Papers
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Characterization of reinforced timber masonry walls in
After the large destruction of Lisbon due to the 1755 earthquake, the city had to be completely rebuilt. The innovative
Year: 2018
Number Pages:
93-106 pp.
Author(s): Gonçalves, A.; Guerreiro, L.; Candeias, P.; Ferreira, J.; Campos Costa, A.
: Engineering Structures
Editor: Elsevier
Volume:
V. 166.
Keywords: Pombalino buildings; Seismic behavior; Dynamic tests; Timber masonry walls
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Characterization of reinforced timber masonry walls in
After the large destruction of Lisbon due to the 1755 earthquake, the city had to be completely rebuilt. The innovative
Year: 2018
Number Pages:
93-106pp.
Author(s): Gonçalves, A.; Guerreiro, L.; Candeias, P.; Ferreira, J.; Campos Costa, A.
: Engineering Structures
Editor: Elsevier
Volume:
Volume 166.
Keywords: Timber masonry walls;
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Characterization of ship motions induced by wake waves
This paper analyses the hydrodynamic interaction between two ships, one stationary and the other navigating nearby, using physical and numerical modelling. The passing ship is a self-propelled scale model of the
Year: 2018
Number Pages:
547-555pp.
Author(s): Pedro, F.; Pinheiro, L.; Fortes, C. J. E. M.; Santos, J. A.; Hinostroza , M.
: Progress in Maritime Technology and Engineering
Editor: Taylor & Francis
Keywords: Wake waves; SWAMS; Ship motions
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Characterization of timber masonry walls with dynamic tests
Timber-framed wall buildings are seen all over Europe, especially in seismic regions, given its adequacy to resist earthquakes. The
Year: 2018
Number Pages:
16p.
Author(s): Gonçalves, A.; Candeias, P.; Guerreiro, L.; Ferreira, J.; Campos Costa, A.
: International Journal of Architectural Heritage - Conservation, Analysis, and Restoration
Editor: Taylor&Francis
Volume:
Volume 12, 2018.
Keywords: Timber masonry walls; Shaking table; Resist earthquakes; Rehabilitation; Dynamic tests
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Characterization of timber masonry walls with dynamic tests
Timber-framed wall buildings are seen all over Europe, especially in seismic regions, given its adequacy to resist earthquakes. The
Year: 2018
Number Pages:
298-313pp.
Author(s): Gonçalves, A.; Candeias, P.; Ferreira, J.; Campos Costa, A.; Guerreiro, L.
: International Journal of Architectural Heritage
Editor: Taylor & Francis
Volume:
Vol.13.
Keywords: Timber masonry walls; Shaking table; Resist earthquakes; Dynamic tests; Rehabilitation
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Coastal risk forecast system
The run-up and overtopping by sea waves are two of the main processes that threaten coastal structures, leading to flooding, destruction of both property and the environment, and harm to people. To build early warning systems, the consequences and associated risks in the affected areas must be evaluated. It is also important to understand how these two types of spatial information integrate with sensor data sources and the risk assessment methodology. This paper describes the relationship between consequences and risk maps, their role in risk management and how the HIDRALERTA system integrates both aspects in its risk methodology. It describes a case study for Praia da Vito´ria Port, Terceira Island, Azores, Portugal, showing that the main innovations in this system are twofold: it represents the overtopping flow and consequent flooding, which are critical for coastal and port areas protected by maritime structures, and it works also as a risk assessment tool, extremely important for long-term planning and decision-making. Moreover, the implementation of the system considers possible known variability issues, enabling changes in its behaviour as needs arise. This system has the potential to become a useful tool for the management of coastal and port areas, due to its capacity to effectively issue warnings and assess risks.
Year: 2018
Number Pages:
26p.
Author(s): Sabino, A.; Poseiro, P.; Rodrigues, A.; Fortes, C. J. E. M.; Reis, M. T. L. G. V.; Reis, R.; Araújo, J
: Journal of Geographical Systems
Editor: Springer
Keywords: Software product lines; Geographic information systems; Early warning; Risk management; Coastal flooding; Wave overtopping
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Comprehensive performance indicators for road pavement condition assessment
The selection and use of technical parameters and performance indicators plays an essential role in thepavement management process. It is known that if more parameters are used, a more accurate evaluationof pavement condition is achieved, improving the choice of maintenance and rehabilitation interventions.However, one of the most expensive activities of the pavement management process is data collection.Accordingly, it is necessary to find a balance between the data collected and the real needs of the process.This paper presents a new approach for the development of pavement condition indicators using a machinelearning algorithm named regularised regression with lasso. The present discussion is supported by a casestudy, which compares the proposed method with current practice for the description of the condition of aPortuguese motorway. The results suggest that the application of machine learning methods can improvethe accuracy of pavement condition indicators when less data are available, contributing to achieve abalance between the needed data and information obtained.
Year: 2018
Number Pages:
1433-1445pp..
Author(s): Marcelino, P.; Antunes, M. L.; Fortunato, E.
: Structure and Infrastructure Engineering
Editor: Taylor & Francis Online
Volume:
14:11.
Keywords: Performance indicators; Regression analysis; Machine learning algorithms; Statistical models; Highway maintenance; Pavement maintenance
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Concentration polarization in ultrafiltration/nanofiltration for the recovery of polyphenols from winery wastewaters
Concentration polarization is intrinsically associated with the selective character ofmembranes and often means flux decline and which causes a subsequent decrease of ultrafiltrationand nanofiltration performance. More important is the fact that it acts as a precursor of membranefouling and creates severe fouling problems in the longer times range. The quantification of itsdependence on the operating parameters of cross-flow velocities and transmembrane pressuresmakes recourse to the film theory to introduce mass-transfer coefficients that generally are calculatedby dimensionless correlations of the Sherwood number as a function of the Reynolds and Schmidtnumbers. In the present work, the mass-transfer coefficients are obtained through the fitting ofexperimental results by the pressure variation method. The ultrafiltration/nanofiltration of the winerywastewaters from the racking operation is carried out with the membranes ETNA 01PP (Alfa Laval)and NF 270 (Dow Filmtec) under a wide range of cross-flow velocities and transmembrane pressuresup to 15 bar.
Year: 2018
Number Pages:
11pp..
Author(s): Giacobbo, A.; Bernardes, A.M.; Rosa, M. J.; Pinho, M.N.
: membranes
Editor: MDPI
Volume:
Volume 8, Numero 46.
Keywords: Polyphenols recovery; Winery wastewater; Nanofiltration; Ultrafiltration; Concentration polarization
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Crushing and oedometer compression of rockfill using DEM
A new methodology was developed to perform computer simulations of crushable rockfill particles using the dis-crete element method. Rockfill was modelled using a clump logic, responsible for providing a statistical and spatial variability in the strength and shape of the particles. Clumps have a major advantage of severely decreasing the number of contact equations to be solved in the model, resulting in less computer time. A series of single-particle crushing tests and an oedometer test were simulated using crushable particles and were in agreement with experimental data. A comprehensive study of the brittle failure of single-particle crushing tests is presented.
Year: 2018
Number Pages:
11-22pp.
Author(s): Manso, J.; Marcelino, J.; Caldeira, L.
: Computers and Geotechnics
Editor: Elsevier
Volume:
101.
Keywords: Clumps; Bonded particles; Crushing strength; Particle breakage; Discrete element method; Rockfill
Info
Dependable outlier detection in harsh environments monitoring systems
Environmental monitoring systems are composed by sensor networks deployed in uncertain and harsh conditions, vulnerable to external disturbances, posing challenges to the comprehensive system characterization and modelling. When unexpected sensor measurements are produced, there is a need to detect and identify, in a timely manner, if they stem from a failure behavior or if they indeed represent some environment-related process. Existing solutions for fault detection in environmental sensor networks do not portray the required sensitivity for the differentiation of these processes or they are unable to meet the time constraints of the affected cyber-physical systems.We have been developing a framework for dependable detection of failures in harsh environments monitoring systems, aiming to improve the overall sensor data quality. Herein we present the application of an early framework implementation to an aquatic sensor network dataset, using neural networks to model sensors
Year: 2018
Number Pages:
224-233pp.
Author(s): Jesus, G.; Casimiro, A.; Oliveira, A.
: Lecture Notes in Computer Science
Editor: Springer
Volume:
vol 11094.
Keywords: Water monitoring; Neural networks; Machine learning; Outlier detection; Data quality; Dependability
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