Experimental Temperature Data Research Articles

Resolving Anodic Current and Temperature Distributions in a Polymer Electrolyte Membrane Water Electrolysis Cell Using a Pseudo-Two-Phase Computational Fluid Dynamics Model

Expanding upon our prior experimental work, we constructed a three-dimensional model of a polymer electrolyte membrane water electrolyzer using computational fluid dynamics. We applied the assumption of pseudo-two-phase flow, the flow of two phases with equal velocity. Experimental data were used to obtain parameters and to determine the conditions under which this model was valid. Anodic distributions of current density, temperature, liquid saturation, and relative humidity were obtained at various flow rates. The overall current density and temperature difference from inlet to outlet at the anode agreed strongly with experimental measurements under most circumstances. This verification allowed us to further examine the apparent gas coverage calculated from experimental and model temperature data. Results suggested a low liquid saturation and low relative humidity at the anode due to the consumption of liquid water and water vapor. However, we questioned the accuracy of the pseudo-two-phase assumption at low water feed rates. We concluded that the model was applicable to systems with liquid water feed rates greater than 0.6 ml min−1 cm−2. Therefore, it is a fair screening method that can advise which operating conditions lead to excessive temperatures or drying at the anode, thereby promoting the longevity of the membrane and catalyst.

A novel transient infrared-thermography based experimental method for the inverse estimation of heat transfer coefficients in rotating bearings

Heat Transfer at moving bearing interfaces is a key parameter for the thermal characterization and design of high precision machine tools and electrical engine systems for e-mobility application. Yet, the majority of experimental approaches use tactile sensors to obtain the required temperature information for the calculation of heat transfer coefficients. However, only a limited amount of sensors can be placed in the investigated system, also including significant measurement uncertainties, long investigation times, and providing only access to local temperature information. To overcome these shortcomings, a novel method is presented, using infrared thermography to obtain transient and spatially resolved temperature information of bearing front surfaces. The recorded temperature data is used in an inverse evaluation algorithm, to determine the heat transfer coefficient, considering for modeling heat conduction as well as convective fluxes due to rotating components. Finally, experimental temperature data and calculated heat transfer coefficients are presented, discussing further the effect of low angular velocities on the heat transfer. It is shown, that this method is capable to detect changes in heat transfer coefficient due to variations in rotational speed which was not possible with existing methods. Concluding, this approach can be used in future work to focus in detail on the influence of different rolling elements, geometry and interstitial media.

Contribution to the Sustainability of Agricultural Production in Greenhouses Built on Slope Soils: A Numerical Study of the Microclimatic Behavior of a Typical Colombian Structure

The use of covered structures is an alternative increasingly used by farmers to increase crop yields per unit area compared to open field production. In Latin American countries such as Colombia, productive areas are located in with predominantly hillside soil conditions. In the last two decades, farmers have introduced cover structures adapted to these soil conditions, structures for which the behavior of factors that directly affect plant growth and development, such as microclimate, are still unknown. Therefore, in this research work, a CFD-3D model successfully validated with experimental data of temperature and air velocity was implemented. The numerical model was used to determine the behavior of air flow patterns and temperature distribution inside a Colombian passive greenhouse during daytime hours. The results showed that the slope of the terrain affects the behavior of the air flow patterns, generating thermal gradients inside the greenhouse with values between 1.26 and 16.93 °C for the hours evaluated. It was also found that the highest indoor temperature values at the same time were located in the highest region of the terrain. Based on the results of this study, future researches on how to optimize the microclimatic conditions of this type of sustainable productive system can be carried out.

Modeling and improvement of a packed bed latent heat storage filled with non-spherical encapsulated PCM-Elements

A thermal energy storage filled with a packed bed of macro-encapsulated latent heat storage elements is studied. Such a storage can be used in combination with, for example, a solar thermal heating system. Conventional capsule designs based on spherical shape do not allow for optimal packing density and heat transfer within the capsule. Therefore, capsule designs were introduced, which deviate from this basic geometry. These designs are built upon a super-ellipsoidal shape with multiple surface extensions, e.g. holes and grooves, in order to enhance heat transfer.To further optimize the thermal performance of the storage system, a model describing the charging and discharging processes of the heat storage was developed based on a new approach for the treatment of non-spherical capsules. The model was validated against experimental temperature data obtained from charging and discharging measurements with flow rates ranging from 216 to 1000 kg/h. The maximal observed deviation between simulation and experiment was ±0.82 K.Furthermore, new capsule geometries based on super-ellipsoids were evaluated with respect to their storage capacity and thermal power output. A promising capsule design was identified which has a more than 20% higher storage capacity than the other shapes and provides a reasonable thermal power output of approximately 4 kW during the phase change of the storage material. The energy density was increased from 51.5 kWh/m³ to 64.1 kWh/m³.

Kinetic Studies of the Glycerolysis of Urea to Glycerol Carbonate in the Presence of Amberlyst-15 as Catalyst

Amberlyst-15, a strong acidic ion-exchange resin, has showed as a potential and an effective catalyst for the glycerolysis process of urea to glycerol carbonate. In this work, the kinetic model of the urea glycerolysis over Amberlyst-15 catalyst was investigated. The kinetic model was developed by considering simultaneous steps of urea dissolution in glycerol, mass transfer of urea and glycerol from the bulk of the liquid into the outer part of the catalyst, diffusion of urea and glycerol into the inner part of the particle through the catalyst pores, and irreversible second order reaction of urea and glycerol on the active sites. The irreversibility of second order reaction of urea glycerolysis was validated and proven. The proposed kinetic model was simulated and validated with the experimental data. The kinetic studies show that mechanism proposed works well. Furthermore, the activation energy was found to be 145.58 kJ.mol−1 and the collision factor was in 8.00×1010 (m3)2.kg−1.mol−1.s−1. The simulation result shows that the predicted liquid temperatures were close to the experimental temperature data. It also gave glycerol concentration profile inside the catalyst particle as a function of glycerolysis time and position. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Simulation approaches for the mechanisms of thermoset polymerization reactions

Abstract Detailed modeling and simulation of the reaction of alcohol and isocyanate moieties to form urethane have provided a reason to question conventional opinions that this is a step-growth polymerization process. In particular, industrial formulations are dominated by catalytic mechanisms, and these chain mechanisms can change the polymer growth mechanism. This paper's research evaluates experimental data of reaction temperature and resin viscosity of urethane gel reactions that substantiate a chain-growth mechanism. One of the artifacts of a chain-growth mechanism is the rapid appearance of relatively large molecules that reduce gel point times earlier with step-growth mechanisms.

Experiment and numerical analysis of catalytic CO2 methanation in bubbling fluidized bed reactor

This study experimentally and numerically investigated the hydrodynamics, reaction kinetics, and heat transfer of a bench-scale bubbling fluidized bed (BFB) reactor for CO2 methanation. A three-dimensional gas–solid Eulerian computational fluid dynamics (CFD) model coupled with a modified Syamlal–O’Brien drag model and reaction kinetics for Ni-based catalysts was developed. The CFD model was validated against experimental data for pressure, temperature, and gas composition at 1 bar and an inlet flow rate of 2 L/min with an inlet N2 content of 77.5%. The axial pressure drop, solid volume fraction, temperature, gas composition, and bed-to-wall heat transfer coefficient (HTC) were compared for four inlet N2 contents: 77.5%, 50%, 25%, and 0%. As the inlet N2 content decreased, the mean bed temperature increased from 340 to 456 °C, the gas volume decreased owing to the reaction, the fluidizing number (ug/umf) decreased from 4.1 to 3.5, and the solid holdup increased. Consequently, the HTC increased from 327 to 386 W/m2/K. This study identified successfully the effects of hydrodynamics and reaction kinetics on HTC in the BFB for CO2 methanation.

Monte Carlo study of the phase diagram of disordered FepAl1−p alloys: A site-diluted isotropic Heisenberg model

A site-diluted classical Heisenberg model on the bcc lattice, with only isotropic nearest-neighbor exchange interactions, is used to describe the phase diagram of ${\mathrm{Fe}}_{p}\ensuremath{-}{\mathrm{Al}}_{q}$ alloys ($p+q=1$) in the structurally disordered phase. Due to the larger size of Al atoms, the Fe-Fe exchange interactions along the border of the Al clusters are assumed to increase since the distance between Fe atoms becomes smaller in this region and remains constant for the rest of the lattice. However, for higher Al concentrations the Fe-Fe exchange interaction should decrease as a result of the increase of the lattice size parameter. Considering these assumptions, we have employed Monte Carlo simulations to obtain the thermodynamic properties of the model and obtain quite good fits to the experimental data of the transition temperature as a function of $q$. The results are still better than those recently obtained by assuming superexchange interactions induced by Al between next-nearest-neighbor Fe atoms.

Development and validation of a computational model for steak double-sided pan cooking

The objective of this study was to develop and validate a numerical model to adequately simulate the double-sided pan cooking of beef in a domestic environment. The proposed model takes into account the heat flow from the pan to the meat and the moisture transfer, simultaneously with the meat deformation. The model considers the swelling pressure gradient caused by the shrinkage of the meat fibers and connective tissue due to the denaturation of proteins and the loss of the water holding capacity during cooking. The model results were successfully verified with experimental data of the central temperature and weight loss recorded during cooking for three degrees of doneness. The measured experimental temperatures at the center of the meat were 30 ± 3 °C (very rare), 44 ± 3 °C (rare) and 57 ± 2 °C (done) for a 19 mm steak thickness. Meanwhile, their water losses were 4 ± 2 % , 8 ± 1 % and 11 ± 2 % , respectively. The root mean squared errors of the model predictions were 2.16 °C (very rare), 3.56 °C (rare) and 4.57 °C (done) for the central temperature and 1.48 % , 2.08 % and 2.40 % , respectively for the water loss. The model also correctly predicts cooking times for steaks of different thicknesses, taking weight loss as a reference to set this time. The proposed model is postulated as a useful cooking assistance tool to estimate the optimal cooking time according to consumer preferences.

Passive Heating and Cooling of Photovoltaic Greenhouses Including Thermochromic Materials

The integration of photovoltaic technologies into greenhouse envelopes appears to be an innovative and environmentally-friendly way to supply their various energy demands. However, the effect on the inner growing conditions, especially on the temperature, must be assessed in order to effectively implement this solution. In this study, experimental temperature data were obtained over two years for four structures built with different photovoltaic technologies (mono-crystalline silicon, amorphous silicon, cadmium telluride, and an organic polymeric technology) and fitted to a thermal model in order to provide a comprehensive analysis of their potential utilization as a cover material in greenhouses. Additionally, the thermal effect of color in structures composed of several common construction materials (brick, wood, plasterboard and glass) was quantified and modelled, supplementing the thermal analysis of passive solutions for this application. In all cases, inner and ambient temperature differences of up to +20 °C, created by a passive heating effect during the day, and −5 °C, created by a passive cooling effect during the night, have been observed, suggesting the use of the photovoltaic modules with different degrees of structure coverage, complemented with the color tuning of the modules themselves as passive methods to control the temperature and light spectrum of greenhouses.

Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories

Emerging Trends in the use of smart portable accessories, particularly within the context of the Internet of Things (IoT), where smart sensor devices are employed for data gathering, require advancements in energy management mechanisms. This study aims to provide an intelligent energy management mechanism for wearable/portable devices through the use of predictions, monitoring, and analysis of the performance indicators for energy harvesting, majorly focusing on the hybrid PV-wind systems. To design a robust and precise model, prediction algorithms are compared and analysed for an efficient decision support system. Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) prediction algorithms are used to develop a Shallow Neural Network (SNN) for time series prediction. The proposed SNN model uses a closed-loop NARX recurrent dynamic neural network to predict the active power and energy of a hybrid system based on the experimental data of solar irradiation, wind speed, wind direction, humidity, precipitation, ambient temperature and atmospheric pressure collected from Jan 1st 2015 to Dec 26th 2015. The historical hourly metrological data set is established using calibrated sensors deployed at Middle East Technical University (METU), NCC. The accessory considered in this study is called as Smart Umbrella System (SUS), which uses a Raspberry Pi module to fetch the weather data from the current location and store it in the cloud to be processed using SNN classified prediction algorithms. The results obtained show that using the SNN model, it is possible to obtain predictions with 0.004 error rate in a computationally efficient way within 20 s. With the experiments, we are able to observe that for the period of observation, the energy harvested is 178 Wh/d, where the system estimates energy as 176.5 Wh/d, powering the portable accessories accurately.

Design and implementation of minichannel evaporator for electronics cooling

The present study elucidates the design and experimentation of a minichannel evaporator in an R134a vapour compression refrigeration system for electronics cooling applications. In the current study, a calculation module was developed to design a minichannel evaporator to keep the surface temperature of the chip below a certain value for reliable operation conditions in electronic cooling applications. In the calculation module, the conventional-scale heat transfer correlation was used to predict the surface temperature of the chip. On the other hand, the conventional-scale and microscale pressure drop correlations were tested to assess the pressure drop in the minichannel evaporator. The proposed calculation module was verified using experimental tests for different heat loads. It was found that the proposed calculation model predicted very well the experimental data of the surface temperature of the chip for all heat input. The calculation module with micro-scale pressure drop correlation predicted well the experimental pressure drop data in the minichannel evaporator for all heat loads. Moreover, the effects of the degree of subcooling, superheating degree and condensation temperature on the surface temperature of the chip and pressure drop in the minichannel evaporator were investigated to determine optimum operating conditions at different cooling capacities using the calculation module. The results showed that the increase in the degree of subcooling enhances the performance of the minichannel evaporator. On the other hand, the lower degree of superheating and condensation temperature yielded better performance for the minichannel evaporator. The feasibility of the results for electronic cooling applications is discussed based on the findings.

3D finite element model of dynamic material behaviors for multilayer ultrasonic metal welding

Ultrasonic metal welding (UMW) has been widely applied as a high throughput solid-state joining technology for multilayers of sheet metal. During a typical UMW process, multilayer work materials are mechanically compressed by a knurl-patterned horn (also known as a sonotrode) onto an anvil tool, and a simultaneous in-plane sliding is applied to the horn at an ultrasonic frequency (20 kHz or higher) to help form the weld at the material interfaces. There is a great challenge in modeling and simulating the dynamic behavior of the work material and the whole weld formation process is subject to ultrasonic mechanical loadings imposed by the knurl-patterned horn tool. In this work, finite element (FE) models are developed to simulate the multilayer UMW process using knurl-patterned tools by directly applying the ultrasonic vibration as a model input. For a short weld duration of 0.1∼0.5 s, a high-fidelity FE modeling approach is developed using ABAQUS/Explicit to simulate the dynamic material response under the 20 kHz horn vibration. For an extended long welding duration of approximately 1.0 s, a computationally efficient hybrid approach is developed using both ABAQUS/Explicit and DEFORM-3D in order to leverage the strengths of each software package. The developed models are validated using experimental data of dynamic welding force, temperature, and weld geometry from in-situ process measurements of UMW. The 3D FE models developed in this study are the most comprehensive solution to date to simulate the complex material response subject to UMW process conditions and provide engineering guidance for the design of UMW applications.

On the Mg-Pb system. Calorimetric studies and thermodynamic calculations

In this paper, the experimentally determined integral and partial molar enthalpy of mixing of liquid Mg-Pb alloys is presented. Five separate measurements were performed at 1012 and 1014 K with the use of MHTC 96 Line Evo line drop calorimeter. The values of integral molar mixing enthalpy are characterized by negative deviations from the ideal solutions in the entire concentration range. Based on obtained results and other thermodynamic quantities available in the literature the Mg-Pb phase diagram was optimized. The calculated and experimentally obtained values of the integral molar mixing enthalpy are also compared with the Miedema model prediction of the integral molar mixing enthalpy. The formation enthalpy for the Mg2Pb phase is computed by ab initio calculations and equals −5978 J/mol of atoms at 0 K. For the Mg2Pb intermetallic phase, the calculated bulk isothermal and adiabatic modulus, as well as a variation of primitive cell volume and thermal expansion coefficient with the temperature, are presented. Moreover, the heat content of the Mg2Pb intermetallic phase is shown and compared with experimental data for temperatures from 0 K to its melting temperature.

Numerical study of preheating primary air on pinewood and corn straw co-combustion in a fixed bed using Eulerian-Eulerian approach

The effect of preheating primary air on the co-combustion characteristics of a 50–50% blend of pinewood and corn straw in a fixed bed. The primary air temperatures were assessed from 20 to 130 °C. The co-combustion characteristics were included the co-combustion behaviors and emissions. In order to reveal the features of the combustion process in the porous bed, a two-dimensional unsteady state model was employed to investigate the combustion process in a fixed bed of blended biomass on the combustion process in a fixed bed reactor. Conservation equations of the bed were implemented to describe the combustion process. The gas phase turbulence was modeled using the k-ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. Results showed that by increasing primary air temperature the residual mass on bed decreased, while the average burning rates and ignition front propagation velocity increased At the primary air temperature of 85 °C the smallest unburned carbon was left in the ash, and the emissions of nitrogen-compounds were relatively small. In contrast, the primary air temperature of 85 °C was found to be well-operating condition, which can be suggested for industrial boiler during blend co-combustion. The simulation results were then compared with experimental data for different temperature, which shows that the combustion process in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data.

Viscosity-temperature relation based on the evolution of medium-range structures of silica

The viscosity of glass is the most important technological property to glass manufactures and various applications. Practically, finding an accurate equation to express the glass viscosity behavior in the entire glass transition temperature range is tremendously challenge because it spans more than ten orders of magnitude. After a brief review of existing empirical viscosity equations, this work focuses on the correlating silica viscosity behavior with the evolution of glass medium-range structure, based on the recently proposed nanoflake model. From this new model, a new equation is constructed, which correctly describes the Arrhenius-type behavior of silica viscosity η above the melting temperature Tm, and non-Arrhenius-type behavior from Tm to a critical temperature Tc. At temperature lower than Tc, the equation predicts Arrhenius-type behavior again for the viscous flow with increased activation energy. The new equation agrees with experimental data in the entire temperature spanned from extremely high to extremely low. The application of the new equation is shown to extend to sodium silicate glasses as well.

Optimisation of solar-hydrogen power system for household applications

A numerical method was developed for optimising solar–hydrogen energy system to supply renewable energy for typical household connected with the grid. The considered case study involved household located in Diyala Governorate, Iraq. The solar–hydrogen energy system was designed to meet the desired electrical load and increase the renewable energy fraction using optimum fuel cell capacity. The simulation process was conducted by MATLAB based on the experimental data for electrical load, solar radiation and ambient temperature at a 1-min time-step resolution. Results demonstrated that the optimum fuel cell capacity was approximately 2.25 kW at 1.8 kW photovoltaic power system based on the average of the daily energy consumption of 6.8 kWh. The yearly renewable energy fraction increased from 31.82% to 95.82% due to the integration of the photovoltaic system with a 2.25 kW fuel cell used as a robust energy storage unit. In addition, the energy supply, which is the economic aspect for the optimum system, levelised electricity cost by approximately $0.195/kWh. The obtained results showed that the proposed numerical analysis methodology offers a distinctive property that can be used effectively to optimise hybrid renewable energy systems.

Statistical relationship between soot volume fraction, temperature, primary particle diameter and OH radicals along transects normal to the local reaction zone in a turbulent flame

We present a new method to extract experimental data from simultaneous planar images in turbulent sooting flames, to derive transects of key species based on local coordinates that are aligned normal to the instantaneous, fluctuating reaction zone. Such statistics represent a milestone in the assessment of turbulent sooting flames, because they are one-dimensional and based on local coordinates conditioned on the distribution of soot sheets, in contrast to previous statistics, which are typically Eulerian and single point in nature. The local coordinate system was determined from instantaneous images of soot volume fraction (fv) based on a varying threshold and the local reaction zone was identified by further referring OH images. Quantitative experimental data of fv, temperature (T) and primary particle diameter (Dp), together with qualitative OH intensities, were extracted along the direction normal to the local reaction zone from simultaneous images of the four parameters. These results were measured in a pre-vaporized toluene diffusion flame (Reynolds number = 10,000) using advanced laser-based techniques. Statistical data were combined together and used to generate the profiles for these four parameters with high accuracy and level of resolution that is not possible using previous statistics methods based on Eulerian coordinates. These new kind results showed that the spatial relationship between fv, T and OH remains broadly similar anywhere in the flame, while the profiles of Dp significantly shift away from those of the other three parameters with the increase in the height of the flame. The mean values of fv, Dp and T also show a clear relationship as a function of the height, even though the trends of mean fv and Dp along the height are different from that of T, also suggesting a strong relationship exists between soot and temperature in the local reaction zone.

Axial variability of pattern formation in Rayleigh-Bénard convection: MRI velocimetry in a low aspect ratio cylinder

Natural convection is a fundamental hydrodynamic instability and a template process for the study of pattern formation. It is also an important mode of energy transport in natural geophysical and environmental systems, as well as technological applications. In solar heating devices, pasteurization processes, industrial mixing, and pebble-bed nuclear reactors, low aspect ratio systems of greater depth than width are widely used for their favorable convection properties. Here, magnetic resonance imaging was used to quantify the axial spatial variation of flow patterns in a narrow cylinder. Fluid velocity maps were acquired in multiple transverse and longitudinal planes. It is shown that the flow patterns vary significantly as a function of the height above the heated bottom boundary. The large scale circulation varies among predicted azimuthal mode patterns. Azimuthal 180o reorientation of the upward and downward flow cells was observed over short axial distances. The complex circulation patterns observed suggest acquisition of velocity data in only one plane could lead to mischaracterization of flow patterns in low aspect ratios systems, an aspect of the current literature which is lacking quantification. A preliminary computational fluid dynamics model in STAR-CCM+, corroborated by the experimental results, provided velocity and temperature data for the full fluid column height. Together these results indicate the need for further investigation into circulation characteristics in long narrow cylinders. Enhanced understanding of these rapid axial variations in flow pattern will allow better modeling of heat and mass transport in low aspect ratio natural convection flows.

A parametric study of a photovoltaic panel with cylindrical fins under still and moving air conditions in Iraq

AbstractPhotovoltaic (PV) panel temperature plays a vital role in the performance of PV panels. When PV temperature increases, the electrical power and efficiency decrease. In the present study, a simple simulated model is derived and implemented for a 70‐W finned PV panel and the results are compared with those for a reference (unfinned) PV panel. The effect of various parameters including fin diameter, fin height, ambient temperature, fin coverage‐to‐area ratio, and solar irradiance level on PV performance are examined. It is concluded that more electrical power is generated under moving air than under still air conditions as solar irradiance increases. The optimum values for fin diameter, fin height, and fin coverage‐to‐area ratio are 0.005 m, 0.25 m, and 50%, respectively. The maximum simulated power difference between the finned and unfinned PV panels is 5 W under realistic weather conditions. The amount of power generated during the summer season would be about 3.32 kW·h greater than that by the reference PV panel over the same period. The root square percent deviation values between the results of the proposed model and previously published experimental data for panel temperature, electrical power, and electrical efficiency are 3.36%, 5.26%, and 5.48%, respectively.