Mathematical and neural network models for predicting the electrical performance of a PV/T system

There are many photovoltaic/thermal (PV/T) systems' designs that are used mainly to reduce the temperature of the PV cell by using a thermal medium to cool the photovoltaic module. In this study, a PV/T system uses nano‐phase change material (PCM) and nanofluid cooling system was adopted. Three cooling models were compared using nanofluid (SiC‐water) and nano‐PCM to improve the performance and productivity of the PV/T system. Three mathematical models were developed for linear prediction, and their results were compared with the predicted artificial neural network results, results were verified, and experimental results were appropriate. Three common evaluation criteria were adopted to compare that the results of proposed forecasting models with other models developed in many research studies are done, including the R², mean square error (MSE), and root‐mean‐square error (RMSE). Besides, different experiments were implemented using varying number of hidden layers to ensure that the proposed neural network models achieved the best results. The best neural prediction models deployed in this study resulted in good R² score of 0.81 and MSE of 0.0361 and RMSE and RMSE rate is 0.371. Mathematical models have proven their high potential to easily determine the future outcomes with the preferable circumstances for any PV/T system in a precise way to reduce the error rate to the lowest level.     

Preparation,characterization, viscosity,and thermal conductivity of nitrogen-doped graphene aqueous nanofluids

Nanofluids perform a crucial role in the development of newer technologies ideal for industrial purposes. In this study, Nitrogen-doped graphene (NDG) nanofluids, with varying concentrations of nanoparticles (0.01, 0.02, 0.04, and 0.06 wt%) were prepared using the two-step method in a 0.025 wt% Triton X-100 (as a surfactant) aqueous solution as a base. Stability, zeta potential, thermal conductivity, viscosity, specific heat, and electrical conductivity of nanofluids containing NDG particles were studied. The stability of the nanofluids was investigated by UV–vis over a time span of 6 months and concentrations remain relatively constant while the maximum relative concentration reduction was 20 %. The thermal conductivity of nanofluids was increased with the particle concentration and temperature, while the maximum enhancement was about 36.78 % for a nanoparticle loading of 0.06 wt%. These experimental results compared with some theoretical models including Maxwell and Nan’s models and observed a good agreement between Nan’s model and the experimental results. Study of the rheological properties of NDG nanofluids reveals that it followed the Newtonian behaviors, where viscosity decreased linearly with the rise of temperature. It has been observed that the specific heat of NDG nanofluid reduced gradually with the increase of concentration of nanoparticles and temperature. The electrical conductivity of the NDG nanofluids enhanced significantly due to the dispersion of NDG in the base fluid. This novel type of fluids demonstrates an outstanding potential for use as innovative heat transfer fluids in medium-temperature systems such as solar collectors.     

Effect of wettability on oil recovery and breakthrough time for immiscible gas flooding

The effect of wettability on oil recovery at higher water saturation is still not fully understood, especially in the case of mixed wettability. This study was conducted to examine the effects of wettability on oil recovery and breakthrough time through experiments for two wettability conditions (water-wet and mixed-wet) and three water saturations (20%, 40%, and 60%). Clashach sandstone core with a porosity of 12.8% and a permeability of 75 md was utilized as the porous media. Immiscible gas flooding was performed by injecting nitrogen gas into the core at room temperature and pressure. The results showed 54.3% and 48.8% of the initial oil in place (IOIP) as the ultimate oil recovery at 40% water saturation from mixed-wet core and water-wet core respectively. In contrast, the water-wet core displayed better results (32.6% of the IOIP) in terms of breakthrough time compared to the results of water-wet core (10.6% of the IOIP) at the same water saturation. In conclusion, oil recovery was found highly dependent on water saturation while breakthrough time was mainly affected by the wettability of the cores.     

Multiple access interference cancelation technique in optical CDMA systems

This paper presents a simple and efficient multiple access interference (MAI) cancelation technique in optical code division multiple access (OCDMA) system. The proposed technique is based on hybrid frequency shift keying (FSK) with an enhanced modified prime code as a signature sequence for coding techniques. Coherent FSK modulation along with incoherent demodulation using Arrayed-Waveguide Grating has been examined in the transceiver structure. In the proposed technique, a reference signal is constructed by using one of the addressed spreading sequences, and MAI cancelation is performed by subtracting the reference signal from the received signal of the desired user. The performance of the proposed FSK-OCDMA system is compared with the performance of the existing pulse position modulation (PPM)–OCDMA system. The simulation results reveal that the bit-error rate performance of the proposed technique is superior to the performance of the pulse position modulation (PPM) technique. Also, the results indicate that the proposed technique is very power efficient, and when the bit rate is constant, the network capacity can be expanded to accommodate a large number of simultaneous active users with low error rate. Moreover, the proposed technique simplifies the hardware of the receiver design.     

VAE/MPM/GA Technique for DoA Estimation Using Optimized Antenna Arrays

Many algorithms have been proposed to estimate the direction of arrival for the targets, but through using a large number of snapshots. In real time applications such as automotive radar, this is unacceptable as it causes delay and heavy processing. Instead, if only a small number of snapshots or, optimally, a single snapshot is available for DoA estimation, it will be fast and efficient. Single snapshot algorithms have a drawback as they require a large number of antenna elements, which considered a limiting factor. In this paper, a single snapshot DoA estimation technique is introduced by using optimized antenna arrays. The proposed algorithm is based on utilization of virtual array extension, matrix pencil method, and the genetic algorithm. The use of virtual array extension greatly improves the MPM performance. Furthermore, it exhibits a high DoA estimation accuracy by using a reduced number of antenna elements. The genetic algorithm is employed to determine the minimum number of antenna elements, which are required to estimate the DoAs with minimal root mean square error.

     

Two‐Dimensional Molybdenum Trioxide and Dichalcogenides

In the quest to discover the properties of planar semiconductors, two‐dimensional molybdenum trioxide and dichalcogenides have recently attracted a large amount of interest. This family, which includes molybdenum trioxide (MoO₃), disulphide (MoS₂), diselenide (MoSe₂) and ditelluride (MoTe₂), possesses many unique properties that make its compounds appealing for a wide range of applications. These properties can be thickness dependent and may be manipulated via a large number of physical and chemical processes. In this Feature Article, a comprehensive review is delivered of the fundamental properties, synthesis techniques and applications of layered and planar MoO₃, MoS₂, MoSe₂, and MoTe₂ along with their future prospects.     

Key Factors Influencing the Energy Absorption of Dual-Phase Steels: Multiscale Material Model Approach and Microstructural Optimization

Metallurgical and Materials Transactions A - The increase in use of dual-phase (DP) steel grades by vehicle manufacturers to enhance crash resistance and reduce body car weight requires the...     

Classification of image distortion based on the generalized Benford’s law

Multimedia Tools and Applications - Distortion classification is an important step in blind image quality assessment. In this paper, a new image distortion classification algorithm is presented....