Applications of feedforward multilayer perceptron artificial neural networks and empirical correlation for prediction of thermal conductivity of Mg(OH)2–EG using experimental data

This paper presents an investigation on the thermal conductivity of nanofluids using experimental data, neural networks, and correlation for modeling thermal conductivity. The thermal conductivity of Mg(OH)₂ nanoparticles with mean diameter of 10 nm dispersed in ethylene glycol was determined by using a KD2-pro thermal analyzer. Based on the experimental data at different solid volume fractions and temperatures, an experimental correlation is proposed in terms of volume fraction and temperature. Then, the model of relative thermal conductivity as a function of volume fraction and temperature was developed via neural network based on the measured data. A network with two hidden layers and 5 neurons in each layer has the lowest error and highest fitting coefficient. By comparing the performance of the neural network model and the correlation derived from empirical data, it was revealed that the neural network can more accurately predict the Mg(OH)₂–EG nanofluids' thermal conductivity.     

Buoyancy-driven heat transfer of water-based Al2O3 nanofluids in a rectangular cavity

In this paper, thermal characteristics of natural convection in a rectangular cavity heated from below with water-based nanofluids containing alumina (Al₂O₃ nanofluids) are theoretically investigated with Jang and Choi’s model for predicting the effective thermal conductivity of nanofluids and various models for the effective viscosity. To validate theoretical results, we compare theoretical results with experimental results presented by Putra et al. It is shown that the experimental results are put between a theoretical line derived from Jang and Choi’s model and Einstein’s model and a theoretical line from Jang and Choi’s model and Pak and Cho’s correlation. In addition, the effects of the volume fraction, the size of nanoparticles, and the average temperature of nanofluids on natural convective instability and heat transfer characteristics of water-based Al₂O₃ nanofluids in a rectangular cavity heated from below are theoretically presented. Based on the results, this paper shows that water-based Al₂O₃ nanofluids is more stable than base fluid in a rectangular cavity heated from below as the volume fraction of nanoparticles increases, the size of nanoparticles decreases, or the average temperature of nanofluids increases. Finally, we theoretically show that the ratio of heat transfer coefficient of nanofluids to that of base fluid is decreased as the size of nanoparticles increases, or the average temperature of nanofluids is decreased.     

Lifted methane-air jet flames in a vitiated coflow

The present vitiated coflow flame consists of a lifted jet flame formed by a fuel jet issuing from a central nozzle into a large coaxial flow of hot combustion products from a lean premixed H₂/air flame. The fuel stream consists of CH₄ mixed with air. Detailed multiscalar point measurements from combined Raman-Rayleigh-LIF experiments are obtained for a single base-case condition. The experimental data are presented and then compared to numerical results from probability density function (PDF) calculations incorporating various mixing models. The experimental results reveal broadened bimodal distributions of reactive scalars when the probe volume is in the flame stabilization region. The bimodal distribution is attributed to fluctuation of the instantaneous lifted flame position relative to the probe volume. The PDF calculation using the modified Curl mixing model predicts well several but not all features of the instantaneous temperature and composition distributions, time-averaged scalar profiles, and conditional statistics from the multiscalar experiments. A complementary series of parametric experiments is used to determine the sensitivity of flame liftoff height to jet velocity, coflow velocity, and coflow temperature. The liftoff height is found to be approximately linearly related to each parameter within the ranges tested, and it is most sensitive to coflow temperature. The PDF model predictions for the corresponding conditions show that the sensitivity of flame liftoff height to jet velocity and coflow temperature is reasonably captured, while the sensitivity to coflow velocity is underpredicted.     

Modeling the effective thermal conductivity of nanofluids using full factorial design analysis

In this paper, a full factorial design analysis is proposed for predicting nanofluid thermal conductivity ratio (TCR) as well as determining the effects of critical factors and their interactions. A statistical design of experiment approach with three variables (volume fraction, temperature, and nanoparticle diameter) at two levels is carried out. Three types of oxide‐water nanofluids (Al₂O₃‐water, CuO‐water, and TiO₂‐water) are used to evaluate the effectiveness of the proposed mathematical model. The significance and adequacy of the regression model were evaluated by the analysis of variance. The predicted model has a root mean square error equals to 0.0074, R² = 0.99, and P < .0013, thus showing good results compared to a set of experimental data as well as other mathematical model results. The results illustrate that the TCR of metallic oxide nano?uids increases with temperature and nanoparticles volume fraction but decreases when nanoparticle size intensi?es. Furthermore, it is found that the nanoparticles volume fraction has a great impact on the nano?uids thermophysical properties. Finally, the obtained results confirm that the proposed model is considerably accurate and capable of predicting nano?uids thermal conductivity and that it can be used with ease as an alternative to many other models.     

Comparative study of Euler and mixture models for turbulent flow of Al2O3 nanofluid inside a horizontal tube

In this paper, turbulent forced convective flow of water Al₂O₃ nanofluid, with particle diameter equal to 40 nm in a horizontal circular tube, exposed to convection with saturated steam at the wall, is numerically analyzed. Two different approaches are taken into consideration: Euler and mixture models. It is comprehended that convective heat transfer coefficient enhances with increasing the particle volume concentration and Reynolds number. The two models almost showed the same results. However, mixture model was in a better agreement with experimental results for the estimation of average Nusselt number.     

Experimental investigation of oxide nanofluids laminar flow convective heat transfer

In the present investigation nanofluids containing CuO and Al₂O₃ oxide nanoparticles in water as base fluid in different concentrations produced and the laminar flow convective heat transfer through circular tube with constant wall temperature boundary condition were examined. The experimental results emphasize that the single phase correlation with nanofluids properties (Homogeneous Model) is not able to predict heat transfer coefficient enhancement of nanofluids. The comparison between experimental results obtained for CuO / water and Al₂O₃ / water nanofluids indicates that heat transfer coefficient ratios for nanofluid to homogeneous model in low concentration are close to each other but by increasing the volume fraction, higher heat transfer enhancement for Al₂O₃ / water can be observed.     

Viscosity of nanofluids based on an artificial intelligence model

By using an FCM-based Adaptive neuro-fuzzy inference system (FCM-ANFIS) and a set of experimental data, models were developed to predict the effective viscosity of nanofluids. The effective viscosity was selected as the target parameter, and the volume concentration, temperature and size of the nanoparticles were considered as the input (design) parameters. To model the viscosity, experimental data from literature were divided into two sets: a train and a test data set. The model was instructed by the train set and the results were compared with the experimental data set. The predicted viscosities were compared with experimental data for four nanofluids, which were Al₂O₃, CuO, TiO₂ and SiO₂, and with water as base fluid. The viscosities were also compared with several of the most cited correlations in literature. The results, which were obtained by the proposed FCM-ANFIS model, in general compared very well with the experimental measurement.     

The microalgae derived hydrogen process in compact photobioreactors

This paper investigates the feasibility of a microalgae derived hydrogen process at a pilot scale. For that, a general transient mathematical model for managing microalgae derived hydrogen production, with temperature dependence of the cultivation medium is developed. The tool allows for the determination of the resulting whole system temperature, and mass fractions distribution. The simplified physical model combines principles of classical thermodynamics, mass, species and heat transfer, resulting in a system of differential equations which are discretized in space using a three-dimensional cell-centered finite volume scheme, namely a volume element model (VEM). A Michaelis–Menten type expression is proposed for modeling the rate of H₂ production with dependence on O₂ inhibition. Tridimensional simulations are performed in order to determine the mass fractions distributions inside a compact photobioreactor (PBR), under different operating conditions. A relatively coarse mesh was used (6048 volume elements) to obtain converged results for a large compact PBR computational domain (2 m × 5 m × 8 m). The largest computational time required for obtaining results was 560 s, i.e., less than 10 min. The numerical results for microalgal growth are validated by direct comparison to experimental measurements. Hydrogen production simulations are conducted to demonstrate PBR intermittent operation (aerobic and anaerobic stages) feasibility and adequate species evolution trends in an indirect biophotolysis approach. Therefore, after experimental validation for a particular H₂ production system, it is reasonable to state that the model could be used as an efficient tool for PBR systems thermal design, control and optimization for maximum H₂ production.     

Phase equilibria prediction model for semiclathrate hydrates formed from CH4, CO2, and N2 in the presence of tetra-n-butyl ammonium bromide

In this work, a prediction model was studied and carried out to predict phase equilibrium conditions for semiclathrate hydrates formed from the ternary system of liquid water, tetra-n-butyl ammonium bromide, and CO₂, CH₄, or N₂. Based on the Soave–Redlich–Kwong equation of state along with the Chen–Guo model, the predictions of phase equilibria of semiclathrates of CO₂, CH₄, and N₂ + pure water/tetra-n-butyl ammonium bromide aqueous solution has been made. A new correlation for activity relating to the system temperature and tetra-n-butyl ammonium bromide concentration has been proposed. The prediction results were analyzed and showed good agreement with the experimental data.     

Design of a hydrogen compressor for hydrogen fueling stations

Hydrogen compressors dominate the hydrogen refueling station costs. Metal hydride based thermally driven hydrogen compressor (MHHC) is a promising technology for the compression of hydrogen. Selection of metal hydride alloys and reactor design have a great impact on the performance of the thermally driven MHHC. A thermal model is developed to study the performance characteristics of the two-stage MHHC at different operating conditions. The effects of heat source temperature and hydrogen supply pressure on the compression ratio and isentropic efficiency are investigated. Finite volume method is used for discretizing the reaction kinetics, continuity, momentum and energy equations. Metal hydrides selected for this analysis are Mm_0.2La_0.6Ca_0.2Ni₅ and Ti_1.1Cr_1.5Mn_0.4V_0.1. The thermal model was validated with the results extracted from an experimental study. Validation results demonstrated that the numerical results are in good agreement with the data reported in literature.     

Numerical investigation for turbulent heat transfer of TiO2–SiO2 nanofluids with wire coil inserts

A numerical model has been developed for turbulent flow of hybrid nanofluids in a tube with wire coil inserts. The model was developed from van Driest eddy diffusivity equation. The model can be implemented with the consideration of new variables in eddy diffusivity of momentum and heat by using the coefficient, K and Prandtl index, ζ, respectively. The numerical analysis are undertaken for wide range of Reynolds number, different volume concentration, ? and various pitch ratio, P/D of wire coil. The numerical results were validated with the experimental data of TiO₂–SiO₂ nanofluids undertaken for wide range of Reynolds number and volume concentration. The final regression models of coefficient K and Prandtl index ζ were developed as a function of Reynolds number, Re or dimensionless radius, R⁺, volume concentration, ? and pitch ratio, P/D. A good agreement between the experimental data and numerical model indicating the validity of the numerical model for hybrid nanofluids with wire coil inserts. The numerical analysis was proved that the hybrid nanofluids contributes to higher Nusselt number and thus have better heat transfer performance compared to single nanofluids.     

Modeling of particulate carbon and species formation in coflowing diffusion flames of ethylene

A model of species and particulate formation in laminar diffusion flames is presented. The kinetic model is based on the chemistry of fuel oxidation and pyrolysis, the formation of aromatics and their growth into particle nuclei, particle growth by surface reactions, coagulation, and finally particle oxidation. A sectional model is used for the particle phase. The sectional method divides the particle mass range into classes of species each with a rate equation for surface growth, coagulation, and oxidation. An inception model links the gas-phase mechanism with the smallest particle section. Predictions are compared with experimental data in two laminar coflowing diffusion flames of ethylene for which experimental profiles of stable species, aromatic compounds, high-molecular-mass precursor species, and soot are available. The predictions show good agreement with data for total particulates, defined as the sum of soot plus nano-organic carbon particles. The model has a continuous size distribution and is able to address nanoparticles which comprise a significant part of the total particle loading. A conclusion from the sensitivity analysis is that the inception process, the molecular growth process by aromatic addition on particle nuclei, and surface addition of C₂H₂ all play important roles which need to be studied in greater detail to predict the right size distribution and volume fraction of particulates formed in flames.     

Investigation of thermal aspects of hydrogen storage in a LaNi5‐H2 reactor

In this work, hydrogen absorption in a LaNi₅‐H₂ reactor is investigated experimentally and numerically. Experimental measurements were carried out on a cylindrical metal‐hydride reactor filled with LaNi₅ alloy. During the experiments hydrogen was charged at a constant pressure. The performance of the reactor during hydriding process was obtained at different fluid temperatures and hydriding process was identified from measured temperature histories. The temperature changes in the reactor were measured at several locations and recorded in a computer. The numerical simulation of the reactor was also performed. A two‐dimensional mathematical model has been established and solved numerically by the method of finite volume for the simulation. The numerical results are compared with the measured data to validate the mathematical model. The predicted results are in good agreement with the experimental measurements. Copyright © 2005 John Wiley & Sons, Ltd.     

The Effect of Thermal Loading Due to Laser Pulse in Generalized Thermoelastic Medium with Voids in Dual Phase Lag Model

The aim of the present study is concerned with the thermal loading due to laser pulse on thermoelastic medium with voids in the dual phase lag model (DPL). The material is a homogeneous isotropic elastic half-space and heated by a non-Gaussian laser beam with pulse duration of 8 ps. A normal mode method is proposed to analyze the problem and obtain numerical solutions for the displacement components, stresses, temperature distribution and change in the volume fraction field. The results of the physical quantities have been illustrated graphically by comparison between (DPL) and Lord-Schulman (L–S) theory for two values of time and for different values of a phase-lag of heat flux τ _q .     

Alternative fuelled hybrid electric vehicle (AF-HEV) with hydrogen enriched internal combustion engine

In this paper, hybrid electric vehicle (HEV) that powered by hydrogen (H₂) enriched internal combustion (ICE) engine was studied both simulation and experimental. As an alternative fuel, the usage of H₂ as additional fuel on an ICE that used for HEV, investigated in this partially simulational study for the first time. The study was consisted two parts. In the first part, the effects of 10% H₂ enrichment on performance and emissions were experimented in a 1.8 L Ford Spark Ignition (SI) engine. Then, AVL Boost tool was used for simulation and validation under this ICE's properties and has compared with experimental results. After the simulations and experiments results were found consistent each other, AVL Cruise was used for hybridization of H₂ enriched ICE, for the second part. Combustion, performance and emission values are given comparatively with selected driving cycle of model vehicle were realized with simulation tools. Hybrid mode's ICE becomes more environmentally friendly due to H₂ enrichment with increasing performance. The model HEV has delivered promising results on performance and emission values and this improvement added to literature with this study. Results showed that, enrichment of H₂ is presented 3.56% improvement in ICE torque and 2.37% for ICE power. Cumulative fuel consumption and emission pollution decreased by 12.6% and 14–33% respectively, for hybrid mode.     

Gasification reactivity of biomass chars with CO2

In this study, carbon conversion was calculated from the data obtained with a real-time gas analyzer. In a lab-scale furnace, each biomass sample was pyrolyzed in a nitrogen environment and became biomass char. For preparation of the char, the furnace was electrically heated over 40 min up to the wall temperature of 850 °C, and maintained at the same temperature over 17 min. The furnace was again heated over 3 min to a temperature higher than 850 °C and then CO₂ was injected. The biomass char was then gasified with CO₂ under isothermal conditions. The reactivity of biomass char was investigated at various temperatures and CO₂ concentrations. The VRM (volume reaction model), SCM (shrinking core model), and RPM (random pore model) were used to interpret the experimental data. For each model, the activation energy (E) and pre-exponential factor (A) of the biomass char-CO₂ reaction were determined from gas-analysis data by using the Arrhenius equation. For the RPM, the apparent reaction order was determined. According to this study, it was found that the experimental data agreed better with the RPM than with the other two models. Through BET analyses, it was found that the structural parameter (ψ) of the surface area for the RPM was obtained as 4.22.     

Differences in characteristics of dye-sensitized solar cells containing acetonitrile and ionic liquid-based electrolytes studied using a novel model

A performance simulation model of dye-sensitized solar cells including a “bulk” electrolyte layer separated from a TiO₂ layer has been presented. The calculation results with this novel model agree well with experimental results, which indicates the importance of considering the bulk electrolyte layer in theoretical models. The model allows us to specify the diffusion coefficients of ionic species in nano-pores of the TiO₂ layer and in the bulk electrolyte layer separately, and the importance of ionic diffusions in each layer is discussed. We further clarify the difference between ionic liquid-type cells and acetonitrile type cells, and discuss the important issues for increasing the efficiencies in cells containing ionic liquid-based electrolytes.     

Phase stability and elastic property of PdH and PdCuH phases

First principles calculation based on density functional theory is used to comparatively investigate phase stability, elastic properties, and electronic structures of PdH and PdCuH phases with various H concentrations. Calculation shows that PdCuH_x phases possess smaller heats of formation than corresponding PdH_x as 0 ≤ x < 0.105, whereas PdH_x phases are energetically more stable when x exceeds 0.105. It is also revealed that the volume expansion of PdCuH phase as a result of H addition is smaller than that of PdH at low H concentrations, implying that the alloying of Cu could lower hydrogen embrittlement of PdH. Furthermore, it is indicated that Cu should have an important effect of solid-solution strengthening in the Pd lattice, and the PdCuH phase has bigger E, G, and G/B values than PdH. The calculated results are discussed in terms of electronic structures, and are in good agreements with experimental observations in the literature.     

Three dimensional lattice Boltzmann simulation for mixed convection of nanofluids in the presence of magnetic field

In the present study, a three dimensional thermal lattice Boltzmann model was developed to investigate the flow dynamics and mixed convection heat transfer of Al₂O₃/water nanofluid in a cubic cavity in the presence of magnetic field. The model was first validated with previous numerical and experimental results. Satisfactory agreement was obtained. Then the effects of Rayleigh number, nanoparticle volume fraction, Hartmann number and Richardson number on nanofluid flow dynamics and heat transfer were examined. Numerical results indicate that adding nanoparticles to pure water leads to heat transfer enhancement for low Rayleigh numbers. However, this enhancement might be weakened and even reversed for high Rayleigh numbers. In addition, the results show the external applied magnetic field has an effect of suppressing the convective heat transfer in the cavity. Moreover, the results demonstrate that the Richardson number in mixed convection has significant influences on both streamlines and temperature field.