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Nogal, Maria
Preferred name
Nogal, Maria
Official Name
Nogal, Maria
Research Output
Now showing 1 - 3 of 3
- PublicationTRUSS, a European Innovative Training Network Dealing with the Challenges of an Aging Infrastructure Network(NDT.net, 2019-04-01)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; Inspections and maintenance of infrastructure are expensive. In some cases, overdue or insufficient maintenance/monitoring can lead to an unacceptable risk of collapse and to a tragic failure as the Morandi bridge in Genoa, Italy, on 14th August 2018. An accurate assessment of the safety of a structure is a difficult task due to uncertainties associated with the aging and response of the structure, with the operational and environmental loads, and with their interaction. During the period from 2015 to 2019, the project TRUSS (Training in Reducing Uncertainty in Structural Safety) ITN (Innovative Training Network), funded by the EU H2020 Marie Curie-Skłodowska Action (MSCA) programme, has worked towards improving the structural assessment of buildings, energy, marine, and transport infrastructure. Fourteen Early Stage Researchers (ESRs) have been recruited to carry out related research on new materials, testing methods, improved and more efficient modelling methods and management strategies, and sensor and algorithm development for Structural Health Monitoring (SHM) purposes. This research has been enhanced by an advanced program of scientific and professional training delivered via a collaboration between 6 Universities, 1 research institute and 11 companies from 5 European countries. The high proportion of companies participating in TRUSS ITN has ensured significant industry expertise and has introduced a diverse range of perspectives to the consortium on the activities necessary to do business in the structural safety sector.222 - PublicationA bespoke signal processing algorithm for operational modal testing of post-tensioned steel and concrete beamsThe extraction of modal properties, specifically natural frequency, damping ratio and mode shape is a difficult task, especially when output-only data is measured. The accuracy of the estimation these modal properties is compromised by noisy signals, and signal filtering is required to suppress unwanted frequency content. Care is required however to avoid over-filtering of the output data, which can eliminate valid structural frequency content if required care is not exercised. This paper describes the development of a bespoke signal processing algorithm to extract the modal properties of both simply supported post-tensioned steel and concrete sections. Dynamic impact testing was conducted on a series of different post-tensioned steel rectangular hollow sections, and 9 different post-tensioned concrete beams, each with differing straight profiled post-tensioning strand eccentricities. Acceleration time-history data was recorded for each of the steel and concrete beams via an accelerometer. This data was subsequently processed, first centring the acceleration-time history using a moving average filter, and subsequently removing any zero drift in the accelerometer via a second order low pass Butterworth filter. Electrical noise was then removed via a notch filter. The accelerometer data was then smoothed in the time domain. The Fast Fourier Transform (FFT) was applied to the signal to convert into the frequency domain and finally a bespoke peak-picking algorithm was invoked to extract the natural frequencies of the beams. A comparison is subsequently made between the accuracy of the estimation of the modal properties of the steel and concrete beams for filtered and unfiltered data, and a sensitivity analysis of the filtering and peak picking parameters is conducted to determine the effect that this has on the accuracy of the estimation of the modal parameters. The results show the effectiveness of the bespoke signal processing algorithm in increasing the accuracy of the estimation of the modal properties as opposed to the raw unprocessed signals.
379 - PublicationTRUSS, a European innovative training network dealing with the challenges of an aging infrastructure network(2018-11-12)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; Inspections and maintenance of infrastructure are expensive. In some cases, overdue or insufficient maintenance/monitoring can lead to an unacceptable risk of collapse and to a tragic failure as the Morandi bridge in Genoa, Italy, on 14th August 2018. An accurate assessment of the safety of a structure is a difficult task due to uncertainties associated with the aging and response of the structure, with the operational and environmental loads, and with their interaction. During the period from 2015 to 2019, the project TRUSS (Training in Reducing Uncertainty in Structural Safety) ITN (Innovative Training Network), funded by the EU H2020 Marie Curie-Skłodowska Action (MSCA) programme, has worked towards improving the structural assessment of buildings, energy, marine, and transport infrastructure. Fourteen Early Stage Researchers (ESRs) have been recruited to carry out related research on new materials, testing methods, improved and more efficient modelling methods and management strategies, and sensor and algorithm development for Structural Health Monitoring (SHM) purposes. This research has been enhanced by an advanced program of scientific and professional training delivered via a collaboration between 6 Universities, 1 research institute and 11 companies from 5 European countries. The high proportion of companies participating in TRUSS ITN has ensured significant industry expertise and has introduced a diverse range of perspectives to the consortium on the activities necessary to do business in the structural safety sector.253