Search

Using nanofluids in thermal energy devices, such as flat-plate solar collectors, is gradually making progress, and getting awareness in the scientific community. Experiments were performed to study the effect of using CeO 2 -water on the efficiency of flat-plate solar collector by three different volume fractions of CeO 2 nanoparticles of 0.0167%, 0.0333% and 0.0666%, while the mean particle dimension was kept constant at 25 nm. An ultrasonic process was used for maintaining the stability of the CO 2 -water nanofluid. The working fluid mass flux rates were 0.015, 0.018 and 0.019 kg/s m 2 . The experiments were carried out in Budapest, Hungary on the latitude of 47°28′N and longitude of 19°03′E. Higher collector efficiency was achieved when using CeO 2 -water nanofluid compared to results achieved with water application. Based on present data, the efficiency of the collector is directly proportional with the mass flux rate and with the volume fraction in the ranges of the present study. Experiments indicate that the highest rise in efficiency of the collector at zero value of [(T i  – T a )/G T ] is 10.74%, for volume fraction ( φ ) 0.066%, and for mass flux rate of 0.019 kg/s m 2 compared to water. [ABSTRACT FROM AUTHOR]

• Modeling of CO 2 hydrogenation to hydrocarbons in a three-side reactor is developed. • Tr, Ts, Tt, θ and φ are considered as main effects in determining product yields. • Statistical analysis is performed to study the effects of variables on the yields. • Optimized operating conditions are determined to maximize olefin yields. Direct CO 2 hydrogenation to hydrocarbons is a promising method of reducing CO 2 emissions along with producing value-added products. However, reactor design and performance have remained a challenging issue because of low olefin efficiency and high water production as a by-product. Accordingly, a one-dimensional non-isothermal mathematical model is proposed to predict the membrane reactor performance and statistical analysis is used to assess the effects of important variables such as temperatures of reactor (Tr:A), shell (Ts:B) and tube (Tt:C) as well as sweep ratio (θ:D) and pressure ratio (φ:E) and their interactions on the products yields. In addition, the optimized operating conditions are also obtained to achieve maximum olefin yields. Results reveal that interacting effects comprising AB (TrTs), AC (TrTt), AE (Trφ), BC (TsTt), CE (Ttφ), CD (Ttθ) and DE (θφ) play important roles on the product yields. It is concluded that higher temperatures at low sweep and pressure ratios can maximize the yields of olefins, while simultaneously the yields of paraffins are minimized. In this regard, optimized values for Tr, Ts, Tt, θ and φ are determined as 325 °C, 306.96 °C, 325 °C, 1 and 1, respectively. [ABSTRACT FROM AUTHOR]

• Modeling of CO 2 hydrogenation to hydrocarbons in CR, AFSR and RFSR are accomplished. • Kinetic parameters are estimated via heuristic DA optimization algorithm. • Performance of the theoretical CR is compared with available experimental data. • Effect of reactor configuration is investigated in terms of conversion and selectivity. Climate change and global warming, as well as growing global demand for hydrocarbons in industrial sectors, make great incentives to investigate the utilization of CO 2 for hydrocarbons production. Therefore, finding an in-depth understanding of the CO 2 hydrogenation reactors along with simulating reactor responses to different operating conditions are of paramount importance. However, the reaction mechanisms for CO 2 hydrogenation and their corresponding kinetic parameters have been disputable yet. In this regard, considering the previously proposed Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism, which considered CO 2 hydrogenation as a combination of reverse water gas shift (RWGS) and Fischer-Tropsch (FT) reactions, and using a one-dimensional pseudo-homogeneous non-isothermal model, kinetic parameters of the rate expressions are estimated via fitting experimental and modelling data through a novel swarm intelligence optimization technique called dragonfly algorithm (DA). The predicted reactants conversion using DA algorithm are closer to the experimental data (with about 4% error) comparing to those obtained by the artificial bee colony (ABC) algorithm, and are in significant agreement with available literature data. The proposed model is used to assess the effect of reactor configuration on the performance and temperature fluctuations. Results show that axial flow spherical reactor (AFSR) and radial flow spherical reactor (RFSR) exhibiting the same surface area with that of the cylindrical reactor (CR), i.e., AFSR-2 and RFSR-2-i are the most efficient exhibiting hydrocarbons selectivity of 40.330% and 40.286% at CO 2 conversion of 53.763% and 53.891%. In addition, it is revealed that the location of the jacket has an essential role in controlling the reactor temperature. [ABSTRACT FROM AUTHOR]