This work presents a mathematical model for the simultaneous optimisation of water and energy usage in hydraulic fracturing using a continuous time scheduling formulation. The recycling/reuse of fracturing water is achieved through the purification of flowback wastewater using thermally driven membrane distillation (MD). A detailed design model for this technology is incorporated within the water network superstructure in order to allow for the simultaneous optimisation of water, operation, capital cost, and energy used. The study also examines the feasibility of utilising the co-produced gas that is traditionally flared as a potential source of energy for MD. The application of the model results in a 22.42% reduction in freshwater consumption and 23.24% savings in the total cost of freshwater. The membrane thermal energy consumption is in the order of 244 × 10³ kJ/m³ of water, which is found to be less than the range of thermal consumption values reported for membrane distillation in... [more]

Ferroferric oxide nanoparticle (denoted as Nano-Fe₃O₄) has low toxicity and is biocompatible, with a small particle size and a relatively high surface area. It has a wide range of applications in many fields such as biology, chemistry, environmental science and medicine. Because of its superparamagnetic properties, easy modification and function, it has become an important material for addressing a number of specific tasks. For example, it includes targeted drug delivery nuclear magnetic resonance (NMR) imaging in biomedical applications and in environmental remediation of pollutants. Few articles describe the preparation and modification of Nano-Fe₃O₄ in detail. We present an evaluation of preparation methodologies, as the quality of material produced plays an important role in its successful application. For example, with modification of Nano-Fe₃O₄, the surface activation energy is reduced and good dispersion is obtained.

A model predictive control (MPC) framework, exploiting both feedforward and feedback control loops, is employed to minimize large disturbances that occur in military water networks. Military installations’ need for resilient and efficient water supplies is often challenged by large disturbances like fires, terrorist activity, troop training rotations, and large scale leaks. This work applies the effectiveness of MPC to provide predictive capability and compensate for vast geographical differences and varying phenomena time scales using computational software and actual system dimensions and parameters. The results show that large disturbances are rapidly minimized while maintaining chlorine concentration within legal limits at the point of demand and overall water usage is minimized. The control framework also ensures pumping is minimized during peak electricity hours, so costs are kept lower than simple proportional control. Thecontrol structure implemented in this work is able to sup... [more]