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The data-driven material models have attracted many researchers recently, as they could directly use material data. However, there are limited studies about material uncertainty in previous data-driven models. This thesis proposes a new Gaussian Process Regression (GPR)-based approach to capture the material behaviour and the associated material uncertainty from the dataset. The GPR approach is firstly used for the nonlinear elastic behaviour. The obtained GPR-based model is verified by the material datasets. Then, an improved GPR model, called the Heteroscedastic Sparse Gaussian Process Regression (HSGPR) model, is applied for the plastic flow behaviour. The flow stress predicted by the HSGPR model also agrees with the experiments. As a new data-driven material model is introduced, the associated frameworks, which implement the GPR-based model and HSGPR-based model into the finite element method for structural reliability analysis, are developed. The frame problem is used to demonstrate the GPR-based model in the elastic stochastic structural analysis, while the beam and punch problems validate the HSGPR-based model in the plastic stochastic structural analysis. It is concluded that the GPR-based approach can accurately identify both the elastic and plastic stochastic structural responses. To consider the possible correlation of the stochastic material behaviours, a novel GPR-based approach, which combines the HSGPR model with the Proper Orthogonal Decomposition (POD) algorithm, is proposed. Two case studies on the metal strength and the rock joint behaviour have demonstrated that the material behaviours correlation can be effectively retained in the POD-HSGPR-based model. As indicated by its application in a rock slope problem, it is critical to consider the material properties correlation for the accurate evaluation of structural reliability.

To reduce the cost of lightweight concrete (LWC) partition panels and to address recycling concrete waste, this work utilized completely recycled fine aggregate (CRFA) to replace the natural fine aggregate and ceramsite in the preparation of LWC and LWC partition panels. To this end, an autoclave-free curing process and an air-entraining agent were used to prepare the CRFA-LWC. The workability, compressive strength, drying shrinkage, and pore structure of the CRFA-LWC and the performance of the CRFA-LWC partition panels were then investigated. The results show that the optimal ratio of the CRFA to the cement is 2.2 for the lightweight concrete, and the optimal panel cross section is a rounded rectangular one. All the pores in the CRFA-LWC have a diameter of smaller than 0.17 mm, and the diameter of 89% of them is less than 0.05 mm. In order to satisfy the drying shrinkage requirements stipulated by Chinese code JC/T 169-2016, the CRFA-LWC should be cured for at least 10 days. The economic analysis concludes that the material cost of CRFA-LWC is 40% lower than that of the autoclaved ceramsite concrete. In addition, utilizing CRFA in lightweight concrete can ease the shortage of natural aggregate.

The undesirable properties of conventional recycled fine aggregate (RFA) often limit its application in the construction industry. To overcome this challenge, a method for preparing completely recycled fine aggregate (CRFA), which crushes all concrete waste only into fine aggregate, was proposed. The obtained CRFA had high apparent density, and its water absorption was lower than that of the conventional RFA. To take advantage of the CRFA, this paper introduced the modified packing density method for the CRFA concrete mix design. The modified packing density method took account of the powder with a particle size of smaller than 75 &mu, m in the CRFA and balanced both the void ratio and the specific surface area of the aggregate system. Concrete (grade C55) was prepared using the CRFA to validate the feasibility of the proposed method. The unit price of the prepared CRFA concrete was around 12.7% lower than that of the natural aggregate concrete. Additionally, the proposed procedure for the concrete mixture design could recycle all concrete waste into the new concrete and replace all the natural fine aggregate in the concrete mixture.