Application of acoustic emission technique for bond characterization in FRP-masonry systems

The acoustic emission (AE) technique is used for investigating the interfacial fracture and damage propagation in GFRP-and SRG-strengthened bricks during debonding tests. The bond behavior is investigated through single-lap shear bond tests and the fracture progress during the tests is recorded by means of AE sensors. The fracture progress and active debonding mechanisms are characterized in both specimen types with the aim of AE outputs. Moreover, a clear distinction between the AE outputs of specimens with different failure modes, in both SRG-and GFRP-strengthened specimens, is found which allows characterizing the debonding failure mode based on acoustic emission data.

Economic evaluation of occupational safety preventive measures in a hospital

BACKGROUND: When an organization performs an integrated analysis of risks through its Occupational Health and Safety Management System, several steps are suggested to address the implications of the identified risks. Namely, the organization should make a detailed analysis of the monetary impact for the organization of each of the preventive measures considered. However, it is also important to perform an analysis of the impact of each measure on society (externalities). OBJECTIVE: The aim of this paper is to present a case study related to the application of the proposed economic evaluation methodology. METHODS: An analysis of the work accidents in a hospital has been made. Three of the major types of accidents have been selected: needle stings, falls and excessive strain. Following the risk assessment, some preventive measures have been designed. Subsequently, the Benefit/Cost ratio (B/C) of these measures has been calculated, both in financial terms (from the organization’s perspective) and in economic terms (including the benefits for the worker and for the Society). RESULTS: While the financial ratio is only advantageous in some cases, when the externalities are taken into account, the B/C ratio increases significantly. CONCLUSIONS: It is important to consider external

Spectrum-based energy leak localization

Dissertação de Mestrado em Engenharia Informática

Cost-effective energy and carbon emission optimization in building renovation – A case-study in a low income neighbourhood

Construction sector is one of the major responsible for energy consumption and carbon emissions and renovation of existing buildings plays an important role in the actions to mitigate climate changes. Present work is based on the methodology developed in IEA Annex 56, allowing identifying cost optimal and cost effective renovation scenarios improving the energy performance. The analysed case study is a residential neighbourhood of the municipality of Gaia in Portugal. The analysis compares a reference renovation scenario (without improving the energy performance of the building) with a series of alternative renovation scenarios, including the one that is being implemented.

Active magneto-optical control of spontaneous emission in graphene

We investigate the spontaneous emission rate of a two-level quantum emitter near a graphene-coated substrate under the influence of an external magnetic field or strain induced pseudo-magnetic field. We demonstrate that the application of the magnetic field can substantially increase or decrease the decay rate. We show that a suppression as large as 99$\%$ in the Purcell factor is achieved even for moderate magnetic fields. The emitter's lifetime is a discontinuous function of $|{\bf B}|$, which is a direct consequence of the occurrence of discrete Landau levels in graphene. We demonstrate that, in the near-field regime, the magnetic field enables an unprecedented control of the decay pathways into which the photon/polariton can be emitted. Our findings strongly suggest that a magnetic field could act as an efficient agent for on-demand, active control of light-matter interactions in graphene at the quantum level.

Predicting SO2 pollution incidents by means of additive models with optimum variable selection

The aim of this paper is to predict time series of SO2 concentrations emitted by coal-fired power stations in order to estimate in advance emission episodes and analyze the influence of some meteorological variables in the prediction. An emission episode is said to occur when the series of bi-hourly means of SO2 is greater than a specific level. For coal-fired power stations it is essential to predict emission epi- sodes sufficiently in advance so appropriate preventive measures can be taken. We proposed a meth- odology to predict SO2 emission episodes based on using an additive model and an algorithm for variable selection. The methodology was applied to the estimation of SO2 emissions registered in sampling lo- cations near a coal-fired power station located in Northern Spain. The results obtained indicate a good performance of the model considering only two terms of the time series and that the inclusion of the meteorological variables in the model is not significant.

Exploring the factor structure of neurocognitive measures in older individuals

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the "best fit" model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate.