Parameter estimation and control design of solar maximum power point tracking

Parameters evaluation, design, and intelligent control of the solar photovoltaic model are presented in this work. The parameters of zeta converters such as a rating of an inductor, capacitor, and switches for a particular load are evaluated its values to compare the trade of the existing model and promoted to research in the proposed area. The zeta converter is pulsed through intelligent controller-based maximum power point tracking (intelligent-MPPT). The intelligent controller is a fuzzy logic controller (FLC) which extracts maximum power from the solar panel using the zeta converter. The performance of evaluated parameters based on the solar system and zeta converter is seen by an intelligent control algorithm. Moreover, evaluated parameters of solar photovoltaic (PV) and zeta converter can be examined the performance of fuzzy based intelligent MPPT under transient and steady-state conditions with different solar insolation. The brushless direct current motor-based water pump is used as the direct control (DC) load of the proposed model. The proposed model can enhance the research and assist to develop a new configuration of the present system

Performance Assessment of Three Latent Heat Storage Designs for a Solar Hot Water Tank

Solar hot water tanks (SHWT) based on a latent heat storage system are gaining momentum for their integration into solar heater water collectors. They can efficiently store daytime solar thermal energy and shift on-peak period loads to off-peak periods. However, their performance is generally limited by the tank configuration, the design of the thermal storage system, and the selection of the appropriate phase change material (PCM). This work presents a numerical investigation of three SHWT-PCM storage designs. A mathematical model was developed to predict the effectiveness of the geometric design and operating conditions in the SHWT-PCM system. Moreover, a sensitivity analysis was performed on the PCM type and PCM thermo-physical properties. The obtained numerical results demonstrated that the energy efficiency of the SHWT-PCM system was significantly impacted by the PCM thermo-physical properties (melting temperature, thermal conductivity, and enthalpy). In addition, it was found that using encapsulated PCM tubes with an external PCM jacket in the SHWT can result in a thermal efficiency of 70%

Parametric Analysis on the Progression of Mechanical Properties on FSW of Aluminum-Copper Plates

The contemporary work manifests that friction stir welding (FSW) is a viable avenue for joining AA1100 aluminium (Al) to C12200 copper (Cu) plates. In this present study, the response of distinctive welding parameters (viz. tool geometries, tool rotational speed, tool travel speed, and tool plunging depth) on weld quality has been investigated. The present work focused on both microstructural investigation and mechanical properties examination. It has been observed that the process parameters have significant effects on weld quality. The design of the experiments has been executed considering four welding input parameters in two variables and selected L-16 orthogonal array to limit the experimental replications. It has been observed that good quality of welds produced by keeping the tool pin offset around 4mm towards the aluminium side and 2mm towards the copper side. And it has also been noticed that right-hand threaded tool pins are giving good weld quality compared to left-handed thread. The joint efficiencies for the welds E2, E14 which were welded by RHT tools were 75.3% and 74.61% and the Strength (UTS) of the welds for the same tools exhibit’s greater than the LHT tools i.e., 98 and 95Mpa. Moderate hardness values are observed for the same welds E1 and E14 with the parameters 1100rpm, 98welding speed, and 1.6mm tool plunge depth. . It also noticed that the weld quality can be significantly enhanced by using proper tool plunge and tool pin geometries compared to the other process parameters

An Efficient Wireless Sensor Network Based on the ESP-MESH Protocol for Indoor and Outdoor Air Quality Monitoring

The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO2, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks

An Efficient Wireless Sensor Network Based on the ESP-MESH Protocol for Indoor and Outdoor Air Quality Monitoring

The main aim of this work is to establish a sensor MESH network using an ESP-MESH networking protocol with the ESP32 MCU (a Wi-Fi-enabled microcontroller) for indoor and outdoor air quality monitoring in real time. Each sensor node is deployed at a different location on the college campus and includes sensor arrays (CO2, CO, and air quality) interfaced with the ESP32. The ESP-MESH networking protocol is a low-cost, easy-to-implement, medium-range, and low-power option. ESP32 microcontrollers are inexpensive and are used to establish the ESP-MESH network that allows numerous sensor nodes spread over a large physical area to be interconnected under the same wireless network to monitor air quality parameters accurately. The data of different air quality parameters (temperature, humidity, PM2.5, gas concentrations, etc.) is taken (every 2 min) from the indoor and outdoor nodes and continuously monitored for 72 min. A custom time-division multiple-access (TDMA) scheduling scheme for energy efficiency is applied to construct an appropriate transmission schedule that reduces the end-to-end transmission time from the sensor nodes to the router. The performance of the MESH network is estimated in terms of the package loss rate (PLR), package fault rate (PFR), and rate of packet delivery (RPD). The value of the RPD is more than 97%, and the value of the PMR and PER for each active node is less than 1.8%, which is under the limit. The results show that the ESP-MESH network protocol offers a considerably good quality of service, mainly for medium-area networks

Adherence and activation of human mesenchymal stromal cells on brushite coated porous titanium

Tri-calcium-phosphate Ca3(PO4)2 is considered a promising material to improve implant and bone tissue linking. Titanium (Ti), a highly porous material, was coated with crystalline brushite using an electrochemical process so that it could be used as an implant material. The aim of this research is to get a faster ingrowth of bone-tissue inside the porous structure. The crystalline coating was characterized by the standard XRD and SEM techniques. Additionally, the phase evolution of Ca3(PO4)2-crystals with different kinds of sterilization techniques was observed. In-vitro tests on the biocompatibility of the coating were done with human mesenchymal stem cells (HMSCs). The HMSCs are the most promising cell type for regenerative medicine and tissue engineering owing to their ability to differentiate into several tissues, such as, bone, cartilage, tendon, and muscle. For the treatment of local bone defects expanded HMSCs could be loaded on Ca3(PO4)2 coated metallic matrices and delivered to the target site. A possible application is brushite-coated porous titanium as a carrier matrix. To determine whether cell functions of HMSCs are influenced by the brushite surface, HMSCs were cultured on brushite-coated and uncoated porous titanium specimens. The viability and proliferation of HMSCs were successfully analyzed. Additionally, the release of cytokines (IL-6, IL-8, IL-11) were quantified as a marker of cell activation. The viable cells could be detected on specimens after 48 h initial seeding. After 8 days cell number on both specimens increased, although the proliferation on brushite-coated titanium was decreased compared to the uncoated surfaces. The release of both, IL-8 and IL-11 increased significantly due to the cultivation of HMSCs on the coated specimens for 8 days

Plant Extract-Based Fabrication of Silver Nanoparticles and Their Effective Role in Antibacterial, Anticancer, and Water Treatment Applications

Ammi visnaga is a biennial or annual herbaceous plant belonging to the family Apiaceae. For the first time, silver nanoparticles were synthesized using an extract of this plant. Biofilms are a rich source of many pathogenic organisms and, thus, can be the genesis of various disease outbreaks. In addition, the treatment of cancer is still a critical drawback for mankind. The primary purpose of this research work was to comparatively analyze antibiofilms against Staphylococcus aureus, photocatalytic activity against Eosin Y, and in vitro anticancer activity against the HeLa cell line of silver nanoparticles and Ammi visnaga plant extract. The systematic characterization of synthesized nanoparticles was carried out using UV–Visible spectroscopy (UV-Vis), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), dynamic light scattering (DLS), zeta potential, and X-ray diffraction microscopy (XRD). The initial characterization was performed with UV-Vis spectroscopy, where a peak appeared at 435 nm, which indicated the SPR band of the silver nanoparticles. AFM and SEM were performed to determine the morphology and shape of the nanoparticles, while EDX confirmed the presence of Ag in the spectra. The crystalline character of the silver nanoparticles was concluded with XRD. The synthesized nanoparticles were then subjected to biological activities. The antibacterial activity was evaluated by determining the inhibition of the initial biofilm formation with Staphylococcus aureus using a crystal violet assay. The response of the AgNPs against cellular growth and biofilm formation was found to be dose dependent. Green-synthesized nanoparticles showed 99% inhibition against biofilm and bacteria, performed excellent anticancer assay with an IC50 concentration of 17.1 ± 0.6 µg/mL and 100% inhibition, and photodegradation of the toxic organic dye Eosin Y up to 50%. Moreover, the effect of the pH and dosage of the photocatalyst was also measured to optimize the reaction conditions and maximum photocatalytic potential. Therefore, synthesized silver nanoparticles can be used in the treatment of wastewater contaminated with toxic dyes, pathogenic biofilms, and the treatment of cancer cell lines

A Comparative Assessment of High-Throughput Quantitative Polymerase Chain Reaction versus Shotgun Metagenomic Sequencing in Sediment Resistome Profiling

Prolonged and excessive use of antibiotics has resulted in the development of antimicrobial resistance (AMR), which is considered an emerging global challenge that warrants a deeper understanding of the antibiotic-resistant gene elements (ARGEs/resistomes) involved in its rapid dissemination. Currently, advanced molecular methods such as high-throughput quantitative polymerase chain reaction (HT-qPCR) and shotgun metagenomic sequencing (SMS) are commonly applied for the surveillance and monitoring of AMR in the environment. Although both methods are considered complementary to each other, there are some appreciable differences that we wish to highlight in this communication. We compared both these approaches to map the ARGEs in the coastal sediments of Kuwait. The study area represents an excellent model as it receives recurrent emergency waste and other anthropogenic contaminants. The HT-qPCR identified about 100 ARGs, 5 integrons, and 18 MGEs (total—122). These ARGs coded for resistance against the drug classes of beta-lactams > aminoglycoside > tetracycline, macrolide lincosamide streptogramin B (MLSB) > phenicol > trimethoprim, quinolone, and sulfonamide. The SMS picked a greater number of ARGs (402), plasmid sequences (1567), and integrons (168). Based on the evidence, we feel the SMS is a better method to undertake ARG assessment to fulfil the WHO mandate of “One Health Approach.” This manuscript is a useful resource for environmental scientists involved in AMR monitoring

Machine learning enabled prediction of tribological properties of Cu-TiC-GNP nanocomposites synthesized by electric resistance sintering: A comparison with RSM

In the present study, copper matrix composites were successfully produced through the powder metallurgy route by applying the electrical resistance sintering technique. Copper composites were reinforced with 5 wt. % TiC and different concentrations of GNP (0.1, 0.2, and 0.3 wt. %). Microstructural investigations confirmed uniform dispersion of TiC and GNP micro and nanoparticles in the copper matrix. A sintering temperature of 900 °C resulted in better densification and hardness of the prepared composites. Moreover, ML models were developed to predict the sintered density, hardness, and wear loss of the composites. Further, it was found that Multi-Layer Perceptron outperforms all other ML models with R2 values of 0.975, 0.934, and 0.948 in the prediction of density, hardness, and wear loss of the composites. On the other hand, RSM shows predicted R2 values of 0.8012, 0.8507, and 0.8756