This paper describes the relevant research activities that are being carried out on the development of a novel shotcrete technology capable of applying, autonomously and in real time, fibre reinforced shotcrete (FRS) with tailored properties regarding the optimum structural strengthening of railway tunnels (RT). This technique allows to apply fibre reinforced concrete (FRC) of strain softening (SSFRC) and strain hardening (SHFRC) according to a multi -level advanced numerical simulation that considers the relevant nonlinear features of these FRC, as well as their interaction with the surrounding soil, for an intended strengthening performance of the RT. Building information modelling (BIM) is used for assisting on the development of data files of the involved design software, integrating geometric assessment of a RT, damages from inspection and diagnosis, and the characteristics of the FRS strengthening solution. A dedicated computational tool was developed to design FRC with target properties. The preliminary experimental results on the evaluation of the relevant mechanical properties of the FRS are presented and discussed, as well as the experimental tests on the bond between FRS and current substrates found in RT. Representative numerical simulations were performed to demonstrate the structural performance of the proposed FRS -based strengthening technique. Computational tools capable of assuring, in real time, the aimed thickness of the layers forming the FRS strengthening shell were also developed. The first generation of a mechanical device for controlling the amount of fibres to be added, in real time, to the FRS mixture was conceived, built and tested. A mechanism is also being developed to improve the fibre distribution during its introduction through the mechanical device to avoid fibre balling. This work describes the relevant achievements already attained, as introduces the planned future initiatives in the scope of this project.

Extracting local resources from excavated lunar regolith will help support a sustainable presence on the Moon. For example, water ice beneath the lunar permanently shadowed region can be processed into liquid oxygen/hydrogen propellant. The availability of space acquired propellant could dramatically decrease the cost of Earth to space transportation. To address this need, this work proposes an autonomously controlled robot with trilateration-based localization for optimized excavation of lunar regolith. A proof-of-concept design for an autonomous lunar mining rover is presented. The autonomous rover is capable of traveling to known dig sites, excavating lunar regolith/water ice simulant, and transporting the lunar regolith/water ice simulant back to a collection sieve, without the need for user input. The work included phases for requirements and planning, conceptual design, detailed design, and testing for performance validation. Contributions of the proposed design include an autonomously controlled rover for excavation of lunar regolith, with design optimization to maximize the amount of successfully deposited material. The proposed design offers an optimal balance between opposing cost functions and design constraints for reducing the size and weight of the rover, while maximizing the operational performance of the rover for mining, transit, and depositing.