Reversible solid oxide cells can provide efficient and cost-effective scheme for electrical-energy storage applications. However, this technology faces many challenges from material development to system-level operational parameters , which should be tackle for practical purposes. Accordingly, this study focuses on developing novel robust artificial intelligence-based blackbox models to optimize operational variables of the system. A genetic-programming algorithm is used for Pareto modeling of reversible solid oxide cells in a multi-objective fashion based on experimental input-output data. The robustness of the obtained optimal model evaluated using Monte Carlo simulations technique. An optimization study adopted to optimize the operating parameters, such as temperature and fuel composition using a differential evolution algorithm. The objective functions that have been considered for Pareto multi-objective modeling process are training error and model complexity. In addition, the discrepancy between maximum and minimum output voltage in the whole operation of the system is chosen as the optimization process objective function. The robustness of the optimal trade-off model is shown in terms of statistical indices for varied uncertainty levels from 1 to 10%. The optimized operational condition based on the suggested model reveals optimal intermediate temperature of 762 °C and fuel mixture of about 29% H 2 , 25% H 2 O, and 14% CO.
Light intensity profiles inside an open tank were studied using ANSYS Fluent. Experiments were performed by taking Scenedesmus arcuatus, green microalgae at three different concentrations under actual sunlight conditions. Absorption of light intensity at different depths was measured experimentally. The results generated from CFD simulations were compared with the experimental results and the cornet model. It has been found that there is a good agreement between the light intensity profile obtained from the CFD simulation and that calculated using the Cornet's model. Light intensity profiles at different depths were calculated using CFD simulation by varying the dimensions of the tank. The effect of wall reflectivity, diffuse fraction and scattering phase function on light profile in side open tank are also studied using CFD simulation.
A mathematical model based on one-dimensional energy and mass balance across the solar chimney has been developed. The air flow characteristics such as exit velocity and temperature are evaluated with respect to the collector inclination angle, hourly solar radiation, ambient temperature, and wind speed. The model is validated by comparing the performance parameters obtained, with the experimental results and also with the experimental data of different geometrical range and environmental conditions from the literature. An average deviation of 8% for exit air velocity and 1.35% for exit air temperature is obtained for the solar chimney with absorber inclination angle 30°, collector area 0.41 m 2 , and chimney height 0.24 m. The experimental daily average and maximum exit air velocity during the month of April are 0.5 and 0.88 m/ s, respectively. The predicted optimum operating conditions are 75°inclination angle, 0.63 m 2 absorber area, and 0.48-m chimney height. The maximum average exit air velocity and temperature numerically obtained are 0.64 m/s and 331 K, respectively, when operating with optimum conditions. It is observed that the exit air velocity increases 33% by increasing the absorber area from 0.5 to 3 m 2 for a solar chimney with 0.5 m height. An increase in exit air velocity of 52% was obtained by increasing the chimney height from 0.5 to 3 m for a solar chimney with 0.64 m 2 absorber area. A reduction in exit air velocity of 4% was observed for the increment in wind flow over the glass cover from 1.5 to 3 m/s. These results confirm that the solar chimney could be designed based on the predicted monthly performance by the present model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.