Search Results (3,328)

Hydrogen embrittlement is known to adversely affect the mechanical properties of low-carbon steels used for pipelines and pressure vessels, leading to accelerated crack growth and lowered fracture toughness. To overcome the limitations of surface-based analysis, this study employs X-ray micro-computed tomography (µ-CT) to provide a comprehensive 3D evaluation of the crack evolution. This approach is used to assess hydrogen-assisted crack growth in P355NH compact tension samples from previous fracture mechanical tests and enables a precise quantification of the internal crack path and the crack tip opening angle (CTOA) across the entire specimen thickness as well as the local damage morphology. By integrating these spatial parameters, a deeper understanding of the impact of hydrogen on local fracture mechanisms is achieved, revealing insights that have remained hidden in previous two-dimensional microscopy observations. For instance, µ-CT results clearly demonstrate that the hydrogen-assisted crack propagation is associated with increased void formation and secondary cracking in vicinity of the crack tip. However, it is proposed that the results are superimposed with continuous hydrogen desorption, which implies a need for in situ charging during mechanical loading and an analysis of the hydrogen concentration profile. Both will be the scope of further studies. Full article

The presence of random fissures significantly alters the mechanical properties and failure mechanisms of rocks. To systematically investigate the impact of fissures on the failure behavior of sandstone, a multivariable random fissure numerical model was developed based on the Weibull distribution probability density function, in combination with a random fissure generation algorithm and cohesive element embedding method. This study primarily focuses on analyzing the influence of fissure ratio (R), fissure dip angle interval (A), fissure length interval (L), and fissure width interval (W) on the sandstone failure process. The results show that the failure modes change with variations in R, A, L, and W, specifically manifested as the formation of “X”-shaped, “Y”-shaped, or inverted “Y”-shaped primary cracks; the increase in fissure ratio significantly reduces both peak stress and total damage dissipated energy (ALLDMD), and promotes the propagation of tensile cracks; the increase in L leads to more complex failure patterns, but its effect on peak stress and peak strain fluctuates non-linearly, the ALLDMD remains insensitive to this change, while the number of tensile cracks decreases as L increases; conversely, an increase in W results in a failure mode characterized by a single crack path, the peak stress first increases and then decreases, and the ALLDMD exhibits an “N”-shaped fluctuation, though the overall variation is limited. Full article

This study investigated the enhancement mechanisms and optimal mix proportion of basalt fiber (BF) in concrete for ship lock galleries. It focused on improving crack resistance, freeze–thaw resistance, impermeability, and abrasion–erosion resistance under complex hydraulic environments. Single-factor tests first determined the reasonable parameter ranges, which were subsequently used in a three-factor, four-level orthogonal experiment to analyze the effects of the water-to-binder ratio, fiber content, and fiber length on concrete’s mechanical properties. Range analysis of the orthogonal experiment indicated that the water-to-binder ratio was the most dominant factor (R = 57.4), followed by fiber content. Based on this, further durability tests were conducted, including ring restraint cracking, impermeability, freeze–thaw resistance, and abrasion–erosion resistance. Multi-objective optimization was performed using full factorial experiments and a comprehensive performance evaluation system. The final optimal mix proportion was determined as: a water-to-binder ratio of 0.35, a fiber content of 0.2%, and a fiber length of 12 mm. With this mix, the concrete’s ring cracking time was extended by 69.9%, the relative dynamic elastic modulus retention reached 73.0% after 100 freeze–thaw cycles, the relative permeability coefficient was 1.04 × 10⁻⁶ cm/h, and the abrasion–erosion resistance strength increased to 7.05 h·m²/kg, which achieved an optimal synergy among the mechanical properties, key durability indicators, and their workability. Mechanism analysis revealed that BF formed a three-dimensional, randomly distributed fiber network that comprehensively enhanced concrete performance through multi-scale mechanisms, including bridging, pore refinement, and energy dissipation. This research has provided systematic experimental evidence and mix proportion support for the durability design and engineering application of BF concrete in ship lock galleries. Full article

Welded joints in API 5L X70 pipeline steel represent critical locations for pipelines intended for hydrogen service because welding can create microstructural inhomogeneity, stress concentrations, and uneven mechanical properties that can promote hydrogen-assisted degradation. In hydrogen-containing environments, these effects may manifest as reduced ductility, loss of fracture resistance, and increased cracking susceptibility, particularly in the weld metal and heat-affected zone. Therefore, welding procedures for X70 intended for hydrogen applications must be evaluated using systematic mechanical testing and microstructural characterization under defined hydrogen exposure conditions. The study investigates the detrimental effects of hydrogen on the mechanical integrity of pipeline materials, focusing on welded joints of the API 5L X70 steel, a candidate material for use in hydrogen-containing environments. The weldability and structural performance of the X70 pipeline steel joints in hydrogen environments, produced using automated multi-pass metal active gas (MAG) welding, was experimentally studied. Welding was performed on a DN800 pipe with precise control over welding parameters. Comprehensive analyses were conducted on the welded joints, including microstructure examinations, hardness measurements, slow strain rate testing in high-pressure gaseous H₂ with a N₂ baseline and fracture toughness testing. In high-pressure hydrogen SSRT showed a moderate reduction in ductility relative to nitrogen, with reduction of area decreasing from 81.2% (N₂) to 69.1 and 71.5% (H₂), while time-to-failure remained comparable (475 min in N₂ vs. 497 and 496 min in H₂) Ultimate tensile strength was not reduced (579 MPa in N₂ vs. 609 and 597 MPa in H₂). Secondary surface cracks were observed only on specimens tested in hydrogen. Fracture mechanics testing after hydrogen exposure yielded K_IH values of 58–59 MPa√m in the weld metal and 57–61 MPa√m in the HAZ, exceeding the 55 MPa√m acceptance threshold applied in this study. The results highlight the necessity of optimized welding techniques and targeted material analyses to ensure the safety and durability of pipelines in hydrogen-rich environments, thereby contributing to the development of reliable infrastructure for sustainable energy systems. Full article

Laser Powder Bed Fusion for metals (PBF-LB/M) is a complex additive manufacturing process in which metal powder is selectively melted layer-by-layer to fabricate 3D parts. Process parameters critically influence the resulting microstructure in nickel alloys, with features such as melt pool marks, grain size and orientation, porosity, and cracks serving as key process signatures. These features are typically analyzed post-process to identify suboptimal conditions. This research aims to develop automated post-process measurement and analysis techniques using image processing, pattern recognition, and statistical learning to correlate process parameters with part quality. Optical microscopy images of build surfaces are analyzed using machine learning algorithms to evaluate porosity, grain size, and relative density in fabricated test coupons. Effect plots are generated to identify trends related to increasing energy density. A novel deep learning approach based on Mask R-CNN is used to detect and segment melt pool regions in optical microscopy images. From the segmented regions, melt pool dimensions—such as width, depth, and area—are extracted using bounding geometry coordinates. Manually labeled images (Type I and Type II) are used to train the model. A comparison between ResNet-50 and ResNet-101 backbones shows that the ResNet-50-based model (Model 2) achieves superior performance, with lower training loss (0.1781 vs. 0.1907) and validation loss (8.6140 vs. 9.4228). Quantitative evaluation using the Jaccard index, precision, and recall metrics shows that the ResNet-101 backbone outperforms ResNet-50, achieving about 4% higher mean Intersection-over-Union, with values of 0.85 for Type I and 0.82 for Type II melt pools, where Type I is detected more accurately due to its more regular morphology and clearer boundaries. By extending Faster R-CNNs with a mask prediction branch, the method allows for precise melt pool measurements, providing valuable insights into process quality and dimensional accuracy, and aiding in the detection of defects in PBF-LB-fabricated parts. Full article

Rock fracture behavior is strongly influenced by grain size and boundary effects, which complicate the determination of fracture parameters and the interpretation of size-dependent failure. This study investigates the fracture behavior of sandstone and diorite within the framework of the boundary effect model (BEM) using three-point bending tests, acoustic emission (AE), and digital image correlation (DIC). By varying the prefabricated crack length, different values of the structural geometric parameters a_e were obtained, and the fracture toughness K_IC and tensile strength f_t were identified by regression analysis. The results show that K_IC = 0.6841 MPa·m^0.5 and f_t = 4.5625 MPa for sandstone, whereas K_IC = 2.7233 MPa·m^0.5 and f_t = 21.8218 MPa for diorite. Increasing the prefabricated crack length reduces the peak load and prolongs the pre-peak damage evolution stage. Diorite, with a larger average grain size, exhibits higher AE energy release, a higher proportion of high-energy AE events, and a larger fracture process zone (FPZ) than sandstone. Moreover, the AE energy distribution along the crack propagation direction shows a distinct “three-stage” characteristic, consistent with the non-uniform distribution of local fracture energy g_f predicted by boundary effect theory. The results indicate that BEM can reasonably characterize the fracture behavior of rocks with different grain sizes, and the identified material parameters can be used to construct a BEM-based structural failure curve for estimating nominal failure stress over a wider range of structural geometric parameters. Full article

The paper investigates the applicability of time series models for processing data obtained from a customized crack-propagation sensor. Because the sensor records a variable and noise-affected waveform, the study focuses on models capable of forecasting signals composed of both trend and stochastic components. Adaptive, analytical, and autoregressive approaches were examined, with particular attention to their suitability for short, non-stationary sequences typical of fatigue-related measurements. Based on the statistical characteristics of the sensor output during crack growth, the ARIMA model was selected for further analysis and algorithm development. The forecasting performance of ARIMA was evaluated for different parameter configurations by comparing the range and variability of the base and predicted data. Initial tests using first-order parameters produced unsatisfactory results, with high variance observed in both raw and modeled signals. Therefore, model parameters were optimized using the aicbic function, and the analyses were repeated. For the selected datasets, variance reduction by 3–4 orders of magnitude was achieved, demonstrating a substantial improvement in prediction stability. The presented results confirm that the proposed methodology is effective for processing complex sensor signals and highlight the broader significance of applying statistically grounded time series models in structural health monitoring. The study introduces an innovative framework for evaluating fatigue-related sensor data and establishes a reliable baseline for future predictive methods. Full article

This study investigates the effect of microstructure on water-induced embrittlement of dual-phase austempered ductile iron (ADI). Dual-phase ADI materials were produced by austenitization at 780, 800, 820, and 840 °C followed by austempering at 400 °C/1 h, resulting in microstructures composed of varying fractions of free ferrite and ausferrite. Tensile properties were evaluated under dry conditions and in distilled water. The embrittlement zones were observed in all samples investigated; however, they were not critical in all cases. The results indicate that free ferrite is less sensitive to water-induced embrittlement, whereas increasing ausferrite content promotes the formation and growth of the embrittlement zone. Elongation was identified as the most sensitive mechanical parameter, showing statistically significant reductions of up to ~80% for microstructures containing more than ~65% ausferrite, while proof strength remained largely unaffected. Fracture surface analysis revealed fatigue-like striation features within the embrittlement zone, indicating cyclic crack initiation and propagation. Based on correlations between tensile behavior, fracture morphology, and microstructural features, a water-induced embrittlement mechanism involving cyclic local chemisorption and surface-initiated crack growth is proposed. These findings highlight the critical roles of phase type, volume fraction, and spatial distribution in controlling the resistance of dual-phase ADI to embrittlement in aqueous environments. Full article

Surface cracking is a key visible indicator of deterioration in concrete infrastructure and is routinely captured by vision sensors during field inspections. To translate inspection imagery into actionable maintenance information, crack delineation must be accurate at the pixel level and robust to challenging conditions where cracks are slender, discontinuous, low-contrast, and easily confused with joints, stains, texture patterns, and illumination artifacts. This study proposes a lightweight CNN–Mamba hybrid segmentation framework built upon Vm-unet for reliable crack mapping under heterogeneous inspection scenarios and resource-constrained deployment. The framework couples boundary-sensitive convolutional features with long-range state-space representations via a spatially modulated convolution design, refines skip-connection features using reciprocal co-modulation attention to suppress background interference, and enhances cross-scale interactions through a decoder interaction fusion scheme to preserve fine-crack continuity and sharp boundaries. Experiments on a multi-source composite dataset and public benchmarks show consistent improvements over representative CNN-, Transformer-, and Mamba-based baselines. The proposed method achieves 80.11% mIoU and 82.05% Dice on the composite dataset, while maintaining an efficient accuracy–cost trade-off (36.049 GFLOPs, 25.991 M parameters). The resulting crack masks provide a dependable basis for inspection-driven quantitative assessment and maintenance decision support. Full article

Plasma-facing materials (PFMs) for future fusion reactors require advanced mechanical and thermal properties to withstand the extreme challenges of high heat flux, plasma exposure, and neutron irradiation. Tungsten is one of the most suitable materials for use as a PFM in the divertor region. However, considering the high thermal loading/thermal stress combining plasma exposure and neutron irradiation/embrittlement, one of the major concerns for tungsten in PFMs is its intrinsic brittleness. To avoid cracking and components failure, tungsten toughening has been widely investigated, including the development of tungsten fiber-reinforced tungsten composites (W_f/W) using an extrinsic toughening mechanism, which could provide damage resilience against neutron embrittlement. Recently, a type of aligned long-fiber W_f/W (L-W_f/W) based on a powder metallurgical fabrication process was developed, demonstrating advanced fracture toughness while retaining other application-relevant properties. For L-W_f/W, the relatively easy production process suggests the feasibility and basis of industrialization. This work reports on the initial progress in industrializing L-W_f/W, with a focus on adapting the lab sintering process to a sintering process with industrial partner (Dr. Fritsch Sondermaschinen GmbH) and optimizing the process parameters. To improve the sinterability of tungsten and achieve higher density, various tungsten powders were explored, including commercial W powders, bimodal mixtures of different particle sizes, and granulated W powders. At the dedicated yttria interface, the thickness of yttria coating on the fibers was also optimized to ensure effective separation between the fibers and the matrix. Series of samples were produced with different dimensions up to 100 mm × 100 mm × 4 mm. After optimization, samples with 93% density and desired pseudo-ductility were prepared. Similarly to production in the lab, a major challenge in this work involved balancing the densification of the tungsten matrix with controlling fiber recrystallization and mitigating damage to the yttria interface. Full article

To meet the requirement of real-time bridge crack detection, this paper proposes a lightweight detection model based on YOLOv7-tiny. First, an edge-preserved image enhancement method is proposed. It effectively enhances the image contrast and preserves the structural features of crack edges. This provides a high-quality data foundation for the detection network. Second, a LWCSP module is introduced. This module integrates hybrid convolution and shuffle operations. It reduces the model’s parameter count and computation. Simultaneously, it maintains strong feature representation capability. A good balance between detection performance and efficiency is achieved. Finally, an improved SWise-IoU is proposed to optimize the bounding box regression in YOLOv7-tiny. This method dynamically evaluates sample quality. It enables differentiated gradient adjustment for samples of different qualities. This promotes sufficient learning of sample features by the model, thereby improving detection accuracy. Experimental results show that the proposed model delivers strong performance on a public bridge crack dataset. Compared to the baseline, the mAP@0.5 is 12.1 higher, and model size, parameter count, and FLOPs are reduced by 7.3%, 8.03%, and 10%, respectively. The final model size is only 11.4 MB, and mAP@0.5 is 86.1%, suitable for a real-time crack detection task. Full article

High nitrogen austenitic stainless steels are an important engineering structural material. Under annealing conditions, the addition of interstitial solid solution element nitrogen can improve the yield strength and tensile strength of the alloy without reducing its plasticity. In addition, nitrogen can partly or completely replace the more expensive nickel element at a relatively cheap element cost to improve economic benefits, while maintaining or even enhancing the excellent corrosion resistance of stainless steels. However, the cracks and defects caused by high nitrogen austenitic stainless steels during hot working in high temperature ranges have always been the pain points in the engineering field. High nitrogen elements bring high temperature strength, but also narrow the hot working temperature range, the possibility of nitride precipitation and the tendency of heat induced cracking, which limit the further engineering application of high nitrogen austenitic stainless steels. It is urgent to analyze and study the hot deformation law of high nitrogen austenitic stainless steels in engineering. This article commences with an examination of the developmental trajectory of high nitrogen austenitic stainless steel, elucidates the role and strengthening mechanism of nitrogen, and delineates the factors influencing the mechanical behavior of high nitrogen austenitic stainless steel during hot working. These factors include the impact of nitrogen content and manufacturing processes, hot-working parameters, grain size distribution, and the presence of precipitated phases. This article synthesizes various studies, analyzes the causes of thermal cracking, and proposes potential solutions. Ultimately, it summarizes the practical applications and future prospects of high nitrogen austenitic stainless steel, highlighting its substantial potential. Full article

The advancement of sustainable construction requires the development of earthen materials compatible with 3D printing (additive manufacturing), along with specified engineering standards. Many existing studies improve workability and early strength using chemical stabilizers such as cement; however, these additives increase embodied carbon and undermine sustainability objectives. Challenges remain in the formulation of an earthen mixture that satisfies both printability and structural requirements for large-scale construction. Previous earth-based mixes have reported excessive shrinkage and inadequate compressive strength. This study presents the systematic optimization of a low-carbon, 3D-printable earthen mixture using locally sourced clay-loam soil from Belén, New Mexico (NM). The soil was modified with graded concrete sand and rice hull fiber to improve printing parameters such as buildability, extrudability, and printability while meeting the NM Earthen Building Code requirements for compressive and flexural strength. Soil characterization tests (particle size distribution, consistency, optimal water content) guided iterative refinement to enhance dimensional stability and mechanical performance. A baseline 2:1 soil-to-sand ratio (max aggregate size No. 4) was established. Incorporating $2\%$ rice hull fiber and reducing max aggregate size to No. 16 (S67F2) early-age shrinkage was reduced from $12.33\%$ to $3.48\%$ ($72\%$ reduction) while maintaining a 28-day compressive strength exceeding 660 psi, more than twice the code minimum. The optimized mixture supported 24 printed layers without deformation, achieved 189 psi flexural strength (three times the code minimum), and produced a stable 2-ft-diameter dome with minimal cracking. Full article

Friction stir welding (FSW) is a key technology for manufacturing T-shaped thin-walled structures and avoiding fusion welding defects. However, the quantitative relationship between its process parameters and the microstructure properties of the joint remains unclear. To address this, this study established regression models via response surface methodology (RSM) relating rotational speed (w), welding speed (v), and plunge depth (h) to the mechanical properties of T-joints. The optimal process parameters (400 rpm, 60 mm/min, 0.21 mm) were determined, under which the ultimate tensile strength (UTS) and weld nugget hardness (WNH) of the joint reached 74.1% (377 MPa) and 94.4% (153 Hv) of the base materials (BM) respectively, with v showing the most significant influence on joint mechanical properties. Microstructural observations revealed that from the BM to the stirring zone (SZ), the grains underwent a continuous evolution from coarsening, partial recrystallization to complete dynamic recrystallization (DRX). In the SZ, due to severe plastic deformation and high heat input, the continuous dynamic recrystallization (CDRX) was the dominant mechanism, and the grain was significantly refined. The heat input in the thermomechanical affected zone (TMAZ) is relatively low, mainly geometric dynamic recrystallization (GDRX). DRX-driven grain refinement was the primary strengthening factor in the joint, with hardness closely related to grain size. However, thermal cycling induced softening in the heat-affected zone (HAZ) and promoted the precipitation of brittle compounds such as Al₃Mg₂ and MgZn₂, which caused crack initiation exhibiting intergranular brittle fracture. Subsequently, under stress drive, it extends to SZ, mainly characterized by ductile fracture. Full article

Arch–gravity dams feature both arch action and large concrete volume, yet targeted research on temperature control and crack prevention for this type remains insufficient. To address this, a Two-Parameter Decision Chart Method for predicting allowable placing temperature, an Analytical–Numerical Hybrid Estimation Method for estimating cooling durations, and the Comprehensive Cracking Risk Index (CCRI) for assessing lifecycle concrete safety are proposed, forming a complete design methodology. A case study on a proposed project using full-process simulation quantitatively evaluates the contribution of various measures in mitigating thermal stress across dam zones. Results show that without measures, the CCRI values for interior and surface concrete reach 68.9% and 38.1%, respectively. After implementing combined optimization measures targeting the control of maximum temperature, final temperature before grouting, and internal–external temperature difference throughout the entire process, both CCRI values are reduced to zero. Contribution analysis reveals distinct zonal effectiveness: for interior concrete, low-temperature placement with first-stage cooling contributes most (59.9%); for surface concrete, second- and third-stage cooling dominates (72.7%). Therefore, in practical engineering applications for temperature control and crack prevention in arch–gravity dams, a combination of measures centered on controlling the maximum temperature, optimizing the cooling process, and enhancing surface insulation should be adopted based on the characteristics of interior and surface zones, thereby improving cracking safety. Full article