Experimental assessment and modeling of solar air heater with V shape roughness on absorber plate

A roughness of the absorber plate can improve the efficiency of a solar air heater. To boost the efficiency of triangle solar air heaters, this research presents the results of a comparison study between with and without rib roughness on absorber plates. Both use black paint with graphene nanoparticles infused into it, coating an absorber plate. Both numerical and experimental methods have been used to examine the impact of surface roughness on friction factors and heat transport properties. ANSYS 14.5 software module and RNG turbulence, k-€ model is used to conduct a three-dimensional simulation and solve the governing equations in the turbulent situation. Based on experimental data, it has been established that smooth plates are more efficient in converting heat into useful work than rough ones, on average, by a factor of 4.82 and 4.46, respectively. The length of the duct in the solar air heater mitigates the temperature gradient seen in the simulation result. The roughness of V-shaped ribs has a far larger effect on the heat transfer and friction factor properties than do variations in relative roughness pitch (P/e) and Reynolds number (Re). Experimental observations supported by modeling and simulation confirms that triangular duct absorber surface roughness provides improved outcome

Cross electromagnetic nanofluid flow examination with infinite shear rate viscosity and melting heat through Skan-Falkner wedge

This demonstration of study focalizes the melting transport and inclined magnetizing effect of cross fluid with infinite shear rate viscosity along the Skan-Falkner wedge. Transport of energy analysis is brought through the melting process and velocity distribution is numerically achieved under the influence of the inclined magnetic dipole effect. Moreover, this study brings out the numerical effect of the process of thermophoresis diffusion and Brownian motion. The infinite shear rate of viscosity model of cross fluid reveals the set of partial differential equations (PDEs). Similarity transformation of variables converts the PDEs system into nonlinear ordinary differential equations (ODEs). Furthermore, a numerical bvp4c process is imposed on these resultant ODEs for the pursuit of a numerical solution. From the debate, it is concluded that melting process cases boost the velocity of fluid and velocity ratio parameter. The augmentation of the minimum value of energy needed to activate or energize the molecules or atoms to activate the chemical reaction boosts the concentricity inclined magnetized flow, infinite shear rate viscosity, Brownian motion, 2-D cross fluid, melting process of energy, thermophoresis diffusion melting of energy.Campus Chiclay

New Robust Estimators for Handling Multicollinearity and Outliers in the Poisson Model: Methods, Simulation and Applications

The Poisson maximum likelihood (PML) is used to estimate the coefficients of the Poisson regression model (PRM). Since the resulting estimators are sensitive to outliers, different studies have provided robust Poisson regression estimators to alleviate this problem. Additionally, the PML estimator is sensitive to multicollinearity. Therefore, several biased Poisson estimators have been provided to cope with this problem, such as the Poisson ridge estimator, Poisson Liu estimator, Poisson Kibria–Lukman estimator, and Poisson modified Kibria–Lukman estimator. Despite different Poisson biased regression estimators being proposed, there has been no analysis of the robust version of these estimators to deal with the two above-mentioned problems simultaneously, except for the robust Poisson ridge regression estimator, which we have extended by proposing three new robust Poisson one-parameter regression estimators, namely, the robust Poisson Liu (RPL), the robust Poisson Kibria–Lukman (RPKL), and the robust Poisson modified Kibria–Lukman (RPMKL). Theoretical comparisons and Monte Carlo simulations were conducted to show the proposed performance compared with the other estimators. The simulation results indicated that the proposed RPL, RPKL, and RPMKL estimators outperformed the other estimators in different scenarios, in cases where both problems existed. Finally, we analyzed two real datasets to confirm the results

New Robust Estimators for Handling Multicollinearity and Outliers in the Poisson Model: Methods, Simulation and Applications

The Poisson maximum likelihood (PML) is used to estimate the coefficients of the Poisson regression model (PRM). Since the resulting estimators are sensitive to outliers, different studies have provided robust Poisson regression estimators to alleviate this problem. Additionally, the PML estimator is sensitive to multicollinearity. Therefore, several biased Poisson estimators have been provided to cope with this problem, such as the Poisson ridge estimator, Poisson Liu estimator, Poisson Kibria–Lukman estimator, and Poisson modified Kibria–Lukman estimator. Despite different Poisson biased regression estimators being proposed, there has been no analysis of the robust version of these estimators to deal with the two above-mentioned problems simultaneously, except for the robust Poisson ridge regression estimator, which we have extended by proposing three new robust Poisson one-parameter regression estimators, namely, the robust Poisson Liu (RPL), the robust Poisson Kibria–Lukman (RPKL), and the robust Poisson modified Kibria–Lukman (RPMKL). Theoretical comparisons and Monte Carlo simulations were conducted to show the proposed performance compared with the other estimators. The simulation results indicated that the proposed RPL, RPKL, and RPMKL estimators outperformed the other estimators in different scenarios, in cases where both problems existed. Finally, we analyzed two real datasets to confirm the results

Multi-Objective Optimization of an Islanded Green Energy System Utilizing Sophisticated Hybrid Metaheuristic Approach

Responding to the global call for sustainable renewable energy sources amidst growing energy demands, exhaustion of fossil fuels, and increasing greenhouse gas emissions, this study introduces a multi-objective optimization of an islanded green energy system. The focus is on the implementation of a sophisticated hybrid metaheuristic approach in a Hybrid Renewable Energy System (HRES) specifically designed for a university campus in Turkey. The developed HRES combines an array of technologies, including Photovoltaic (PV) panels, wind turbines, batteries, diesel generators, and inverters. One of the novel aspects of our work is the deployment of a rule-based Energy Management Scheme for effectively orchestrating the power flow between different system components. We employed various algorithms, namely Genetic Algorithm (GA), Firefly Algorithm (FA), Particle Swarm Optimization (PSO), and a novel hybrid of the Firefly and PSO algorithms (HFAPSO) to ensure optimal sizing of HRES. This proves critical for achieving a cost-effective system that can meet specific load demands and adhere to techno-economic indicators. Our study employed four distinct scenarios, with the optimal scenario being met through PV/Battery components. Our approach effectively addressed the high Total Gas Emissions (TGE) observed in scenarios 3 and 4, leading to uninterrupted annual load coverage with zero TGE and 100% renewable energy, akin to scenario 1. The simulation results demonstrate the supremacy of the HFAPSO algorithm in sizing HRES. This approach proved more effective than the HOMERPPro software tool, as well as the GA, FA, and PSO algorithms. In addition, a comparative analysis of the time performances of these algorithms highlighted the superior performance and convergence of HFAPSO. The application of the HFAPSO algorithm in the most efficient system configuration resulted in 2787.341 kW PV and 3153.940 kW Battery. This led to an annual system cost (ACS) of ${\$}$ 479340.57, a net present cost (NPC) of ${\$}$ 7777668.32, and an energy cost of ${\$}$ 0.2201 per kWh. The system, entirely covered by solar panels, achieved a Renewable Energy Fraction (REF) of 100%.This study highlights the potential of efficient utilization and management of renewable energy sources through multi-objective optimization. Our method provides a valuable solution for reliably meeting energy demands and minimizing the annual cost of energy systems. The optimization was programmed using the MATLAB simulation package

Measurement of Power Frequency Current including Low- and High-Order Harmonics Using a Rogowski Coil

The measurement of a power frequency current including low- and high-order harmonics is of great importance in calibration as well as in testing processes. Therefore, this paper presents the measurement of the power frequency current of light-emitting diode (LED) luminaires. LED luminaires were chosen as their input current includes both low- and high-order harmonics. The measurement process depends on reconstructing an LED luminaire current without using the coil parameters. Hence, the current reconstruction process is designed to be dependent on the measured characteristics of the Rogowski coil itself considering the frequency range at which the measurement process is required. An evaluation of the proposed measurement process was theoretically and experimentally carried out. A theoretical evaluation was carried out using MATALB SIMULINK software. However, the experimental evaluation was performed by building a Rogowski coil to measure the input currents of different LED luminaires having different power ratings of 300 W, 400 W, and 600 W. The currents measured using the Rogowski coil were compared with reference currents measured using a standard measurement technique. The obtained results show the efficacy of the proposed measurement method

A reliable numerical investigation of an SEIR model of measles disease dynamics with fuzzy criteria

Abstract The terms susceptibility, exposure, infectiousness, and recovered all have some inherent ambiguity because different population members have different susceptibility levels, exposure levels, infectiousness levels, and recovery patterns. This uncertainty becomes more pronounced when examining population subgroups characterized by distinct behaviors, cultural norms, and varying degrees of resilience across different age brackets, thereby introducing the possibility of fluctuations. There is a need for more accurate models that take into account the various levels of susceptibility, exposure, infectiousness, and recovery of the individuals. A fuzzy SEIR model of the dynamics of the measles disease is discussed in this article. The rates of disease transmission and recovery are treated as fuzzy sets. Three distinct numerical approaches, the forward Euler, fourth-order Runge-Kutta, and nonstandard finite difference (NSFD) are employed for the resolution of this fuzzy SEIR model. Next, the outcomes of the three methods are examined. The results of the simulation demonstrate that the NSFD method adeptly portrays convergent solutions across various time step sizes. Conversely, the conventional Euler and RK-4 methods only exhibit positivity and convergence solutions when handling smaller step sizes. Even when considering larger step sizes, the NSFD method maintains its consistency, showcasing its efficacy. This demonstrates the NSFD technique’s superior reliability when compared to the other two methods, while maintaining all essential aspects of a continuous dynamical system. Additionally, the results from numerical and simulation studies offer solid proof that the suggested NSFD technique is a reliable and effective tool for controlling these kinds of dynamical systems.The convergence and consistency analysis of the NSFD method are also studied

Thermal analysis of the influence of harmonics on the current capacity of medium-voltage underground power cables

Funding Information: The authors acknowledge the support grant received from the Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, Espoo, Finland. Publisher Copyright: © 2023 The Authors. Energy Science & Engineering published by Society of Chemical Industry and John Wiley & Sons Ltd.In this article, an algorithm is proposed and used to study the influence of harmonics on the behavior of medium-voltage underground cables in flat formation. The proposed algorithm is a thermal model based on the heat equilibrium of the thermal circuit nodes of the medium-voltage cable system. The impact of harmonics on the temperature rise of the cable elements and the cable capacity is evaluated in this article. Also, the impact of harmonics on the derating factors of cable for different soil types is presented. Finally, the measurement of temperatures of cable cores is carried out experimentally and compared with the calculated results to validate the proposed algorithm. One of the algorithm merits is that several harmonic percentages can be taken into account for each cable phase individually, and the heat exchange between the cable phases and their sheath is also taken into consideration. From the obtained results, it is illustrated that the presence of harmonics has a remarkable influence on the cable core temperature; mainly, harmonics of the third and fifth orders may lead to dry zone formation around the cable. It is also observed that the presence of harmonics has an important influence on the cable current, especially when it is buried in soil that has high thermal resistivity during the summer season (suction tension = ∞). In summer, the cable core temperature reached 152.162°C, 139.053°C, and 133.375°C when lime, sand, and silty sand, respectively, are used as backfill materials, rather than 90°C in the normal operating condition of the 11 kV three-phase single-core cable. It is observed also that with the increase of the soil thermal resistivity, the ratio of (Formula presented.) / (Formula presented.)) reached about 1.2 times at 2.5 K m/W soil thermal resistivity. In addition, it is also observed that the impact of harmonics leads to a percentage reduction in the derating factor of the cable center phase by 11.88%–12.37% depending on the composition of the backfill materials.Peer reviewe

Multiple-Source Single-Output Buck-Boost DC–DC Converter with Increased Reliability for Photovoltaic (PV) Applications

This paper presents an improved topology for a DC–DC converter suitable for PV applications. The proposed converter has the ability to be energized from multiple DC sources. Hence, it can be energized from two, three or a higher number of sources according to the number of modules adopted in its design. The proposed converter can supply a single load with DC power at a voltage lower or higher than the summation of all excitation DC voltages with a non-reversed voltage polarity at its output. Moreover, it provides a more reliable operation compared to other DC–DC converters due to its ability for operation with partial failures in its exciting sources. In this paper, the theoretical discussion of the proposed converter is presented considering its construction and its principle of operation. The performance of the proposed converter is theoretically evaluated using simulation based on power simulation (PSIM) software at different conditions. The performance of the converter is theoretically evaluated using PSIM considering photovoltaic (PV) sources as input sources for the proposed converter to show its validity for renewable energy applications. For more evaluation, experimental work is carried out by building a prototype and testing it at different operating conditions

Analyzing Reliability and Maintainability of Crawler Dozer BD155 Transmission Failure Using Markov Method and Total Productive Maintenance: A Novel Case Study for Improvement Productivity

Surface mining is the world’s most costly industry due to its enormous expenses. Reduced production is forcing mining companies to automate their equipment, predominantly heavy earth mining machinery (HEMMs), for example, dump trucks, shovels, and dozers. The backbone of pit mining is the crawler dozer, commonly known as a dozer. Crawler dozers are tracked earth-moving machines with metal blades positioned in front for pushing materials such as rocks, soil, etc. In order to survive the harsh competition, dozers must be durable and adequately maintained. Crawler dozers work under challenging conditions to avoid production delays that result in losses such as breakdowns, transmission failures, and other issues in mining operations. Transmission failures, among other issues with dozers, are one of the hardest to resolve. This study evaluates the reliability, availability, and maintainability (RAM) of a BD155 crawler dozer transmission using failure and repair data and the Markov method. A realistic case study on (BD155) transmission failure and associated subsystems has been performed. Potential approaches and alternatives are also identified to increase dependability and performance. This article also discusses best maintenance practices for minimizing transmission failures and boosting productivity. The availability of the BD155 increases to 71% from 62% using proper planning and maintenance