This paper presents a method for optimal pressure sensor placement in water distribution networks using information theory. The criterion for selecting the network nodes where to place the pressure sensors was that they provide the most useful information for locating leaks in the network. Considering that the node pressures measured by the sensors can be correlated (mutual information), a subset of sensor nodes in the network was chosen. The relevance of information was maximized, and information redundancy was minimized simultaneously. The selection of the nodes where to place the sensors was performed on datasets of pressure changes caused by multiple leak scenarios, which were synthetically generated by simulation using the EPANET software application. In order to select the optimal subset of nodes, the candidate nodes were ranked using a heuristic algorithm with quadratic computational cost, which made it time-efficient compared to other sensor placement algorithms. The sensor placement algorithm was implemented in MATLAB and tested on the Hanoi network. It was verified by exhaustive analysis that the selected nodes were the best combination to place the sensors and detect leaks.

Microalgal biomass has the capacity to accumulate relatively large quantities of triacylglycerides (TAG) for the conversion of methyl esters of fatty acids (FAME) which has made microalgae a desirable alternative for the production of biofuels. In the present work Verrucodesmus verrucosus was evaluated under autotrophic growth conditions as a suitable source of oil for biodiesel production. For this purpose BG11 media were evaluated in three different light:dark photoperiods (L:D; 16:08; 12:12; 24:0) and light intensities (1000, 2000 and 3000 Lux) in a photobioreactor with a capacity of three liters; the evaluation of the microalgal biomass was carried out through the cell count with the use of the Neubauer chamber followed by the evaluation of the kinetic growth parameters. So, the lipid accumulation was determined through the lipid extraction with a Soxhlet system. Finally, the fatty acid profile of the total pooled lipids was determined using gas chromatography-mass spectroscopy (GC-MS). The results demonstrate that the best conditions are a photoperiod of 12 light hours and 12 dark hours with BG11 medium in a 3 L tubular photobioreactor with 0.3% CO₂, 25 °C and 2000 Lux, allowing a lipid accumulation of 50.42%. Palmitic acid is identified as the most abundant fatty acid at 44.90%.

Nowadays, reducing energy consumption is the fastest way to reduce the use of fossil fuels and, therefore, greenhouse gas emissions. Heating, Ventilation, and Air Conditioning (HVAC) systems are used to maintain an indoor environment in comfortable conditions for its occupants. The combination of these two factors, energy efficiency and comfort, is a considerable challenge for building operations. This paper introduces a design approach to control an HVAC, focused on an energy consumption reduction in the operation of the HVAC system of a building. The architecture was developed using a Raspberry Pi as a coordinator node and wireless connection with sensor nodes for environmental variables and electrical measurement nodes. The data received by the coordinator node is sent to the cloud for storage and further processing. The control system manages the setpoint of the HVAC equipment, as well as the turning on and off the HVAC compressor using an XBee-based solid state relay. The HVAC temperature control system is based on the Predicted Mean Vote (PMV) index calculation, which is used by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) to find the appropriate setpoint to meet the thermal comfort of 80% of users. This method combines the values of humidity and temperature to define comfort zones. The coordinator node makes the compressor control decisions depending on the value obtained in the PMV index. The proposed PMV-based temperature control system for the HVAC equipment achieves energy savings ranging from 33% to 44% against the built-in control of the HVAC equipment, when operating with the same setpoint of 26.5 grades centigrade.

This work presents the modeling and simulation of a hydraulic network with four nodes and two branches that form a two-level water distribution system. It also proposes a distribution of hydraulic valves that allows emulating a leak using a valve and different network configurations, e.g., simple ducts, closed networks and branched networks. The network is modeled in the steady state considering turbulent flow. Numerical experiments are performed, and the results show that the proposed network is useful for the design of leakage diagnosis and control algorithms in different configurations and leakage scenarios.