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This study comprehensively analyzes an integrated renewable energy system complementing offshore wind turbines (OWT) and floating solar photovoltaic (FPV) technology designed for producing electric power and green hydrogen. The research explores the technical feasibility, techno-economic performance, and optimal sizing of the system components. The system integrates OWT farms, FPV arrays, water electrolyzer, and hydrogen storage tank, to minimize the levelized cost of energy (LCOE), loss of power supply probability (LPSP), and excess energy. A novel optimization approach, Dung Beetle Optimization (DBO) algorithm, is utilized and compared with the Grey Wolf Optimizer (GWO) for performance validation. To ensure the robustness of the proposed DBO algorithm, it is thoroughly tested on two system configurations: a standalone OWT hydrogen production system and a hybrid FPV/OWT hydrogen production system. The results showed that the DBO algorithm outperforms the GWO algorithm in terms of system efficiency, cost-effectiveness, and reliability. The optimization findings reveal that the FPV/OWT hybrid system, optimized with the DBO algorithm, leads to a more cost-effective configuration, with the OWT component contributing 45.96 % of the total costs. Moreover, the optimized FPV/OWT system achieves a lower levelized cost of energy (LCOE) of 0.5797 $/kWh compared to 0.8190 $/kWh for the standalone OWT system. Furthermore, the hybrid FPV/OWT system maintains a levelized cost of hydrogen (COH) of 1.205 $/kg, making it a competitive option for large-scale hydrogen production. Conclusively, the findings demonstrate the technical feasibility and economic viability of the designated hybrid system for sustainable off-grid rural electrification and hydrogen production, offering a robust solution to meet future energy demands.

The energy-exergy and environ-economic (4E) analysis was conducted on a solar still with and without a hybrid thermal energy storage system (TESS) and a solar air heater. The proposed solar still was modified by integrating a rectangular aluminium box filled with paraffin wax and black gravel as the TESS and coupled with a solar air heater. Paraffin wax was selected due to its widespread availability and proven effectiveness in accelerating desalination, improving process uniformity, and maintaining optimal temperature levels. Throughout the experiments, meticulous data on mass loss, air velocity, and temperature were recorded for both conditions. The daily energy efficiency varies from 40.80% to 31.72%, showing a reduction rate with increased water depth. Estimates were made on the average exergy efficiency, losses, outflow, and inflow for the solar still. These were done for both setups. The analysis revealed that CO2 mitigation and credit were more favorable with the TESS. Furthermore, the Energy Payback Time (EPBT) for the hybrid heat storage-based single-slope solar still coupled with a solar air heater is 1.87 years. On the other hand, EPBT values for the hybrid heat storage single-slope solar still and the conventional single-slope solar still were 1.65 years and 0.95 years, respectively. Integrating a thermal energy storage system and solar air heater significantly improved the performance and sustainability of the solar still for desalination, making it a more efficient and environmentally friendly option for freshwater production.

Shell and tube heat exchangers (STHXs) are special systems that transfer thermal energy, and they have a significant position in numerous industries. The structure and arrangement of baffles play a vital role in boosting heat transfer rate, increasing thermo-hydraulic performance, and reducing the pumping cost. The numerical study is based on computational fluid dynamics (CFD) to run and investigate 3-D turbulent flow in the STHXs and the thermal performances of two unique combinations of baffles. The combination of double and triple flower baffles (COMB-A) and the combination of triple and novel quadruple flower baffles (COMB-B) are compared with double flower baffle (DFB) and triple flower baffle (TFB). The numerical model of STHX with segmental baffles (SGB) shows promising results while validating it with the previously published results. In the same way, the thermo-hydraulic performances of DFB-STHX, TFB-STHX, COMB-A STHX, and COMB-B STHX are evaluated and then compared. Based on numerical results, the heat transfer rate of COMB-B STHX is greater than DFB-STHX by 6.80 % and 10.76 % than the TFB-STHX. The pressure drop on the shell side for two novels STHXs i.e. COMB-A STHX and COMB-B STHX is reduced by 7.74 %, and 9.39 %, respectively, as compared to DFB-STHX. The comprehensive performance of COMB-A STHX and COMB-B STHX is better than that of the STHX with common flower baffles by 4.16 % and 8.16 % respectively. On the shell side, the fluid flow behavior in COMB-A STHX and COMB-B STHX improves the interaction between cold and hot fluids to optimize thermo-hydraulic performance.

This study involves a computational analysis to find the effectiveness of incorporating twisted tape within a twisted square duct for improving heat transfer, focusing on laminar single-phase flow. The primary goal is to study how varying the tape pitch (y) influences the hydrothermal performance of this system. The twisted square duct pitch (S) and twist ratio (H) were kept constant. The numerical analysis is performed under conditions of uniform wall temperature, and varying the pitch ratio (y/S) across values of 0.25, 0.5,0.75, 1, 1.25, 1.5 and 1.75. The obtained findings suggest that the addition of twisted tape within the twisted square duct results in a greater rate of heat exchange and pressure drop relative to the simple twisted square duct. Research reveals that despite a higher rate of heat transfer for a pitch ratio of 0.25 the increased friction factor results in less effective thermal performance compared to the cases with pitch ratios of 0.75 and 0.5. The thermal performance factor reaches its peak at 1.32, corresponding to the Reynolds number 1000 for a pitch ratio of 0.75 case. Conversely, the lowest thermal performance factor value of 0.89 is observed at the Reynolds number 500 for pitch ratio 1.25 case.

Solar stills represent a crucial technology in the quest to provide clean and accessible water, particularly in regions facing water scarcity and limited energy resources. This study investigates various solar still designs, exploring their advantages and limitations in water purification. Through an analysis of the current global landscape of solar still usage and ongoing research endeavors, this study aims to highlight the potential of solar stills and propose modifications to enhance their efficiency. The study also investigates various extensive analysis of diverse solar still designs and their performance metrics, including factors like reflectors, wick materials, absorber plates, and air velocity, this study elucidates key strategies to augment water output and energy utilization. Reflectors and pebbles, variations in wick materials, and modifications in absorber plate design have shown promising results in increasing productivity. Additionally, insights into the impact of environmental variables such as solar radiation, wind velocity, and ambient temperature on solar still performance are provided, informing the design optimization process. Through an analysis of global usage patterns and ongoing research efforts, this study highlights the untapped potential of solar stills and proposes strategies to enhance their performance. Furthermore, it suggests avenues for future research, including the integration of heat storage materials and the development of advanced modeling and control algorithms, to further enhance the performance of solar stills. Through these efforts, solar stills can emerge as a sustainable and reliable solution for water purification, contributing significantly to global efforts to combat water scarcity.

Building integrated photovoltaic thermal (BIPV/T) systems offer a highly effective means of generating clean energy for both electricity and heating purposes in residential buildings. Hence, this article introduces a new BIPV/T system to optimally minimize the energy consumption of a household residential building. The meticulous design of the proposed BIPV/T system is accomplished through MATLAB/Simulink® dynamic modeling. Performance analysis for the BIPV/T system is performed under different seasonal conditions with in-depth techno-economic analyses to estimate the expected enhancement in the thermal, electrical, and economic performance of the system. Moreover, a sensitivity analysis is conducted to explore the impact of various factors on the energetic and economic performances of the proposed BIPV/T system. More so, the two-layer feed-forward back-propagation artificial neural network modeling is developed to accurately predict the hourly solar radiation and ambient temperature for the BIPV/T. Additionally, a multi-objective optimization using the NSGA-II method is also conducted for the minimization of the total BIPV/T plant area and maximization of the total efficiency and net thermal power of the system as well as to estimate the optimized operating conditions for input variables across different seasons within the provided ranges. The sensitivity analysis revealed that higher solar flux levels lead to increased electric output power of the BIPV/T plant, but total efficiency decreases due to higher thermal losses. Moreover, the proposed NSGA-II shows a feasible method to attain a maximum net thermal power and optimal total efficiency of 5320 W and 63% with a minimal total plant area of 32.89 m2 that attained a very low deviation index from the ideal solution. The levelised cost of electricity is obtained as 0.10 $/kWh under the optimal conditions. Thus, these findings offer valuable insights into the potential of BIPV/T systems as a sustainable and efficient energy solution for residential applications.

Since performance of thermal systems may depend on fluids’ thermal conductivities being utilized as coolants, improvement of thermal efficiencies of fluids having micro-structures and involving ternary hybrid nanomaterials may be highly valued. In fact, microrotation of ternary hybrid nanofluids (THNFs) in oblique incinerator-shaped chamber may find applications in industrial processes involving polymeric solutions and lubricants where they help in reduction of drag forces and act as better cooling agent. In view of this, the present study carries out thermal and second law dissection of micropolar THNF within an oblique incinerator-shaped chamber heated from bottom emplacing a roundish heater under a fixed heat flux. The THNF comprises of Al2O3, CNT and graphene as nanoparticles. The study reveals that streamlines and isotherms undergo prominent change due to inclination of the chamber. When Raleigh number and diameter of heater amplify streamlines, microrotations, and entropy generation intensify while average Bejan number whittles down. Average heat transfer rate ameliorates by 4.54 % and 2.17 % when total volume fraction augments from 1.5 % to 3 % and 3 %–4.5 %, respectively. Heat transfer rate reduces by 1.23 %, 0.48 %, 3.33 %, 5.24 %, 2.07 %, and 1.66 % when inclination angle increases from 0° to 90° with inclination angle step 15°.

This article explores the enhancement of thermal exchange in a dissipative Triple-nanoparticle (Al2O3+CuO+Cu) hybrid fluid over a stretchable wavy cylindrical surface with slip effect, incorporating Python bvp algorithm with artificial intelligence AI analysis of numerical results. The stochastic AI analysis gives the enhanced and optimized results with predictive modeling, incorporating randomness of influencing parameters and nonlinear turbulent behavior of model. The model has significant importance and application in noise reducing and drag reduction devices or structures. Moreover, the presented geometrical structure is useful in enhancing thermal conduction characteristic. The intricate interplay of constituent nanoparticles and their effect on complex heat transfer in drag optimization devices is the main focus of this study. Mathematical Model of PDEs of this flow problem is converted into system of ODEs by similarity transformations with introducing dimensionless parameters. Numerical solutions of the emerged system are obtained by Python bvp solver algorithm and graphical solutions by Python are presented. To expedite the solution process and enhance the accuracy of prediction, advanced AI algorithm, such as neural network and machine learning technique is adopted. Numerical dataset obtained from Python is embedded for further AI analysis by using Levenberg Marquardt Feed-forward Algorithm (LMFA) with 10 computing neurons and 4 output layers representing results for 4 parametric variations.A rise in the fluid flow speed is observed with higher of value yield stress or Newtonian-behavior i.e. of Casson parameter a1 and stretching parameter λ for the sheet, but shows a decline with enhancing turbulence s2. Temperature profile show a descending behavior with inclination of Eckert ratio Ec, and Prandtl ratio of momentum-thermal diffusivity.

The recent study concentrates on magnetohydrodynamics (MHD). Williamson fluid drifts over an exponentially extending sheet. The porous medium is also crucial to improving thermal efficiency. The flow pattern model considers the inspirations of Joule heating, heat generation, viscous dissipation, and thermal radiation. This study also comprises the activation energy, bio-convectional, and gyrotactic microorganism phenomena. Furthermore, the Brownian and thermophoresis effects of nanoparticles are taken into consideration. Using proper similarity transformation, PDEs of the impetus, temperature, concentricity, motility microbe density, and boundary constraints upgrade into a non-linearly ordinary differential equations (ODEs) mode. Using MATLAB, transformed non-dimensional ODEs are dealt with using shooting procedures and results of significant physical strictures using a built-in bvp4c solver. Finally, it is elaborated and briefly explored numerically and visually can find interesting physical strictures versus the velocity gradient, temperature gradient, solutal gradient of species, and microbes' gradient. Incorporating microorganisms and nanoparticles into Williamson fluids can create novel materials with tailored properties for diverse applications. However, it's crucial to consider stability, biocompatibility, and environmental impact when designing these advanced fluid systems.

The study of natural convection and heat transfer in a trapezoidal cavity finds a wide range of technological applications including thermal energy storage systems, building ventilation/insulation, waste heat recovery, electronic device cooling, controlling PV panel temperature, energy conservation, exchangers, nuclear reactors, furnaces, glass production, food processing, and drying technologies. The purpose of the current study is to explore the entropy and natural convection of non-Newtonian nano-encapsulated phase change material (NEPCM) suspension in a saturated porous medium enshrouded in a trapezoid-shaped domain with three heated blocks fitted with the bottom surface. The novelty of the present work is the introduction of power-law (Ostwald-de Waele) model subject to NEPCM suspension in trapezoidal enclosure emplacing three heated fins at its bottom surface embedded in Brinkman-Forchheimer extended Darcy medium with variant porosity. The finite element method is implemented to solve the governing equations numerically. The important findings of the present study include streamlines, isotherms, velocities, and apparent viscosity enhance while entropy generation whittles down with rise in Darcy number. Entropy generation ameliorates by 519.16 % for low to high porosity of Brinkman-Forchheimer extended Darcy medium. The maximum apparent viscosity augments by 1441.24 % when power law index ameliorates.

Tianjin, as one of the pioneering and most prominent cities in China, has a long history of harnessing geothermal energy. The geothermal resource available in Tianjin is primarily characterized as a low- to medium-temperature hydrothermal geothermal resource. This manuscript introduces the ongoing status and potential of geothermal utilization in China, with a particular focus on the characteristics and utilization status of geothermal resources in Tianjin, China. Moreover, the relevant strategies and challenges for cost-efficient sustainable utilization of Tianjin geothermal resources are identified. The formation parameters of heat storage characteristics of Tianjin geothermal resources are also discussed. In addition, the key paths, guidelines and challenges on how to solve the obstacles related to the geothermal resources development in Tianjin are also suggested. The summarized results indicate that the geothermal reservoirs exploited in Tianjin vary greatly, which include sandstone of Neogene Minghuazhen formation, Guantao formation, Ordovician and Cambrian and carbonate of Proterozoic Wumishan formation. Most of the exploitative geothermal resources (146 geothermal wells) in Tianjin have mainly been produced from the Wumishan formation of the Jixian system and the Guantao formation of the Neogene system. The current production capacity has been doubled, and a two-stage cascade utilization system has been established, incorporating geothermal power generation and geothermal heating. The geothermal utilization share in Tianjin is estimated to be 81.66% for heating, 16.6% for domestic hot water and 1.35% for bathing. In conclusion, notwithstanding the diversity of geothermal resources in Tianjin, it is difficult to guarantee the sustainable development and utilization of geothermal resources in Tianjin due to the unreasonable layout of geothermal wells, imbalance of production and reinjection. Hence, the integration of distributed temperature sensing and distributed strain sensing monitoring demonstrates significant promise and effectiveness in tracking water circulation and detecting flow localization problems as dynamic monitoring processes and smart thermal response tests should be recommended and established as a substantial feature required in the future utilization and development of geothermal resources in Tianjin.

The present work deals with thermal aspect and entropy of ternary hybrid nanofluid (Graphene, Al2O3, and MWCNT as nanoparticles and water as base fluid) inside an inclined domain considering heat generation/absorption. The domain possesses triangle-shaped corrugated walls with variable height and a semi-circular heater located on its bottom wall. Finite element method (FEM) is employed to acquire a well-defined solution of the non-dimensional governing equations along with the boundary conditions. The influence of the pertinent parameters along with their ranges (0.2≤b≤0.3), (105≤Ra≤106), (0o≤η≤90o), (−1≤Hs≤1) has been studied. Some striking outcomes of the present investigation are that streamlines and entropy generation (EnT) peter out while local Nusselt number (Nuloc) and average Bejan number (Beave) ameliorate with rise in dimensionless height of the corrugated wall (b). The absolute maximum values of vertical and horizontal velocities of ternary hybrid nanofluid enhance by 96.47 % and 29.5 %, respectively, when inclination angle (η) increases from 45o to 90o. It is visualized that Nusselt number is maximum subject to heat sink while it attains a minimum value in response to heat source. Because of triangle shaped corrugated walls and ternary hybrid nanofluid, the present problem contributes superior cooling in thermal systems featured with such complex geometry in industries.

Incorporating distributed renewable energy sources into heating, power, and cooling systems is facilitating the drive toward intelligent building energy solutions. However, the inherent uncertainties associated with controllable renewable resources pose challenges for the thermo-economic scheduling of smart buildings. Nonetheless, the flexibility inherent in smart buildings can be leveraged through various market mechanisms. Hence, this research introduces a sustainable energy-building system driven by an autonomous solar/dish Stirling engine (SDSE) and wind turbine combined with a sophisticated control strategy and battery storage, which is designed to provide heat and power requirements. The proposed control strategy is also devised to optimize energy generation, ensuring prudent conservation and minimal waste, thereby amplifying overall efficiency and financial viability. The meticulous design of the system is accomplished through advanced MATLAB/Simulink® modeling. A thorough technical sensitivity analysis meticulously hones design parameters, revealing optimal operational thresholds. Simulation outcomes unveil a consistent Stirling engine (SE) efficiency, achieving a pinnacle of 35 %, while the SDSE attains over 28 %, respectively. The horizontal axis wind turbine, encompassing 100 kW and 500 kW modules, demonstrates power coefficients spanning from 0.18 to 0.09, with corresponding land area requirements ranging from 4.22 m2 to 21.10 m2, emphasizing the pivotal roles of module power and land area optimization. This paper also casts a spotlight on the environmental repercussions of the system, illustrating its potential to avert up to 30,000 kg of CO2 emissions per kWh/year. Moreover, the levelized cost of electricity ranges from 0.13 to 0.16 $/kWh, accompanied by an hourly cost that fluctuates between 3 $/h and 40 $/h, respectively. Conclusively, the developed modeling can be regarded as a significant stride in the realm of hybrid renewable energy systems, replacing the conventional photovoltaic/wind models with cutting-edge solar/wind configurations managed by a sophisticated control strategy and battery storage system.

Hydromagnetic nanoliquid establish an extraordinary category of nanoliquids that unveil both liquid and magnetic attributes. The interest in the utilization of hydromagnetic nanoliquids as a heat transporting medium stem from a likelihood of regulating its flow along with heat transportation process subjected to an externally imposed magnetic field. This analysis reports the hydromagnetic nanoliquid impact on differential type (second-grade) liquid from a convectively heated extending surface. The well-known Darcy-Forchheimer aspect capturing porosity characteristics is introduced for nonlinear analysis. Robin conditions elaborating heat-mass transportation effect are considered. In addition, Ohmic dissipation and suction/injection aspects are also a part of this research. Mathematical analysis is done by implementing the basic relations of fluid mechanics. The modeled physical problem is simplified through order analysis. The resulting systems (partial differential expressions) are rendered to the ordinary ones by utilizing the apposite variables. Convergent solutions are constructed employing homotopy algorithm. Pictorial and numeric result are addressed comprehensively to elaborate the nature of sundry parameters against physical quantities. The velocity profile is suppressed with increasing Hartmann number (magnetic parameter) whereas it is enhanced with increment in material parameter (second-grade). With the elevation in thermophoresis parameter, temperature and concentration of nanoparticles are accelerated.

This article employs an artificial neural network technique to approximate the solution for the stagnation point flow with velocity and thermal slip effects, as well as radiative heat transfer. The PDE governing system is transformed into a set of coupled ordinary differential systems by incorporating similarity variables. The shooting method is used to obtain a dataset in Mathematica. To test the precision of the suggested model, the operations of training, testing, and validation are performed, and the results are compared to a reference dataset. The Levenberg-Marquardt backpropagation neural network model is utilized to solve the system of equations under different scenarios, and its output is evaluated using mean square error, state transition dynamics, error histograms analysis, and regression illustrations. The findings indicate that the neural network approach achieves a high level of accuracy when predicting thermal analysis. Moreover, the current Artificial Neural Network model has an advantage over other numerical techniques in that it can handle more intricate mathematical models while minimizing the resources required for problem-solving.

The current research looks into magnetohydrodynamics Casson nanofluid flow and suction/injection implications for a nonlinearly stretched interface. To improve heat transport, joules of heat, radiation impacts and thermal stratification are used. A Darcy-Forchheimer porous media is used to conduct fluid flow. Chemical reactions involving energies of activation and solutal stratum are additionally considered. The Keller-box technique is used to solve the resulting non-linear set of ordinary differential equations. The impacts of a number of variables are examined employing diagrams of quantity, velocity, and heat. Increased assessments of porousness, Darcy-Forchheimer, and Casson fluid characteristics result in a decrease in velocity trends. For improved measurements of Lewis number and solutal fractionated factors, the intensity pattern reduces. The skin friction factor increases with increasing Casson parameter estimate. In the instance of the porous and nonlinear stretching parameters, the Nusselt number rises. For increasing levels of the Lewis number and Brownian motion factors, the Sherwood number drops. Furthermore, Nusselt number ratios are estimated with Prandtl numbers with regard to current information available, which shows remarkable consistency. For varied incorporated parameters, streamlines, heatlines, and masslines additionally displayed.

Purpose: The current study aims to enhance the double diffusive natural convection in an Ostwald-de Waele fluid filled in a hexagonal enclosures using non-uniform magnetic field embedded with circular obstacle. The upper wall has maximum temperature Th∗ and concentration (Ch∗) whereas the lower wall is kept at minimum temperature Tc∗ and concentration Cc∗. The parameters that play a significant role in the heat and mass transfer are evaluated, including Hartmann number, power law index, Rayleigh number and buoyancy ratio. Design/Methodology/approach: In two-dimensions, the governing formulation is written as a set of balancing equations for velocities, pressures, energies and concentrations. The nonlinear governing PDEs are solved using numerical approach based on Finite Element Method (FEM). The discretization is performed using the stable finite element pair ℘2/℘1. Code validation and results are ensured by conducting a grid convergence and comparison test respectively. Findings: The influence of flow on velocity, isotherms and iso-concentration field is examined by analyzing a broad variety of variables such as power-law index 0.7≤n≤1.2, Hartmann number 0≤Ha≤50, Rayleigh number 104≤Ra≤106, inclination angle 0°≤γ≤90° and buoyancy ratio -2≤N≤2. The findings are displayed graphically, including the flow, temperature and concentration fields. Heat and mass transfer rates are maximum for shear thinning fluids while for shear thickening fluids it reduces, whereas it is maximum for concentration dominated assistant flow and minimum for concentration dominant counter flow. Application: The novel aspects of the research include its thorough examination of solar thermal power conversion and its inventive energy deficiency devices and a wide range of electrical design applications.

Artificial neural networks (ANNs) have a wide range of applications in science and technology. Artificial neural networks (ANNs) widely utilized in image and speech recognition, neural language processing, drug discovery, genomics and bioinformatics, Robotics and control systems, material science and energy and power system. Due to the above applications, the main focus of this article is to scrutinize the impact of inclined magnetic field on a cross nanofluid flow with slip velocity and convective boundary conditions over a variable porosity. Gold (Au) nanoparticles are suspended in base liquid blood. Thermal stratification and heat generation with joule heating impact is taken in the energy equation in order to see the heat transfer. To transform the non-linear partial differential equations (PDE's) into non-linear ordinary differential equations (ODE's) utilized the von-Karman similarity transformation parameters. For the solutions of the non-linear ODE's, the 4th- order Runge-Kutta numerical method is employed. A dataset for the employed neural network back propagated Levenberg-Marquard scheme (NN-BLMS) is generated for various estimations of the embedded parameters like Weissenberg number, magnetic parameter, angle of inclination, porosity and permeability parameters, thermal stratification parameter by utilizing the 4th-order Runge-Kutta numerical scheme. The testing, validation and training methods of NN-BLMS are utilized to scrutinize the approximate solution of cross nanofluid with slip velocity and convective boundary conditions. The performance of the proposed NN-BLMS to successfully solved the cross nanofluid model is endorsed via mean squared error, error histogram and regression analysis. Streamlines and heatlines are plotted for different parameters including in velocity and temperature equations.

The current study represents a sensitivity analysis of the flow of gold nanoparticles in blood over a rotating disk with the combined impacts of viscous dissipation, nonlinear thermal radiation, joule heating, and slippage using response surface methodology. We use response surface methodology to investigate the relationships between the model's parameters (the input parameters), and the response variables. Response Surface Methodology is a useful method for finding the best values for the input parameters that improve the output. It can also help researchers create a list of experiments to predict the output. We often use response surface methodology with sensitivity analysis to see how the output depends on the input parameters and to suggest the optimal values of them. After incorporating the effects of MHD, viscous dissipation, nonlinear thermal radiation, and joule heating, the boundary layer flow equations are solved using NDSolve command of Mathematica. The influences of dimensionless parameters on all flow profiles and physical quantities are presented and discussed. The arithmetic has been considered for a specific range of values for the apparent parameters in order to calculate and analyze the physical quantities of interest for various relevant parameters, for instance 2≤M≤5, 0≤β≤2, 0.6≤A≤1.5, 0.1≤Br≤0.65, 0.5≤δ≤2, 0≤φ≤0.15, 15≤Pr≤21, 0.1≤Rd≤1.5. For sensitivity analysis, we consider skin friction coefficient and local Nusselt number for three independent input parameter namely, the radial stretching rate, the magnetic field parameter, and the thermal slip parameter. After using the statistical measures such as residual quantile – quantile plots, hypothesis testing, and adjusted R2, we concluded that our models for the skin friction coefficient and local Nusselt number are best fitted.

The carbon nanotubes (CNTs) possess unique properties due to their structural mechanism. The CNTs comprise of exceptional electrical, mechanical and thermal attributes. This paper aims to interpret the correlation of carbon nanotube nanoparticles with motile microorganisms in a rotating magnetohydrodynamic flow with respect to slip as well as convective boundary conditions. Multi-wall carbon nanotubes (MWCNTs) are incorporated as nanoparticles whereas water (H2O) as host fluid. The dimension free appearance of governing differential equations is caused by the similarity transformation. Afterward, the combination of order reduction and finite differences is used to determine the approximate solution of the problem. The consequences of problem parameters for temperature, velocity, Nusselt number and skin friction are deliberated through tables and graphs. The code efficiency is assessed by equating the results, under limiting cases, with the previous ones and found to be in an exceptional agreement. The temperature seems to be elevating with the influence of Biot number. On the other hand, a decreasing trend in the velocity profile is noticed when we increase the parametric values of rotation as well as slip parameter. The Peclet number is one of the factor that reduces the microbe's density distribution within the boundary layer regions.

The present work distinguishes the thermal attributes of zirconium oxide (ZrO2) and single wall-carbon nanotubes (SWCNTs) in a three dimensional rotating frame under the magnetic field environment. Sodium alginate (NaC6H7O6) is assumed to be the base fluid. The slippage and convective conditions on boundary have also been incorporated. The analysis comprehends, comparatively, features of both SWCNTs-NaC6H7O6 and ZrO2–NaC6H7O6 nanofluids. The amalgamation of nanomaterial SWCNTs-ZrO2 in sodium alginate builds up the thermal characteristics. An algorithmic approach deals with the approximate solutions of the problem. The numerical algorithm is mainly based on order reduction and central difference discretization. A comparison, in limiting case, appraises the proficiency of the code. The outcomes are physically and numerically interpreted via graphical and tabular representations against the prime parameters. The nano-composition of SWCNTs-ZrO2 convincingly improves and embellishes the heat transport rate. It has been revealed from the results that higher the microrotation parameter Ω0, higher will be the thermal boundary layer thickness in both cases of nanofluids such as SWCNTs/NaC6H7O6 and ZrO2/NaC6H7O6. A sensible judgment of the outcomes discloses that SWCNTs possess, comparatively, better heat transfer features than zirconium oxide.

The power that comes from renewable sources is made back faster than it is used. Infinitely renewable examples include solar and wind energy. There are many sources of clean energy all around us. Motive behind current study: A framework has now been developed throughout this research to investigate the impact of the sun's rays on novel Xue tetra hybrid magnetized cross nano-liquid as it moves through an expanding sheet inside that PV sheet of a solar module installed on top of such an offshore solar oil field. A novel Xue tetra hybrid nanofluid model has been developed and utilized to explore the impact of tetrahybrid nanoparticles on liquid flowing in order to investigate heat transport analysis. By directing the liquid's motion through a magnetic field, we may examine its velocity impact. The concentration aspect of nanofluid has been examined by including homogeneous and heterogeneous chemical processes, and indeed, the temperature accessibility of cross-nanofluid is obtained by taking into consideration effects like thermal conductivity and thermal radiation. Technique: The PDEs derived from the working prototype are then subjected to the resemblance factors, yielding the ODEs. The bvp4c scheme is used to get numerical results. The procedure is an ODE solver that belongs to the Runge-Kutta family. In order to provide precise answers in the fourth and fifth orders, it performs six function evaluations. The discrepancy between them is therefore interpreted as the solution's (fourth-order) inaccuracy. Adaptive stepsize integration techniques greatly benefit from this error estimation. Fehlberg's (RKF) integration strategy is quite similar to Cash and Carp technique. Significant finding: From obtained results, it is detected that the addition of novel tetrahybrid nanoparticles in the conventional liquid (Xue tetrahybrid nanofluid) enhances heat transfer rate and temperature profile more quickly in contrast to conventional ternary hybrid nanofluid and dihybrid nanofluid available in the existing literature. The thing which makes the present work novel and one step ahead in contrast to existing available literature is the development and implementation of a tetrahybrid nanofluid model in contrast to conventional ternary hybrid and dihybrid nanofluid models. Tetra hybridity nanoliquid generates extra heat in distinction to already existing ternary hybridity and dihybrid nanofluid models and more heat is absorbed by PV sheets in the existence of tetrahybrid nanoparticles. Conclusions: When the nanomaterials are submerged inside this liquid, their temperature increases throughout both the shear thinning and shear thickening cases. This is because the homogeneous chemical reaction mimics the migration of nanoparticles within the liquid. The increased magnetic force, in addition to an enhancement of Lorentz's force, slows down the nanofluid motion. The increased volume percentage of tetrahybrid nanoparticles, thermal radiation, and thermal conductivity boost the heat that's captured by a PV sheet, and that heat is utilized for other functions, such as drilling or navigation, on that solar offshore rig. Cost analysis: Cost analysis has also been presented in terms of Pakistan offshore oil rigs in terms of solar panels and diesel generators and it is observed that 49% cost is reduced if we replaced offshore oil rigs with solar-powered energy.

To improve heat transfer, this work provides a unique theoretical mathematical model of ternary hybrid nanofluid. In this analysis, the tri-hybrid nanoparticles TiO2, Al2O3, and AA7072 are submerged in ethylene glycol (EG), resulting in the mixture TiO2+Al2O3+AA7072/EG. The tri hybridity nanofluid is considered 3-D flowing via a rotate permeable cone embedded in Darcy-Forchheimer porousness material in the existence of fluctuating temperature generating (sink) and current radiate fluxing. The Keller box scheme (KBS) is exploited to resolve the liquid flowing and temperature equations numerically after converting them to ordinary differential equations employing similarity transformations. The results are graphed, and it is shown that the tri-hybrid nanofluid (THNF) has superior thermal conductance to the hybrid nanofluid (HNF) and that the fluid's velocity and temperature develop as a consequence of enlargement in thermal radiative fluxing and variable thermal conductivity effects. Raising values of De and Fr decline drag friction but drag friction coefficient values are improved as a result of positive variation in M, Re, ς, and λ. It is apparent that the rate of heat transference amplifies owing to magnification in QT, QE and Rd but the heat transfer rate diminishes due to magnification in Re and Fr. Incremental change in volume fraction of nanoparticles φ=0.005 to 0.03 delivers more heat in the case of tri-HNFs TiO2+Al2O3+AA7072 in contrast to ethylene glycol based TiO2+Al2O3 fluid. The optimal percentage error diminishes for the drag friction phenomenon from 1.4% up to 1.1% by adopting De from 1 to 1.5 and λ=0.5. The percentage error in terms of heat transfer rate is getting smaller from 3.6% to 3.0% because of a positive change in QT by keeping Rd=1.5.

Prandtl Eyring fluid and stretchable wedge have multiple usages in many industries. The present study aims to investigate the impact of modified Buongiorno trihybrid nanofluid on Prandtl Eyring fluid past a wedge with the addition of various influences like endothermic/exothermic reactions, thermal radiation, and thermal conductivity, Cattaneo-Christov double diffusion. Aluminium alloys (AA7072), Aluminium alloys (AA7075) and Silver (Ag) are used as nanocomponents. Prandtl Eyring fluid is employed as a conventional liquid in the preparation of nanofluids by blending nano components into the base fluid. Further, the flow model is imposed with Modified Buongiorno nanofluid. By using the similarity approach, the proposed mathematical flow model of partial differential equations (PDEs) is turned into highly nonlinear ordinary differential equations (ODEs). Throughout the whole range of material parameters, the solution for the ensuing nonlinear boundary value issue is given by employing the finite element method (FEM). The numerical results of Prandtl Eyring ternary HNF motion, thermal and solute profiles are performed through graphical amassment on the collected data and discussed in detail. The numerical significances of material sections, such as the frictional force, local Nusselt quantity, and local Sherwood number requirements, are supplied in tabular form. Further, it also presents the validation and performance characteristics of the proposed device with previously published work and found excellent accuracy. In comparison to hybrid nanoparticles, the consequences reveal that heat transmission is amplified in the case of tri-hybrid nanoparticles. The numerical consequences show that the heat transfer amount reduces in the situation of exothermic reactions parameter Ω1.

This work reported to investigate convective flow of non-Newtonian fluid effect on an exponentially stretchable surface. Effect of nanoparticle is considered in heat and mass equation. The transformation technique utilized on dimensionless equations is converted to non-dimensionless equations are solved thought numerical approach Bvp4c. Influence of approatiate analysis of velocities, heat and mass transport are scrutinized through figures. Furthermore, the comparative analysis of drag forces, Nusselt number and Sherwood number are evaluated over and done with tabulated values. It is give details that the temperature field strengthens with intensification in thermophoresis and random diffusions. Similarly, rises in thermophoresis effect parameter both temperature and concentration profile increasing.

Ethanol and biodiesel, which both belong to the first generation of biofuel technology, are the two most popular forms of biofuels now in use. In order to create next-generation biofuels using waste, cellulosic biomass, and algae-based resources, the Bioenergy Technologies Office (BETO) is working with business. The present article is designed to study the effect of tetra hybrid nanoparticles with the utilization of the novel Hamilton and Crosser model and catalytic reaction on binary fluid with the consideration of ethanol biofuel as a base fluid. Ethanol comprising tetra hybrid nanoparticles and heterogeneous catalytic reaction amplifies thermal conductivity and significantly increases brake thermal efficiency and reduces brake-specific fuel consumption in diesel engines. Therefore, the aim of this article is a theoretical checkup that is related to heat and mass transport of biofuel flow considering binary fluid accompanied with autocatalysis reaction and novel tetra hybrid nanoparticles on biofluid flow subjected to a Riga wedge. Transportation of heat via nonuniform heat source/sink, thermal radiation, and thermal conductivity are in our consideration. The mathematics of the assumed problem generates the system of non-linear partial differential equations from basic equations of momentum, energy, and mass. The usage of non-dimensional variables gave a system of non-linear ODEs with boundary conditions which are further dealt with in the Lobatto111A scheme. The results are obtained for stretching/shrinking wedge with several parameters. From obtained results, it is observed that the velocity field diminishes owing to magnification in Weissenberg number and Casson fluid parameter. The temperature field diminishes by amplifying heat generation, thermal radiation, and variable thermal conductivity parameter. Concentration distribution escalates by rising homogeneous reaction parameters.

This communication analyzes the dual convection regime of Newtonian fluid flow in a Y shaped porous enclosure with heat and mass distribution, using a mathematical model of dimensionless PDEs and an effective finite element method. The top curved wall of the enclosure is assumed hot and side walls are cold while the bottom wall is assumed adiabatic. The problem is discretized using P2 and P1 finite element methods to approximate the displacement, pressure, and velocity. The linearized system of equations is solved using Newton’s iterative scheme. The study evaluates the impact of key parameters such as the Hartmann number, Lewis number, Rayleigh number, and buoyancy ratio on the flow, heat transfer rate, and mass transfer rate. Results indicate that an increase in the Hartmann number, Rayleigh numbers and buoyancy ratio amplifies both mass and heat transfer rates. The buoyancy ratio has a noteworthy impact on the flow and transfer rates, with a greater influence seen for. The study presents graphical representations of flow and temperature fields, as well as Nusselt and Sherwood numbers provide a comprehensive visualization of the results. Heat and mass transfer rate is minimum for concentration dominated counter flow (N=−2) and maximum for concentration dominated assisting flow N=2.

The purpose of the present research is to conduct an examination of entropy generation in a 2D magneto Williamson hybrid nanofluid flow that contains cobalt ferrite and titanium oxide nanoparticles and undergoes surface-catalyzed reactions through a thin vertical needle. The consequences of joule heating and viscous dissipation are considered to elaborate the features of heat transport. Further, the influence of thermal stratification, thermal radiation, and homogeneous-heterogeneous reaction is also taken into account. Through the application of appropriate similarity variables, the dimensionless system of coupled ordinary differential equations is achieved. The coupled system of equations is numerically solved by the usage of the bvp4c technique in the MATLAB algorithm. The current investigation also compared the existing outcomes with the available literature, which shows great harmony between the two. The consequences of the physical parameters are discussed graphically and with numerical data. It is worth noting that larger values of homogeneous reaction strength and the surface-catalyzed parameter diminish the concentration field. Further, the velocity distribution and their related momentum boundary layer thickness, diminishes with the enlargement of the Weissenberg parameter.

Abstract Manufacturing waste has been quickly increasing over time as a result of the fast-rising population as well as the consumption of foods that are thrown away dishonestly, resulting in environmental contamination. As a result, it has been suggested that industrial waste disposal may be considerably reduced if it could be integrated into cement concrete manufacturing. The aim of this study is to analyze the properties of concrete employing waste glass (WG) as a binding material in proportions of 5%, 10%, 15%, 20%, 25%, and 30% by weight of cement. The fresh property was assessed using a slump cone test, while mechanical performance was assessed using flexural, compressive, splitting tensile, and pull-out strength after 7, 28, and 56 days. Furthermore, microstructure analysis was studied by scan electronic microscopic (SEM), Fourier-transform infrared spectroscopy (FTIR) and thermo-gravimetric analysis (TGA) test. The results reveal that the addition of discarded glass reduces the workability of concrete. Furthermore, mechanical performance was increased up to a 20% substitution of waste glass and then gradually declined. Waste glass can be employed as a micro filler or pozzolanic material without affecting the mechanical performance of concrete, according to microstructure research.

Due to its wide range of uses in numerous manufacturing, technological, and industrial processes, mineral oil (MO) is extremely significant. Mineral oil (MO) is used in the manufacture of PVC, polystyrene, as a lubricant and cutting fluid, thermoplastic rubber, glossing products, wood products, cleaning products, lamp oil, glues, toys, veterinary, cosmetic, food preparation, and other things. Due to the above applications, this article deals with the exact solution of unsteadiness naturally convective flowing of Maxwell nanofluid with radiation and uniform heat flux. Al2O3 nanoparticles are suspended in so-called mineral oil to make a homogeneous solution of nanofluid. The problem is demonstrated regarding coupled PDEs with initial and boundary conditions. Certain dimensionless factors are utilized to make the governing equation into a dimensionless structure. The solution for energy and momentum profiles is captured through the Laplace transform method. To predict heat transport and shear stress at the wall, the temperature and velocity gradient is also calculated. In the lack of the radiation factor, the relevant heat equation is simplified to the well-known solution in the literature. These solutions are greatly affected by the variety of different dimensionless variables like the thermal radiation parameter, volume fraction, and Grashof number. In a specific situation, the solutions relating to Newtonian fluids are retrieved, and a graphic juxtaposition of Newtonian and Maxwell fluids is displayed. Finally, the impact of pertinent parameters is shown by plotting graphs. The range of the pertinent parameters is 0.1≤λ≤0.4, Gr=5×K(K=1,2,3,4), 0.01≤χ≤0.04, Nr=5×K(K=1,2,3,4), t=1,3,5,7 while Pr=158 is fixed for mineral oil. The volume fraction declines the nanofluid's temperature while accelerating the velocity. The amplification in the Grashof number and radiation parameter improves the velocity. The increasing Maxwell fluid factor enhances the nanofluid's velocity. A decrease in the nanofluid's shear stress occurs, but after certain estimations of y, the nanofluid's shear stress goes up against the Maxwell fluid factor.

In industry, double-diffusive convection has various and important technical applications. These applications include electronic apparatus cooling, drying processes, fuel cells, geothermal engineering, and thermal storage. We provide an entropy-thermal based analysis of magnetized Boussinesq-free double-diffusive convection engendered by internal heat and concentration source block in a nanofluid-filled C-shaped inclined confined space. Findings may be interpreted and assessed in terms of the leading variables such as Lewis number (Le = 2 to 8), Hartmann number (Ha= 0 to 20), buoyancy ratio (N = 1 to 3), and Rayleigh number (Ra = 105 and 106). Besides, to determine the effective geometry and good control of the phenomenon, the investigation also covered the system geometry parameters including the position of the concentration and heat source block (h/L = 0.2 to 0.8) and the inclination angle of the enclosure (δ = 0°–90°). We state that the mass and heat transfer rates increase with Ra, N, and δ while decreasing with Ha, Le, and h/L parameters. Furthermore, when Le, Ha, N, and δ increase, overall entropy increases, whereas it decreases as the h/L parameter increases.

This study investigates the performance of a hybrid system that combined thermoelectric generators (TEG) with a solar flat plate collector system (SFPC) to turn more renewable energy into useable energy under normal operating and environmental conditions. A multi-month case study was first time conducted to explore the performance of SFPC with and without TEGs under the cold climatic conditions of Abha, Saudi Arabia. The result demonstrates that the heat losses from the rear surface of the SFPC's absorber plate were effectively utilized by TEGs, thereby decreasing overall heat losses and increasing the SFPC's overall thermal efficiency. Further, it was found that adding TEGs at the rear surface of SFPC's absorber plate improves thermal efficiency and exergy efficiency by 8.4% and 1.3%, respectively. The hybrid TEG-SPFC system can turn waste heat into useable electricity, with a peak power output of 2.2 W at midday. Maximum power was generated around midday, when the temperature differential between the upper and lower layers of TEGs was greatest. In addition, it was noticed that the thermal efficiency of the SFPC diminishes when the inlet water temperature rises. A hybrid TEG-SFPC system's exergy efficiency depends on ambient temperature variation and solar irradiance.

Abstract The knowledge of sustainable development believes that natural resources should be treated limited, and waste must be managed rationally. This idea and the constant striving to reduce production costs make the use of waste materials potential substitutes for traditionally used raw materials. In cement concrete technology, there are many possibilities to use waste materials either as cement replacement or aggregate in concrete production. The basic aim of this research work is to study the impact of wooden ash (WA) as binding material in proportions 10%, 20%, and 30% by weight of cement on high strength ductile cementitious composite concrete. The fresh property was evaluated through the slump cone test, while the mechanical property was evaluated through compressive and split tensile strength test. Load deflection curve, ductility index, and maximum and minimum crack were also studied to find flexure cracking behaviors of reinforced cement concrete (RCC) beam. The durability of high-strength ductile concrete was studied through water absorption and acid attacks test. Pozzolanic activity of wooden ash was studied through XRD analysis.

Non-Newtonian flows are a relatively recent aspect of industrial heat transfer and fluid mechanics. The development of new products, the use of conventional fluids under special conditions, the interaction of heat exchange phenomena with viscosity variations, and the search for new manufacturing processes all encourage us to evaluate industrial problems involving fluid flows that do not obey Newton's classical law. The present study deals with the modelling and the numerical simulation of natural convective flow, heat exchange, and entropy generation features within a hexagonal-shaped domain influenced by an inclined magnetic field and filled with a non-Newtonian shear-thickening fluid charged with Alumina nanoparticles. Three variant configurations of three cooling channels positioned inside the domain are considered. The equations system resulting from the mathematical modelling of the physical problem has been discretized via the finite element method. The spatial distribution of apparent viscosity was portrayed in this study. The findings represented that by growing the Power-law index from 1.2 to 1.8 as well as the magnetic field's power from 0 to 80, the mean Nusselt would descend 27.5% and 12.1%, respectively. Moreover, it was recognized that Config.2 might present the highest mean Nu among other cases examined in this research.

A recent advancement in fluid dynamics is the consideration of nanofluids which has an extraordinary thermal conductivity characteristics and upsurge heat transfer in fluids. This paper examines the heat and mass transfer properties of a steady 3D movement of a sutterby nanomaterial on a bidirectional stretching plane. Nanoparticle mass flow and convective boundary conditions are deliberated. In addition, the effect of heat generation/absorption and non-linear thermal radiation is explored. Moreover, the latest proposed model of the nanofluid has been pondered which involves controlling the nanoparticle volume element at the wall submissively relatively than dynamically. We introduced a similarity transformation to change the equations of boundary layer to a self-similar system after that processed analytically with the help of the bvp4c scheme. The outcomes of several control parameters on heat and mass transfer properties are shown among graphs then scrutinized. The systematic outputs of the Nusselt number are premeditated via tables. We observed that by increasing the estimates of the Lewis number (Le) indicates a reduction in the concentration field as well as the thickness of the equivalent boundary layer. Similarly, it is seen that the concentration field decreases rapidly according to the Brownian motion parameter as compared to the Lewis number (Le).

Solar energy is a significant, environment-friendly source of renewable energy. The solar absorber transforms solar radiation into heat energy as an effective green energy source. Therefore, increasing its absorbing capacity can improve a solar absorber’s effectiveness. This paper proposes a tungsten tantalum alloy with silicon dioxide (WTa-SiO2) ceramic layer-based solar absorber system with two different metasurfaces to enhance absorptivity and boost the solar absorber efficacy. The absorbance is also improved by adjusting the resonator thickness and material thickness, and the maximum visible light absorption is achieved by the suggested solar filter design. Moreover, Golden Eagle Optimization (GE)-based deep AlexNet algorithm is proposed for predicting the parameter variation and their effect on absorbance. The optimization technique is used to increase the effectiveness of the solar absorber by optimizing the design parameters. The features from the WTa-SiO2 design are extracted by the proposed Principal Component-Autoencoder (PC-AE) method. Experimental results show that the proposed system can effectively predict absorptivity with a reduced computational time. The proposed method demonstrates superior prediction performance with an absorption prediction efficiency of 99.8% compared to the existing methods. Thus, the proposed WTa-SiO2 metasurface-based solar absorber can be used for photovoltaic applications.

To decrease indoor relative humidity and have relaxing environments, small dehumidifiers are widely used in tropical climatic. Due to the benefits of eco-friendly, small size and silence operation, the thermoelectric dehumidifier has gained interest but has limited practical application due to poor efficiency. Therefore, this study investigates the dehumidification characteristics of the thermoelectric module powered by a photovoltaic system for the production of fresh water under real climatic conditions. The performance of a novel prototype named as the Photo-Thermoelectric Dehumidifier (PVTE-D) was investigated both numerically and experimentally in different combinations of airflow rate and input power. The results obtained from the experiment suggested that the water condensate collection was increased by increasing the input power from a PV panel to the TE-D. In the month of May, the maximum water condensate collection of 1,852.3 mL/hr was attained at the input supply of 6 A and 5 V to the PVTE-D system. In the majority of cases, when the airflow rate is below 0.013 kg/s, maximum collections of water condensate have been achieved. This study provides a detailed understanding of the optimally suitable structural parameters of the PVTE-D under different operating conditions and reveals a novel configuration for higher water condensation capacity. HIGHLIGHTS Photovoltaic powered thermoelectric dehumidification system.; Simulation and experimental study of PVTED system.; Optimum performance parameter evaluation by regulating input power and air flow rate.;

This study considers the natural convection of viscoelastic fractional-type Maxwell fluid flowing on an inclined oscillating plate with generalized equations for stress-shear and thermal flux of thickness vector. A recent and modified fractional technique, namely Prabhakar fractional derivative, is utilized for the generalized memory effect. The solution of non-dimensional and transformed governed equations is explored by integral transform. Prabhakar-like fractional-Maxwell fluid's energy and momentum profiles are compared with classical Fourier thermal flux and ordinary Maxwell fluid with generalized heat transport. To see insight into the physical behavior of the governed equations, different exceptional cases of momentum profiles are described whose physical significance is well-explained in the existing literature, and also the graphical interpretation is presented for the comparison and influence of all parameters on momentum and energy fields. As a result, we have concluded that the Prabhakar fractional operators signify the possibility of a convenient choice of different fractional constraints, which has good fitting in both experimental and theoretical data. Furthermore, the ordinary-type Maxwell fluid with Fourier thermal flux represents less velocity rate as compared to ordinary Maxwell fluid with fractional thermal flux and fractional Maxwell fluid with fractional thermal flux.

This study investigates the parametric electrical and thermal performance of a novel photovoltaic trombe wall with a venetian blind system (PVTW-VB) in a semi-arid climatic conditions. A three-dimensional computational fluid dynamics (CFD) model is developed to determine the optimal parametric configuration for the PVTW-VB and is validated using experimental data. The experimental results indicated that the CFD model could accurately predict the operational performance of the PVTW-VB system. According to the findings, the VB spacing within the air gap, the VB angle, and the PVTW air flow rate should be 0.09 m, 60°, and 0.2 m/s, respectively. Additionally, PVTW-VB is compared with PVTW without VB. The average electrical power generation and PV panel surface temperature are found to be 8.6% higher and 3.2 °C lower in case of PVTW-VB configuration, respectively. Thermal regulation studies are conducted for three different test room configurations (i.e., a normal test room, test room with PVTW and test room with PVTW-VB). The study found that PVTW-VB system reduces the thermal load of the test room.

Nanofluids have been extensively studied in recent decades and have been regarded as “next-generation heat transfer fluids” due to their superior properties. However, dispersion stability and application at higher temperatures are among the challenges that must be overcome. In this work, a new class of stable hybrid nanofluid based on multi-walled carbon nanotube (MWCNT) + cupric oxide (CuO) nanocomposite is produced with Therminol55 (TH55) as the base fluid. Nanofluids' thermophysical characteristics are investigated at varying concentrations (0.005–0.08 wt%), and they are subsequently employed as the heat transfer medium in a tube heat exchanger (HEX) for the turbulent flow regime. Thermal conductivity was significantly increased by 128.4% at the maximum nanocomposite concentration of 0.08 wt%. Despite this, nanocomposites enhanced the nanofluids' viscosity, which climbed gradually with concentration to a maximum enhancement of around 25% at 0.08 wt%. The heat transfer performance of the formulated nanofluids was numerically assessed and found to be good; for example, when compared to pure TH55, the heat transfer coefficient improved by up to 128%. The highest increase in Nu was 38.4%, while the maximum increase in pumping power was determined to be 103.88%. Furthermore, the maximum exergy efficiency was 47.84% at a 0.08 wt% concentration and a Reynolds number (Re) of 12500, which is somewhat higher than the 40.96% attained with pure TH55. The highest thermal performance factor was 1.31 for 0.08 wt %, exceeding the maximum thermal performance factors of 1.17, 1.11, 1.08, and 1.03 for 0.04, 0.02, 0.01, and 0.005 wt %, respectively. Consequently, a nanofluid made of MWCNT + CuO/TH55 might be a promising candidate for usage as a heat transfer fluid.

To meet the growing energy demand, double pipe heat exchangers (DPHEX), which are used in a variety of energy and thermal engineering applications, require improved heat transfer performance. In this study, a new class of surfactant-free Ionanofluid is formulated at three different concentrations of 0.01, 0.05 and 0.10 wt% and thermophysical and rheological properties are assessed. Zeta potential analysis is executed to assess the dispersion stability. An optimum concentration has been selected to investigate the hydrothermal performance of an insert fitted DPHEX at varying Re from 400 to 2000. The conventional twisted tape (TT) insert is modified by introducing different types of geometrical (triangular, rectangular, and circular) cuts on its surface. According to the Ionanofluid characterization, 0.10 wt % Ionanofluid has the highest thermal conductivity enhancement of 64% and heat capacity of 16.1% when compared to the base fluid, with a maximum enhancement in Nu of about 116–136% at varying Re. The rectangular-cut TT imparts highest heat transfer enhancement as the additional vortices is more intensive than other cut-inserts. Nevertheless, the value of PEC for the combination of Ionanofluid and RCTT insert, remaining between 1.61 and 1.68 over the entire range of Re, is greater than other combinations.

A significant growth in solar photovoltaic (PV) installation has observed during the last decade in standalone and grid-connected power generation systems. The solar PV system has a non-linear output characteristic because of weather intermittency, which tends to have a substantial effect on overall PV system output. Hence, to optimize the output of a PV system, different maximum power point tracking (MPPT) techniques have been used. But, the confusion lies while selecting an appropriate MPPT, as every method has its own merits and demerits. Therefore, a proper review of these techniques is essential. A “Google Scholar” survey of the last five years (2015-2020) was conducted. It has found that overall seventy-one review articles are published on different MPPT techniques; out of those seventy-one, only four are on uniform solar irradiance, seven on non-uniform and none on hybrid optimization MPPT techniques. Most of them have discussed the limited number of MPPT techniques, and none of them has discussed the online and offline under uniform and hybrid MPPT techniques under non-uniform solar irradiance conditions all together in one. Unfortunately, very few attempts have made in this regard. Therefore, a comprehensive review paper on this topic is need of time, in which almost all the well-known MPPT techniques should be encapsulated in one paper. This article focuses on classifications of online, offline, and hybrid optimization MPPT algorithms, under the uniform and non-uniform irradiance conditions. It summarizes various MPPT methods along with their mathematical expression, operating principle, and block diagram/flow charts. This research will provide a valuable pathway to researchers, energy engineers, and strategists for future research and implementation in the field of maximum power point tracking optimization.

Subjective analysis of thermal comfort of occupants relates to the recording of the level of satisfaction or dissatisfaction of occupants with regard to indoor environmental conditions on a scale which ranges from -5 to +5. This requires recruitment of subjects and matching for gender, age etc. In this study, we have tried to predict the thermal comfort of occupants by observing their real behavior inside the test room fitted with a novel thermoelectric air duct (TE-AD) cooling system rather than a conventional air conditioning system. Firstly, real experimental data were collected for more than two months from the test room equipped with the TE-AD cooling system operated at an input power supply of 6 A and 5 V. After that, the ANN model was developed based on the Levenberg-Marquardt algorithm by taking experimental parameters such as air temperature, relative humidity, globe temperature, wind speed, metabolic rate, and clothing value as model input. The ANN model is optimized by developing different models with different data points as a starting input in the training and validation process. The neuron optimization has been carried out in these models to minimize the mean square error (MSE) for the ANN model. The result shows that among the three models M1, M2, and M3, the optimum predictive mean value (PMV) was obtained from M1 at 10 neurons with MSE of 0.07956, while for predicted percentage dissatisfied (PPD), M3 gives optimum accuracy at 10 neurons with MSE value of 5.1789. The ANN model is then generalized to predict thermal comfort for one week and then for one month. Finally, all the model results were validated with the experimental data.

An important aspect in improving the energy efficiency of buildings is the effective use of building heating and cooling load prediction models. A lot of studies have been undertaken in recent years to anticipate cooling and heating loads. Choosing the most effective input parameters as well as developing a high-accuracy forecasting model are the most difficult and important aspects of prediction. The goal of this research is to create an intelligent data-driven load forecast model for residential construction heating and cooling load intensities. In this paper, the shuffled shepherd red deer optimization linked self-systematized intelligent fuzzy reasoning-based neural network (SSRD-SsIF-NN) is introduced as a novel intelligent data-driven load prediction method. To test the suggested approaches, a simulated dataset based on the climate of Dhahran, Saudi Arabia will be employed, with building system parameters as input factors and heating and cooling loads as output results for each system. The simulation of this research is executed using MATLAB software. Finally, the theoretical and experimental results demonstrate the efficacy of the presented techniques. In terms of Mean Square Error (MSE), Root Mean Square Error (RMSE), Regression (R) values, Mean Absolute Error (MAE), coefficient of determination (R2), and other metrics, their prediction performance is compared to that of other conventional methods. It shows that the proposed method has achieved the finest performance of load prediction compared with the conventional methods.

In an attempt to meet the global demand, renewable energy systems (RES) have gained an interest in it due to the availability of the resources, especially solar photovoltaic system that has been an importance since many years because of per watt cost reduction, improvement in efficiency, and abundant availability. Photovoltaic system in remote and rural areas is very useful where a grid supply is unavailable. In this scenario, power electronic converters are an integral part of the renewable energy systems particularly for electronic devices which are operated from renewable energy sources and energy storage system (fuel cell and batteries). In this article, a new topology of charge pump capacitor (CPC) which is based on high voltage gain technique DC-DC boost converter (DCBC) with dynamic modeling is proposed. To testify the efficacy of the introduced topology, a prototype has been developed in a laboratory, where input was given 10VDC and 80VDC output voltage achieved at the load side. Furthermore, the experimental result shows that the voltage stress of MOSFET switches is very less in comparison with the conventional boost converter with the same parameters as the proposed converter.

The current research focuses on formulating a new class of Therminol55-based nanofluids that incorporates an MXene/Al2O3 nanocomposite as the new class of dispersant at three different concentrations of 0.05, 0.10, and 0.20 wt%. The optical and thermophysical properties of the formulated nanofluid are assessed experimentally. Zeta potential and FTIR analyses are employed to evaluate the composite particles' surface charge and chemical stability, respectively. Thermal conductivity is observed to increase with nanoparticle loading and maximally augmented by 61.8% for 0.20 wt%, whereas dynamic viscosity increased with adding nanoparticles but remarkably dropped with increasing temperature. In addition, the prepared TH55/MXene + Al2O3 samples are thermally stable up to 200 °C according to TGA analyses. Moreover, the proposed correlations for the thermal conductivity and viscosity showed good agreement with the experimental data. The study’s findings suggest that the formulated nanofluid could be a viable contender to be used as a heat transfer fluid in the thermal sector.