bluuebunny/crossref_metadata_2025_split huggingface dataset:
Convolutional Neural Network Models for Reconstruction and Sizing of Three-Dimensional Metal-Loss Defects in Oil and Gas Pipelines Based on Magnetic Flux Leakage Signals
Authors: Shen Yufei , Zhou Wenxing 
Published: November 2023

Abstract
In this study, a three-dimensional nonlinear finite element magnetostatic model is developed in the commercial package COMSOL Multiphysics (Version 5.6) to simulate magnetic flux leakage (MFL) signals for corroded pipelines. A large number of parametric finite element analysis cases covering wide ranges of locations and sizes of corrosions defects idealized as semi-ellipsoidal-shaped are used to produce the magnetic flux density signals. The white noises characterized by different signal-to-noise ratios are employed in the parametric analysis to represent the measurement errors in the MFL tool. The results of the parametric analyses are then used to train and validate a convolutional neural network (CNN) model to predict the location, depth, length and width of the corrosion defect simultaneously. The results indicate that the developed CNN model has a high predictive accuracy.
Comparison of Impact Toughness Properties in Grade 22 Steel HAZ After PWHT and Temper Bead Welding
Authors: Jang Eun , Alexandrov Boian , McCracken Steven L. , Barborak Darren 
Published: November 2023

Abstract
Welding of thick low alloy steel components without elevated preheat imposes rapid cooling rates that may promote martensite formation in the coarse-grained heat affected zone (CGHAZ). Freshly formed martensite contains a distorted and supersaturated matrix with high dislocation densities. As a result, fracture and impact toughness properties of these regions are inherently low and post weld tempering procedures are typically required. Conventional postweld heat treatment (PWHT) involves extended isothermal holds at elevated temperature which allows for considerable softening of the martensitic structure but has been found to have less effect on improving impact toughness. In contrast, short-term tempering processes with rapid heating and cooling rates and short times at elevated temperature have been shown to greatly improve impact toughness through a shift in the kinetics of martensite tempering that produces high number densities of refined carbides. Temper bead welding (TBW) was developed for inservice repair of thick steel components where PWHT was impractical or not possible. With temper bead welding, the heat-affected-zone is tempered by one or more rapid re-heat cycles from overlapping weld beads or weld layers. This study compares the Charpy V-notch impact toughness and fracture morphology of the CGHAZ in the as-welded condition, with conventional PWHT, single temper bead reheat, and multiple temper bead reheats for an SA-387 Grade 22 alloy steel.
Fatigue Crack Growth Rate Study of New X52 Line Pipe Steel in Hydrogen Blended Methane
Authors: Chandra Ashwini , Thodla Ramgopal , Sosa Siari 
Published: November 2023

Abstract
Hydrogen is an alternative fuel to consider for decarbonization as its combustion does not result in production of greenhouse gases. The transport of hydrogen from production to end use location is a critical part of deployment and blending of hydrogen in the natural gas transmission and distribution pipeline network is a cost effective option. However, the interaction of hydrogen with the pipeline material needs to be evaluated due to risks associated with hydrogen embrittlement. In this study, fatigue properties of a new X52 line pipe material with an HFW seam weld was evaluated to identify the impact of up to 10% hydrogen blending at a pressure of 1800 psi. A fracture mechanics-based approach was used to test the fatigue crack growth rate (FCGR) of microstructures associated with parent pipe, seam weld, seam weld – heat affected zone (HAZ), girth weld and girth weld HAZ. The gas environment was simulated in an autoclave pressurized to 1800 psi (12.4 MPa) total pressure using 1, 5 and 10 mole% hydrogen blends in methane. FCGR was also measured in 100% methane environment to establish a baseline to compare the properties in the selected hydrogen blends. The Paris curves were measured at a constant R ratio of 0.3. Increase of the FCGR above those measured in the 100% methane environment baseline was observed for all the microstructures at all concentrations of hydrogen. The degree of increase in FCGR as well as in the range of stress intensity factor (ΔK) where the increase was observed, varied to some extent between microstructures. Results were also compared to the ASME B31.12 curve for carbon steel in hydrogen, to understand the degree of conservatism associated with the ASME curve for the hydrogen blends.
Modeling and Experimental Analysis of Electromagnetic Ultrasonic Testing Considering Effect of Rough Surface
Authors: Wang Zhe , Fan Zhichao , Chen Xuedong , Cheng Jingwei , Wang Haibin , Bu Yangguang 
Published: November 2023

Abstract
Electromagnetic acoustic transducer (EMAT) is widely used in wall thickness measurement, which is suitably used in periodic inspection or long-term monitoring of pressure equipment. However, the corroded surfaces appearing on the pressure pipes and vessels usually cause an increase of background noise and variation of sound field, which restrict the improvement of measurement accuracy. In this paper, a numerical model of EMAT containing random rough surface is established based on the constitutive equation of Lorentz force and magnetostriction force. The distribution of eddy current at the skin layer in the excitation or receiving process of EMAT are analyzed. The characteristics of energy conversion of multi-physical coupling fields under effect of rough surface is clarified. Then, the variation law of measurement accuracy of wall thickness for EMAT under rough surface is obtained and compared by simulation and experiment. The results show that more interference sound waves come into being under rough front surface and the attenuation of signal-to-noise ratio (SNR) is more significant comparing to rough back surface. When the roughness is within 120μm, a better wall thickness accuracy can be obtained by means of multiple measurements. When the surface roughness is larger than 120μm, the measurement error exceeds 0.1mm. Therefore, when the surface of pressure equipment is in good condition, the high-precision thickness measurement of EMAT without grinding process can be realized. Otherwise, local grinding can significantly improve the measurement accuracy.
Fracture Toughness Estimation of High-Grade Pipeline Steel Girth Weld in Ductile-Brittle Transition Zone
Authors: Gui Lele , Zhou Tianyu , He Renyang 
Published: November 2023

Abstract
Determination of fracture toughness for weld has always been a difficult problem because of the existence of defects and material discontinuity in weld. In this paper, the fracture toughness distribution and ductile-brittle transition characteristic of X70 pipeline steel girth weld were investigated by means of fracture toughness curves based on RTNDT, master curve method, instrument indentation method and convention fracture toughness test, applicability of these methods is studied by comparing with actual-measured fracture toughness values and charpy impact test results. The results show that fracture toughness curves based on RTNDT are sufficiently conservative in the whole ductile-brittle transition zone and lower bound. The lower envelop curve is more conservative when it is higher than DBTT, while revised fracture toughness curve is more conservative when it is lower than DBTT. The reference temperature of Master Curve for X70 pipeline steel girth weld by 0.5T SE(B) specimens equals −98 °C, 1% and 95% cumulative failure probability curves can well envelop the fracture toughness distribution of X70 girth weld, which shows great flexibility in the estimation of fracture toughness of X70 pipeline steel girth weld. Fracture toughness values of ductile mode by instrumented indentation can be used to estimate the DBTT of X70 girth weld.
Application of Multivariate Acoustic Emission Parameters in Damage Monitoring and Assessment of a Low-Alloyed Steel
Authors: Lai Chuanjing , Xu Wei , Chai Mengyu , Duan Quan , Zhang Zaoxiao 
Published: November 2023

Abstract
Acoustic Emission (AE) as a nondestructive evaluation technique has been frequently utilized to monitor the damage progression of materials and structures. Analysis based on multivariate features is more viable in completely understanding the damage progression than using only one single or limited AE parameters. Program or software facilitates the processing of AE data by finishing the feature extraction and other analysis work. This article presents the application of multivariate AE parameters in damage analysis and evaluation of a low-alloyed steel. An AE software system to understand the AE events multi-dimensionally is developed. The software is capable of feature extraction, visualization, variational mode decomposition (VMD) and Hilbert-Huang transform (HHT) for the source mechanism analysis. The AE signals generated from three-point bending of Cr-Mo steel was processed and analyzed to verify the viability of the system. Nineteen different AE features are calculated from time and frequency domains. The variation of different features associated with AE events among different stages of the test are discussed. Moreover, AE signals are decomposed by VMD into several modes that indicate the dominant frequency of AE events. Hilbert spectrum obtained via HHT presents the amplitude of AE signal in both time and frequency domain. The results of the application may provide insights in multivariate feature extraction and methods of damage assessment in metallic materials and engineering structures.
Design of Centrifugally Cast Fe-Cr-Ni Heat-Resistant Alloys Driven by Material Genome Technology
Authors: Fan Zhichao , Xiang Shulin , Chen Tao 
Published: November 2023

Abstract
Due to the excellent creep and corrosion resistance at high temperatures, heat-resistant alloy tube is the key component of hydrogenation reformer and ethylene pyrolysis furnaces in petrochemical industries. The development of material genome technology provides a new idea for the control and optimization of heat-resistant alloys. Based on the CALculation of PHAse Diagram (CALPHAD) method, the effect of key microalloying elements on the evolution of phases is detected, hence the preliminary content range of the microalloying element is determined. According to coupled finite element-cellular automaton (CAFE) model and experimental verification, the grain morphology model of centrifugal cast heat-resistant alloy is established, and the optimized parameters of pouring temperature and rotation speed are put forward. The correlation analysis between component/microstructure and creep rupture life is carried out using a machine learning (ML) approach. The classification of alloy microstructure (grain size, primary carbide morphology, etc.) based on a convolution neural network is established, and the regression of creep rupture life using a deep learning model based on multi-source heterogeneous data is exploited. Combined with the optimization algorithm, an accurate design of alloy composition for target service life is developed. The alloy design method based on material genome technology will accelerate the R&D and application of new heat-resistant materials and advanced components.
Investigation of Ultimate Behavior of Elbow Pipes by Tensile Loading Test in the Direction of In-Plane Bending
Authors: Shimazu Ryuya , Sakai Michiya , Ono Yohei 
Published: November 2023

Abstract
Probabilistic risk assessment is useful in considering the safety of nuclear power plants. To recognize the weaknesses of structures, a realistic fragility assessment must be conducted. Furthermore, it is important to set the failure mode appropriately for a realistic fragility assessment. However, few experimental data for the ultimate state of elbow piping with ductile rupture compared to fatigue exist. In this study, tensile loading tests of full-scale elbow pipes were conducted to enrich the knowledge of failure modes of piping systems. 150A Sch80 and 200A Sch40 elbow pipes made of carbon steel (JIS STPT410S) did not rupture despite the ductility factor exceeding 30. Therefore, the possibility of ductile rupture of elbow pipe under earthquakes is extremely low. Aiming at a realistic fragility assessment of ductile rupture, analytical models that precisely predict the test results were investigated. For a 150A Sch80 pipe, which did not show buckling deformation in the test, the FEM model using shell elements was able to predict with good accuracy. For a 200A Sch40 pipe, even one that buckled at the top of the elbow, the behavior, including buckling, was able to be predicted with good accuracy.
Exploring 3D X-Ray Diffraction Method to Validate Approaches in Materials Modelling
Authors: Ramadhan Ranggi S. , Al Mamun Abdullah , Ball James A. D. , Demir Eralp , Collins David M. , Agius Dylan , Mostavafi Mahmoud , Knowles David 
Published: November 2023

Abstract
Cyclic high temperature deformation, which is a precursor to creep-fatigue damage is one of the main life limiting factors in thermal power plants. Microstructurally informed models such as crystal plasticity have shown great promise in predicting cyclic plasticity and creep deformation; however, further validation of predicted meso-scale deformation is required to ensure accurate damage calculations. Here, a novel 3D X-ray diffraction (3DXRD) experiment was performed to resolve and investigate the response of individual grains within a polycrystalline material under loading at elevated temperature. Specimens were made from 316H stainless steel, which is an alloy commonly used for critical structural components in thermal power generation plants. The 3DXRD experiments were conducted at the UK national synchrotron facility, Diamond Light Source. The measurements provided positions, strain tensors, and orientations of individual grains within a gauge volume. The data generated from 3DXRD was used both as an input and for the validation of a crystal plasticity finite element model (CPFE). The results provided demonstrate the importance of microstructural information in materials modelling.
Overview of Revisions to the ASME Boiler and Pressure Vessel Code Section VIII Division 3 for the 2023 Edition and Near Future
Authors: Peters Daniel T. , Subramanian Kannan , Sarzynski Melanie 
Published: November 2023

Abstract
This paper gives an overview of the major revisions pending in the upcoming 2023 edition of the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC) Section VIII Division 3, Alternative Rules for Construction of High Pressure Vessels, and potential changes being considered by the Subgroup on High Pressure Vessels (SG-HPV) for future editions.
This will include an overview of significant actions which will be included in the upcoming edition, including updates to the rules for User’s Design Specifications (UDS’s). Many changes include clarifications regarding subjects such as the definition of T vs. t in material testing, and the supplementary requirements for toughness testing in KM-250 and when they are required. Another was to clarify that the requirements in ASME VIII-3 which may conflict with certain requirements in material specifications make it such that all parts of material specifications do not need to be followed. There was another change regarding interpolation between low alloy fatigue curves. Another significant change was clarification regarding which constitutive material model is to be used in various design by analysis situations and the need for consistency between those material models. Several changes were also made regarding environmental interaction and stress corrosion cracking.
Investigation on a Method of Counting Low-Cycle Fatigue in Steel Under Crack Closure and Random Variable Amplitude Loading
Authors: Watanuki Jo , Kawabata Tomoya , Takagi Shunsuke 
Published: November 2023

Abstract
Low-cycle fatigue (LCF) plays an important role in the evaluation of steel structures subjected to cyclic large stresses, such as the reactor pressure vessel. In LCF, fracture is caused by the propagation of cracks generated by large deformations. Therefore, it is important to predict how the cracks will grow and when the structures are broken. However, the conventional method for predicting the number of cycles of fracture (Nf) in LCF is incomplete. This is because it is not revealed whether the conventional counting method of the number of random amplitudes, Rain Flow Method, can be applied after crack initiated because the crack closure occurs. This means that the invalid cycles which do not contribute to the crack propagation due to the crack closure are counted by using Rain Flow Method. In other words, it is required to confirm whether Rain Flow Method is applicable to the cracked material and make a mechanism for precisely predicting the life in random LCF amplitudes by removing the crack closure.
In this paper, the validation of Rain Flow Method was investigated with following two steps. First, the relationship of the ΔVg, amp-Nf were obtained. Second, the prediction of the life in random LCF amplitudes was employed through ΔVg, amp-Nf, Rain Flow Method and Linear Cumulative Damage Rule (LCDR). In addition, the investigation of how to remove the crack closure was conducted by using the point of the change of slope of P-Vg, the analysis of dadN-Δδeff, and FE model.
Evaluation of the API 579-1/ASME FFS-1 KCSCCL1 Global Bending Stress Intensity Factors
Authors: Bouse Scott , Altstadt Steven 
Published: November 2023

Abstract
The API 579-1/ASME FFS-1 2021 (API 579) Fitness-For-Service stress intensity factor solution for a cylinder with a long surface crack in the circumferential direction (i.e., 360 degrees), subjected to Pressure, a Net-Section Axial Force and Global Bending (KCSCCL1) was independently investigated in this work. Linear elastic finite element models of cracked cylinders subjected to various applied global bending stress fields were created and used to estimate stress intensity factors (K), from which were determined the respective influence coefficient values for global bending (G5). The comparison of the newly calculated values to the existing stress intensity factors shows reasonable agreement for larger internal radius to thickness ratios (Ri/t), but significant differences for low ratios representing thick wall cylinders. The new influence coefficients were also compared to values previously published in the literature for the parameter combinations that exactly overlap with API 579 for the Ri/t ≤ 10 parametric space. The new stress intensity factor equation and associated influence coefficient values presented in this work are recommended as an improvement for fitness for service assessments where Ri/t &lt; 10. For thin wall cylinders, the existing API 579 approach for KCSCCL1 is acceptable.
Semi-Analytical Solutions of Fracture Parameters for Curved CT Specimen From CANDU Pressure Tube
Authors: Cao Yupeng , Bao Chen 
Published: November 2023

Abstract
The pressure tubes of Zr-2.5Nb are primary pressure boundaries in a CANDU reactor. The major threat to the inservice pressure tubes is posed by Delayed Hydrogen Crack (DHC) initiation and growth. The fracture initiation toughness values are the necessary input data required by CSA N285.8[1]. The curved compact tension (CCT) specimens are recommended. However, the CCT specimen is not a standard specimen specified by ASTM E1820[2]. This paper studies the K factor, the compliance C and the J-integral solutions for the CCT specimen using theoretical analysis and FEA modeling. The modified solutions are compared with the results from the solution for standard CT specimen in E1820 and from FEA. The applicability of the modified solutions is discussed in this paper.
A Novel Machine Learning Based Framework for the Seismic Risk Assessment of Industrial Plant
Authors: Quinci Gianluca , Paolacci Fabrizio 
Published: November 2023

Abstract
In last decades, Machine learning techniques (ML) have been extensively studied as a possible reliable family of regression methods. Recently ML, which originated in the field of computer science, has been widely investigated as an alternative and helpful method for solving engineering problems. The main feature of ML techniques is learning from a dataset, containing a certain amount of input/output fidelity data, in order to predict future output data related to a new set of input data in cost-effective computation time. With these premises, the application of this type of techniques to the civil engineering field, where a sufficient amount of data is available by means numerical and experimental simulations and from structural monitoring, seems interesting. Along this vein, the present paper aims to investigate the suitability of a novel ML based framework for the risk assessment of a Non Structural Component (NSC) of an industrial plant. The proposed method, which aims to solve some critical issues associated to the traditional risk assessment methodology, has the follow main advantages: (i) reduction of computational time by means an Artificial Neural Network (ANN) surrogate model; (ii) avoidance of prior assumptions on the distribution of fragility curves, sampling a large amount of data from the ANN surrogate model; (iii) avoidance of the record to record variability of the seismic input through a new record selection algorithm; (iv) integration of hazard and vulnerability analysis in the same framework. In this respect, a comprehensive sensitivity analysis of the ANN input parameters is performed (features selection), identifying the type and number of Intensity Measures (IMs) that represent the seismic input best related to the structural output, using Principal Component Analysis (PCA). Furthermore, a multiple stripe analysis is performed on a nonlinear finite element model (FEM) of the structure, deriving the set of data used to train and validate the ANN. Then, two different surrogate models in series are derived, investigating the architecture of the models (i.e. the number of hidden layers and parameters weight), to take into account both the dependence between the selected IMs and the relation between the IMs and the structural response. Different training and test subsets are used to derive the surrogate models, to find the best-performing structure. A sampling of the seismic input parameters of the ANN is obtained followed their probability distribution by means Metropolis-Hastings algorithm, to take in account the hazard of the site, and the risk assessment is directly carried out from the observed damage evaluated. The proposed framework, which represents an interesting alternative for seismic risk assessment, is finally applied to an industrial NSC.