Papers

Today, there are several computational models to predict the mechanical behaviour of masonry structures subjected to external loading. Such models require the input of material parameters to describe the mechanical behaviour and strength of masonry constructions. Although such masonry material parameters are characterised by stochastic?probabilistic nature, engineers are assigning the same material properties throughout the structure to be analysed. The aim of this paper is to propose a methodology which considers material spatial variability and stochastic strength prediction for masonry structures. The methodology is illustrated on a case study covering the in?plane behaviour of a low bond strength masonry wall panel containing an opening. A 2D non?linear computational model based on the Discrete Element Method (DEM) is used. The computational results are compared against those obtained from the experimental findings in terms of failure mode and structural capacity. It is shown that computational models which consider the spatial variability of masonry material properties better predict the load carrying capacity, stiffness and failure mode of the masonry structures. Theseobservations provide new insights into structural behaviour of masonry constructions and lead to suggestions for improving assessment techniques for masonry structures.

In recent years the study of renderings within conservation practice has acquired major technical and methodological advances. Due to the need of compatibility, usually repair mortars must be based on lime, and standardized tests are sometimes ineffective for these compatible substitution materials, which are often low strength mortars. The influence of the aggregates' characteristics on several factors that affect the adhesive strength of lime-based mortars is assessed and a new non-standard test method to determine the tensile bond strength of low strength mortars to porous substrates is presented and validated. The outcome shows that the new methodology offers the advantages of precision of the test device, ease of application and mostly consistency of the results. Furthermore, the main data show close relationship between the tensile bond strength and the pore size distribution of the mortars, which is very sensitive to the aggregates’ characteristics: In general, increasing the mortars pore volume of coarse pores (above the critical pore diameter of the substrate) strengthens the effective bond between these elements. Moreover, the compositional similarity between the aggregates and the substrate could also favour the bond between these elements.

Urban water systems (UWSs) are energy-intensive worldwide, particularly for drinking-water pumping and aeration in wastewater treatment. Usual approaches to improve energy efficiency focus only on equipment and disregard the UWS as a continuum of stages from source-to-tap-to-source (abstraction/transport—treatment—drinking water transport/distribution—wastewater and stormwater collection/transport—treatment—discharge/reuse). We propose a framework for a comprehensive assessment of UWS energy efficiency and a four-level approach to enforce it: overall UWS (level 1), stage (level 2), infrastructure component (level 3) and processes/equipment (level 4). The framework is structured by efficiency and effectiveness criteria (an efficient but ineffective infrastructure is useless), earlier and newly developed performance indicators and reference values. The framework and the approach are the basis for a sound diagnosis and intervention prioritising, and are being tested in a peer-to-peer innovation project involving 13 water utilities (representing 17% of the energy consumption by the Portuguese water sector in 2017). Results of levels 1–3 of analysis herein illustrated for a water utility demonstrate the framework and approach potential to assess UWS effectiveness and energy efficiency, and to select the stages and infrastructures for improvement and deeper diagnosis.

During the last decade, many vibration-based structural health monitoring systems have been successfully implemented in different structures such as bridges, towers, stadia and wind turbines, with the aim of studying the structure dynamics and its evolution over time, eventually detecting the occurrence of novel structural behaviour that may indicate the presence of damage. Such vibration-based monitoring systems generally rely on the identification of modal properties, which are then used as monitoring features. Therefore, from operational modal analysis to the tracking of those features and finally to data normalization, many processing steps occur that depend on the accuracy of the identified modal properties. Thus, the estimation of the uncertainties associated with the identified modal properties increases the robustness of this process. In this context, data obtained from the continuous dynamic monitoring of a concrete arch dam has been used to evaluate the gains of quantifying the uncertainties of modal properties, evaluating in particular the effect of taking these uncertainties into consideration when performing automated operational modal analysis, modal tracking and data normalization. Nevertheless, it is observed that the most significant gains of considering estimates uncertainties occur when these quantities are used for removing outliers during modal tracking.

Accurate pavement performance prediction models are essential to ensure optimal allocation of resources in maintenance management. These models are developed using inventory and monitoring data regarding pavement structure, climate, traffic, and condition. However, numerous road agencies have limited pavement data. Due to the inexistence of historical data, data collection frequency, and/or quality issues, the amount of data available for the development of performance models is reduced. As a result, the resource allocation process is significantly undermined. This paper proposes a transfer learning approach to develop pavement performance prediction models in limited data contexts. The proposed transfer learning approach is based on a boosting algorithm. In particular, a modified version of the popular TrAdaBoost learning algorithm was used. To test the proposed transfer learning approach, a case study was developed using data from the Long-Term Pavement Performance (LTPP) database and from the Portuguese road administration database. The results of this work show that it is possible to develop accurate performance prediction models in limited data contexts when a transfer learning approach is applied. All the models resulting from this approach outperformed baseline models, especially in what regards long-term forecasts. The results also showed that the transfer learning models perform consistently over different time frames, with minor performance losses from one-step to multi-step forecasts. The findings of this study should be of interest to road agencies facing limited data contexts and aiming to develop accurate prediction models that can improve their pavement management practice.

In recent years, interest has increased in new renewable energy solutions for climate change mitigation and increasing the efficiency and sustainability of water systems. Hydropower still has the biggest share due to its compatibility, reliability and flexibility. This study presents one such technology recently examined at Instituto Superior Técnico based on a transient-flow induced compressed air energy storage (TI-CAES) system, which takes advantage of a compressed air vessel (CAV). The CAV can produce extra required pressure head, by compressing air, to be used for either hydropower generation using a water turbine in a gravity system or to be exploited in a pumping system. The results show a controlled behaviour of the system in storing the pressure surge as compressed air inside a vessel. Considerable power values are achieved as well, while the input work is practically neglected. Higher power values are attained for bigger air volumes. The TI-CAES offers an efficient and flexible solution that can be exploited in exiting water systems without putting the system at risk. The induced transients in the compressed air allow a constant outflow discharge characteristic, making the energy storage available in the CAV to be used as a pump storage hydropower solution.

The effects of climate dynamics on urban areas involve the aggravation of existing conditions and the potential for emergence of new hazards or risk factors. Floods are recognized as a leading source of consequences to society, including disruption of critical functions in urban areas, and to the environment. Consideration of the interplay between services providers ensuring urban functions is essential to deal with climate dynamics and associated risks. Assessment of resilience to multiple hazards requires integrated and multi-sectoral approaches embracing each strategic urban sector and interactions between them. A common limitation resides in the limited data and tools available for undertaking these complex assessments. The paper proposes a methodology to undertake the spatial characterization of the flood related hazards and exposure of both essential functions and services providers in urban areas, in the context of limitations in data and in ready-to-use tools. Results support the resilience assessment of these hazards, taking into account interdependencies and cascading effects. The approach is applied to Lisbon city as the study case. Results are promising in demonstrating the potential of combining data and knowledge from different sources with dual modelling approaches, allowing us to obtain trends on the magnitude of effects of climate scenarios and to assess potential benefits of adaptation strategies. Quantification of the effects is reached, but results need to be assessed together with the underlying levels of uncertainty. The methodology can facilitate dialogue among stakeholders and between different decision levels

A set of scale-model tests carried out to enlarge the range of wave steepness values analysed in run-up, overtopping and armour layer stability studies, focusing on oblique extreme wave conditions and on their effects on a gentler slope breakwater’s trunk armour and roundhead, is presented in this paper. A stretch of a rubble mound breakwater (head and part of the adjoining trunk, with a slope of 1(V):2(H)) was built in a wave basin at the Leibniz University Hannover to assess, under extreme wave conditions (wave steepness of 0.055) with different incident wave angles (from 40º to 90º), the structure behaviour in what concerns wave run-up, wave overtopping and damage progression of the armour layer. Two types of armour elements (rock and Antifer cubes) were tested. Non-intrusive methodologies including a new application of laser scanning technique for the assessment of both armour layer damage and wave run-up and overtopping were used. It is expected that such work will contribute also with data to improve empirical formulas as well as to validate complex numerical model for wave-structure interaction.

The interface between the main channel and the floodplain of a compound channel is often populated by trees or buildings that normally remain emergent during floods. This study investigates how drag on an emergent cylinder is affected by the shear flow that develops at the interface. The experimental set-up features a circular cylinder at the interface of a straight compound channel under uniform flow conditions. The integral form of the equation of conservation of momentum was used to calculate the magnitude and direction of the time-averaged drag force per unit submerged-length of the cylinder. All terms were experimentally determined, except for those associated with fluid interaction with the cylinder. The same method was also applied to a cylinder under symmetrical flow conditions. It is concluded that the existence of the shear layer leads to an asymmetrical drag force and to a reduced drag coefficient.

This paper presents the development and application of a comprehensive methodology for the systematic water balance calculation in collective irrigation systems (CIS), applicable to pressurized pipelines or open canals. Existing approaches focus solely on the assessment the water resources use efficiency of CIS single components (e.g., leakage in some canal reaches), without a system-wide approach. A water balance approach allows accounting for the different system volume inputs (i.e., water abstraction, imported water, water volume due to precipitation or surface runoff), authorized and non-authorized consumptions and water losses either in canal, mixed or pressurized CIS, which has never been presented in literature. The proposed methodology allows the assessment of different water loss components (i.e., evaporation losses, unauthorized uses, metering errors, leakage and discharges) and the calculation of water loss performance indicators that allow the identification of the main problems in terms of water losses and provides guidance about measures to control water losses. Although based on the existing and consolidated water balance schemes specifically developed for urban water supply systems, the proposed methodology includes novel components in terms of system input volume, authorized consumption and water loss that are specific of CIS. The methodology is tested and applied to a mixed collective irrigation system. Results show that the water losses due to discharges in canal systems can be one of the most relevant component of the non-revenue water, representing approximately half of its total volume, followed by leakage in canals and metering errors. These results highlight the importance of improving daily operation of these systems and also rehabilitating ageing infrastructures.