Prediction of the spray scrubbers’ performance in the gaseous and particulate scrubbing processes

In this study, the spray scrubber's performance in its two classical applications, i.e. gaseous pollutants scrubbing and aerosol removing processes has been simulated by developing two proper mathematical models. The droplets dynamic behavior has been modeled in the Lagrangian framework in which the PSI-Cell model has been applied to obtain the droplets concentration in each tower increment. In order to apply the Lagrangian approach, a mathematical model has been presented for the classical pressure nozzles. One of the unique advantages of the models is their capability to predict the liquid film formation. Moreover, the droplet size distribution and especially the nozzles’ real locations have been incorporated into the models and their probable effects have been investigated. The effects of liquid film formation on both the gaseous and particulate scrubbing efficiency have been probed as well. After validation of the model by some experimental data from the literature, the effect of different parameters such as nozzle locations, nozzle jet velocity and other parameters have been explained.     

Techno-economic assessment of bioethanol production from wheat straw: a case study of Iran

Clean Technologies and Environmental Policy - A process of ethanol production from wheat straw in Iran was simulated using SuperPro Designer. Wheat is the main cereal crop in Iran. Khuzestan...     

A new approach to multi-objective optimisation method in PEM fuel cell

This paper presents an optimisation model for polymer electrolyte membrane fuel cell system based on simultaneous power maximisation and cost minimisation. The results show that, by employing appropriate relation between the objectives, the innovative design could be proposed. Genetic algorithm is applied to solve the optimisation problem. Power maximisation results reveal that at maximum amount of power (1.95 kW), unit cost of energy is $0.64. In contrast, minimisation of cost decreases unit cost of energy to $0.33. In this condition, output power is reduced approximately to 0.93 kW. To consider both optimisation problems concurrently, weighting method and Pareto set are employed. Our outcomes proposed that applying Pareto set to any optimisation problem leads to realistic decision-making. Eventually, sensitivity analysis is done on Pareto set, based on different Nafion membrane types and hydrogen cost variation.     

Interacting multiple model and sensor selection algorithms for manoeuvring target tracking in wireless sensor networks with multiplicative noise

This article addresses the problem of tracking a manoeuvring target in a wireless sensor network (WSN) consisting of distance-measuring sensor nodes. In order to cope with target manoeuvres, an interacting multiple model (IMM) filter is applied to estimate the position and velocity of the target. The distance-dependent measurement error of sensors is formulated as both additive and multiplicative noise in the observation equation. To deal with nonlinearities in the process and observation equations and also to solve the problem of multiplicative measurement noise, a new particle filter (PF)-based IMM approach is developed. Furthermore, the multiple-model posterior Cramér-Rao lower bound (PCRLB) is derived in the presence of both additive and multiplicative noise and it is used to perform a sensor selection algorithm to reduce energy consumption in WSN nodes. Simulation results show the effectiveness of the proposed IMMPF and sensor selection algorithms in target tracking.     

Improving hydrogen production via water splitting over Pt/TiO2/activated carbon nanocomposite

Mesoporous TiO₂/AC, Pt/TiO₂ and Pt/TiO₂/AC (AC = activated carbon) nanocomposites were synthesized by functionalizing the activated carbon using acid treatment and sol–gel method. Photochemical deposition method was used for Pt loading. The nano-photocatalysts were characterized using XRD, SEM, DRS, BET, FTIR, XPS, CHN and ICP methods. The hydrogen production, under UV light irradiation in an aqueous suspension containing methanol has been studied. The effect of Pt, methanol and activated carbon were investigated. The results show that the activated carbon and Pt together improve the hydrogen production via water splitting. Also methanol acts as a good hole scavenger. Mesoporous Pt/TiO₂/AC nanocomposite is the most efficient photocatalyst for hydrogen production compared to TiO₂/AC, Pt/TiO₂ and the commercial photocatalyst P25 under the same photoreaction conditions. Using Pt/TiO₂/AC, the rate of hydrogen production is 7490 μmol (h g catal.)⁻¹ that is about 75 times higher than that of the P25 photocatalyst.