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Modeling, simulation, and prediction of global energy indices remain veritable tools for econometric, engineering, analysis, and prediction of energy indices. Thus, this paper differentially modeled, simulated, and non-differentially predicated the global energy indices. The state-of-the-art of the research includes normalization of energy indices, generation of differential rate terms, and regression of rate terms against energy indices to generate coefficients and unexplained terms. On imposition of initial conditions, the solution to the system of linear differential equations was realized in a Matlab environment. There was a strong agreement between the simulated and the field data. The exact solutions are ideal for interpolative prediction of historic data. Furthermore, the simulated data were upgraded for extrapolative prediction of energy indices by introducing an innovative model, which is the synergy of deflated and inflated prediction factors. The innovative model yielded a trendy prediction data for energy consumption, gross domestic product, carbon dioxide emission and human development index. However, the oil price was untrendy, which could be attributed to odd circumstances. Moreover, the sensitivity of the differential rate terms was instrumental in discovering the overwhelming effect of independent indices on the dependent index. Clearly, this paper has accomplished interpolative and extrapolative prediction of energy indices and equally recommends for further investigation of the untrendy nature of oil price.

A comparative computational fluid dynamics (CFD) study was conducted on the three different types of pressurized water reactor (PWR) upper plenum, named TYPE 1 (support columns (SCs) and control rod guide tubes (CRGTs) with two large windows), TYPE 2 (SCs and CRGTs without windows), and TYPE 3 (two parallel perforated barrel shells and CRGTs). First, three types of upper plenum geometry information were collected, simplified, and adopted into the BORA facility, which is a 1/5 scale system of the four-loop PWR reactor. Then, the geometry, including the upper half core, upper plenum region, and hot legs, was built using the platform. After that, an unsteady calculation to simulate the reactor balance operation at hot full power scenario was performed. Finally, the differences of flowrate distribution at the core outlet and temperature distribution and transverse velocity inside the hot legs with different upper plenum internals were compared. The results suggest that TYPE 1 upper plenum internals cause the largest flowrate difference at the core outlet while TYPE 3 leads to the most even distributed flowrate. The distribution and evolution pattern of the tangential velocity inside hot legs is highly dependent on the upper plenum internals. Two counter-rotating swirls exist inside the TYPE 1 hot leg and only one swirl revolving around the hog leg axis exist inside the TYPE 2 hot leg. For TYPE 3, two swirls like that of TYPE 1 rotating around the hot leg axis significantly increase the temperature homogenization speed. This research provides meaningful guidelines for the future optimization and design of advanced PWR upper plenum internal structures.

In the last two decades, renewable energy has been paid immeasurable attention to toward the attainment of electricity requirements for domestic, industrial, and agriculture sectors. Solar forecasting plays a vital role in smooth operation, scheduling, and balancing of electricity production by standalone PV plants as well as grid interconnected solar PV plants. Numerous models and techniques have been developed in short, mid and long-term solar forecasting. This paper analyzes some of the potential solar forecasting models based on various methodologies discussed in literature, by mainly focusing on investigating the influence of meteorological variables, time horizon, climatic zone, pre-processing techniques, air pollution, and sample size on the complexity and accuracy of the model. To make the paper reader-friendly, it presents all-important parameters and findings of the models revealed from different studies in a tabular mode having the year of publication, time resolution, input parameters, forecasted parameters, error metrics, and performance. The literature studied showed that ANN-based models outperform the others due to their nonlinear complex problem-solving capabilities. Their accuracy can be further improved by hybridization of the two models or by performing pre-processing on the input data. Besides, it also discusses the diverse key constituents that affect the accuracy of a model. It has been observed that the proper selection of training and testing period along with the correlated dependent variables also enhances the accuracy of the model.

In recent years, Fe-N-C catalyst is particularly attractive due to its high oxygen reduction reaction (ORR) activity and low cost for proton exchange membrane fuel cells (PEMFCs). However, the durability problems still pose challenge to the application of Fe-N-C catalyst. Although considerable work has been done to investigate the degradation mechanisms of Fe-N-C catalyst, most of them are simply focused on the active-site decay, the carbon oxidation, and the demetalation problems. In fact, the 2e pathway in the ORR process of Fe-N-C catalyst would result in the formation of H O , which is proved to be a key degradation source. In this paper, a new insight into the effect of potential on degradation of Fe-N-C catalyst was provided by quantifying the H O intermediate. In this case, stability tests were conducted by the potential-static method in O saturated 0.1 mol/L HClO . During the tests, H O was quantified by rotating ring disk electrode (RRDE). The results show that compared with the loading voltage of 0.4 V, 0.8 V, and 1.0 V, the catalysts being kept at 0.6 V exhibit a highest H O yield. It is found that it is the combined effect of electrochemical oxidation and chemical oxidation (by aggressive radicals like H O /radicals) that triggered the highest H O release rate, with the latter as the major cause.

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