Inside the Industrial Revolution 4.0, the concepts as Smart Cities and Smart Society are important parts in protection of humans against natural disasters, as strong earthquakes. Older or newer protection strategies of Civil Engineering structures (bridges, buildings) must be updated with elements of the actual technological revolution as sensors, drones, robots, nanotechnologies, AI, big data, cloud computing and so on. This paper is focused on a optimal structural active control of buildings started by many researchers during the last decades. Now, the target is to improve an optimal strategy developed by authors by proposing a more efficient use of computation. The success of this strategy leads to a faster response of computers that direct the control devices. This provides the ground for a larger range of control devices based on a larger number of sensors and, therefore, a better energy use together with a more precise anti-seismic structural protection

Civil Engineering structures are already an important part in the Smart Cities concept. In connection to this, integration of new technologies is under way in the field of Structural Engineering as in all Civil and Buildings/Bridges Engineering. One of the main goals is to protect structures from possible harm from earthquakes. In order to achieve this goal, Optimal Active Control has been proposed and used with a high degree of success. However, the application strategies are continuously improving. A strategy consisting in simplifying the Optimal Active control for full states has been proposed by the authors and relatively recently modified for an increased efficiency. That was a theoretical research taking into account the possibility to reduce the order of magnitude of matrices involved in computations. The present paper is assuming the previous theoretical result and simulates its application to the structural model of a ground floor plus ten floors building specially designed for this purpose. The reinforced concrete frame building’s behaviour is analysed under seismic actions. Efficiency and the control strategy are observed in different scenarios. The structural response is revealing that the new strategy is working faster in limiting the effects of earthquake input. In addition, the reduced computational time leads to a faster control and smaller phase-shift in practical use.

This work assesses the frictional wear of lubricated transmission chains, correlating the coefficient of friction, root mean square (RMS) acoustic emissions, and vibrations induced by friction, incorporating Industrial Internet of Things (IIoT) components. The work is divided into two phases: understanding the frictional interactions between the steel pins of commercial transmission chain and high chrome steel plate (mimicking the interaction between the pin and roller of the chain) using a reciprocating tribometer (20 N, 2.5 Hz, 15.1 stroke length) in the presence of three commercial lubricant aerosols (Grade A, Grade B, and Grade C) and analyzing the frictional wear, sound, and vibration signals generated during the tribo-tests. In the second phase, the findings from the laboratory scale are validated using a commercial transmission chain under aerosol lubrication. Results indicated that the coefficient of friction in the case of dry conditions was 41% higher than that of Grade A aerosol and Grade C aerosol and 28% higher than that of Grade B aerosol. However, the average wear scar diameter on the pin with Grade C (0.401 ± 0.129 mm) was higher than that on the pins with Grades A (0.209 ± 0.159 mm) and B (0.204 ± 0.165 mm). Grade A and Grade B aerosols exhibited similar frictional conditions, while the wear-scar diameter in Grade C was the highest among Grades A and B but still less than in dry conditions. Analyzing the sound and vibrations generated during the friction test, it can be seen that the dry condition produced approximately 60% more sound level than the Grade A and Grade B conditions, and 41% more sound than the Grade C condition. The laboratory results were validated with a real-time transmission chain using an in-house chain wear test rig. Results from the chain wear test rig indicated that the elongation of the chain with Grade B is the least amongst the aerosols and dry conditions. The surface characterizations of the steel pins also indicated intense deep grooves and surface damage in dry conditions, with Grade A exhibiting the most severe damage, followed by Grade C, and the least severe in Grade B. Additionally, dark patches were visually observed on the rollers of the lubricated commercial chains, indicating stressed areas on the rollers, while polished wear was observed on the rollers under dry conditions.