Search Results (2,066)

Underwater explosion ice-breaking technology is critical for Arctic development and ice disaster prevention due to its high efficiency, yet it faces challenges in understanding the coupled dynamics of shock waves, pulsating bubbles, and heterogeneous ice fracture. This review synthesizes theoretical models, experimental studies, and numerical simulations investigating damage mechanisms. Key findings establish that shock waves initiate brittle fracture via stress superposition while bubble pulsation drives crack propagation through pressure oscillation; optimal ice fragmentation depends critically on charge weight, standoff distance, and ice thickness. However, significant limitations persist in modeling sea ice heterogeneity, experimental replication of polar conditions, and computational efficiency. Future advancements require multiscale fluid–structure interaction models integrating brine migration effects, enhanced experimental diagnostics for transient processes, and optimized numerical algorithms to enable reliable predictions for engineering applications. Full article

This work presents a multiscale, microstructure-aware framework for predicting fatigue strength distributions in additively manufactured (AM) alloys—specifically, laser powder bed fusion (L-PBF) AlSi10Mg and Ti-6Al-4V—by integrating density functional theory (DFT), instrumented indentation, and Bayesian inference. The methodology leverages principles common to all 3D printing (additive manufacturing) processes: layer-wise material deposition, process-induced defect formation (such as porosity and residual stress), and microstructural tailoring through parameter control, which collectively differentiate AM from conventional manufacturing. By linking DFT-derived cohesive energies with indentation-based modulus measurements and a MAP-based statistical model, we quantify the effect of additive-manufactured microstructural heterogeneity on fatigue performance. Quantitative validation demonstrates that the predicted fatigue strength distributions agree with experimental high-cycle and very-high-cycle fatigue (HCF/VHCF) data, with posterior modes and 95 % credible intervals of ${\widehat{\sigma }}_f^{\mathrm{AlSi}10\mathrm{Mg}}={86}_{-7}^{+8}\mathrm{MPa}$ and ${\widehat{\sigma }}_f^{\mathrm{Ti}–6\mathrm{Al}–4\mathrm{V}}={115}_{-9}^{+10}\mathrm{MPa}$, respectively. The resulting Woehler (S–N) curves and Paris crack-growth parameters envelop more than 92 % of the measured coupon data, confirming both accuracy and robustness. Furthermore, global sensitivity analysis reveals that volumetric porosity and residual stress account for over 70 % of the fatigue strength variance, highlighting the central role of process–structure relationships unique to AM. The presented framework thus provides a predictive, physically interpretable, and data-efficient pathway for microstructure-informed fatigue design in additively manufactured metals, and is readily extensible to other AM alloys and process variants. Full article

Grain boundary weakening in high-temperature environments significantly influences the fatigue crack growth mechanisms of nickel-based superalloys, introducing challenges in accurately predicting fatigue life. In this study, a dislocation-density-based crystal plasticity phase-field (CP–PF) model is developed to simulate the fatigue crack growth behavior of the GH4169 alloy under both room and elevated temperatures. Grain boundaries are explicitly modeled, enabling the competition between transgranular and intergranular cracking to be accurately captured. The grain boundary separation energy and surface energy, calculated via molecular dynamics simulations, are employed as failure criteria for grain boundary and intragranular material points, respectively. The simulation results reveal that under oxygen-free conditions, fatigue crack propagation at both room and high temperatures is governed by sustained shear slip, with crack advancement hindered by grains exhibiting low Schmid factors. When grain boundary oxidation is introduced, increasing oxidation levels progressively degrade grain boundary strength and reduce overall fatigue resistance. Specifically, at room temperature, oxidation shortens the duration of crack arrest near grain boundaries. At elevated service temperatures, intensified grain boundary degradation facilitates a transition in crack growth mode from transgranular to intergranular, thereby accelerating crack propagation and exacerbating fatigue damage. Full article

Cement production significantly contributes to CO₂ emissions (8% of worldwide CO₂ emissions) and global warming, accelerating climate change and increasing air pollution, which harms ecosystems and human health. To this end, this research investigates the fresh and hardened properties of sustainable concrete fabricated with three different replacement percentages (0%, 5%, and 10% by weight) of ordinary Portland cement (OPC) using rice husk ash (RHA). The hardened properties were evaluated at 14, 28, 60, 90, and 120 days of water curing. In addition, data-based models were developed, validated, and optimised, and the models were compared with experimental results and validated with the literature findings. The outcomes reveal that the slump values increased (17% higher) with the increased content of RHA, which aligns with the lower temperatures (12% lower) of freshly mixed concrete with RHA than the control mix (100% OPC). The slopes of the stress–strain profiles decreased at early ages and improved at longer curing ages (more than 28 days), especially for mixes with 5% RHA. The compressive strength decreased slightly (18% at 28 days) with increased percentages of RHA, which was minimised with increased curing ages (8% at 90 days). The data-based model accurately predicted the stress–strain profiles (coefficient of determination, $R^2$ ≈ 0.9950–0.9993) and compressive strength at each curing age, including crack progression (i.e., highly nonlinear region) and validates its effectiveness. In contrast, the optimisation model shows excellent results, mirroring the experimental data throughout the profile. These outcomes indicate that the 10% RHA could potentially replace OPC due to its lower reduction in strength (8% at 90 days), which in turn lowers CO₂ emissions and promotes sustainability. Full article

Hydrogen has gradually become one of the indispensable sources of energy for mankind. Since the discovery of hydrogen embrittlement (hydrogen-induced degradation of material properties) more than 100 years ago, fatigue properties in hydrogen environments have been studied. Fatigue crack growth of materials in a hydrogen environment is a complex process involving the interaction of multiple factors. Hydrogen binds to atoms within the material, leading to diffusion and aggregation of hydrogen atoms, which causes an increase in internal stresses. These stresses may concentrate at the crack tip, accelerating the rate of crack expansion and leading to fatigue fracture of the material. The work of current researchers has summarised a number of fatigue models to help understand this phenomenon. This paper firstly summarises the existing hydrogen embrittlement mechanisms as well as hydrogen embrittlement experiments. It then focuses on the mechanism of fatigue crack propagation in hydrogen environments and related literature. It also analyses and summarises a cluster diagram of the literature generated using CiteSpace. The fatigue life prediction methods for materials in hydrogen environment are then summarised in this paper. It aims to provide some guidance for the selection and design of materials in developing fields such as fatigue materials in hydrogen environment. Finally, challenges in the current research on the fatigue properties of materials under hydrogen embrittlement conditions are pointed out and discussed to guide future research efforts. Full article

This study investigates the mechanical properties of LiCoO₂ (LCO) cathode materials under varying states of charge (SOCs) using both an empirical Buckingham potential model and a machine learning-based Deep Potential (DP) model. The results reveal a substantial decrease in Young’s modulus with decreasing SOC. Analysis of stress factors identified pairwise interactions, particularly those involving Co³⁺ and Co⁴⁺, as key drivers of this mechanical evolution. The DP model demonstrated superior performance by providing consistent and reliable predictions reflected in a smooth and monotonic stiffness decrease with SOC, in contrast to the large fluctuations observed in the classical Buckingham potential results. The study further identifies the increasing dominance of Co⁴⁺ interactions at low SOCs as a contributor to localized stress concentrations, which may accelerate crack initiation and mechanical degradation. These findings underscore the DP model’s capability to capture SOC-dependent mechanical behavior accurately, establishing it as a robust tool for modeling battery materials. Moreover, the calculated SOC-dependent mechanical properties can serve as critical input for continuum-scale models, improving their predictive capability for chemo-mechanical behavior and degradation processes. This integrated multiscale modeling approach can offer valuable insights for developing strategies to enhance the durability and performance of lithium-ion battery materials. Full article

Freeze–thaw damage is a critical durability challenge in cold climates that leads to surface spalling, cracking, and degradation of structural performance. In northern China, the severity of winter conditions further accelerates the degradation of concrete infrastructure. This study investigates the reinforcement of frost-damaged concrete using engineered cementitious composites (ECC) prepared with Yellow River sedimentary sand (YRS), employed as a 100% mass replacement for quartz sand to promote sustainability. The interface bonding performance of ECC-C40 specimens was evaluated by testing the impact of various surface roughness treatments, freeze–thaw cycles, and interface agents. A multi-factor predictive formula for determining interface bonding strength was created, and the bonding mechanism and model were examined through microscopic analysis. The results show that ECC made with YRS significantly improved the interface bonding performance of ECC-C40 specimens. Specimens treated with a cement expansion slurry as the interface agent and those subjected to the splitting method for surface roughness achieves the optimal reinforced condition, exhibited a 27.57%, 35.17%, 43.57%, and 42.92% increase in bonding strength compared to untreated specimens under 0, 50, 100, and 150 cycles, respectively. Microscopic analysis revealed a denser interfacial microstructure. Without an interface agent, the bond interface followed a dual-layer, three-zone model; with the interface agent, a three-layer, three-zone model was observed. Full article

This study examines fatigue crack growth behavior in induction-hardened S38C axle steel with a gradient microstructure. High-frequency three-point bending fatigue tests were conducted to evaluate crack growth rates (da/dN) across three depth-defined regions: a hardened layer, a heterogeneous transition zone, and a normalized core. Depth-resolved da/dN–ΔK relationships were established, and Paris Law parameters were extracted. The surface-hardened layer exhibited the lowest crack growth rates and flattest Paris slope, while the transition zone showed notable scatter due to microstructural heterogeneity and residual stress effects. These findings provide experimental insight into the fatigue performance of gradient-structured axle steels and offer guidance for fatigue life prediction and inspection planning. Full article

The accumulation of fatigue damage is primarily caused by cyclic plastic deformation. In low-cycle fatigue, cyclic plastic deformation is the dominant deformation mode. In high-cycle fatigue, although most deformation is elastic, plastic deformation may still occur in localized regions of stress concentration and plays a critical role in the initiation of fatigue cracks. Considering that cyclic plastic deformation can be characterized by hysteresis loops, this study modifies the flow stress equation and the cyclic plastic deformation relationship based on stress–strain hysteresis loops at half-life cycles under different strain amplitudes. An improved model for life prediction that incorporates the effects of strain amplitude is proposed. The results of experiments on 310S stainless steel and 1045 carbon steel demonstrate that the model achieved prediction errors within a factor of two and provided reliable predictions for both high-cycle and low-cycle fatigue life across the entire ε-N curve. Full article

The composition design of asphalt mixtures plays a pivotal role in determining pavement performance and durability. To improve skeleton stability, paving uniformity, and mechanical strength, this research proposes a three-dimensional optimization framework for asphalt mixture design, focusing on aggregate gradation and optimum asphalt content. A skeleton-dense and anti-segregation gradation optimization method was developed by integrating a previously established skeleton-dense model with a segregation tendency prediction approach. In parallel, a mechanically driven method for determining optimum asphalt content was proposed by introducing the maximum migration shear stress as a performance-based alternative to the conventional Marshall stability parameter. Research results show that asphalt mixtures designed and compacted with the optimized gradation exhibit significantly enhanced high-temperature stability, while maintaining satisfactory low-temperature cracking resistance and moisture susceptibility. Field validation was conducted through the construction of a trial pavement section using the optimized gradation under recommended mixing and compaction temperatures. The resulting pavement demonstrated excellent compaction, strong resistance to segregation, and a highly stable spatial structure. These findings confirm the effectiveness of the proposed methodology in enhancing the high-temperature deformation resistance and overall structural integrity of asphalt mixtures. Full article

This study investigates a novel anchor-based method for controlled rock fragmentation, designed as an alternative to conventional excavation or explosive techniques. The proposed solution utilizes a specially modified undercut anchor that induces localized failure within the rock mass through radial expansion rather than traditional pull-out forces. Finite Element Method simulations, performed in ABAQUS with an extended fracture mechanics approach, were used to model the initiation and propagation of failure zones in sandstone. The results revealed a two-phase cracking process starting beneath the anchor’s driving element and progressing toward the rock’s free surface, forming a breakout cone. This behavior significantly deviates from conventional prediction models, such as the 45° cone or Concrete Capacity Design methods (cone 35°). The simulations were supported by field tests, confirming both the feasibility and practical advantages of the proposed anchor system, especially in confined or safety-critical environments. The findings offer valuable insights for the development of compact and efficient rock fragmentation technologies suitable for mining, rescue operations, and civil engineering applications. Full article

It has been proven that the performance of fluid catalytic cracking (FCC), as the most important oil refining process for converting low-value heavy oils into high-value transportation fuels, light olefins, and feedstocks for petrochemicals, depends strongly on the quality of the feedstock. For this reason, characterization of feedstocks and their relationships to FCC performance are issues deserving special attention. This study systematically reviews various publications dealing with the influence of feedstock characteristics on FCC performance, with the aim of identifying the best characteristic descriptors allowing prediction of FCC feedstock cracking capability. These characteristics were obtained by mass spectrometry, SARA analysis, elemental analysis, and various empirical methods. This study also reviews published research dedicated to the catalytic cracking of biomass and waste oils, as well as blends of petroleum-derived feedstocks with sustainable oils, with the aim of searching for quantitative relationships allowing prediction of FCC performance during co-processing. Correlation analysis of the various FCC feed characteristics was carried out, and regression techniques were used to develop correlations predicting the conversion at maximum gasoline yield and that obtained under constant operating conditions. Artificial neural network (ANN) analysis and nonlinear regression techniques were applied to predict FCC conversion from feed characteristics at maximum gasoline yield, with the aim of distinguishing which technique provided the more accurate model. It was found that the correlation developed in this work based on the empirically determined aromatic carbon content according to the n-d-M method and the hydrogen content calculated via the Dhulesia correlation demonstrated highly accurate calculation of conversion at maximum gasoline yield (standard error of 1.3%) compared with that based on the gasoline precursor content determined by mass spectrometry (standard error of 1.5%). Using other data from 88 FCC feedstocks characterized by hydrogen content, saturates, aromatics, and polars contents to develop the ANN model and the nonlinear regression model, it was found that the ANN model demonstrated more accurate prediction of conversion at maximum gasoline yield, with a standard error of 1.4% versus 2.3% for the nonlinear regression model. During the co-processing of petroleum-derived feedstocks with sustainable oils, it was observed that FCC conversion and yields may obey the linear mixing rule or synergism, leading to higher yields of desirable products than those calculated according to the linear mixing rule. The exact reason for this observation has not yet been thoroughly investigated. Full article

Creep and stress sensitivity can lead to the long-term conductivity degradation of fractures, and this influences the accuracy of long-term productivity predictions in ultra-deep carbonate reservoirs (UDCRs). However, the current models do not consider these two factors. For the long-term conductivity degradation of acid-etched symmetry fractures in UDCRs, a new fracture permeability evolution model incorporating creep and stress sensitivity effects was established. Building upon this, a numerical simulation model for UDCRs was developed for the first time to quantitatively analyze the impacts of creep, stress sensitivity, and production strategies on well productivity. The research revealed that the creep and stress sensitivity characteristics of acid-etched fractures had a significant impact on the well productivity for UDCRs. The larger the creep coefficient and stress sensitivity coefficient, the lower the oil well productivity. The larger the initial reservoir pressure and drawdown pressure, the higher the daily production and cumulative production of the oil well, but the cumulative production growth rate decreased. The cumulative production in the early stage of the released-pressure production was significantly higher than that of the pressure-controlled production, but with the increase in the pressure-controlled time, the cumulative production reversed. When the pressure was controlled for three years, the cumulative production increased by 5952 m³ (38.8%); as the creep coefficient increased, the cumulative production increased by greater than the pressure-released production. This shows that the larger the creep coefficient, the better the effect of controlling pressure production. The research results can provide a theoretical basis and technical support for the efficient development of UDCRs. Full article

This study presents a comprehensive finite element investigation into the design optimization of an ultra-high temperature ceramic matrix composite thruster for green bipropellant systems. Focusing on ZrB₂–SiC–Cfiber composites, it explores their thermal and mechanical response under realistic transient combustion conditions. Two geometries, a simplified and a complex full-featured model, were evaluated to assess the impact of geometric fidelity on stress prediction. The complex thruster model (CTM) offered improved resolution of temperature gradients and stress concentrations, especially near flange and convergent regions, and was adopted for optimization. A parametric study with nine wall thickness profiles identified a 2 mm tapered configuration in both convergent and divergent sections that minimized mass while maintaining structural integrity. This optimized profile reduced peak thermal stress and overall mass without compromising safety margins. Transient thermal and strain analyses showed that thermal stress dominates initially (≤3 s), while thermal strain becomes critical later due to stiffness degradation. Damage risk was evaluated using temperature-dependent stress margins at four critical locations. Time-dependent failure maps revealed throat degradation for short burns and flange cracking for longer durations. All analyses were conducted under hot-fire conditions without cooling. The validated methodology supports durable, lightweight nozzle designs for future green propulsion missions. Full article

Cracks and concentrated stresses can develop in precast concrete slabs, depending on the quality of the joints. The open-type joint method was adopted herein to fabricate a full-scale precast concrete slab joint. The open-type joint method features an exposed joint configuration that allows for direct installation of shear connectors without temporary formwork, improving constructability and load transfer efficiency. Full-scale load testing was carried out using a four-point loading experiment, revealing that the precast concrete slab had a yield load of 550 kN and maximum load of 733 kN. A slab using the cast-in-place method was measured to have a yield load of 500 kN and maximum load of 710 kN. A finite element analysis (FEA) model modeled the precast concrete slab, and the displacement and maximum load were analyzed. The FEA showed a maximum error within 7%. Therefore, the FEA results can predict the structural performance of the load–displacement of the precast concrete slab. The support vector regression model predicted key structural performance indicators such as concrete compressive strength, maximum load, displacement, and principal stress. The prediction results indicated that the average error converged within 3%. The prediction results of the SVR model can complement FEA by estimating outcomes without the need for complex modeling. Thus, the precast concrete slab using the open-type joint method was able to achieve structural performance equivalent to that of the slab using the cast-in-place technique. Furthermore, FEA and machine learning will be able to predict the structural performance of precast concrete slabs using the open-type joint method. Full article