Grup de Recerca en Sistemes Dinàmics Aplicats a l'Energia Solar (INSPIRES)

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    Open Access
    Design and test of shape memory alloy fins for self-adaptive liquid cooling device
    (Elsevier, 2022-01-22) Regany Vendrell, Desideri; Majós, Francesc; Barrau, Jérôme; Rosell Urrutia, Joan Ignasi; Ibáñez, Manuel; Fréchette, L. G.; Vilarrubí, Montse
    Thermal management complexity increases in high-performance chips, where the heat loads vary spatially and temporally, while liquid cooling systems are usually designed for most stringent stationary conditions. Several works developed heat transfer enhancement techniques to increase the cooling capacity of liquid cooled heat sinks, but pumping power is increased in a permanent way due to the addition of elements within the channels. Here, a liquid cooling self-adaptive heat sink that can efficiently adapt the distribution of its heat extraction capacity to time dependent and non-uniform heat load scenarios is proposed. Numerical design of the mesoscale cooling device with bimorph metal/SMA fins, definition of the fabrication and training procedure of the SMA fins to reach the desired behavior and experimental assessment is presented. The capacity of the self-adaptive fins to locally boost the heat transfer is numerically and experimentally demonstrated. Results obtained show that the self-adaptive fins can improve the temperature uniformity by 63% with respect to plain channel. The reduction in thermal resistance using bimorph metal/SMA fins sample allows the surface maximum temperature gradient to remain almost constant although heat flux increases. Energy savings are maximized in applications where partial load intervals contributes significantly to the overall operating period.
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    EMPOWERING, a Smart Big Data Framework for Sustainable Electricity Suppliers
    (Institute of Electrical and Electronics Engineers (IEEE), 2018) Mor Martínez, Gerard; Vilaplana Mayoral, Jordi; Danov, Stoyan; Cipriano, Jordi; Solsona Tehàs, Francesc; Chemisana Villegas, Daniel
    This paper presents the EMPOWERING project, a Big Data environment aimed at helping domestic customers to save electricity by managing their consumption positively. This is achieved by improving the information received about energy bills and offering online tools. The main contributions of EMPOWERING are the creation of a novel workflow in the electricity utility sector regarding the implementation of data analytics for their customers and the fast implementation of data-mining techniques in massive datasets within a Big Data platform to achieve scalability. The results obtained show that EMPOWERING can be of use for customers of electrical suppliers by changing their energy habits to decrease consumption and so increase environmental sustainability.