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In this study, the hybrid power system of the diesel, as the main power source, and new energy, as the auxiliary energy is developed. An optimal energy management strategy was proposed for the hybrid ship, aiming to minimize consumption of the fuel. The model of the hybrid power system was established in the MATLAB/SIMULINK simulation environment. The optimal energy management strategy was verified by simulation according to the typical drive cycle of ship compared to original energy management strategy. The simulation results show that the proposed optimization can improve fuel economy while the state of charge of the battery is maintained at reasonable range.

Abstract Hybrid nanofluids are a novel class of colloidal fluids which have drawn significant attention due to potential tailoring of their thermo-physical properties for heat transfer enhancement by a combination of more than one nano-additive to meet specific requirements of an application. In the present work, ceramic copper oxide/carbon (SiO2-CuO/C) nanoparticles in 80:20 (wt%) composition were prepared by ultrasonic-assisted wet mixing technique. The hybrid nanofluid was formulated by dispersing the nanoparticles into a base fluid mixture of 60:40 (% by mass) glycerol and ethylene glycol (G/EG) using the two-steps method. The influence of nanoparticles on the augmentation of specific heat, thermal conductivity and viscosity was examined in the volume concentration range of 0.5–2.0% in the temperature range of 303.15–353.15 K. The results demonstrate that the synthesized SiO2-CuO/C hybrid nanoparticles enhanced the thermo-physical properties of the base fluid mixture which is higher than using SiO2 alone. In the case of SiO2–G/EG nanofluid, the specific heat capacity decremented by a maximum value of 5.7% whereas the thermal conductivity and viscosity incremented by 6.9% and 1.33-times as compared with G/EG at maximum volume concentration of 2.0% at a temperature of 353.15 K. Comparatively, a reinforcement of 80% SiO2 with 20% CuO/C in G/EG mixture led to thermal conductivity and viscosity enhancement by 26.9% and 1.15-times, respectively with a significant reduction of specific heat by 21.1%. New empirical correlations were proposed based on the experimental data for evaluation of thermophysical properties.

In developing economies, there is a lack of certainty in energy and environmental economic policy. In contrast, research into the interplay between population, economic growth (GDP), renewable energy, nuclear energy, fossil fuels, and greenhouse gas (GHG) emissions has received comparatively little attention. Thus, the main motive of this exploration is to analyze the influence of population, economic growth, and various energy sources consumption on the selected South Asian economy's GHG emissions using the STIRPAT model. The period 1972–2021 is used to estimate results by considering cross-sectional dependence (CSD) and slope homogeneity (SH) tests, as well as second-generation unit root and cointegration tests. Due to the presence of SH, CSD, and mixed-order unit root problems, the cross-sectional autoregressive distributive lag (CS-ARDL) model has been used to estimate the value of selected variables. The impact of GDP and population is positive but insignificant for South Asian countries in the short run, but GDP is significant in the long run. The research also revealed that burning fossil fuels significantly contributes to atmospheric gas emissions level. In addition, renewable and nuclear energy play useful and substantial roles in reducing pollution in South Asian countries. Therefore, it is recommended that the economies of the South Asian countries maintain a uniform approach to economic policy to fully benefit from the advantages of increased green and safe energy production.

Pollen allergies are a cause of much suffering in an increasing number of individuals. Current pollen monitoring techniques are lacking due to their reliance on manual counting of pollen by human technicians. In this study, we present a neural network architecture capable of distinguishing pollen species using data from an automated particle measurement device. This study presents an improvement over the current state-of-the-art in the task of automated pollen classification using the fluorescence spectrum of aerosol particles.

In this paper an electric arc model is presented, model which depended of the desired active power of the electric arc. The model was implemented in PSCAD — EMTDC as a custom embedded component defined by the user. The components are designed, implemented and can be saved into a PSCAD library in order to be used in simulation of electric arc schemes. The performances of the model were also studied using PSCAD — EMTDC.

Due to resource constraints in wireless sensor networks (WSNs), energy consumption and networks' lifetime are considered significant challenges. Because sensors have a tiny battery and cannot be charged again. In WSN, collected data is usually transferred to the Base station (BS) directly or hop-by-hop. Therefore, load balancing and routing are one of the main issues in the WSN. This paper proposes a new routing scheme with load-balancing capability using the Markov Model (MM) and the Artificial Bee Colony (ABC) algorithm. LEACH algorithm is used to maintain load balancing between Cluster Heads (CHs). Then the Markov Model and the Artificial Bee Colony (MMABC) algorithm were used to find the best candidate nodes of each cluster to be turned into a CH. The simulation results in MATLAB software demonstrated that the proposed method surpasses the compared methods in terms of energy efficiency, number of alive nodes, and the number of delivered packets to BS and CH. European Union [861219]; Marie Curie Actions (MSCA) [861219] Funding Source: Marie Curie Actions (MSCA) This study has been conducted under the project Mobility and Training for beyond 5G ecosystems (MOTOR5G)'. The project has received funding from the European Union's Horizon 2020 program under the Marie Sklodowska Curie Actions (MSCA) Innovative Training Network (ITN) having grant agreement No. 861219.

The primary processing represents an important link of the process of capitalization of vegetal-origin products and, at the same time, an essential operation of the conditioning chain. Taking into account all considerations, the experts׳ attention has been drawn by the study of phenomena which influence upon the impurities separation process, aiming at a maximum reduction impurities. The paper presents the constructive-functional scheme of an gravitational separator SP-0 0 design, manufactured and testing at INMA Bucharest and the movement Eq. of gravitational separator centrifugally driven by means of non-balanced eccentric masses and also the constructive scheme of electric motovibrator, in view of its utilisation with best results for the drive of vibrating sieves of technical equipments used for impurities separation out of cereal seeds.

Abstract The natural convection heat transfer and entropy generation of Al2O3-water nanofluid, in a square cavity with inclination angle θ and the presence of a constant axial magnetic field B0 are examined in this paper. The governing equations are solved numerically by finite volume method. Also an effective parameters analysis was performed by using of the Response Surface Methodology (RSM). The effects of the Rayleigh number (103, 104, 105 and 106), Hartmann number (0, 10, 30 and 50) and also inclination angles (0°, 30°, 60° and 90°) are investigated. It is observed that the mean Nusselt number and the total entropy generation increase when the Rayleigh number increases. It is also found that, regardless of the Ha parameter, by increasing of the inclination angles, the mean Nusselt number and entropy generation rate increase until inclination angle 30° and then they decrease. Also, for low Ra numbers, by increasing the Ha parameter, the mean Nusselt number increases until Ha = 10 and then decreases. The analysis showed that the sensitivity of the Nusselt number and the entropy generation to Ha parameter was too small, and as a result it was negligible. Also, the sensitivity of the mean Nusselt number and the entropy generation to inclination angle, θ, increases by increasing of this angle. It is also observed that the mean Nusselt number and the entropy generation were more sensitive to the inclination angle θ than the Ha parameter.

Abstract A new strategy based on a real-time switching of the fueling regulators’ inputs is proposed in this paper to achieve better fuel saving for the fuel cell systems. The performance of the proposed strategy is compared with two basic strategies that operate in full loading range. In fact, by splitting the operating range in two ranges, where each basic strategy operates best, the proposed strategy mixes the benefits of these two strategies. The switching threshold between the loading ranges is optimally set using the sensitivity analysis. The fuel savings for all strategies analyzed in this study are compared to those obtained using the static feed-forward strategy for fueling regulators. The load-following mode for fueling regulators is implemented based on switching rule of the basic strategies, comparing the load demand with the aforementioned switching threshold. The load-based control provides huge advantages regarding battery size and operation in charge-sustained mode (which increases its lifetime). The best fuel saving can be obtained in real-time based on search flexibility on the optimization surface (with two variables). Compared with the best basic strategy, the fuel saving is 1.63 and 2.07 – times higher for a pulsed load and stair load, respectively. Also, compared with the total fuel consumption of the static feed-forward strategy, the fuel saving is 25.87% and 13.72% for the aforementioned load profiles. The obtained results are good and can motivate the further research in order to test and validate this strategy for fuel cell vehicles.