Explosive spalling is a severe threat to concrete at high temperature. The addition of steel fibers is believed to be useful to mitigate explosive spalling of concrete. But predicting explosive spalling of steel fiber reinforced concrete remains to be a challenging topic. This paper adopted a popular machine learning approach, i.e., artificial neural network (ANN), to predict explosive spalling of steel fiber reinforced concrete and furthermore study the effect of steel fibers on explosive spalling resistance of concrete. Two ANN models were developed, with ANN1 concrete mix-based and ANN2 concrete strength-based. Twenty groups of heating tests were conducted to validate the proposed ANN models. Both ANN models showed the prediction accuracy of 100%, which demonstrates that ANN is a powerful tool for assessing explosive spalling risk of steel fiber reinforced concrete. A parametric study was also conducted to investigate the effect of steel fibers on explosive spalling resistance of concrete using the well-validated ANN1.

This study aims to propose a calculation method of shear capacity for RC beams based on the shear resisting mechanisms known as the beam and arch actions. Static four-point bending tests were conducted on 12 RC beams with various stirrup ratio and shear span ratio, and the contribution of each mechanism was calculated based on the strain distribution of tensile steel bars. The contribution of concrete in the beam action at the peak load tends to decrease with higher stirrups amount, while the contribution of the arch action tends to increase with higher stirrups amount and smaller shear span ratio. Based on these results, a new method to calculate the shear capacity of RC beams was proposed. The shear capacity carried by the beam action was obtained from deterministic equations. The shear capacity carried by the arch action was obtained through iteration process, which indirectly takes the compatibility condition into account. From the comparison of a total of 86 experimental and analytical results, the proposed method showed better accuracy to estimate the shear capacity of RC beams with stirrups.

This paper has proposed a new and simple approach to making drift-hardening circular concrete columns with reduced residual deformation by utilizing non-prestressing PC strands as longitudinal rebars. In order to verify the effectiveness of this method, quasi-static tests on five circular concrete columns were carried out. Four columns were reinforced by PC strands and the other one was reinforced by normal-strength rebars. The experimental variables included the axial load ratio, the shear span ratio, and the confinement method within the potential plastic hinge region. The test results show that the columns utilizing PC strands possess a drift-hardening capability up to 5% drift and the residual drifts are significantly reduced if the PC strands are well anchored at both ends. In addition, it is indicated that partial confinement by bolted steel tube (BST) can further enhance the lateral drift-hardening stiffness and reduce the residual deformation. Furthermore, a new nonlinear analysis method considering the bond-slip effect is introduced to evaluate the lateral response of the proposed columns. Comparisons between the experimental and analytical results indicate that the presented nonlinear analysis method can predict the lateral response of the proposed columns very well.

A multi-scale model for significant characteristics of cementitious composite and structural concrete at high temperatures is presented and the experimental verification at micro, meso and macro-scales is conducted. Deterioration of cement hydrates, reduced stiffness of concrete composite and their rehydration are modeled at high temperature of 100 – 1000°C and integrated up to the multi-scale simulation platform. This framework enables us to reproduce some meso-scale chemo-physics such as progressive spalling of concrete cover and exposure of reinforcing bars. The temperature-dependent thermal characteristics of both aggregates and cement matrix are also considered to truck the rising temperature inside RC members. The behavioral simulation of columns, slabs and beams, which are subjected to axial compression and out-of-plane flexural shear, is conducted to be ready for fire.

In this study, a novel synthesized form of nanoeggshell is introduced and its use in cementitious composites is proposed as a green, safe and low-cost additive. The nanoeggshell was characterized using FTIR, SEM, BET and viscometer techniques and results showed that the ultrasonic effect was a major factor for the structure of synthesized hierarchical 3D flower-like nanoeggshell. The intrinsic viscosity, voluminosity, and shape factor of nanoeggshell were calculated to understand rheological properties of the structure. Different error functions were used to find the optimum. Regarding the effect of the novel 3D flower-like nanoeggshell on the mechanical properties of mortar, four different cement mor-tar mixtures were prepared with varying percentages of nanoeggshell (0%, 0.1%, 0.5% and 1%). It is concluded that compressive strength of the mixtures increased with the increasing amount of nanoeggshell additive. Additionally, flexural strain capacity was improved with the additive due to bridging effect in the cement matrix, thus induced higher ductility. In addition, better workability was noted in the mixtures with nanoeggshell. As a result, the introduced 3D flower-like nanoeggshell is a novel potential nanomaterial that can be used as an effective additive for improving the mechanical properties of cementitious composites.

Less calcium carbonate in low temperature significantly restricts the application of microbial-induced carbonate precipitation (MICP) technology. Bacillus megaterium was chosen and calcification precipitation tests were studied via varying experimental conditions. Moreover, crack repair tests based on MICP were performed, using the viable cell concentration, sonic time values, unconfined compressive strength and productive rates for calcium carbonate as indicators to evaluate repair effects. Results show that adding nutrients to the gelling solution and determining the optimal reaction conditions can increase production rates for calcium carbonate in low temperature. However, for undomesticated and domesticated B. megaterium, the optimum calcification reaction conditions were different. With MICP technology, cracks were successfully sealed by calcium carbonate in low temperature and the strengths of specimens with different crack widths all recovered. The smaller the crack width, the better was the microbial utilization efficiency but worse repair uniformity. The repair effect with undomesticated B. megaterium was worst, and the specimens repaired by the method, domesticated B. megaterium and adding urea, had the best repair effect. Therefore, results demonstrated the feasibility of MICP crack repair at low temperature, which lay the foundation for subsequent practical engineering application with B. megaterium in low temperature.