropy-based modelling to capture the complex interplay between stress, frequency, and temperature rise. This allows for predicting the life of a fatigue-loaded PMC specimen by accounting for the interplay between mechanical loading and thermal effects. The proposed framework provides a rapid methodology for characterizing the fatigue performance of PMCs, playing a key role in refining the structural integrity assessment of PMCs.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 207-214"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2025.12.294
Afshin Khatammanesh , Christina Mamagkinidou , Martin Rester , Maximilian Prunbauer , Michael Proschek , Bernd M. Schönbauer
In the present investigation, the very high cycle fatigue (VHCF) properties of precipitation-hardened chromium-nickel martensitic stainless steel sheets are studied. Test specimens were extracted from 1.8 mm, 2.3 mm, and 3.1 mm thick 14-7PH steel sheets with comparable hardness (454–470 HV10). Experiments were conducted using ultrasonic fatigue testing up to 1010 cycles at fully reversed loading. Fractographic investigations were performed to identify the type and location of failure.
Failure in the high cycle fatigue (HCF) regime originated mainly from surface inclusions, whereas VHCF fracture was solely from the interior. The fatigue strength was slightly lower in both the HCF and VHCF regimes for specimens extracted from the 2.3 mm thick sheet. The 1.8 mm thick sheet exhibited the highest VHCF strength, while the lifetimes of the 3.1 mm sheet were in between. The lower fatigue strength of the 2.3 mm steel can be explained by crack initiation at, in mean, larger inclusions compared to the other steel sheets. A fracture mechanics evaluation of the data – considering the size-dependency of the threshold stress intensity factor for small, crack-like defects – suggests that compressive as well as tensile residual stresses at the surface and in the interior, respectively, significantly affect the fatigue properties.
{"title":"Very high cycle fatigue properties of martensitic stainless steel sheets","authors":"Afshin Khatammanesh , Christina Mamagkinidou , Martin Rester , Maximilian Prunbauer , Michael Proschek , Bernd M. Schönbauer","doi":"10.1016/j.prostr.2025.12.294","DOIUrl":"10.1016/j.prostr.2025.12.294","url":null,"abstract":"<div><div>In the present investigation, the very high cycle fatigue (VHCF) properties of precipitation-hardened chromium-nickel martensitic stainless steel sheets are studied. Test specimens were extracted from 1.8 mm, 2.3 mm, and 3.1 mm thick 14-7PH steel sheets with comparable hardness (454–470 HV10). Experiments were conducted using ultrasonic fatigue testing up to 10<sup>10</sup> cycles at fully reversed loading. Fractographic investigations were performed to identify the type and location of failure.</div><div>Failure in the high cycle fatigue (HCF) regime originated mainly from surface inclusions, whereas VHCF fracture was solely from the interior. The fatigue strength was slightly lower in both the HCF and VHCF regimes for specimens extracted from the 2.3 mm thick sheet. The 1.8 mm thick sheet exhibited the highest VHCF strength, while the lifetimes of the 3.1 mm sheet were in between. The lower fatigue strength of the 2.3 mm steel can be explained by crack initiation at, in mean, larger inclusions compared to the other steel sheets. A fracture mechanics evaluation of the data – considering the size-dependency of the threshold stress intensity factor for small, crack-like defects – suggests that compressive as well as tensile residual stresses at the surface and in the interior, respectively, significantly affect the fatigue properties.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"76 ","pages":"Pages 115-122"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2025.12.295
Vladimír Mára , Martin Matušů , Jan Papuga , Martin Nesládek , Zdeněk Pitrmuc , Jan Šimota
In the present work, the impact of defect geometry, size and position on the high cycle fatigue (HCF) properties was studied on AlSi10Mg alloy manufactured by Laser Powder Bed Fusion (LPBF). Different types and variations of heat treatment were applied on fatigue testing specimens from several building platforms. To investigate the influence of porosity and its characteristics on fatigue crack initiation, propagation and fatigue life, specimens were tested in the state of as built, after three types of annealing with various impact on supersaturated eutectic Si, and after two types of T6 heat treatment resulting in dissolution of Si network and reprecipitation of Si particles (total of 6 configurations of heat treatment). Fatigue crack growth and propagation mechanism together with defect evaluation were determined by fractographic analysis, while the influence of heat treatment on microstructural transformations was analyzed using light and scanning electron microscopy (SEM) combined with electron backscatter diffraction (EBSD). Based on the results, maximum stress intensity factor was determined, and the prediction of fatigue limit was established for each material state. The synergistic effect of heat treatment and defects properties on high cycle fatigue is discussed.
{"title":"The combined influence of defects and various heat treatment levels on high cycle fatigue performance of additively manufactured AlSi10Mg alloy","authors":"Vladimír Mára , Martin Matušů , Jan Papuga , Martin Nesládek , Zdeněk Pitrmuc , Jan Šimota","doi":"10.1016/j.prostr.2025.12.295","DOIUrl":"10.1016/j.prostr.2025.12.295","url":null,"abstract":"<div><div>In the present work, the impact of defect geometry, size and position on the high cycle fatigue (HCF) properties was studied on AlSi10Mg alloy manufactured by Laser Powder Bed Fusion (LPBF). Different types and variations of heat treatment were applied on fatigue testing specimens from several building platforms. To investigate the influence of porosity and its characteristics on fatigue crack initiation, propagation and fatigue life, specimens were tested in the state of as built, after three types of annealing with various impact on supersaturated eutectic Si, and after two types of T6 heat treatment resulting in dissolution of Si network and reprecipitation of Si particles (total of 6 configurations of heat treatment). Fatigue crack growth and propagation mechanism together with defect evaluation were determined by fractographic analysis, while the influence of heat treatment on microstructural transformations was analyzed using light and scanning electron microscopy (SEM) combined with electron backscatter diffraction (EBSD). Based on the results, maximum stress intensity factor was determined, and the prediction of fatigue limit was established for each material state. The synergistic effect of heat treatment and defects properties on high cycle fatigue is discussed.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"76 ","pages":"Pages 123-130"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-01DOI: 10.1016/j.prostr.2026.01.007
A. Hell , A. Molz , T. Werning , K. Schisler , H.-G. Herrmann
The aim of this study was to develop a methodology to investigate hydrogen effects on crack growth resistance in low alloy ferritic steels using cathodic hydrogen precharging with the focus on stable crack growth in pressure vessel steel grade P355NH. Inert gas fusion measurements (IGF) were performed to determine hydrogen uptake and estimate diffusion behavior. Numerical calculations allowed a first prediction of the concentration profile in compact tension specimens. To assess the influence of internal hydrogen on crack growth resistance, fatigue precracking was performed and J-∆a-curves were measured. Accelerated fatigue crack growth was observed for high stress intensities and low frequencies. In the J-∆a-analysis, the crack growth resistance in hydrogen charged material was reduced in contrast to uncharged specimens. However, no unstable crack growth was perceivable. In conclusion, the steel remains predominately ductile with the applied charging conditions. The findings from fracture mechanical investigation were further confirmed using optical and scanning electron microscopy.
{"title":"Influence of hydrogen on crack growth resistance of steels for energy infrastructure applications","authors":"A. Hell , A. Molz , T. Werning , K. Schisler , H.-G. Herrmann","doi":"10.1016/j.prostr.2026.01.007","DOIUrl":"10.1016/j.prostr.2026.01.007","url":null,"abstract":"<div><div>The aim of this study was to develop a methodology to investigate hydrogen effects on crack growth resistance in low alloy ferritic steels using cathodic hydrogen precharging with the focus on stable crack growth in pressure vessel steel grade P355NH. Inert gas fusion measurements (IGF) were performed to determine hydrogen uptake and estimate diffusion behavior. Numerical calculations allowed a first prediction of the concentration profile in compact tension specimens. To assess the influence of internal hydrogen on crack growth resistance, fatigue precracking was performed and <em>J</em>-<em>∆a</em>-curves were measured. Accelerated fatigue crack growth was observed for high stress intensities and low frequencies. In the <em>J</em>-<em>∆a</em>-analysis, the crack growth resistance in hydrogen charged material was reduced in contrast to uncharged specimens. However, no unstable crack growth was perceivable. In conclusion, the steel remains predominately ductile with the applied charging conditions. The findings from fracture mechanical investigation were further confirmed using optical and scanning electron microscopy.</div></div>","PeriodicalId":20518,"journal":{"name":"Procedia Structural Integrity","volume":"77 ","pages":"Pages 41-48"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号