Heat is fundamental to power generation and many industrial processes, and is most useful at high temperatures because it can be converted more efficiently to other types of energy. However, efficient transportation, storage and conversion of heat at extreme temperatures (more than about 1,300 kelvin) is impractical for many applications. Liquid metals can be very effective media for transferring heat at high temperatures, but liquid-metal pumping has been limited by the corrosion of metal infrastructures. Here we demonstrate a ceramic, mechanical pump that can be used to continuously circulate liquid tin at temperatures of around 1,473-1,673 kelvin. Our approach to liquid-metal pumping is enabled by the use of ceramics for the mechanical and sealing components, but owing to the brittle nature of ceramics their use requires careful engineering. Our set-up enables effective heat transfer using a liquid at previously unattainable temperatures, and could be used for thermal storage and transport, electric power production, and chemical or materials processing.
A horn shaped Langevin ultrasonic transducer used in a single axis levitator was characterized to better understand the role of the acoustic profile in establishing stable traps. The method of characterization included acoustic beam profiling performed by raster scanning an ultrasonic microphone as well as finite element analysis of the horn and its interface with the surrounding air volume. The results of the model are in good agreement with measurements and demonstrate the validity of the approach for both near and far field analyses. Our results show that this style of transducer produces a strong acoustic beam with a total divergence angle of 10°, a near-field point close to the transducer surface and a virtual sound source. These are desirable characteristics for a sound source used for acoustic trapping experiments.
Coastal communities around the world are experiencing increased flooding. Water level sensors provide real-time information on water levels and detections of flood risk. Previous sensor installations, however, have relied on qualitative judgments or limited quantitative factors to decide on sensor locations. Here, we provide a method to optimally place real-time water level sensors across a community. We utilize a multi-objective optimization approach, including traditional measures of sensor network performance such as coverage and uncertainty, and new flood-specific parameters such as hazard estimations (flood likelihood, critical infrastructure exposure), serviceability (sensor accessibility), and social vulnerability (socio-economic index, vulnerable residential communities index). We propose a workflow combining quantitative analyses with local expertise and experience. We show the method is able to reduce the set of possible new sensor locations to just 1.3% of the full solution set, supporting effective and feasible community decision-making. The method also supports sequential expansion of a sensor network, creating a network that provides detailed and accurate real-time water level information at the hyperlocal level for flood risk assessment and mitigation in coastal communities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.