Browsing by Author "Teixeira, Abel"
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- A multidisciplinary engineering-based approach for tunnelling strengthening with a new fibre reinforced shotcrete technologyPublication . Barros, Joaquim; Costelha, Hugo; Bento, David; Brites, Nelson; Luís, Rui; Patrício, Hugo; Cunha, Vítor M.C.F.; Bento, Luís; Miranda, Tiago; Coelho, Paulo; Azenha, Miguel; Neves, Carlos; Salehian, Hamidreza; Moniz, Gonçalo; Nematollahi, Mojtaba; Teixeira, Abel; Taheri, Mahsa; Mezhyrych, Anton; Hosseinpour, Emad; Correia, Tales; Kazemi, Hamid; Hassanshahi, Omid; Rashiddel, Alireza; Esmail, BriarThis 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.
- Point Cloud Alignment for Deposited Material Assessment in Tunnel EnvironmentsPublication . Teixeira, Abel; Costelha, Hugo; Neves, Carlos; Bento, Luis CondeThe assessment of deposited material in tunnel reinforcement operations can be performed using a 3D model generated from multiple scans. For this purpose, an accurate alignment of the scanned models is required. Aligning existing structure model with data scanned after surface deformations can be challenging, particularly if reference markers are not available or were displaced. For scenarios where the surrounding structure is largely changed, certain procedures can be adapted when processing the scanned data to achieve consistent alignment between scanned and reference structure models. This work proposes a methodology to cope with these situations, analysing the impact of different approaches. Experiments were performed in a realistic scenario related with shotcrete of railway tunnels wall surfaces, with the results showing the applicability of the developed work. The proposed procedure relies in highlighting the importance of specific points that describe the same feature in the reference and aligning PC. The proposed methodology achieved an RMS difference of 0.0173 m, which lead to a drastic improvement in the point cloud alignment compared to the use of standard ICP algorithm without data preprocessing, which achieved 0.0518 m in the studied use-case.
- Survey of SLAM Algorithms with ROS SupportPublication . Teixeira, Abel; Costelha, Hugo; Bento, Luis Conde; Neves, CarlosSimultaneous Localization and Mapping (SLAM) algorithms are a key component in enabling autonomous navigation for robotic systems. This study presents a comprehensive assessment of state-of-the-art SLAM algorithms, focusing exclusively on those with Robot Operating System (ROS) support. The study aims to provide insights into the computational performance of these algorithms by leveraging the benchmark results reported in their respective studies. Each algorithm's performance metrics, as reported in their benchmark studies, are analyzed and compared. This compara-ive analysis not only highlights the strengths and weaknesses of individual algorithms but also provides a broader understanding of their applicability across diverse robotic platforms and environments. Overall, this study contributes to the advancement of SLAM research by offering a comparative evaluation tailored to ROS-supported algorithms. The findings serve as a valuable resource to make informed decisions regarding the selection and implementation of SLAM solutions in real-world applications.