Pub Date : 2025-11-08DOI: 10.1016/j.ijpvp.2025.105700
Davoud Shahgholian-Ghahfarokhi , Mohsen Abyani , Mohammad Karimi
This research examines the failure assessment of high-pressure, high-temperature offshore pipelines made of API 5L X65 steel with the outer diameter and wall thickness equal to 32” and 20.6 mm, subjected to complex-shaped corrosion defects. An efficient algorithm generated 700 randomly shaped defect geometries representing a more realistic corrosion morphology. Nonlinear Finite Element Analyses (FEA) determined failure pressures for each geometry. Grayscale images of defect cross-sections, annotated with FEA results, are used to train a Convolutional Neural Network (CNN) model. The CNN achieves high accuracy in predicting failure pressures, reducing error and training time compared to traditional machine learning methods by effectively extracting spatial features from images. Additionally, the defects are assessed using the DNVGL-RP-F101 code-based method. The results show a strong correlation (R2 = 97.83 %) between FEA and CNN predictions. In 578 of 700 cases, numerical failure pressures exceeded those from the code, indicating that the code-based approach is generally conservative.
{"title":"Evaluation of offshore pipeline failure due to complex shaped corrosion defects using deep learning methods","authors":"Davoud Shahgholian-Ghahfarokhi , Mohsen Abyani , Mohammad Karimi","doi":"10.1016/j.ijpvp.2025.105700","DOIUrl":"10.1016/j.ijpvp.2025.105700","url":null,"abstract":"<div><div>This research examines the failure assessment of high-pressure, high-temperature offshore pipelines made of API 5L X65 steel with the outer diameter and wall thickness equal to 32” and 20.6 mm, subjected to complex-shaped corrosion defects. An efficient algorithm generated 700 randomly shaped defect geometries representing a more realistic corrosion morphology. Nonlinear Finite Element Analyses (FEA) determined failure pressures for each geometry. Grayscale images of defect cross-sections, annotated with FEA results, are used to train a Convolutional Neural Network (CNN) model. The CNN achieves high accuracy in predicting failure pressures, reducing error and training time compared to traditional machine learning methods by effectively extracting spatial features from images. Additionally, the defects are assessed using the DNVGL-RP-F101 code-based method. The results show a strong correlation (R<sup>2</sup> = 97.83 %) between FEA and CNN predictions. In 578 of 700 cases, numerical failure pressures exceeded those from the code, indicating that the code-based approach is generally conservative.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105700"},"PeriodicalIF":3.5,"publicationDate":"2025-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.ijpvp.2025.105699
Yuan-Xu Song , Kun Zhang , Jian-Ping Tan , Tao Wang , Xuan Zhang , Jie Su , Xuan Liu , Jing-Bo Yan , Peng Liu , Jian-Feng Wen , Ning Wang , Xian-Cheng Zhang
In this work the applicability of notched plate tension (NPT) and circumferentially notched tension (CNT) specimens to determine the multiaxial stress rupture criterion (MSRC) of creeping materials is evaluated by the direct and indirect methods based on the uniaxial and multiaxial (NPT and CNT specimens) creep data of a nickel-based alloy GH4169 at 650 °C. Also, the evaluation covers four commonly-used MSRCs, three of which (termed Type 1 hereafter) involve an adjustable factor, while the last (termed Type 2 hereafter) does not. Results indicate that the NPT specimen is probably not suitable for determining the MSRC for the alloy regardless of the determination method and the MSRC examined. This is because, for the Type 1 MSRC, the adjustable factor in each MSRC turns out to vary greatly depending on the notch size and the location on which relevant stresses are extracted. While for the Type 2 MSRC, the predicted multiaxial creep life depends on the location of stress extraction. Moreover, the determined MSRC based on the NPT specimen cannot be directly applied to predicting the creep life of CNT specimens, and vice versa. Interestingly, the use of CNT specimen with the same notch size of NPT specimen is found to be suitable for determining the MSRC. This is because when the skeletal point stresses of a CNT specimen with the same notch size of NPT specimen are used, the resulting adjustable factor becomes much less affected by the stress state and by the MSRC adopted. Moreover, the predicted lives of CNT specimens with different notch root radii agree well with the experimental counterparts when the determined adjustable factor is used.
{"title":"Applicability of two types of notched tension specimens to determine the multiaxial stress rupture criterion for GH4169 at 650 °C","authors":"Yuan-Xu Song , Kun Zhang , Jian-Ping Tan , Tao Wang , Xuan Zhang , Jie Su , Xuan Liu , Jing-Bo Yan , Peng Liu , Jian-Feng Wen , Ning Wang , Xian-Cheng Zhang","doi":"10.1016/j.ijpvp.2025.105699","DOIUrl":"10.1016/j.ijpvp.2025.105699","url":null,"abstract":"<div><div>In this work the applicability of notched plate tension (NPT) and circumferentially notched tension (CNT) specimens to determine the multiaxial stress rupture criterion (MSRC) of creeping materials is evaluated by the direct and indirect methods based on the uniaxial and multiaxial (NPT and CNT specimens) creep data of a nickel-based alloy GH4169 at 650 °C. Also, the evaluation covers four commonly-used MSRCs, three of which (termed Type 1 hereafter) involve an adjustable factor, while the last (termed Type 2 hereafter) does not. Results indicate that the NPT specimen is probably not suitable for determining the MSRC for the alloy regardless of the determination method and the MSRC examined. This is because, for the Type 1 MSRC, the adjustable factor in each MSRC turns out to vary greatly depending on the notch size and the location on which relevant stresses are extracted. While for the Type 2 MSRC, the predicted multiaxial creep life depends on the location of stress extraction. Moreover, the determined MSRC based on the NPT specimen cannot be directly applied to predicting the creep life of CNT specimens, and vice versa. Interestingly, the use of CNT specimen with the same notch size of NPT specimen is found to be suitable for determining the MSRC. This is because when the skeletal point stresses of a CNT specimen with the same notch size of NPT specimen are used, the resulting adjustable factor becomes much less affected by the stress state and by the MSRC adopted. Moreover, the predicted lives of CNT specimens with different notch root radii agree well with the experimental counterparts when the determined adjustable factor is used.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105699"},"PeriodicalIF":3.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145466361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.ijpvp.2025.105697
Sue-Ray Lin, Hsien-Chou Lin, Chin-Cheng Huang
During the transitional phase of a nuclear power plant's decommissioning process, prior to the removal of spent nuclear fuel from the spent fuel pool, certain key retained equipment—such as passive components like heat exchangers in the spent fuel pool cooling system—is expected to maintain its required functional performance even after the expiration of the operating license. According to a 2023 fatigue assessment report by the International Atomic Energy Agency (IAEA), heat exchanger tubes may experience wear due to vibration and relative motion with support plates, and fouling can also lead to a reduction in heat transfer capacity. Additionally, the plant's maintenance procedure manual specify that detailed disassembly and inspection of heat exchangers are generally performed only when there is evidence of reduced heat exchange performance or increased inlet-outlet pressure differentials. However, during this phase, as the equipment continues to operate, inlet-outlet pressure differentials remain the primary diagnostic criterion.
This study uses computational fluid dynamics (CFD) simulations to model fluid behavior within heat exchanger tubes under hypothetical fouling conditions. Based on the findings, it is recommended that, even though the heat exchange functionality is no longer critical during the transitional phase, potential future degradation caused by fouling cannot be accurately assessed solely based on pressure differentials. Regular detailed disassembly and inspections are necessary to ensure the equipment's functional performance remains reliable beyond its design life, particularly in preventing potential leakage issues.
{"title":"A study on the maintenance and management mechanisms of heat exchangers in spent fuel pool systems during nuclear facility decommissioning transition","authors":"Sue-Ray Lin, Hsien-Chou Lin, Chin-Cheng Huang","doi":"10.1016/j.ijpvp.2025.105697","DOIUrl":"10.1016/j.ijpvp.2025.105697","url":null,"abstract":"<div><div>During the transitional phase of a nuclear power plant's decommissioning process, prior to the removal of spent nuclear fuel from the spent fuel pool, certain key retained equipment—such as passive components like heat exchangers in the spent fuel pool cooling system—is expected to maintain its required functional performance even after the expiration of the operating license. According to a 2023 fatigue assessment report by the International Atomic Energy Agency (IAEA), heat exchanger tubes may experience wear due to vibration and relative motion with support plates, and fouling can also lead to a reduction in heat transfer capacity. Additionally, the plant's maintenance procedure manual specify that detailed disassembly and inspection of heat exchangers are generally performed only when there is evidence of reduced heat exchange performance or increased inlet-outlet pressure differentials. However, during this phase, as the equipment continues to operate, inlet-outlet pressure differentials remain the primary diagnostic criterion.</div><div>This study uses computational fluid dynamics (CFD) simulations to model fluid behavior within heat exchanger tubes under hypothetical fouling conditions. Based on the findings, it is recommended that, even though the heat exchange functionality is no longer critical during the transitional phase, potential future degradation caused by fouling cannot be accurately assessed solely based on pressure differentials. Regular detailed disassembly and inspections are necessary to ensure the equipment's functional performance remains reliable beyond its design life, particularly in preventing potential leakage issues.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105697"},"PeriodicalIF":3.5,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.ijpvp.2025.105698
Meijuan Hu , Qiang Chi , Chunyong Huo , Shengke Yang , Da Lei , Mengnie Victor Li
Wire arc additive manufacturing (WAAM) has emerged as a viable solution for fabricating complex and large-scale structural components, and has been widely adopted in industries such as aerospace, marine engineering, and oil and gas equipment. However, the development of compatible wire materials remains insufficient. To expedite the design of high-performance alloy wires suitable for submerged arc additive manufacturing (SAAM), this study established a high-throughput computing (HTC) framework based on JMatPro software. Through a full factorial experimental design involving 16384 parameter combinations, the optimized CrMo steel composition (Fe-0.063C-0.3Mn-2Cr-0.93Mo-0.33Ni-0.002Ti) was identified, exhibiting excellent strength and corrosion resistance. The microstructure, mechanical properties, and corrosion behavior of the optimized SAAM alloy were investigated using a scanning electron microscope (SEM), energy dispersive spectrometer (EDS), tensile tests, and electrochemical tests, and compared with those of the original SAAM sample. Results indicate that the microstructure of the newly developed CrMo steel is predominantly composed of granular bainite (GB), with densely and uniformly distributed martensite-austenite (M/A) islands. The alloy demonstrates superior mechanical performance, with an ultimate tensile strength of 755 ± 15.4 MPa and a yield strength of 672 ± 14.6 MPa, along with a low corrosion rate of 0.102 mm/a. Following electrochemical testing, a continuous and compact layer of α-FeOOH and Fe2O3 corrosion products formed on the alloy surface, effectively inhibiting further corrosion. This study significantly reduces the time and experimental costs associated with traditional alloy development, highlighting the promising potential of HTC-based methodologies in the design of novel materials tailored for specialized manufacturing processes.
{"title":"High-throughput computing designed wire-powder co-deposition SAAM of optimized CrMo steel: Microstructure, mechanical properties and corrosion behavior","authors":"Meijuan Hu , Qiang Chi , Chunyong Huo , Shengke Yang , Da Lei , Mengnie Victor Li","doi":"10.1016/j.ijpvp.2025.105698","DOIUrl":"10.1016/j.ijpvp.2025.105698","url":null,"abstract":"<div><div>Wire arc additive manufacturing (WAAM) has emerged as a viable solution for fabricating complex and large-scale structural components, and has been widely adopted in industries such as aerospace, marine engineering, and oil and gas equipment. However, the development of compatible wire materials remains insufficient. To expedite the design of high-performance alloy wires suitable for submerged arc additive manufacturing (SAAM), this study established a high-throughput computing (HTC) framework based on JMatPro software. Through a full factorial experimental design involving 16384 parameter combinations, the optimized CrMo steel composition (Fe-0.063C-0.3Mn-2Cr-0.93Mo-0.33Ni-0.002Ti) was identified, exhibiting excellent strength and corrosion resistance. The microstructure, mechanical properties, and corrosion behavior of the optimized SAAM alloy were investigated using a scanning electron microscope (SEM), energy dispersive spectrometer (EDS), tensile tests, and electrochemical tests, and compared with those of the original SAAM sample. Results indicate that the microstructure of the newly developed CrMo steel is predominantly composed of granular bainite (GB), with densely and uniformly distributed martensite-austenite (M/A) islands. The alloy demonstrates superior mechanical performance, with an ultimate tensile strength of 755 ± 15.4 MPa and a yield strength of 672 ± 14.6 MPa, along with a low corrosion rate of 0.102 mm/a. Following electrochemical testing, a continuous and compact layer of α-FeOOH and Fe<sub>2</sub>O<sub>3</sub> corrosion products formed on the alloy surface, effectively inhibiting further corrosion. This study significantly reduces the time and experimental costs associated with traditional alloy development, highlighting the promising potential of HTC-based methodologies in the design of novel materials tailored for specialized manufacturing processes.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105698"},"PeriodicalIF":3.5,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1016/j.ijpvp.2025.105692
Fuchun Zhang , Jun Tu , Xin Shen , Lisha Peng , Grzegorz Tytko , Xiaochun Song
Submarine oil and gas pipelines are prone to various types of corrosive defects during service, posing serious threats to structural integrity and operational safety. In traditional non-destructive testing (NDT), defect classification primarily relies on manual expertise, which is inefficient and susceptible to subjective interference. To address these challenges, this paper proposes a novel automatic detection and grading method for corrosion defects based on a multi-sensory attention network (MSANet). A unidirectional surface wave electromagnetic acoustic transducer (EMAT) is developed to enable defect data acquisition and localization. The raw surface wave signals are processed using Short-Time Fourier Transform (STFT) and denoised through an integrated filtering technique. For the first time in this field, a wavelet attention mechanism (WAT) module is innovatively introduced to extract feature information in the wavelet domain. Furthermore, a heterogeneous branch collaborative attention (HBA) module is designed to simultaneously capture multi-scale and multi-level features while enhancing feature transmission through attention mechanisms. A feature fusion strategy is then employed to integrate the deep features extracted from both modules, forming a comprehensive defect discrimination model. The proposed method is validated on a constructed dataset, and experimental results demonstrate an average recognition accuracy of 97.52 %, significantly outperforming existing mainstream deep learning algorithm.
{"title":"MSANet: Electromagnetic ultrasonic signal recognition and grading of submarine pipeline defects based on a multi-sensory attention network","authors":"Fuchun Zhang , Jun Tu , Xin Shen , Lisha Peng , Grzegorz Tytko , Xiaochun Song","doi":"10.1016/j.ijpvp.2025.105692","DOIUrl":"10.1016/j.ijpvp.2025.105692","url":null,"abstract":"<div><div>Submarine oil and gas pipelines are prone to various types of corrosive defects during service, posing serious threats to structural integrity and operational safety. In traditional non-destructive testing (NDT), defect classification primarily relies on manual expertise, which is inefficient and susceptible to subjective interference. To address these challenges, this paper proposes a novel automatic detection and grading method for corrosion defects based on a multi-sensory attention network (MSANet). A unidirectional surface wave electromagnetic acoustic transducer (EMAT) is developed to enable defect data acquisition and localization. The raw surface wave signals are processed using Short-Time Fourier Transform (STFT) and denoised through an integrated filtering technique. For the first time in this field, a wavelet attention mechanism (WAT) module is innovatively introduced to extract feature information in the wavelet domain. Furthermore, a heterogeneous branch collaborative attention (HBA) module is designed to simultaneously capture multi-scale and multi-level features while enhancing feature transmission through attention mechanisms. A feature fusion strategy is then employed to integrate the deep features extracted from both modules, forming a comprehensive defect discrimination model. The proposed method is validated on a constructed dataset, and experimental results demonstrate an average recognition accuracy of 97.52 %, significantly outperforming existing mainstream deep learning algorithm.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105692"},"PeriodicalIF":3.5,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.ijpvp.2025.105696
Yihuan Wang , Yubo Yang , Jianjun Qin , Yinghao Sun , Guojin Qin
This study presents a probabilistic-based method for modeling realistic corrosion morphology on natural gas pipelines with the random field node mapping coupling (RF-NMC) model. An anisotropic random field is used to reconstruct mesh geometry through node-level random displacement. High-precision mesh deformation and local coordinate mapping enable adaptive geometric transformation. This ensures an accurate representation of corrosion features. The model is embedded in a finite element (FE) modeling to achieve precise, fast, and flexible prediction of failure pressure and identify failure paths. Compared with simplified geometry models, the RF-NMC approach significantly improves the accuracy of failure pressure predictions, as confirmed by burst tests. The method strikes a balance between accuracy and computational efficiency, allowing for the quick simulation of complex corrosion geometries while maintaining reliability. The main novelty lies in directly coupling anisotropic random fields with FE mesh nodes. The proposed method's automation potential is expected to support lifecycle integrity management of pipelines.
{"title":"A probabilistic-based numerical modeling of natural gas pipelines with random corrosion morphology","authors":"Yihuan Wang , Yubo Yang , Jianjun Qin , Yinghao Sun , Guojin Qin","doi":"10.1016/j.ijpvp.2025.105696","DOIUrl":"10.1016/j.ijpvp.2025.105696","url":null,"abstract":"<div><div>This study presents a probabilistic-based method for modeling realistic corrosion morphology on natural gas pipelines with the random field node mapping coupling (RF-NMC) model. An anisotropic random field is used to reconstruct mesh geometry through node-level random displacement. High-precision mesh deformation and local coordinate mapping enable adaptive geometric transformation. This ensures an accurate representation of corrosion features. The model is embedded in a finite element (FE) modeling to achieve precise, fast, and flexible prediction of failure pressure and identify failure paths. Compared with simplified geometry models, the RF-NMC approach significantly improves the accuracy of failure pressure predictions, as confirmed by burst tests. The method strikes a balance between accuracy and computational efficiency, allowing for the quick simulation of complex corrosion geometries while maintaining reliability. The main novelty lies in directly coupling anisotropic random fields with FE mesh nodes. The proposed method's automation potential is expected to support lifecycle integrity management of pipelines.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105696"},"PeriodicalIF":3.5,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-28DOI: 10.1016/j.ijpvp.2025.105689
Kai Yu , Xinhong Li , Ziyue Han , Xiuquan Liu , Yuanjiang Chang , Guoming Chen
Pressure shells are widely employed in subsea energy development. The manufacturing process and harsh marine environments may lead to the damage of shells, which may reduce the strength, and even lead to the instablility of subsea shell. This study aims to investigate the buckling behavior of capsule-shaped pressure shells with defects under hydrostatic pressure corresponding to a 2000 m water depth, with a focus on understanding the effects of single and multiple defects on the critical buckling load. A FE model of a capsule-shaped pressure shell is developed, and nonlinear buckling analyses are performed using the Riks method. Two types of defects are considered, i.e., initial geometric defects, e.g., out-of-roundness, and damage defects, e.g., corrosion or cracks. It is observed that the effect of initial geometric defects on critical buckling load is negligible. For single defects, corrosion area, corrosion depth, and crack length are dominant factors affecting buckling resistance. In cases of the double corrosion defects, the critical buckling load gradually recovers with increasing corrosion distance. For coupled crack-corrosion defects, most significant reduction in critical buckling load occurs when crack boundary just comes into contact with the corrosion pit. This study quantitatively investigates the coupled effects of defects on structural stability, and the outcomes can be applied for integrity management of capsule-shaped subsea pressure shells.
{"title":"Buckling failure assessment of capsule-shaped subsea pressure shell containing defects","authors":"Kai Yu , Xinhong Li , Ziyue Han , Xiuquan Liu , Yuanjiang Chang , Guoming Chen","doi":"10.1016/j.ijpvp.2025.105689","DOIUrl":"10.1016/j.ijpvp.2025.105689","url":null,"abstract":"<div><div>Pressure shells are widely employed in subsea energy development. The manufacturing process and harsh marine environments may lead to the damage of shells, which may reduce the strength, and even lead to the instablility of subsea shell. This study aims to investigate the buckling behavior of capsule-shaped pressure shells with defects under hydrostatic pressure corresponding to a 2000 m water depth, with a focus on understanding the effects of single and multiple defects on the critical buckling load. A FE model of a capsule-shaped pressure shell is developed, and nonlinear buckling analyses are performed using the Riks method. Two types of defects are considered, i.e., initial geometric defects, e.g., out-of-roundness, and damage defects, e.g., corrosion or cracks. It is observed that the effect of initial geometric defects on critical buckling load is negligible. For single defects, corrosion area, corrosion depth, and crack length are dominant factors affecting buckling resistance. In cases of the double corrosion defects, the critical buckling load gradually recovers with increasing corrosion distance. For coupled crack-corrosion defects, most significant reduction in critical buckling load occurs when crack boundary just comes into contact with the corrosion pit. This study quantitatively investigates the coupled effects of defects on structural stability, and the outcomes can be applied for integrity management of capsule-shaped subsea pressure shells.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105689"},"PeriodicalIF":3.5,"publicationDate":"2025-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-27DOI: 10.1016/j.ijpvp.2025.105693
Chih-Hsuan Lee
The nozzles in RPV systems are critical components due to their high-stress concentrations, which can significantly affect the system's structural integrity. Despite the relatively minor impact of material radiation embrittlement, the stress concentration at nozzle corners should be closely monitored and precisely evaluated to ensure long-term operational safety. As different RPV nozzle geometries result in varying stress distributions and stress intensity factors (SIFs) for specific crack depths along a 45° path from the high-stress concentration point, identifying the geometry with the lowest SIFs represents the optimal design. Recently, artificial intelligence (AI) algorithms have been used to assist in calculating the stress distribution in finite element analysis (FEA), which can rapidly acquire a solution without any convergence issues during FEA. In this work, the verified finite element models (FEMs) of the RPV nozzle are established to generate extensive datasets, which correspond to various geometry sizes with the SIFs. These results are then applied to a machine learning model, support vector regression (SVR), which includes a kernel function that is suitable for high-dimensional cases. After training the SVR model, it was applied to particle swarm optimization (PSO) to identify the optimal design for the RPV nozzle geometry. The results demonstrate that the PSO with the trained SVR model can find an optimal design of nozzle geometry, which is better than the FEA results.
{"title":"Prediction and optimization of stress intensity factors for reactor pressure vessel nozzles using support vector regression and particle swarm optimization","authors":"Chih-Hsuan Lee","doi":"10.1016/j.ijpvp.2025.105693","DOIUrl":"10.1016/j.ijpvp.2025.105693","url":null,"abstract":"<div><div>The nozzles in RPV systems are critical components due to their high-stress concentrations, which can significantly affect the system's structural integrity. Despite the relatively minor impact of material radiation embrittlement, the stress concentration at nozzle corners should be closely monitored and precisely evaluated to ensure long-term operational safety. As different RPV nozzle geometries result in varying stress distributions and stress intensity factors (SIFs) for specific crack depths along a 45° path from the high-stress concentration point, identifying the geometry with the lowest SIFs represents the optimal design. Recently, artificial intelligence (AI) algorithms have been used to assist in calculating the stress distribution in finite element analysis (FEA), which can rapidly acquire a solution without any convergence issues during FEA. In this work, the verified finite element models (FEMs) of the RPV nozzle are established to generate extensive datasets, which correspond to various geometry sizes with the SIFs. These results are then applied to a machine learning model, support vector regression (SVR), which includes a kernel function that is suitable for high-dimensional cases. After training the SVR model, it was applied to particle swarm optimization (PSO) to identify the optimal design for the RPV nozzle geometry. The results demonstrate that the PSO with the trained SVR model can find an optimal design of nozzle geometry, which is better than the FEA results.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105693"},"PeriodicalIF":3.5,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145465517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-27DOI: 10.1016/j.ijpvp.2025.105695
Hyun-Jae Lee , Hune-Tae Kim , Seok-Pyo Hong
To investigate the guidance for existing methods to estimate stress intensity factors (KI) and the J-integrals for circumferentially cracked pipes in the presence of weld residual stress (WRS), finite element (FE) analysis is conducted. The axial component of the Level 3 WRS profiles provided in R6 is considered. It is found that the weight function method is applicable for KI estimation, and Vo can be taken as unity for J estimation as advised in R6. Furthermore, the interaction, within elastic-plastic regime, between the Level 3 profiles and axial tension as mechanical loading can be addressed using the no elastic follow-up V-factor, V(2). Noting that reconstruction of WRS for fracture mechanics FE analysis is demonstrated, and an extension to the Level 2 profiles, upper-bound profiles, is discussed as a means to reduce conservatism.
{"title":"FE validation of R6 J estimation for circumferentially cracked pipes under combined residual stress and mechanical loading: Reconstruction of R6 Level 3 axial residual stress for pipe butt weld","authors":"Hyun-Jae Lee , Hune-Tae Kim , Seok-Pyo Hong","doi":"10.1016/j.ijpvp.2025.105695","DOIUrl":"10.1016/j.ijpvp.2025.105695","url":null,"abstract":"<div><div>To investigate the guidance for existing methods to estimate stress intensity factors (<em>K</em><sub><em>I</em></sub>) and the <em>J</em>-integrals for circumferentially cracked pipes in the presence of weld residual stress (WRS), finite element (FE) analysis is conducted. The axial component of the Level 3 WRS profiles provided in R6 is considered. It is found that the weight function method is applicable for <em>K</em><sub><em>I</em></sub> estimation, and <em>V</em><sub><em>o</em></sub> can be taken as unity for <em>J</em> estimation as advised in R6. Furthermore, the interaction, within elastic-plastic regime, between the Level 3 profiles and axial tension as mechanical loading can be addressed using the no elastic follow-up <em>V</em>-factor, <em>V</em><sup><em>(2)</em></sup>. Noting that reconstruction of WRS for fracture mechanics FE analysis is demonstrated, and an extension to the Level 2 profiles, upper-bound profiles, is discussed as a means to reduce conservatism.</div></div>","PeriodicalId":54946,"journal":{"name":"International Journal of Pressure Vessels and Piping","volume":"219 ","pages":"Article 105695"},"PeriodicalIF":3.5,"publicationDate":"2025-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-25DOI: 10.1016/j.ijpvp.2025.105675
Yuman Sun , Wenhong Ding , Zhonghai Zang , Hongyuan Ding , Zhuang Chen , Chenxu Wang
This study investigates the degradation of fracture toughness in AISI 4130 steel exposed to high-pressure hydrogen through integrated experimental testing and finite element modeling. Slow strain rate tensile (SSRT) and elastic-plastic fracture toughness tests were performed at 5 MPa, 10 MPa, and 30 MPa hydrogen pressures, with ambient air serving as a reference. Experimental results revealed a pronounced deterioration of mechanical properties, evidenced by a significant reduction in elastic-plastic fracture toughness (JIC) from 60.34 kJ/m2 in ambient air to 9.99 kJ/m2 under 30 MPa hydrogen pressure. Concurrently, the hydrogen embrittlement index (IHE) increased from 70.68 % at 5 MPa to 86.26 % at 30 MPa. Fractographic analysis further demonstrated a progressive transition from ductile microvoid coalescence (MVC) in ambient air to a mixed mode of quasi-cleavage (QC) and martensitic lath decohesion (MLD) at intermediate pressures, and ultimately to intergranular (IG) fracture at 30 MPa. Coupled finite element simulations elucidated hydrogen diffusion and accumulation at the crack tip under stress gradients. The numerical analysis confirmed that elevated hydrogen pressure enhanced both lattice and trapped hydrogen enrichment, leading to intensified strain localization and a reduction in the critical stress required for crack propagation. These numerical results corroborated the experimental observations, confirming that the synergistic effects of hydrogen-enhanced localized plasticity (HELP) and hydrogen-enhanced decohesion (HEDE) mechanisms inhibit crack-tip blunting, reduce energy dissipation, and accelerate the transition from ductile to brittle fracture. These findings provide a mechanistic foundation for predicting fracture behavior in high-pressure hydrogen environments and underscore the necessity of incorporating fracture toughness degradation into structural integrity assessments of high-pressure hydrogen storage systems.
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