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The purpose of this paper is to explore and compare the influence of diverse coarse aggregate (CA) diffusivities on reinforcing steel corrosion initiation through a quantitative modeling analysis approach.

Finite element analysis was used to solve two‐dimensional chloride diffusion processes, which follow the Fick's second law within the concrete cover. Two non‐dimensional time‐derating factors were employed to quantify the time‐to‐corrosion of steel rebar, T_i, for different models.

The finite diffusivity CA exhibits variable effects on T_i, depending upon: diffusivity ratio between the CA and mortar; CA type; reinforcement corrosion resistance; and cover thickness. The intent of the effects are expressed quantitatively and their implications discussed.

The methodology and results presented in this paper provide insights on the variable reinforcement T_i values as a function of CA diffusivity. The approach employed herein provides an effective tool to select CA materials for reinforced concrete structure where chloride‐induced corrosion is a concern.

Non‐linear reaction‐diffusion processes with cross‐diffusion in two‐dimensional, anisotropic media are analyzed by means of an implicit, iterative, time‐linearized approximate factorization technique as functions of the anisotropy of the heat and species diffusivity tensors, the Soret and Dufour cross‐diffusion effects, and five types of boundary conditions. It is shown that anisotropy and cross‐diffusion deform the reaction front and affect the front velocity, and the magnitude of these effects increases as the magnitude of the off‐diagonal components of the heat and species diffusivity tensors is increased. It is also shown that the five types of boundary conditions employed in this study produce similar results except when there is either strong anisotropy in the species or heat diffusivity tensors and there are no Soret and Dufour effects, or the species and heat diffusivity tensors are isotropic, but the anisotropy of the Soret and Dufour effects is important. If the species and heat diffusivity tensors are isotropic, the effects of either the Soret or the Dufour cross‐diffusion effects are small for the cases considered in this study. The time required to achieve steady state depends on the anisotropy of the heat and diffusivity tensors, the cross‐diffusion effects, and the boundary conditions.

The purpose of the present research is to examine very small-sized samples of approximately 2-mm diameters. For samples of this size, the holder must make contact with the entire perimeter surface of the sample, and the sample is held in place by friction. This necessitates a mathematical model for the direct solution which accommodates the holder and a contact resistance between the holder and the sample.

Most flash diffusivity testing is performed on samples which are nominally 12-13 mm in diameter and are held by only a small contact area around the perimeter of the sample in a holder. With an experiment set up in this way, the effects of conduction between the sample and the holder are normally ignored.

This research examines the effects of the holder and the contact resistance on the measured thermal diffusivity of the sample and includes experimental results from laboratory measurements.

This work provides a method for finding thermal diffusivity for extremely small samples. This capability is important in cases involving precious materials or highly toxic materials where only small samples are available.

The purpose of this study is to solve convective diffusion equation analytically by considering appropriate boundary conditions and using the Taylor-Aris method to determine the solute concentration, the effective and relative axial diffusivities.

>An analysis has been conducted on how body acceleration affects the dispersion of a solute in blood flow, which is known as a Bingham fluid, within an artery. To solve the system of differential equations analytically while validating the target boundary conditions, the blood velocity is obtained.

The blood velocity is impacted by the presence of body acceleration, as well as the yield stress associated with Casson fluid and as such, the process of dispersing the solute is distracted. It graphically illustrates how the blood velocity and the process of solute dispersion are affected by various factors, including the amplitude and lead angle of body acceleration, the yield stress, the gradient of pressure and the Peclet number.

It is witnessed that the blood velocity, the solute concentration and also the effective and relative axial diffusivities experience a drop when either of the amplitude, lead angle or the yield stress rises.

This paper aims to numerically investigate the impact of gas diffusion layer (GDL) anisotropic transport properties on the overall and local performance of polymer electrolyte fuel cells (PEFCs).

A three-dimensional numerical model of a polymer electrolyte fuel cell with a single straight channel has been developed to investigate the sensitivity of the fuel cell performance to the GDL anisotropic transport properties – gas permeability, diffusivity, thermal conductivity and electrical conductivity. Realistic experimentally estimated GDL transport properties were incorporated into the developed PEFC model, and a parametric study was performed to show the effect of these properties on fuel cell performance and the distribution of the key variables of current density and oxygen concentration within the cathode GDL.

The results showed that the anisotropy of the GDL must be captured to avoid overestimation/underestimation of the performance of the modelled fuel cell. The results also showed that the fuel cell performance and the distributions of current density and oxygen mass fraction within the cathode GDL are highly sensitive to the through-plane electrical conductivity of the GDL and, to a lesser extent, the through-plane diffusivity, and the thermal conductivity of the GDL. The fuel cell performance is almost insensitive to the gas permeability of the GDL.

This study improves the understanding of the importance of the GDL anisotropy in the modelling of fuel cells and provides useful insights on improving the efficiency of the fuel cells.

Realistic experimentally estimated GDL transport properties have been incorporated into the PEFC model for the first time, allowing for more accurate prediction of the PEFC performance.

The purpose of the research was to develop a method for the determination of temperature characteristics of thermal diffusivity and specific heat on a single and the same stand, powered from an inverter for induction heating. Determination of the thermal diffusivity has been based on the idea of the pulse method. Searched solutions allowed to reduce inaccuracy of the pulse method when such an unusual source of pulse of energy is used.

Coupled electromagnetic and thermal calculations were carried out to verify proposed methods for estimating thermal properties of an induction heated charge. Presented methods were applied into a real laboratory stand and they were examined experimentally.

Achieved results of calculations allow to estimate thermal properties of the induction heated charge with 2 and 5 per cent of uncertainty, respectively, for heat capacity and thermal diffusivity. It gives possibility to use results as an input for further proceedings connected with estimation of electrical parameters in a more complex system.

Presented methods of estimating thermal properties of the induction heated charge were verified experimentally on a dedicated laboratory stand. It gives a practical possibility to implement previously established assumptions and examine them. This is a significant step toward the construction of an easy-to-use device for a comprehensive determination of material parameters of metals directly in the heat treatment plant.

This study presents a trial of implementation of induction heating as a source of energy in the impulse method for estimation of thermal properties of the material. Additionally, it presents a process of improving results achieved with the flash methods which were presented in previous papers. The method of estimation of specific heat which uses induction heating as the heat source was presented too.

This purpose of this paper is to report about the temperature distribution in metal and ceramic powder beds during 3D printing. The differing powders are thoroughly characterized in terms of thermal conductivity, thermal diffusivity, emissivity spectra and density.

The temperature distribution was measured in a 3D printing appliance (Prometal R1) with the help of thin thermocouples (0.25 mm diameter) and thermographic imaging. Temperatures at the powder bed surface as well as at differing powder bed depths were determined. The thermal conductivity, thermal diffusivity and emissivity spectra of the powders were measured as well. Numerical simulation was used to verify the measured temperatures.

The ceramic powder heated up and cooled down more quickly. This finding corresponds well with numerical simulations based on measured values for thermal conductivity and thermal diffusivity as well as emissivity spectra. An observed color change at the metal powder has only little effect on emissivity in the relevant wavelength region.

It was found that thermocouple‐based temperature measurements at the powder bed surface are difficult and these results should be considered with caution.

The results give practitioners valuable information about the transient temperature evolution for two widely used but differing powder systems (metal, ceramic). The paramount importance of powder bed porosity for thermal conductivity was verified. Already small differences in thermal conductivity, thermal diffusivity and hence volumetric heat capacity lead to marked differences in the transient temperature evolution.

The paper combines several techniques such as temperature measurements, spectral emissivity measurements, measurements of thermal conductivity and diffusivity and density measurements. The obtained results are put into a numerical model to check the obtained temperature data and the other measured values for consistency. This approach illustrates that determinations of surface temperatures of the powder beds are difficult.

The thermal diffusivity of thick film NTC layers based on a metal oxide powder mixture was measured at room temperature by the photoacoustic (PA) technique. The powder mixture was composed of MnO (60 percent), CoO (32 percent) and Fe₂O₃ (8 percent), which were ball milled to nanometer particle size. NTC layers of different thicknesses were made by sequentional screen‐printing followed by drying and co‐firing at 850, 900 and 1,000°C in a hybrid conveyor furnace. The experimental PA phase and amplitude diagrams were numerically analyzed and the thermal diffusivity and electron transport parameters were calculated. An increase of thermal diffusivity with sintering temperature was observed. The fractal structure model was in agreement with the experimental data for modulation frequencies in which the sample behaved as thermally thick.

This paper aims to study the impact of pyro-electricity, moisture and temperature diffusivity on the energy distribution of plane waves at the free surface of an orthotropic piezo-hygro-thermo-elastic medium.

This study presents the novel creation of governing equations for an anisotropic piezothermoelastic medium with moisture impact, which is a significant contribution of this paper.

In addition to providing numerical data for the amplitude ratios and energy ratios of reflected waves, this study identifies five different kinds of coupled reflected plane waves, namely, quasi-longitudinal P wave, quasi-thermal wave, quasi-transverse wave, quasi-moisture wave and electric potential wave.

The graphical analysis examines the impact of various factors, such as the angle of incidence, moisture and temperature diffusivity, pyro-electricity and frequency, on energy distribution.

This paper's results significantly impact the development of more efficient piezoelectric materials and their applications in geophysics.

The authors of the submitted document initiated and produced it collectively, with equal contributions from all members.

Elevated temperature material properties are essential in predicting structural member's behavior in high-temperature exposures such as fire. Even though experimental methodologies are available to determine these properties, advanced equipment with high costs is required to perform those tests. Therefore, performing those experiments frequently is not feasible, and the development of numerical techniques is beneficial. A numerical technique is proposed in this study to determine the temperature-dependent thermal properties of the material using the fire test results based on the Artificial Neural Network (ANN)-based Finite Element (FE) model.

An ANN-based FE model was developed in the Matlab program to determine the elevated temperature thermal diffusivity, thermal conductivity and the product of specific heat and density of a material. The temperature distribution obtained from fire tests is fed to the ANN-based FE model and material properties are predicted to match the temperature distribution.

Elevated temperature thermal properties of normal-weight concrete (NWC), gypsum plasterboard and lightweight concrete were predicted using the developed model, and good agreement was observed with the actual material properties measured experimentally. The developed method could be utilized to determine any materials' elevated temperature material properties numerically with the adequate temperature distribution data obtained during a fire or heat transfer test.

Temperature-dependent material properties are important in predicting the behavior of structural elements exposed to fire. This research study developed a numerical technique utilizing ANN theories to determine elevated temperature thermal diffusivity, thermal conductivity and product of specific heat and density. Experimental methods are available to evaluate the material properties at high temperatures. However, these testing equipment are expensive and sophisticated; therefore, these equipment are not popular in laboratories causing a lack of high-temperature material properties for novel materials. However conducting a fire test to evaluate fire performance of any novel material is the common practice in the industry. ANN-based FE model developed in this study could utilize those fire testing results of the structural member (temperature distribution of the member throughout the fire tests) to predict the material's thermal properties.