http://repositorio.lnec.pt:8080/jspui/handle/123456789/67 CICTI Mon, 26 Oct 2026 10:02:38 GMT 2026-10-26T10:02:38Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1020022 Gestão técnica da unidade de hidráulica metrológica do LNEC: Estrutura dos planos de manutenção e de segurança Ribeiro, A.; Simões, C.; Coelho, G.; Martins, A.; Mendes, R. A.; Fernandes, H. A Unidade de Hidráulica Metrológica (UHM) do LNEC é fundamental para o reconhecimento do LNEC como Instituto Designado para as grandezas caudal e velocidade de escoamento de líquidos, garantindo a rastreabilidade metrológica essencial para a gestão dos recursos hídricos em setores como abastecimento de água, agroindústria e tratamento de águas residuais. Este relatório detalha a estrutura dos planos de manutenção e de segurança que suportam a operação da infraestrutura hidráulica da UHM, composta por sistemas mecânicos, hidráulicos, elétricos e eletrónicos complexos. São abordadas as práticas de manutenção preventiva, corretiva e preditiva, visando a confiança e a qualidade das calibrações. Os planos de segurança incluem a avaliação de riscos, medidas preventivas, equipamentos de proteção, procedimentos de emergência, capacitação do pessoal, auditorias e comunicação, assegurando a segurança das pessoas e o cumprimento dos requisitos da ISO/IEC 17025. Thu, 01 Jan 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1020022 2026-01-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019981 Fault Detection Algorithm Implementation for Distributed Sensor Networks Nunes, W.; Ferreira, P.; Reis, J. P. NDT.net Abstract This work presents the development of a data-driven digital twin at sensor level for structural health monitoring of a metallic suspension bridge in Portugal, with a focus on local validation of strain sensors using long-term monitoring data acquired between 2014 and 2017. The central challenge lies in the automated distinction between normal environmental variations and the onset of critical sensor faults. Using the Prophet library, the proposed model effectively captured the dominant 12-hour and 24-hour cycles governing bridge behavior. The results demonstrate that integrating external temperature and solar position as predictive variables results in a substantial improvement compared to models based solely on solar radiation, reducing the Mean Absolute Percentage Error to 2.5%. The anomaly detection system, based on a Binomial Hypothesis Test, exhibited high sensitivity, successfully identifying debonding faults as small as 5%. It is concluded that the reliability of the digital twin depends on empirically calibrated control limits, as the theoretical uncertainty intervals provided by the software proved unreliable for this application. Overall, this work establishes a robust methodology for long-term sensor self- validation in critical infrastructure. Fri, 01 May 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019981 2026-05-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019868 Towards the operational demonstration of a horizontal axis radial magnetic levitation bearing with zero-field cooled high temperature superconducting bulks Costa, A.; Fernandes, J.; Branco, P.; Zheng, J. Publicado pela Elsevier B.V. em nome da Universidade Jiaotong de Xangai Sat, 07 Mar 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019868 2026-03-07T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019842 Synopsis of Special Issue on Superconductors and Magnetic Materials Costa, A.; Fernandes, J.; Rodriguez, E. Abstract This editorial consists of a synopsis of the research in the Special Issue on “Superconductors and Magnetic Materials”, specifying the studies and highlighting main results and conclusions. This collection of research (1) demonstrates the possibility of notably decreasing AC losses by replacing the copper encapsulation of rare Earth barium copper oxide tapes with strong magnetic encapsulation; (2) predicts typical gains expected from soft-magnet and superconductor flux concentrators for low magnetic field sensing; (3) reveals that the n-value surfaces of high-Tc tapes can be estimated with a high accuracy using feed-forward deep neural network learning; (4) predicts the detection of a monopole plasma phase in high-Tc iron-based superconductors with a Tc above 70 K; and (5) proposes an analytical model to accurately predict the gap-to-Tc ratio for yttrium hydrides at high pressures. Mon, 09 Mar 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019842 2026-03-09T00:00:00Z