Peng Cao

This study systematically investigates the effects of reinforcement ratio, textile orientation, and interface treatment on the tensile behavior of carbon fiber textile-reinforced concrete (TRC) through uniaxial tensile tests and numerical simulation. The experimental results indicate that as the reinforcement ratio increases from 0.44% to 1.33%, the ultimate tensile stress rises from 1.86 MPa to 4.08 MPa (an increase of 119%), the ultimate tensile strain increases from 0.86% to 1.72% (an increase of 100%), and the average crack spacing decreases from 24.3 mm to 8.7 mm (a reduction of 64%). Correspondingly, the failure mode transitions from brittle single-crack fracture to multi-crack quasi-ductile failure. Compared with transverse orientation, the longitudinal orientation yields a 32.7% increase in ultimate tensile stress and a 46.2% increase in ultimate tensile strain, primarily attributable to a 35–45% enhancement in interfacial frictional stress. Under the longitudinal configuration, carbon-glue interfacial treatment further improves the ultimate tensile stress by 36.9% and the ultimate tensile strain by 42.1%, while reducing the average crack spacing to 8.1 mm and shifting the failure mode toward fiber rupture-dominated failure. Digital image correlation (DIC) analysis reveals that the strain inhomogeneity index decreases from 0.65–0.78 to 0.28–0.35. The finite element simulation results indicate that the error in peak load remains below 5%, and the error in crack spacing remains below 10%. This study establishes a quantitative regulatory framework encompassing reinforcement ratio, textile orientation, and interface treatment, thereby providing a basis for performance prediction and optimization of TRC.

During the service of solid rocket motors, propellant grains need to bear various loads such as curing cooling, gravity, and combustion internal pressure. The internal pore defects will seriously affect the structural integrity. In this paper, a three-dimensional finite element model of propellant–insulation layer–mold is established to study the structural responses of pore defects with different sizes (30–100 mm) under three typical working conditions: curing cooling, curing cooling coupled with gravity, and internal pressure loading. It is found that under the curing cooling condition, compared with the non-porous propellant grain structure, the structure with pores will raise the overall mechanical response of the propellant grain, and the maximum stress and strain are mainly concentrated in the front end of the core hole and the wing groove area. The pore size has a limited impact on the overall stress distribution, but will change the local stress concentration degree. Among them, the 80 mm pore reduces the stress in the wing groove area through stress field interference. Moreover, large-size pores will significantly weaken the structural bearing capacity and increase the contact pressure between the propellant and the core mold. Under the condition of curing cooling coupled with gravity, the stress and strain are mainly distributed at the edge of the pores, and the values increase with the increase of pore size. Under the action of internal pressure load, the stress and strain in the middle section of the propellant grain have no obvious change, but stress concentration occurs in the transition area between the core hole and the wing groove and at the end of the wing groove. The results of this study provide a reference for the integrity evaluation and structural optimization of propellant grains with pore defects.

The fracture of bituminous polymer composites is fundamentally dictated by microstructural heterogeneity and the complex viscoelasticity of the asphalt matrix. This study develops a robust numerical framework coupling a random polygonal aggregate distribution algorithm with a bilinear cohesive zone model (CZM) to simulate fracture mechanics in heterogeneous asphalt-based composites. A key feature of the model is the explicit accounting for the stochastic distribution of the coarse aggregate and the time-dependent mechanical response of the fine aggregate matrix (FAM). Following experimental validation via frequency sweep and semi-circular bending (SCB) tests, a multi-scale parametric analysis was conducted to quantify the impacts of aggregate gradation, volume fraction, and shape. Results demonstrate that mixtures with high percentages of large-sized aggregates effectively delay macroscopic fracture by increasing the energy dissipation required for cracks to bypass the aggregate phase. While increasing the volume fraction of aggregates improves peak strength, it simultaneously accelerates post-peak load deterioration and reduces total fracture work, indicating a critical loss in the composite’s deformation capacity. Furthermore, particles with higher angularity provide superior blocking effects compared to rounded counterparts. This research offers a high-efficiency computational tool for the structural optimization of highly filled composites and provides critical insights into their internal stress states and macroscopic fracture mechanics.

Island reef road construction faces a complex marine service environment characterized by high salinity and high humidity. Meanwhile, rapid construction and prompt subgrade repair are urgently required, creating a strong demand for novel calcareous-sand-based stabilization materials that combine excellent mechanical performance with resistance to seawater erosion. To this end, this study developed an early-strength cemented calcareous-sand reinforcement material for road base construction. Sulfoaluminate cement (SAC) and ferrite-aluminate cement (FAC), both featuring rapid setting/early strength development and superior corrosion resistance, were used to cement calcareous sand (CS) and to investigate its mechanical and microstructural characteristics under different water environments. Unconfined compressive strength tests (UCS) showed that SC-CS and FC-CS could meet subgrade requirements at 1 d and 7 d, with SC-CS and FC-CS reaching 3.12 MPa and 3.44 MPa at 1 d, and 3.26 MPa and 3.67 MPa at 7 d, respectively, under seawater SS conditions. Seawater mixing and immersion were found to promote the early strength and stiffness development of both SC-CS and FC-CS, with a more pronounced effect observed for FC-CS. Based on experimental results, a damage model for the stabilized specimens was established with a fitting accuracy of R² > 0.97. This constitutive model accurately describes the stress–strain relationship of the material and quantitatively characterizes its damage evolution. Microscopic XRD and SEM analyses indicated that the main hydration product in freshwater-cured specimens was ettringite, and the interparticle connection of CS was dominated by bridging through rod-like ettringite. In contrast, under seawater conditions, the ettringite content decreased, while hydrotalcite and calcium aluminate hydrate increased, forming massive and lamellar bridging products. Compared with SC-CS, the bridging structure in FC-CS was denser. Moreover, the compactness of the bridging structure not only affected its mechanical properties but also governed the movement mode of CS particles, thereby influencing the damage evolution and failure mode of the specimens. The findings provide theoretical support for the construction needs of island road.

The crosslinked binders formed by using glycidyl azide polymer (GAP) as the binder matrix and bis-propargyl succinate (BPS) as the curing agent have good application prospects in the field of solid propellants. Aiming at the shortcomings of traditional experimental research, such as high cost, and molecular dynamics (MD) simulation, which are time-consuming for complex combination problems, this study will realize accurate prediction of the mechanical properties of binders through machine learning (ML) based on the molecular simulation dataset. Firstly, 273 sets of GAP-BPS binder models under different conditions were formed based on 21 crosslinking degrees and 13 temperatures, and MD simulation and mechanical property simulation were carried out. Then, the initial conditions of molecular simulation (crosslinking degree, temperature) and structural parameters (free volume) were taken as features, and the bulk modulus and shear modulus were taken as labels to form the dataset. Three machine learning models were trained and evaluated based on this dataset to test their prediction performance. Based on the cross-validation results, the Tabular Prior Data Fitting Network (TabPFN) exhibits the highest average prediction values (the average R² for bulk modulus and shear modulus were 0.9684 and 0.8827, respectively). But the significance analysis reveals that TabPFN significantly outperforms the RF model only in predicting bulk modulus. In subsequent prediction tasks with smaller datasets, TabPFN achieves superior average prediction values compared with RF and XGBoost.

Due to the complex mesostructure of calcareous sand, accurately predicting the mechanical response of Asphalt-Bonded Calcareous Sand (ABCS) is extremely challenging. This study pioneers the development of a mesoscale model for ABCS that explicitly incorporates the Interfacial Transition Zone (ITZ) via a random particle algorithm. To overcome the efficiency bottlenecks of traditional time-domain integration, this study establishes a mesoscale framework coupling a random polygonal aggregate algorithm with direct Steady-State Dynamics (SSD) analysis. A major advantage of this framework is its capacity for large-scale parametric sensitivity analysis; herein, 920 independent mesoscale models were generated and rapidly solved across the broadband frequency domain. The framework was rigorously validated, demonstrating high predictive accuracy for both the baseline calibration and an independent 12% asphalt content mixture (baseline R² = 0.99, MAPE = 6.94%; independent validation R² = 0.96, MAPE = 9.73%). Notably, the SSD approach completes calculations (10⁻³ to 10³ Hz) for 10 massive 300 mm RVEs in just 6.5 min. Leveraging this high-throughput capability, the extensive parametric analysis reveals that variations in maximum aggregate size negligibly impact the dynamic modulus under a constant volume fraction. Conversely, an optimal Interfacial Transition Zone (ITZ) thickness of ~75 µm was identified, representing a physical equilibrium between interfacial reinforcement and bulk binder cohesion. Furthermore, an analytical RVE size criterion of 1.7–5.3 times the maximum aggregate size is proposed to satisfy a 5% engineering error tolerance, providing a highly efficient numerical tool for the virtual mix design of reef pavements.

Large flange shafts are the core load-bearing and connecting components of high-end equipment, and their welding multi-physical fields directly affect the quality and service safety of the components. Traditional experiments and finite element methods suffer from long cycles and low efficiency, which can hardly meet the demand for rapid prediction. Aiming at the fast and accurate prediction of welding temperature, deformation and residual stress, this study combines thermal–mechanical coupled finite element simulation with machine learning to construct and compare a variety of prediction models. A dataset is built based on simulation data from 100 groups of process parameters. Overfitting is reduced through strategies including early stopping and dropout, and models such as MLP, RF, RBF-SVR, TabNet, XGBoost, and FT-Transformer are established and verified through 10-fold cross-validation. The results show that the MLP model performs best in the prediction of temperature, deformation and residual stress, and is in good agreement with the simulation values. The prediction errors of the peak temperature of the weld and base metal are below 5%, and the errors of deformation and residual stress are controlled within 10%. The average error of peak residual stress is about 6 MPa, and the deviation of most samples is less than 5 MPa. The RF model ranks second in accuracy, with an average error of about 6.5 MPa for peak residual stress, showing a satisfactory interpretability and engineering applicability. RBF-SVR and TabNet can meet basic prediction requirements. Under the small-sample condition in this work, XGBoost and FT-Transformer present relatively large errors and a weak generalization ability, making it difficult to achieve high-precision prediction. The MLP model established in this paper can effectively reproduce the evolution of welding multi-physical fields and supports the rapid prediction and process optimization of large flange shaft welding. The generalization ability and practical performance of the model can be further improved by expanding the dataset and experimental verification in the future.

The reliability of solid rocket motors depends primarily on the structural integrity of their propellants. Internal cavity defects in the widely used hydroxyl-terminated polybutadiene (HTPB) propellant, formed during manufacturing and service, significantly degrade its mechanical properties and compromise motor safety. This study developed a constitutive model for HTPB propellant based on the generalized incremental stress–strain damage model (GISSMO). The validity of the constitutive model was verified through uniaxial tensile tests conducted at various tensile rates. Based on this constitutive model, numerical simulations were performed to examine the effects of initial modulus, impact rate, and cavity confining pressure on the failure modes of propellants containing cavities with radii from 40 to 100 mm. The results show that the simulation’s force–displacement curve agrees well with the test. The simulation accurately captures the propellant’s transition from elastic–plastic plateau at low rates to elastic response at high rates. The prediction error for the maximum tensile force is less than 5%. For cavities of 80 mm and 100 mm, local stress concentration causes damage to the inner wall, followed by rapid cavity extrusion, collapse, and possible cross-shaped matrix fracture. However, cavities of 40 mm and 60 mm show greater stability, experiencing only volume compression, which rarely causes overall damage. When the propellant’s initial modulus is higher than 24 MPa, damage propagation in large cavities over 80 mm is suppressed. A low modulus worsens structural deformation. At low impact velocity, cavity compression is significant, and the structure remains conformal. At high impact velocity (4000 MPa/s), the cavity stays conformal, the matrix collapses, and the damage value decreases. For 60 mm cavities, damage is localized, and the overall structure is most stable within a confining pressure of 5 to 9.5 MPa. This study clarifies the interaction between engineering parameters and cavity size, providing a basis for optimizing the safety of the propellant structure.

This study develops a unified continuum damage mechanics (CDM) model for high-cycle fatigue life prediction of large manually arc-welded flange shafts manufactured from 45Mn steel (quenched and tempered) under combined bending–torsion loading. Fatigue tests revealed consistent crack initiation at the weld toe, with multiaxial loading reducing fatigue life by 35–42% compared to pure bending. The CDM parameters were calibrated against experimental data and implemented through an ABAQUS 2021 UMAT subroutine, achieving prediction errors below 5%—significantly outperforming conventional nominal and hotspot stress methods. For high-cycle fatigue conditions, a simplified CDM model neglecting plastic damage maintained engineering accuracy while improving computational efficiency by 3–5 times. The damage variable D = 0.9 was identified as a universal threshold for accelerated damage progression. These findings provide quantitative basis for multiaxial fatigue design and structural health monitoring of large welded components.