Hossein Rajabnia

This study investigates pneumatic conveying of four different biomass materials, namely cottonseeds, wood pellets, wood chips, and wheat straw. The performance of a previously proposed model for predicting pressure drop is evaluated using biomass materials. Results indicate that the model can predict pressure with an error range of 30 percent. To minimize the number of trial tests required, an optimization algorithm is proposed. The findings show that with a combination of three trial tests, there is a 60 percent probability of selecting the right subset for accurately predicting pressure drop for the entire range of tests. Further investigation of different training subsets suggests that increasing the number of tests from 3 to 7 can improve the probability from 60% to 90%. Moreover, thorough analysis of all three-element subsets in the entire series of tests reveals that when considering air mass flow rate as the input, having air mass flow rates that are not only closer in value but also lower increases the likelihood of selecting the correct subset for predicting pressure drop across the entire range. This advancement can help industries to design and optimize pneumatic conveying systems more effectively, leading to significant energy savings and improved operational performance.

This study introduces a novel methodology to evaluate the behaviour of biomass material by examining the ratio of aeration and deaeration time constants. To this end, a series of tests were conducted on four different materials, namely, cottonseed, wood chips, wood pellets, and wheat straw, in order to investigate their aeration and deaeration behaviours. The study derives the aeration and deaeration pressure drop equations, and discusses the corresponding time constant expression. Subsequently, the four materials were conveyed in 12 m long batch-fed and continuous pneumatic conveying pipelines to examine their behaviour in longer pipelines. The results indicate that the aeration and deaeration time constants increased with an increase in air superficial velocity. However, the ratio of the aeration and deaeration time constants was identified as a unique number, where a value close to 1 indicates a higher likelihood of plug flow. On the basis of the results, cottonseed, with the lowest ratio of time constant, was more likely to form a stable plug flow in both batch-fed and continuous pneumatic conveying. Given the unique properties of biomass and the limited research on the pneumatic conveyance of biomass, this methodology represents a novel approach for predicting modes of flow in materials with complex properties.

Subcooled flow boiling heat transfer of water/TiO2 nanofluid in a horizontal tube is experimentally investigated. To validate the experimental apparatus as well as the experimental procedure, data for distilled water were compared with the available results on the literature in both single phase and subcooled flow boiling regime. Experimental investigations were carried out at three nanoparticles volumetric concentrations of 0.01%, 0.1%, and 5%. It was found that the nanofluid heat transfer coefficient in single-phase flow regime augments with the nanoparticle concentration. However, in the case of subcooled flow boiling regime the heat transfer coefficient decreases with the nanoparticle volume fractions.