In-situ lunar construction technology is critical for future lunar base development, and the production of geopolymers from lunar regolith—a novel cementitious material with concrete-like properties—has become a vital approach for achieving in-situ resource utilization. This study systematically investigated the influence of basalt fiber content (0–0.4%) on the mechanical properties of lunar regolith simulant geopolymers by controlling key parameters including curing temperature (20 °C and 80 °C), duration (1 d and 7 d), and alkali activator type (strong alkaline solution: a mixture of sodium hydroxide and sodium silicate, and weak alkaline solution: sodium silicate solution). Through testing of 144 specimens, the results revealed that strong alkali-activated specimens with 0.3% fibers cured at 20 °C for 7 d showed optimal ductility with compressive strength of 2.85 MPa and flexural strength of 0.53 MPa, exhibiting characteristic flat stress-strain curves. Specimens with 0.2% fibers under high-temperature curing at 80 °C for 1 d achieved maximum compressive strength of 44.76 MPa and flexural strength of 1.60 MPa but demonstrated brittle failure behavior. Weak alkali-activated specimens containing 0.1% fibers cured at 80 °C for 7 d attained superior comprehensive performance with peak flexural strength reaching 3.88 MPa, showing excellent fiber-matrix synergy. These findings provide important theoretical foundations for optimizing lunar construction materials through customized fiber reinforcement and curing strategies.

The prediction of the low-cycle fatigue life of bimetallic steel bars (BSBs) is essential to promote the engineering application of BSBs. However, research on the low-cycle fatigue properties of BSB is limited, and fatigue experiments are time-consuming. Moreover, considering that sufficient data are needed for model training, the lack of data hinders the leverage of typical data-driven machine learning, which is widely used in fatigue life prediction. To address this issue, a transfer learning framework was suggested to accurately predict the low-cycle fatigue life of BSBs with limited data. To achieve this goal, 54 data points obtained from low-cycle fatigue tests on BSBs and 264 data points of other metallic bars were collected. Source models based on artificial neural networks (ANNs) were first constructed using the collected source dataset. Then, the learned knowledge stored in the source models was transferred to the transfer models. After that, transfer models were further fine-tuned and then tested using the target dataset of BSBs. The ANN models, which were of the same structure as the transfer models but only trained with the target dataset without transferring deep features from the source models, were set as baseline models. Compared with baseline models, the constructed transfer models could be used to accurately predict the fatigue life of BSBs. Moreover, the influence of hidden layers of ANNs on accuracy was examined by comparing one-layer and two-layer transfer models. Furthermore, the influence of key parameters on fatigue life of metallic bars was evaluated by feature analysis.

A bimetallic steel bar (BSB) consisting of stainless-steel cladding and carbon steel substrate exhibits excellent corrosion resistance and good mechanical properties. The bimetallic structure of BSBs may affect their low-cycle fatigue performance, and current investigations on the above issue are limited. In this study, the low-cycle fatigue properties of bimetallic steel bars (BSBs) with inelastic buckling were investigated. Experiments and numerical studies were conducted to investigate the low-cycle fatigue capacity for BSBs, considering buckling. The buckling mode of BSBs is discussed. The hysteretic loops and energy properties of BSBs with various slenderness ratios (L/D) and fatigue strain amplitudes (ε_a) are investigated. With increases in the L/D and ε_a, the original symmetry for hysteresis loops disappears gradually, which is caused by the buckling. A predictive equation revealing the relation between the ε_a and fatigue life is suggested, which considers the effects of the L/D. A numerical modelling method is suggested to predict the hysteretic curves of BSBs. The effect of buckling on the stress and energy properties of BSBs is discussed through the numerical analysis of 44 models including the effects of the L/D, ε_a, and cladding ratios. The numerical analysis results illustrate that the hysteresis loops of BSBs with various ε_a values exhibit similar shapes. The increase in the cladding ratio reduces the peak stress and the dissipated energy properties of BSBs. The hysteresis loop energy density decreases by about 3% with an increase of 0.1 in the cladding ratio. It is recommended that the proportion of stainless steel inBSBs should be minimized once the corrosion resistance requirements are met.

This study investigated the post-fire resistances of 6063-T5 aluminium alloy angle section stub columns (SCs). The post-fire mechanical properties of 6063-T5 aluminium alloy were assessed using tensile coupon tests. Instead of exhibiting a yield plateau, the stress–strain curves indicated a shift from an elastic to a strain-hardening phase. The impacts of elevated-temperature exposure on the residual elastic modulus were negligible. Strength properties decreased while ductile properties increased within the elevated-temperature range of 200 to 450 °C, with a subsequent strength increase observed beyond 450 °C. After the SC tests, gradual decreases in ultimate resistance were observed within 200–450 °C, followed by an increase beyond 450–500 °C. These trends in the ultimate resistance closely paralleled those strength characteristics observed in the stress–strain curves. As regards the failure mode, all specimens experienced local buckling after exposure to the range of elevated temperatures. The failure mode, ultimate resistance, and load–end shortening curve were used to evaluate a numerical modelling approach that was created to simulate the residual resistance of SCs after exposure to different elevated temperatures was applied. The EC9, ADM-2020, AS/NZS 1664, and GB 50429-2007 were among the design approaches that were evaluated using the experimental and numerical data. Due to the increased strain-hardening behaviour caused by elevated temperatures, the existing design methods proved excessively conservative when applied to the direct prediction of ultimate resistances of 6063-T5 aluminium alloy angle section SCs. The modified design provisions in light of the observed post-fire strain-hardening behaviour improved the accuracy in predicting the residual bearing capacity of 6063-T5 aluminium alloy angle section SCs, which showed better agreement with test and numerical results, offering enhanced applicability for post-fire design.

Bimetallic steel, as a layered composite material formed by metallurgically bonding two dissimilar metals, combines the excellent corrosion resistance of the cladding layer with the superior mechanical properties (such as high strength and toughness) of the base layer. It has been widely applied in demanding fields like marine engineering, the petrochemical industry, and energy equipment, where comprehensive material performance is critical. This paper provides a structured review of the research progress and application status of bimetallic steel. First, mainstream fabrication techniques, such as explosive welding and roll bonding, along with their effects on interfacial bonding quality, are analyzed. Subsequently, key material characteristics, including welding performance, mechanical properties, and corrosion behavior, are discussed. Furthermore, the component-level bearing performance and failure mechanisms under various loading conditions are evaluated. Finally, by synthesizing existing research, current knowledge gaps in areas like long-term service life assessment, adaptability to extreme environments, and efficient intelligent manufacturing are identified, and future development trends are outlined. This review provides important academic reference and engineering guidance for deepening the understanding of bimetallic steels and promoting their safer, more reliable, and cost-effective application in major engineering projects.

With the development of infrastructure construction, seawater sea–sand concrete (SWSSC) is expected to solve the shortage of freshwater and river sand. Polyoxymethylene (POM) fiber, owing to its excellent corrosion resistance, provides a novel approach to enhancing the bond performance of SWSSC. This study systematic study of the bond properties of bimetallic steel bars (BSBs) in POM fiber-reinforced SWSSC and develops a predictive model. Mechanical property tests of SWSSC and pull-out tests of BSB and SWSSC were conducted with various POM fiber contents. The results showed that the optimal volume fraction of POM fibers was 0.6%. At this fraction, the compressive strength and splitting tensile strength of SWSSC were improved by 17.7% and 20.3%, respectively, compared with the group without fibers. All pull-out specimens experienced splitting failure. The bond strength increased monotonically with the increase in relative cover thickness and exhibited a trend of first increasing and then stabilizing with rising POM fiber volume fraction. In addition, a bond stress–slip prediction model between BSBs and POM fiber-reinforced SWSSC was established based on the test results, which can provide theoretical support for the numerical simulation and design of BSB-SWSSC structures.