A comparison of the effect of single and multiple cavities on base flows

The paper represents a novel approach to understand the effect of single and multiple cavities on base pressure. We considered a control plate of 1 mm thick between a square nozzle of the cross-sectional area of 100 mm 2 and square duct of the cross-sectional area of 625 mm 2 . Both single and multiple cavities results are compared for a different level of expansion. The nozzle pressure ratio taken are 1.27, 1.33, 1.53 and 1.7. The high-speed compressible subsonic nozzle is being used with internal flow apparatus to achieve flows ranging between Mach 0.6 to Mach 0.9. The comparison between single and multiple cavities are shown graphically with and without control. The multiple cavities were found to be more effective as compared to a single cavity for controlling the base pressure

Neural Network-Based Prediction Model to Investigate the Influence of Temperature and Moisture on Vibration Characteristics of Skew Laminated Composite Sandwich Plates

The present study deals with the development of a prediction model to investigate the impact of temperature and moisture on the vibration response of a skew laminated composite sandwich (LCS) plate using the artificial neural network (ANN) technique. Firstly, a finite element model is generated to incorporate the hygro-elastic and thermo-elastic characteristics of the LCS plate using first-order shear deformation theory (FSDT). Graphite-epoxy composite laminates are used as the face sheets, and DYAD606 viscoelastic material is used as the core material. Non-linear strain-displacement relations are used to generate the initial stiffness matrix in order to represent the stiffness generated from the uniformly varying temperature and moisture concentrations. The mechanical stiffness matrix is derived using linear strain-displacement associations. Then the results obtained from the numerical model are used to train the ANN. About 11,520 data points were collected from the numerical analysis and were used to train the network using the Levenberg–Marquardt algorithm. The developed ANN model is used to study the influence of various process parameters on the frequency response of the system, and the outcomes are compared with the results obtained from the numerical model. Several numerical examples are presented and conferred to comprehend the influence of temperature and moisture on the LCS plates

Power system resilience and strategies for a sustainable infrastructure: A review

The increasing occurrence of severe vulnerabilities, such as natural catastrophes and man-made attacks, has resulted in a corresponding rise in power outages on a global scale. Given the growing recognition of such exceptional occurrences, there is a pressing need to examine the matters pertaining to resilience and the mitigation of risks. This study presents a comprehensive overview of the current state-of-the-art in power system resiliency, as well as an exploration of the measures required to ensure a sustainable environment.These instances of measures include resilience by enabling localized generation and distribution of electricity,diversification of energy resources, withstanding of severe weather conditions, cyberattacks and enabling communities to proactively address the consequences of power outages. There are multiple approaches to bolstering resiliency, which aim to facilitate recovery from unforeseen circumstances and promote stability in the face of uncertain events. These measures also serve to mitigate the impact of unexpected incidents such as power outages. Integrating unpredictable renewable energy sources like solar and wind power into energy networks is difficult, especially in terms of resilience. Renewable energy output fluctuates owing to weather and time of day, requiring sophisticated grid management, energy storage, and demand-response mechanisms to maintain system balance and resilience. This study elucidates the enhanced principles of power system dependability and resilience, in addition to several ways for establishing a sustainable power ecosystem. It examines the complex dynamics of risk assessment, including equipment failures, natural disasters, and human errors, to determine their likelihood and implications. Moreover, the study thoroughly examines the critical moments that occur after accidents, emphasizing the need of prompt reaction and recovery measures in reducing downtime and restoring regular operations to impacted power networks. This involves determining the fundamental reasons behind the incidents, such as whether they arise from equipment malfunctions, human mistakes, external influences like natural calamities, or cyber assaults. In addition, the report examines the efficacy of current response protocols and emergency procedures in reducing the impact of accidents and restoring regular operations to impacted electrical systems

An overview of the existing and future state of the art advancement of hybrid energy systems based on PV-solar and wind

Increasing solar and wind power use in existing power systems could create significant technical issues, especially for grids with poor connectivity or stand-alone systems needing more adequate storage capacity. This is due to the unpredictable and intermittent nature of solar and wind power. The intermittent nature of solar and wind resources can be reduced by integrating them optimally, making the entire system more reliable and cost-effective to operate. The advantages and disadvantages of hybrid wind and solar energy integration systems are discussed in this research. The impact of voltage and frequency oscillations and harmonics is amplified in weak grids, affecting both grid-connected and stand-alone systems. This may be fixed by ensuring that hybrid systems are well designed, equipped with cutting-edge quick reaction control capabilities, and optimized. This review offers an overview of existing advances in PV-solar and wind-based hybrid energy systems while exploring potential future developments. Further, this review also provides an overview of the primary studies published on optimum design considerations for compactness, topologies for power electronics, and control. As the global energy environment shifts toward sustainability and resilience, this review helps researchers, policymakers, and industry stakeholders understand, adapt, and enhance PV-solar-wind hybrid energy systems

Modeling Viscosity and Density of Ethanol-Diesel-Biodiesel Ternary Blends for Sustainable Environment

Rapid depletion in fossil fuels, inflation in petroleum prices, and rising energy demand have forced towards alternative transport fuels. Among these alternative fuels, diesel-ethanol and diesel-biodiesel blends gain the most attention due to their quality characteristics and environmentally friendly nature. The viscosity and density of these biodiesel blends are slightly higher than diesel, which is a significant barrier to the commercialization of biodiesel. In this study, the density and viscosity of 30 different ternary biodiesel blends was investigated at 15 °С and 40 °С, respectively. Different density and viscosity models were developed and tested on biodiesel blends soured from different feedstock’s including palm, coconut, soybean, mustard, and calophyllum oils. The prognostic ability and precisions of these developed models was assessed statistically using Absolute Percentage Error (APE) and Mean Absolute Percentage Error (MAPE). The MAPE of 0.045% and 0.085% for density model and 1.85%, 1.41%, 3.48% and 2.27%, 1.85%, 3.50% for viscosity models were obtained on % volume and % mass basis. These developed correlations are useful for ternary biodiesel blends where alcohols are the part of biodiesel blends. The modeled values of densities and viscosities of ternary blends were significantly comparable with the measured densities and viscosities, which are feasible to avoid the harm of vehicles’ operability

An overview of the existing and future state of the art advancement of hybrid energy systems based on PV-solar and wind

Increasing solar and wind power use in existing power systems could create significant technical issues, especially for grids with poor connectivity or stand-alone systems needing more adequate storage capacity. This is due to the unpredictable and intermittent nature of solar and wind power. The intermittent nature of solar and wind resources can be reduced by integrating them optimally, making the entire system more reliable and cost-effective to operate. The advantages and disadvantages of hybrid wind and solar energy integration systems are discussed in this research. The impact of voltage and frequency oscillations and harmonics is amplified in weak grids, affecting both grid-connected and stand-alone systems. This may be fixed by ensuring that hybrid systems are well designed, equipped with cutting-edge quick reaction control capabilities, and optimized. This review offers an overview of existing advances in PV-solar and wind-based hybrid energy systems while exploring potential future developments. Further, this review also provides an overview of the primary studies published on optimum design considerations for compactness, topologies for power electronics, and control. As the global energy environment shifts toward sustainability and resilience, this review helps researchers, policymakers, and industry stakeholders understand, adapt, and enhance PV-solar-wind hybrid energy systems

Investigation of the dielectric and thermal properties of non-edible cottonseed oil by infusing h-BN nanoparticles

Vegetable oils have emerged as insulating fluids in transformer applications and as a prominent and effective alternative for traditional dielectric fluids. However, most of vegetable oils are edible causing their application on a large scale to be limited. In the present work, a novel non-edible vegetable oil is developed as an insulating fluid. The developed oil is oxidation-inhibited cottonseed oil (CSO) based nanofluids. Tertiary butylhydroquinone was used as antioxidant. The concept of nanofluids was used to overcome the limited dielectric and thermal properties of cottonseed oil. Hexagonal Boron Nitride (h-BN) nanoparticles at low weight fractions (0.01 - 0.1 wt%) were proposed as nanofillers to achieve adequate dielectric strength and improved thermal conductivity. Stability of prepared CSO based nanofluids was analyzed using Ultraviolet-visible (UV-Vis) spectroscopy. Then, the prepared nanofluids were tested for dielectric and thermal properties under a temperature range between 45 °C and 90 °C. The dielectric properties include breakdown strengths under AC and lightning impulse voltages, dielectric constant, dissipation factor, and resistivity, while thermal properties include thermal conductivity and thermogram analysis. The dielectric and thermal properties were significantly improved in CSO based nanofluids. The creation of electric double layer at nanoparticle/oil interface and the lattice vibration of nanoparticles were used to clarify the obtained results. The proposed CSO based h-BN nanofluids open up a great opportunity in both natural ester insulating fluid applications and thermal energy management systems

Two-phase frictional pressure drop with pure refrigerants in vertical mini/micro-channels

Environmental concerns have urged a search for eco-friendly refrigerants in the refrigeration industry to overcome ozone depletion and global warming problems. Therefore, current research emphasizes frictional pressure drop during flow boiling of environment-friendly refrigerants (GWP\u3c150), isobutane, HFC-152a, HFO-1234yf were tested against commonly reported HFC-134a. The data presented here was collected under heat flux-controlled conditions; the test piece was a round tube (1.60 mm diameter). The data collection was performed at 27 and 32 °C with mass velocities in 50-500 kg/m2s range. Effects of critical controlling parameters, like heat flux, mass velocity, exit vapor quality, operating pressure and medium, were studied in detail. It was observed that pressure drop increases along with mass velocity increment in the test piece and increases with exit vapor quality increment. The same was noticed to decrease with saturation temperature increment. Parametric effects and prediction of assessment methods are reported

ANN and CFD driven research on main performance characteristics of solar chimney power plants: Impact of chimney and collector angle

Solar energy systems operate directly connected to the sun. Solar chimney power plants are privileged systems that can provide power output even in cloudy weather and during hours when there is no sun. The design and sizing of this system, which researchers focused on after its first application in the 1980s, is very effective on its performance. In this study, the collector slope and chimney slope that give maximum power output for the Manzanares pilot plant are investigated with a 3D CFD model. Simulations made using the RNG k-e turbulence model and the DO (discrete ordinates) solar ray tracing algorithm provide results that are in high compatibility with experimental data and literature. It is understood that the system provides maximum power at 0.6° collector slope and 1.5° chimney divergence angle. It is seen that the system, which gives a power output of approximately 46 kW in the reference case, exceeds the power output by 4.5 times and reaches 216.853 kW in the design that includes the collector and chimney slope. The effects of the main elements of the system on the performance are also included by changing the collector radius and chimney height while preserving these inclination angles. More than the power output in the reference case, 49.233 kW, can be achieved with the inclined design, with a collector radius of 73.2 m and a chimney height of 155.68 m. Although the effect of increasing the chimney height on power output continues after 1.2 floors, its effect decreases. In the study, it is seen that increasing the chimney height and changing the collector radius provide a greater increase in power output. Furthermore, the scope extends to the incorporation of an Artificial Neural Network (ANN) model, presenting a novel approach to predicting SCPP system performance. The findings ascertain the utilisation of 9 neurons in the hidden layer of the ANN, demonstrating a precise alignment with the study data

Waste Animal Bones as Catalysts for Biodiesel Production; A Mini Review

Slaughterhouse waste is considered to be an emerging issue because of its disposal cost. As an alternative, it would be a great prospect for the bioeconomy society to explore new usages of these leftover materials. As per food safety rules mentioned by EU legislation, all bone waste generated by slaughterhouses ought to be disposed of by rendering. The huge quantity of worldwide bone waste generation (130 billion kilograms per annum) is an environmental burden if not properly managed. The waste animal bones can be efficiently employed as a heterogeneous catalyst to produce biodiesel. This mini review summarized the recent literature reported for biodiesel generation using waste animal bones derived heterogeneous catalyst. It discusses the sources of bone waste, catalyst preparation methods, particularly calcination and its effects, and important characteristics of bones derived catalyst. It suggests that catalysts extracted from waste animal bones have suitable catalytic activity in transesterification of different oil sources to generate a good quality biodiesel