查看更多>>摘要：This current study aims to analyze the bioconvection effect of gyrotactic microorganisms in a Sutterbynanofluid flow across a slippery horizontal cylinder with the participation of Arrhenius kinetics. The modelfor bioconvection analysis includes factors such as Brownian motion, thermophoresis, magnetic field, gravitation,and chemical reaction. The Darcy-Forchheimer rule is applied to assess the porous space’s resistance.By employing the necessary similarity maps, the PDEs in their nonlinear form are converted into a systemof coupled ODEs. The converted ODEs are numerically computed by employing the Runge–Kutta-Fehlbergtechnique in combination with the shooting strategy. The impacts of significant physical factors on transportcharacteristics and engineering parameters are depicted with the dint of Mathematica software intables and figures. The study showed that enhancing the chemical reaction and activation energy factorssignificantly inflates the nanoparticles’ concentration. Moreover, it must be acknowledged that themoment profile rarefies with the Darcy number’s elevation, but higher Forchheimer number seems tohave the opposite effect. The new findings of this study have potential implications in biotechnology andautomobile industry.
查看更多>>摘要：Optimisation of indirect heaters in gas pressure-reducing stations is one of the main goals in countries withhigh natural gas reserves. This paper mainly aims to optimise the 3D-heat exchanger, considering the tubeswith rotating, Elliptical, Half -circular, Square, Rectangular, and Triangular cross sections in three differenttorsional angles. The simulation is conducted by commercial software with high accuracy with an experimentalvalidation model. The simulation result indicates that the creation of turbulence in the pipe pathat torsional cross-sections will increase fluid temperature. After comparing the six designs and selectingthe elliptical tube as the best model, the simulation continues for different torsion angles (360°, 720° and1080° angles) to further optimise the heat exchanger. Outputs illustrate that 360° twisted elliptical tube hasthe highest temperature variations with the lowest pressure drop changes by increasing the path lengthcompared to other torsions.
查看更多>>摘要：In the present investigation, a numerical study has been done to analyse the effect of attachment of brokenV-shaped ribs on the heating surface of the triangular-shaped solar air heater duct. The roughness andflow parameters include relative roughness pitch (between 8 and 14), angle of attack (between 30 and 75degrees) and Reynolds number (between 4000 and 20,000). The effect on heat transfer and flow characteristicshas been observed due to variation in parameters. Considerable enhancement in convective heattransfer is observed along with frictional effect and indicated by Nusselt number and friction factor values.All the variations resulted in an increase in the performance of a solar air heater, which was indicated bythe value of the thermohydraulic performance parameter being more than 1.
查看更多>>摘要：In practical engineering, Off-grid PV systems have failed to meet user requirements due to the absence ofprecise local weather parameters and unverified battery charging times. In this study, off-grid solar streetlights in a village in Haikou were taken as an example. A three-year monitoring period was conductedusing a local PV station. It was observed that in this area, the lowest solar radiation is typically recordedfrom December to January. Over three years, there were four instances of continuous overcast and rainyweather, with the longest period lasting up to 9 days. During these 9 days, the daily average power generationper kilowatt of PV module fluctuated between 0.46 and 0.92 kW. Based on this data, a theoreticalformula for the optimal daily power consumption was derived, and it was determined that 180W and 240Wwere the optimal power consumption levels for continuous overcast and rainy weather. The charging timefor the batteries was verified to be 4 days. Finally, practical validation was conducted using the village’ssolar street lights, confirming that the optimal power consumption during continuous overcast and rainydays was 180W, and during continuous overcast days, it was 230W. These research findings hold significantimportance.
Solomon O. GiwaSamson A. AasaRaymond T. TaziwaMohsen Sharifpur...
2262466.1-2262466.13页
查看更多>>摘要：Measurement-related problems have spurred fuel properties prediction using machine learning techniques.Improved fuel properties offered by hybrid biodiesel (HB) via mixed oils were predicted from theirfatty acid compositions (FACs) using artificial neural network (ANN). FACs and fuel properties of HB sourcedfrom the literature were used to develop ANN models. FAC data were used as the input parameters topredict the fuel properties data (kinematic viscosity (KV), density, calorific value (CV), and flash point (FP))considered as the output parameters of the models. Using the multilayer perception ANN, the models weretrained using Levenberg-Marquardt back propagation learning algorithm coupled with different numbersof neurons and activation functions for the prediction of the fuel properties. The models were observed toaccurately predict these fuel properties with high prediction accuracy (R~2 = 1). The evaluated model performanceerrors were 0.1014 and 0.0504, 0.2905 and 0.4225, 0.1848, and 0.1038, and 0.4726 and 0.7833 forKV, density, CV, and FP using root mean square error and average absolute deviation respectively. Predictionperformance and error estimates were slightly better than those for single feedstock biodiesel. Hence,this study shows the ability of ANN to accurately predict the fuel properties of HB from the Fas.
查看更多>>摘要：This investigation includes the performance of the Couple Stress Nanofluid with microbial activity, activationenergy incorporation of thermal conductivity, heat generation, variable viscosity and other parameters.We used some suitable similarity transformations to convert the governing partial differential equationsand the initial boundary conditions of our model into the coupled structure of ordinary differentialequations and final boundary conditions. Furthermore, the Spectral Quasi Linearization Method (SQLM)was used to numerically solve these ordinary differential equations with boundary conditions, generatingthe reassuring impacts of various parameters taken in our model. The graphical representation for the flow,temperature, solute and microbial distribution was analyzed with activation energy, heat generation andother interesting parameters. The impact of variable viscosity and thermal conductivity with the Prandtlnumber for the local skin friction, Nusselt, Sherwood, and the microbial density numbers was included andreflects the favorable results. The comparison table is also included to validate our model. The rising valuesof the activation energy parameter enhances the solute and microbe profiles, while rising of bio-convectionRayleigh number and Reynolds numbers discriminates the heat profiles, but enhances the solute profile.The microbial profile of the model falls for the rising values of the microbe reaction parameter.
查看更多>>摘要：The fundamental purpose of the present study is to provide a novel framework for investigating the peristalticflow through a vertical asymmetric channel filled with a magnetic third order nanofluid modelsaturated in a porous medium under the influence of varying electrical conductivity. The essential characteristicsof Brownian and thermophoresis phenomena are additionally included in the modelling of the heatequation, in besides joule heating, viscous dissipation, heat generation/absorption, and nonlinear thermalradiation. Furthermore, the effects of double diffusion convection are examined, with a small Reynoldsnumber along with extended wavelength examples that reflect biological scientific assumptions are used.The software Mathematica’s built-in command ND Solve is implemented to solve the derived nonlinearordinary differential equations system numerically. One of the most significant phenomena concerningperistaltic motion, known as the trapping phenomenon, has also been spotlighted using contour plotsand circulating bolus. The key discoveries showed that the size of the trapping bolus tends to decreasewhile the density of trapping bolus increases with an enhancement in the temperature- and concentrationdependentelectrical conductivity coefficient. Further, for all areas under consideration, the rate of heatand mass transmission is enhanced due to an augmentation in the coefficient of temperature-dependentelectrical conductivity.
查看更多>>摘要：The idea of the current investigation is to study the two-dimensional unsteady mixed convection MHDflow of a micro-polar nanofluid with non-uniform heat source/sink. Effects of radiation, reaction, thermodiffusion,and viscous dissipation are considered. Fe_3O_4 nanoparticles are suspended in water base fluid.The governing non-linear system of PDEs is transformed into a system of ODEs using the similaritytransformation and HAM is employed for obtaining solutions. Effects of different physical parameter onmomentum, microrotation, energy, and concentration profiles are discussed through graphs. From graphicalresults, it is concluded that the unsteady parameter and magnetic parameter tend to improve themotion of the fluid. It is also seen that microrotation is raised in the shrinking sheet and reduced in thestretching sheet with the increase in the unsteady parameter. The mass transfer process improved withthermal diffusion parameter while delayed with chemical reaction.
查看更多>>摘要：Forecasting of stochastic renewable energy resources is quintessential for effective planning, operationsand management of the power systems. Existing literature contains ample studies on very short andshort-term forecasting of renewables. But it’s still challenging to obtain high accuracy for medium-termand long-term forecasting. Therefore, an intuitive unified hybrid approach is proposed in this paper formedium to long-term forecasting of power generation from different weather-dependent renewablessingle-handedly by utilising their inherited periodic seasonal patterns iteratively year-on-year basis. Bi-LSTM (Bidirectional Long Short Term Memory) and ARIMA (Auto Regressive Integrated Moving Average)are utilised to construct the proposed approach with the aid of STL (Seasonal-Trend decomposition usingLoess) decomposition and data pre-processing. The performance of proposed approach (STL-ARIMABiLSTM)is validated using seven recent datasets of wind, solar and hydro power. It yields accurate forecastsfor a week-ahead to a year-ahead forecasting horizons. MAE (Mean Absolute Error) lying in range from 6.3%to 6.6%, 5.6% to 6.7% and 4.72% for a year-ahead forecast of wind, hydro and solar power, respectively, isobtained. It is established that these long-term forecast errors are even less than the short-term forecasterrors of some of the existing studies demonstrating novelty and practicality of the proposed approach.
查看更多>>摘要：Now-a-days, with the worldwide economic boom, there has been a steady increase in load demand, whichfurther reduces voltage magnitude of mainly tail-end buses and increases losses. Further, the profit marginof the Distribution Company (DISCO) has also come down and providing reliable power supply hasbecome a major concern. Under this circumstance, this study proposes an analytical method to accomplishthe optimal integration of solar DG and DSTATCOM to enhance techno-eco-environmental benefits.Instead of traditional soft-computing techniques, a simple, easy to implement and computationally efficientanalytical technique is proposed to carry out the device incorporation process. To find suitablelocations for device placement, a new and innovative formula called Device Location Selection Index (DLSI)is developed. To properly design scenario, uncertain nature of DG’s output and load is considered. A meticulousperformance analysis is presented considering different scenarios to facilitate DISCO with an optimalstrategy.
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