Investigating the potential of using human movements in energy harvesting by installing piezoelectric tiles in Egyptian public facilities

Developing countries are facing huge challenges toward energy production. Energy crisis not only negatively affects the industry, agricultural, commercial, and residential sectors, but it also negatively affects the development of these countries. Relying on renewable energy sources is one of the methods used to tackle the energy problem. The increase in energy costs produced from fossil fuel and the decreasing in fossil fuel production helps in decreasing the gap between the cost of energy generated from renewables and fossil fuel. Using the human population density in generating energy from renewable piezoelectric tiles in public facilities is the aim of this research. The presented research intends to investigate the potential of replacing the floor tiles in public facilities with piezoelectric tiles to generate energy and benefit from the high human population density and movements inside these facilities, and people will start to produce nonstop energy from walking throughout the facility. The presented research used quantitative method to investigate the potential of replacing the floor tiles in Shobra El-Khema metro station with piezoelectric tiles toward energy production. The research compared the electricity generated from piezoelectric tiles with the electricity consumed to electrify the station. According to the population density in Shobra El-Khema metro station, the research revealed that installing 7 Waynergy tiles in a location where all the station passengers are passing through will generate 3990 KW, which will electrify the station.

KILKA UWAG O KOLORYSTYCE BAZYLIKI NORBERTANEK W STRZELNIE W XIII-XIV WIEKU

The article sums up the reflections on the relics of medieval plaster and layers of paint on the walls, columns and pillars of the Norbertine nuns convent in Strzelno completed around the 2nd-3rd quarter of the 13th century. The relics of the polychromies observed by numerous enthusiasts of the Romanesque Strzelno and discovered during archaeological excavations were topped with the results of conservation-restoration works which uncovered the first figural polychromies in the chancel’s apse. Following verification of the dating of the colours of the church’s interior, an indication was made that in the 13th century, the colour red prevailed; in the 15th-16th centuries, the figural scenes of the apse sported many colours while the remaining part of the sacrum was brightened up with three-colour, geometric patterns. To complete the range of colours, floor tiles were added. Examples have been provided of specialist painting analyses. The entire arrangement has been compared with selected colourful medieval structures. References have been made to the symbolism of the colours used in the Middle Ages and thecontemporary, erroneous perception of Romanesque architecture as rustic, devoid of plaster and colours.

Optimization and Inverse Design of Floor Tile Airflow Distributions in Data Centers Using Response Surface Method

Computational fluid dynamics (CFD) has become a popular tool compared to experimental measurement for thermal management in data centers. However, it is very time-consuming and resource-intensive when used to model large-scale data centers, and often unrealistic for real-time thermal analyses. In addition, it is prohibitive to use CFD for optimization process where thousands of designs need to be generated. Floor tile airflow distribution control is a key technique for maintaining a sufficient cold air delivery to variable thermal loadings of server cabinets. Regular practice of deploying a set of identical floor tiles may not result in the best solution for airflow uniformity through tiles. In this paper, an optimization procedure based on response surface methodology (RSM) is proposed to find the best arrangement of mixed-porosity floor tiles for different targeted tile airflow distributions. Fast-approximation RSM based on radial basis function (RBF) allows thousands of designs to be generated for the optimization process which uses genetic algorithm as its main solver. The method shows proven success in maximizing floor tile airflow uniformity, and in the inverse design optimization where various tile airflow distribution topologies, i.e., linear, parabolic, and sinusoidal shapes are targeted. For the considered data center and aisle configuration, the improvement over the all-uniform-tile design is 55% in terms of standard deviation to the average tile airflow rate, whereas 90%, 91%, and 94% in root mean square error (RMSE) for the linear, parabolic, and sinusoidal floor tile airflow distribution objectives, respectively.