Existing unreinforced masonry buildings in seismically active regions are in urgent need of consolidation and preservation against seismic action to prevent damage and loss of financial resources. In this research, an experimental study of externally confined brick masonry piers, which are frequently preferred as load-bearing elements in historical buildings, was conducted. The confinement system included a combination of open-grid basalt textile and mortar. Eighteen masonry pier specimens were produced using solid bricks collected from a historical building constructed in approximately the 1930s and a local mortar with substandard mechanical characteristics to simulate mortar properties in existing heritage buildings. All the square/rectangular pier specimens were tested under concentric compressive loads. In general, confinement of the tested textile-reinforced mortar (TRM) improved the energy dissipation of the masonry piers significantly. A comparison was made between the experimental results and theoretical predictions using the available analytical models. The compressive strengths predicted by the models are satisfactory.
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Peer-to-peer (P2P) energy trading has been recognized as an important technology to increase the local self-consumption of photovoltaics in the local energy system. Different auction mechanisms and bidding strategies haven been investigated in previous studies. However, there has been no comparatively analysis on how different market structures influence the local energy system’s overall performance. This paper presents and compares two market structures, namely a centralized market and a decentralized market. Two pricing mechanisms in the centralized market and two bidding strategies in the decentralized market are developed. The results show that the centralized market leads to higher overall system self-consumption and profits. In the decentralized market, some electricity is directly sold to the grid due to unmatchable bids and asks. Bidding strategies based on the learning algorithm can achieve better performance compared to the random method.
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In order to design effective Persuasive Technology (PT) interventions, it is essential that designers understand the multitude of factors that lead to behavioral change, rather than guessing at a solution or imitating successful techniques without understanding why. The few available PT design frameworks solely distinguish behavioral determinants on an individual (micro) level (e.g., motivation), whereas successfully persuading a user is a multifaceted and complex task depending also on factors on a meso (e.g., available resources) and macro (e.g., social support and praise) level. We developed an analysis grid that enables PT designers to acknowledge the multifaceted character of determinants leading to behavioral change and select appropriate PT channels and strategies, preventing the failure of PT design. This analysis grid was validated in a case study in which we designed a PT intervention aimed at reporting minor crime incidents among citizens.
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As electric loads in residential areas increase as a result of developments in the areas of electric vehicles, heat pumps and solar panels, among others, it is becoming increasingly likely that problems will develop in the electricity distribution grid. This research will analyse different solutions to such problems to determine Using a model developed as part of this project, we will simulate various cases to determine under which circumstances load balancing at a community-level is more (cost) effective than alternative solutions (e.g. grid reinforcement and/or household batteries).
