• Energy Research

Optimizing the design of water distribution systems often faces difficulties due to continuous variations in water demands, pressure requirements, and disinfectant concentrations. The complexity of this optimization even increases when trying to optimize both the hydraulic and the water quality design models. Most of the previous works in the literature did not investigate the linkage between both models, either by combining them into one general model or by selecting any representative solution to proceed from one model to another. This work introduces an integrated two-step framework to optimize both designs while investigating the reasonable network configuration selection from the hydraulic design view before proceeding to the water quality design. The framework is mainly based on a modified version of the multi-objective particle swarm optimization algorithm. The algorithm’s first step is optimizing the hydraulic design of the network by minimizing the system’s capital cost while maximizing the system’s reliability. The second step targets optimizing the water quality design by minimizing both the total consumed chlorine mass and the accumulated differences between actual and maximum chlorine concentrations for all the network junctions. The framework is applied to Safi Network in Yemen. Three scenarios of the water quality design are proposed based on the selected decision variables. The results show a superior performance of the first scenario, based on optimized 24-h multipliers of a chlorine pattern for a flow-paced booster station, compared to the other scenarios in terms of the diversity of final solutions.

This study develops an optimized multi-story Trombe Wall (MTW) as a hybrid passive system for heating, cooling, and PV electricity generation. Unlike previous research, which focused on single-story applications and heating efficiency, this study explores MTW performance in hot climates. The methodology includes four phases: identifying TW design parameters, selecting and validating a case study, applying a two-stage optimization, and developing predictive equations. Results show that the MTW achieves up to a 1.94 °C decrease in cooling mode, a 1.56 °C increase in heating mode, a 40% increase in thermal comfort hours, and a 31% rise in annual PV electricity generation. Finally, the developed regression models demonstrated strong predictive capability (R2 = 70.2–95.73%) for discomfort and electricity generation. The proposed MTW provides a cost-effective and sustainable solution, supporting designers and researchers in optimizing building performance.

Greenhouses with efficient controlled environment offer a promising solution for food security against the impacts of increasing global temperatures and growing water scarcity. However, current technologies used to achieve this controlled environment consume a significant amount of energy, which impacts on operational costs and CO2 emissions. Using advanced metal organic framework materials (MOFs) with superior water adsorption characteristics, this work investigates the development of a new technology for a greenhouse-controlled environment. The system consists of MOF coated heat exchanger, air to air heat exchanger, and evaporative cooler. A three-dimensional computational fluid dynamics (CFD) model was developed using COMSOL software and experimentally validated for the MOF-801/Graphene coated heat exchanger (DCHE) to determine the best cycle time and power input. It was found that using desorption time of 16 min and power input of 1.26 W, the maximum water removal rate was obtained from MOF-801/Graphene of 274.4 g/kgMOF/W.hr. In addition, an overall mathematical model for the greenhouse climate control was developed and used to investigate the effects of air humidity and velocity on the input air conditions to the greenhouse. Results showed that with high relative humidity levels of 90% in the greenhouse can be conditioned to reach the required relative humidity of 50%.