Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
Publications

Publications by CAP

2020

Probabilistic structural analysis of Sao Joao Bridge based on the on-site study of the time-dependent behavior of concrete

Authors
Santos, LO; Xu, M; Virtuoso, F;

Publication
STRUCTURAL CONCRETE

Abstract
This article aims to present a procedure to take into account the variability of the time-dependent behavior of concrete on its structural effects, evaluated from the study of creep and shrinkage based on experimental data obtained on-site. For this purpose, the Sao Joao Bridge, a railway bridge built in Porto, Portugal in 1991, is presented as a case study. Sao Joao Bridge is a railway bridge crossing the river Douro. It is a prestressed concrete structure, with a total length of 1,028 m, including the main span of 250 m, two side spans of 125 m, six approaching spans on the left river bank, and three approaching spans on the right river bank (Porto). During bridge construction, a comprehensive structural health monitoring (SHM) system was set up, as well as an on-site study of time-dependent behavior of concrete. This study was based on creep 15 specimens and 15 shrinkage specimens, prepared simultaneously with some segments of the deck, using the same material, and it was kept running during almost 20 years. The results of this study were treated statistically and used as random variables in a probabilistic analysis of the time-dependent behavior of the bridge. After a brief description of the mentioned on-site study and the bridge SHM system, the paper presents the procedure followed on the bridge numerical probabilistic analysis. Finally, the values computed by the numerical model are presented and compared with the experimental values provided by the SHM.

2020

Evaluation of potential tidal impoundment energy systems in Ria de Aveiro, Portugal

Authors
Rocha, J; Abreu, T; Felgueiras, C;

Publication
ENERGY REPORTS

Abstract
The shelving of the seabed and funneling of the water by the estuaries is favorable for tidal impoundment technologies. In this work, the estimation of the tidal potential energy for Ria de Aveiro lagoon was achieved through the application of a model developed in the Delft3D software. This software can reproduce the hydrodynamics of this complex system and simulations were run to identify hot spots to retrieve gravitational potential energy. For the selected places, both power and annual energy were calculated. It was concluded that the tidal energy that can be extracted from Ria de Aveiro is considerable, justifying further studies to consider the accommodation of some type of tidal exploitation, in the foreseeable future. (C) 2020 TheAuthors. Published by Elsevier Ltd.

2020

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

Authors
Paiva, JS; Jorge, PAS; Ribeiro, RSR; Balmana, M; Campos, D; Mereiter, S; Jin, CS; Karlsson, NG; Sampaio, P; Reis, CA; Cunha, JPS;

Publication
Scientific reports

Abstract
With the advent of personalized medicine, there is a movement to develop "smaller" and "smarter" microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the "intelligent" Lab on Fiber (iLoF) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLoF is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.

2020

Femtosecond laser direct written off-axis fiber Bragg gratings for sensing applications

Authors
Viveiros, D; Amorim, VA; Maia, JM; Silva, S; Frazao, O; Jorge, PAS; Fernandes, LA; Marques, PVS;

Publication
Optics and Laser Technology

Abstract
First order off-axis fiber Bragg gratings (FBGs) were fabricated in a standard single mode fiber (SMF-28e) through femtosecond laser direct writing. A minimum offset distance between the grating and core center of 2.5 µm was found to create a multimode section, which supports two separate fiber modes (LP0,1 and LP1,1), each split into two degenerate polarization modes. The resulting structure breaks the cylindrical symmetry of the fiber, introducing birefringence (˜10-4) resulting in a polarization dependent Bragg wavelength for each mode. Based on the modal and birefringence behavior, three off-axis FBGs were fabricated with 3.0, 4.5 and 6.0 µm offsets from the core center, and then characterized in strain, temperature, and curvature. The tested off-axis FBGs exhibited a similar strain sensitivity of ~1.14 pm/µ? and a temperature sensitivity of ~12 pm/C. The curvature and orientation angle were simultaneously monitored by analyzing the intensity fluctuation and the wavelength shift of the LP1,1 Bragg resonance. A maximum curvature sensitivity of 0.53 dB/m-1 was obtained for the off-axis FBG with a 3.0 µm offset. © 2020 Elsevier Ltd

2020

Femtosecond laser-written long period fibre gratings coated with titanium dioxide for improved sensitivity

Authors
Viveiros, D; De Almeida, JMMM; Coelho, L; Vasconcelos, H; Amorim, VA; Maia, JM; Jorge, PAS; Marques, PVS;

Publication
Optical Sensing and Detection VI

Abstract

2020

Author Correction: iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

Authors
Paiva, JS; Jorge, PAS; Ribeiro, RSR; Balmaña, M; Campos, D; Mereiter, S; Jin, C; Karlsson, NG; Sampaio, P; Reis, CA; Cunha, JPS;

Publication
Scientific Reports

Abstract

  • 1
  • 231