Artigos de Revista

Em mais um artigo dedicado à reflexão sobre a habitação para as pessoas mais idosas numa perspetiva integrada e intergeracional, abordamos, especificamente, a importância de uma adequada caraterização residencial em termos de adaptabilidade passiva e ativa quando se visa uma habitação intergeracional especificamente amigável para idosos e fragilizados . Numa primeira parte do artigo faz-se uma introdução global à temática acima referida, passando-se, depois, para a abordagem do tema do interesse que tem o desenvolvimento de habitações, positivamente, à prova do futuro.Em seguida desenvolve-se a temática da adaptabilidade das habitações, realizada no sentido da facilitação da vivência dos idosos e conclui-se o artigo com uma reflexão sobre o assunto específico da opção por se viver em várias (e entre) habitações quando envelhecemos ou quando por isso optamos.

The number of climate-related disasters has progressively increased in the last two decades and this trend will drastically exacerbate in the medium- and long-term horizons according to climate change projections. In this framework, through a multi-disciplinary team and a strong background acquired in recent projects, ICARIA aims to promote the use of asset-level modeling to achieve a better understanding of climate related tangible direct and indirect impacts on critical assets due to complex, cascading, and compound disasters. Furthermore, it takes into account the related risk reduction provided by suitable, sustainable, and cost-effective adaptation solutions. ICARIA focuses on both (i) critical assets and services that were not designed for potential climate change-related impacts that can increase the unplanned outages and failures, and (ii) on housing, natural areas, and population. Cutting edge methods regarding climate scenario building, asset-level-coupled models, and multirisk assessment approaches will be implemented and replicated in three EU regions to understand how future climate scenarios might affect critical assets and to provide decision-making support tools to private and public risk owners to assess the costs and benefits of various adaptation solutions.

This paper investigates the effect of different types of structural and operational measures on water mixing and renewal time in circular and rectangular cross-section water storage tanks, aiming at a better understanding of the flow dynamics to find practicable solutions to improve their design, rehabilitation and operation. An experimental programme, including traditional tracer and dye tracer tests, was carried out in small-scale tanks for different configurations and operating conditions. Two tanks were tested with and without interior structures, with the inlet/outlet pipes at different locations and for constant and variable water level. The main findings are that: i) the most effective measure is operating with fill-and-draw cycles, however, for tanks operated nearly full structural measures are recommendable; ii) reducing the inlet pipe diameter and installing nozzles near the tank bottom improve the mixing conditions; iii) the use of baffles is recommendable when the inlet and outlet pipes are very close.

Insulation materials are fundamental for decreasing energy losses and guaranteeing thermal and acoustic comfort in buildings, which may significantly contribute to decreasing the energy consumption related with poor thermal building conditions. These insulation materials should have a low susceptibility to biological degradation agents to decrease the risks of degradation of other construction materials, as well as decrease possible health risks related with the development of noxious biological degradation agents regarding indoor air quality, for example, or decrease possible structural risks posed by those agents. The present study aimed at evaluating the susceptibility of several insulation materials to mold growth and subterranean termites

By leveraging performance assessment systems (PASs) and incorporating targeted strategies, utilities can enhance the overall effectiveness, reliability, efficiency, and environmental performance of their wastewater treatment facilities. This work presents the results obtained from a comprehensive analysis of treatment reliability and energy performance of three wastewater treatment plants (WWTPs). The results allowed identifying, for each WWTP, improvement needs related to the aeration energy requirements, as well as to determine the effluent concentration targets required to achieve higher reliability levels while potentially reducing running costs. By analysing reliability combined with energy efficiency, this methodology allowed identifying the WWTPs

Promoting the accuracy and coverage of the alighting of passengers in public transport is essential to support route planning and policy decisions aiming to sustainable mobility. Although previous studies place several principles for alighting estimation from incomplete smart card data, most remain dispersed and address one single mode. These gaps hinder a comprehensive comparison of the success rates of existing alighting algorithms. To address the above challenges, this work assesses side-by-side state-of-the-art principles for alight stop inference using smart card data from multimodal transport networks. To our best knowledge, this research is the first incrementally measuring the impact of each principle present in the literature. It further discusses uncertainty factors and proposes a confidence metric on the estimated alighted stops.

Slags and rubber from end-of-life tires represent a liability to the steel and tire industry, causing economic and environmental problems that are difficult to manage. Transport infrastructures can use these industrial by-products instead of extracting natural raw materials, but the adequate mechanical performance of the materials needs to be assured. This paper addresses the mechanical behaviour of slag

This paper reviews the literature on model-driven engineering (MDE) tools and languages for the internet of things (IoT). Due to the abundance of big data in the IoT, data analytics and machine learning (DAML) techniques play a key role in providing smart IoT applications. In particular, since a significant portion of the IoT data is sequential time series data, such as sensor data, time series analysis techniques are required. Therefore, IoT modeling languages and tools are expected to support DAML methods, including time series analysis techniques, out of the box. In this paper, we study and classify prior work in the literature through the mentioned lens and following the scoping review approach. Hence, the key underlying research questions are what MDE approaches, tools, and languages have been proposed and which ones have supported DAML techniques at the modeling level and in the scope of smart IoT services.

Climate change has emerged as a global challenge, with consequences for the environment and societies. To mitigate its impacts, reclaimed water (RW) offers potential by reducing water withdrawal and minimizing pollution discharges in the environment. Safe RW requires disinfection and a sound management of chlorine residuals throughout the RW distribution systems (RWDSs). This study focuses on implementing and calibrating a chlorine decay model using EPANET-MSX in a real RWDS, incorporating both bulk and wall decays. The bulk decay accounts for reactions of monochloramine formation, auto-decomposition, and depletion by a parallel second-order mechanism where monochloramine reacts both with fast and slow organic matter reactive fractions. Two wall decays were considered in the RWDS, one in the tank, modeled through an overall wall decay constant, and one in the pipes, modeled through a wall decay constant. Field experiments were conducted to calibrate the complete model. This model was used as a support tool to diagnose the RWDS status condition and cleaning needs, and to manage its operation. Through simulated scenarios considering monochloramine wall decays similar to those observed in drinking water distribution systems, the model allowed predicting adequate chlorine dosing in summer and winter scenarios, so as to guarantee monochloramine concentrations between 1 mg/L and 5 mg/L through the network. These results point to the potential use of much lower doses than the ones currently applied.