Parameters Thermal Diffusivity Research Articles

Mechanical alloying of Co and P: Structural and photoacoustic studies

A mixture of elemental Co and P powders with nominal CoP3 composition was investigated by the mechanical alloying technique. For milling times greater than 26h, the measured x-ray diffraction (XRD) patterns revealed the coexistence of the skutterudite CoP3, the orthorhombic CoP, and Co2P phases. The structural and photoacoustic properties of as-milled powders were studied by the XRD and photoacoustic spectroscopy (PAS) techniques. The thermal diffusivity parameter of the as-milled sample was measured from fitting the PAS signal phase. The thermoelastic bending process is the main contribution to the PAS signal amplitude.

Thermal neutron diffusion cooling in wet quartz: (Monte Carlo simulations of the pulsed neutron experiments)

The thermal neutron diffusion parameters of a rock material depend on the rock matrix itself and on the water content. The effect has been studied in quartz by Monte Carlo (MC) simulations of the variable buckling experiment for nine series of samples. A hyperbolic dependence of the density-removed diffusion cooling coefficient on the water content shows a variability of this parameter by two orders of magnitude. The function obtained for wet quartz is compared with the analogous dependence for wet dolomite.

Thermal diffusivity and electron transport properties of NTC samples obtained by the photoacoustic method

Thermal diffusivity and electron transport parameters of sintered NTC samples were determined by the photoacoustic (PA) technique. Powder mixtures composed of MnO, NiO, CoO and Fe 2O 3 were milled to nanometer particle size. NTC discs were dry powder pressed and sintered at different temperatures in the range from 900 °C to 1300 °C for 30 min. A second group of NTC discs was sintered at 1200 °C with the sintering time varying from 30 min to 360 min. These NTC samples were polished and exposed to a chopped laser beam in order to plot a response in the acoustic range. The thermal diffusivity of sintered NTC layers based on a metal oxide powder mixture was measured at room temperature by the photoacoustic technique. An increase of thermal diffusivity with the sintering temperature and time of sintering was observed.

Invariant Solutions of the Thermal-Diffusion Equations for a Binary Mixture in the Case of Plane Motion

The group properties of the thermal-diffusion equations for a binary mixture in plane flow are studied. Optimal systems of first-and second-order subalgebras are constructed for the admissible Lie operator algebra, which is infinite-dimensional. Examples of the exact invariant solutions are given, which are found by solving ordinary differential equations. Exact solutions are found that describe thermal diffusion in an inclined layer with a free boundary and in a vertical layer in the presence of longitudinal temperature and concentration gradients. The effect of the thermal-diffusion parameter on the flow regime is studied.

Thermal neutron albedo and diffusion parameter measurements for monolithic and geometric voided reflectors

Experimental measurements of thermal neutron albedo ( β th ) and diffusion parameters have been carried out for monolithic as well as for water reflectors having spherical and cylindrical voids using Am–Be neutron source and BF 3 -detector. The measured saturation values of β th for monolithic water reflector has been found be 0.80 ± 0.024 , which is in good agreement with the corresponding value 0.81 quoted in the literature. In this case, the values of diffusion coefficient ( D ) and diffusion length ( L ) have been found to be 0.142 ± 0.021 and 2.57 ± 0.032 cm which are in good agreement with the standard values 0.144 and 2.755 cm, respectively. For water reflectors with spherical voids having 3.9 cm diameter, the saturation value of β th has been found to be 0.74 ± 0.018 and the values of D and L have been found to be 0.32 ± 0.043 and 4.39 ± 0.059 cm , respectively. In the case of a water reflector with cylindrical voids having diameter 2.54 cm and length 48 cm, the saturation value of β th and the values of D and L have been found, respectively, to be 0.74 ± 0.019 , 0.41 ± 0.034 , 5.79 ± 0.067 cm for parallel configuration and 0.78 ± 0.018 , 0.347 ± 0.028 , 4.22 ± 0.056 cm for the perpendicular configuration, respectively.

Investigation of the thermal diffusivity of thick film NTC layers obtained with the photoacoustic method

The thermal diffusivity of thick NTC layers based on a metal oxide powder mixture was measured at room temperature by the photoacoustic (PA) frequency transmission technique. The experimental PA amplitude and phase diagrams were numerically analyzed and the thermal diffusivity and electron transport parameters were calculated.

High conversion efficiency single-pass second harmonic generation in a zinc-diffused periodically poled lithium niobate waveguide

We report a modified technique for the fabrication of zinc-diffused channel waveguides using z-cut electric-field periodically poled LiNbO3. Unlike previous work, the diffusion was carried out using metallic zinc at atmospheric pressure. By optimizing the thermal diffusion parameters, channel waveguides that preserve the existing periodically poled domain structures, support both TE and TM modes, and enhance photorefractive damage resistance were obtained. Nonlinear characterisation of the channel waveguides was investigated via second harmonic generation of a 1552nm laser with a maximum conversion efficiency of 59%W-1cm-2 at 14.6 masculineC. Using a pulsed source a second harmonic conversion efficiency of 81% was achieved.

Variation of the thermal neutron diffusion cooling properties of wet rock material (Monte Carlo simulations of the pulsed neutron experiments)

The water content in a rock material can significantly change the thermal neutron diffusion parameters with respect to those of the dry medium. The effect has been studied for dolomite, CaMg(CO3)2, by Monte Carlo simulations of the variable buckling experiments for 10 series of samples. The density-removed diffusion cooling coefficient CM varies hyperbolically by two orders of magnitude with water content in the range of 0–20%.

Thermal-diffusion and diffusion-thermo effects on mixed free-forced convective flow and mass transfer over an accelerating surface with a heat source in the presence of suction and blowing in the case of variable viscosity

An analysis has been carried out to obtain the thermal-diffusion and the diffusion-thermo effects on the mixed free-forced convective and mass transfer steady laminar boundary-layer flow over an accelerating surface with a heat source in the presence of suction and blowing. The fluid viscosity is assumed to vary as an inverse linear function of temperature. The partial differential equations governing the problem under consideration have been transformed by a similarity transformation into a system of ordinary differential equations which is solved numerically by applying the shooting method. The results for an impermeable accelerating surface are discussed. The effects of the variable viscosity parameter θr, the thermal diffusion parameter Sr, the diffusion-thermo parameter Df, suction or blowing parameter m, heat flux parameter s and Schmidt number Sc have been examined on the flow field of a hydrogen-air mixture as a non-chemical reacting fluid pair. The effects of varying these parameters are studied in the case of a surface with prescribed wall temperature and a surface with prescribed wall heat flux.

Thermal diffusivity of NTC layers obtained with photoacoustic technique

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.

Multi Input Dynamical Modeling of Heat Flow With Uncertain Diffusivity Parameter

This paper focuses on the multi-input dynamical modeling of one-dimensional heat conduction process with uncertainty on thermal diffusivity parameter. Singular value decomposition is used to extract the most significant modes. The results of the spatiotemporal decomposition have been used in cooperation with Galerkin projection to obtain the set of ordinary differential equations, the solution of which synthesizes the temporal variables. The spatial properties have been generalized through a series of test cases and a low order model has been obtained. Since the value of the thermal diffusivity parameter is not known perfectly, the obtained model contains uncertainty. The paper describes how the uncertainty is modeled and how the boundary conditions are separated from the remaining terms of the dynamical equations. The results have been compared with those obtained through analytic solution.

DYNAMIC MODELING OF RETORT PROCESSING USING NEURAL NETWORKS

Two neural network approaches - a moving-window and hybrid neural network - which combine neural network with polynomial regression models, were used for modeling F(t) and Qv(t) dynamic functions under constant retort temperature processing. The dynamic functions involved six variables: retort temperature (116-132C), thermal diffusivity (1.5-2.3 x 10 -7 m 2 /s ), can radius (40-61 mm), can height (40-61 mm), and quality kinetic parameters z (15-39C) and D (150-250 min). A computer simulation designed for process calculations of food thermal processing systems was used to provide the fundamental data for training and generalization of ANN models. Training data and testing data were constructed by both second order central composite design and orthogonal array, respectively. The optimal configurations of ANN models were obtained by varying the number of hidden layers, number of neurons in hidden layer and learning runs, and a combination of learning rules and transfer function. Results demonstrated that both neural network models well described the F(t) and Qv(t) dynamic functions, but moving-window network had better modeling performance than the hybrid ANN models. By comparison of the configuration parameters, moving-window ANN models required more neurons in the hidden layer and more learning runs for training than the hybrid ANN models. Deux approches par reseaux neuronaux combines avec des modeles de regression polynomiaux sont utilisees pour modeliser les fonctions dynamiques F(t) et Qv(t) dans un procede d'autoclavage a temperature constante. Une simulation par ordinateur destinee aux calculs de procedes des systemes thermiques alimentaires est utilisee pour fournir les donnees fondamentales des modeles. Le reseau par fenetre mobile montre des performances de modelisation superieures a celles du modele hybride.

A generalized interpretation of buckling experiments for thermal neutrons

The buckling experiment is a well-known pulsed measurement method used to determine the thermal neutron diffusion parameters of a medium. In the classic form of the method, a dependence between the geometric buckling B 2 (in cm −2) and the thermal neutron time decay constant λ (in s −1) are involved. In the present paper, dimensionless values for the decay constant and for the buckling are introduced. This unification offers a method to generalize the description of the buckling experiment and makes it possible to compare experiments made for different media. The application of this procedure is exemplified on results for polyethylene of two different densities (from a Monte-Carlo-simulated experiment) and for Plexiglas (from a real laboratory experiment). The conclusion is that the buckling experiment is relatively easy for interpretation in the dimensionless buckling range which does not exceed 0.2. It corresponds, for example, to the geometric buckling B 2=1.1 cm −2 for polyethylene of density 0.57 g cm −3 or to B 2=3.0 cm −2 for polyethylene of density 0.95 g cm −3 .

Monte Carlo simulation of pulsed neutron experiments on samples of variable mass density

A method is presented to facilitate the interpretation of a pulsed neutron experiment (the variable geometric buckling experiment) when the mass densities of individual samples differ. A generalisation of the classic expression, which connects the fundamental mode decay constant to the thermal neutron diffusion parameters and to the geometrical buckling, is presented. The method has been tested (on polyethylene) by means of a computer simulation of the experiments. The simulation has been based on a Monte Carlo method, using the MCNP code. The described generalised buckling method is especially recommended for experiments with bulk materials.

Analysis of two-dimensional effect in the measurement of thermal diffusivity of thin films with an AC calorimetric method

An ac calorimetric method for measuring the thermal diffusivity of thin-film materials has been widely applied. In the application of this method, the systematic errors caused by the heat loss effect, the edge reflection effect, etc., have been analyzed and corresponding correction methods have been developed. But when measuring films with low thermal diffusivity or with thickness comparable to the thermal diffusion length, a two-dimensional effect which will also result in a systematic error of the measurement is present. In this paper, the mechanism of two-dimensional heat conduction within a thin sample which is supplied a periodic heat flux by a chopped light beam is analyzed. A numerical analysis method is developed to study the effect of the two-dimensional heat conduction on the measured thermal diffusivity values. The relations between the measured thermal diffusivity and independent parameters such as frequency, thickness of sample, width of light spot, etc., are demonstrated to indicate the two-dimensional effect. The experimental precondition for minimizing the systematic error caused by the two-dimensional effect is determined. In addition, the analysis method presented in this paper should be useful for more difficult problems such as error estimation of the thermal diffusivity measurement of coatings or composite films.

Robust optimal receding horizon control of the thermal sterilization of canned foods

Open loop optimal control strategies for the thermal sterilization of canned foods are computed and analysed. The optimal retort temperature profiles ensure that the required degree of sterilization is met whilst minimising costs. The costs are defined in terms of batch time and retention of nutrient value in the food material. The model is a finite dimensional approximation of the infinite dimensional system. The errors due to the finite dimensional approximation and the uncertainty in the thermal diffusivity parameter of the model are considered. Based on the analysis a closed loop receding horizon optimal controller is designed. Simulation experiments reveal the robustness of the receding horizon optimal controller with respect to uncertainty in the thermal diffusivity parameter. The simulations also reveal that the loss of performance is relatively small and that the batch-time may be reduced significantly.

A method to calculate thermal neutron diffusion parameters for hydrogenous mixtures

A comprehensive method is proposed to calculate the thermal neutron diffusion parameters for homogeneous mixtures of any non-multiplying non-crystalline compounds, in particular including hydrogenous substances. The macroscopic absorption, scattering, and transport cross sections of the mixture are defined generally as functions of the incident neutron energy. The energy-averaged neutron parameters can be calculated when the energy dependence and the thermal neutron energy distribution are known. For most substances the scattering cross section can be assumed as being almost constant in the thermal neutron region (which results from the free gas model). However, serious deviations are observed for hydrogen atoms bound in molecular systems. In the paper certain effective scattering cross sections are found in this case on the basis of individual accurate data for a few hydrogenous media. The macroscopic parameters calculated are averaged over the Maxwellian energy distribution for the thermal neutron flux. Results agree well with available data.

Sensitivity analysis of one-dimensional heat transfer in tissue with temperature-dependent perfusion.

Design criteria for implantable heat-generating devices such as the total artificial heart require the determination of safe thresholds for chronic heating. This involves in-vivo experiments in which tissue temperature distributions are obtained in response to known heat sources. Prior to experimental studies, simulation using a mathematical model can help optimize the design of experiments. In this paper, a theoretical analysis of heat transfer is presented that describes the dynamic, one-dimensional distribution of temperature from a heated surface. Loss of heat by perfusion is represented by temperature-independent and temperature-dependent terms that can reflect changes in local control of blood flow. Model simulations using physiologically appropriate parameter values indicate that the temperature elevation profile caused by a heated surface adjacent to tissue may extend several centimeters into the tissue. Furthermore, sensitivity analysis indicates the conditions under which temperature profiles are sensitive to changes in thermal diffusivity and perfusion parameters. This information provides the basis for estimation of model parameters in different tissues and for prediction of the thermal responses of these tissues.

Revised model calculations for the thermal histories of ordinary chondrite parent bodies

Abstract— Recent measurements of ordinary chondrite physical and thermal properties along with new geothermometry studies have provided the necessary parameters for updating a previously proposed model (Miyamoto et al., 1981) for the thermal evolution and internal structure of ordinary chondrite parent bodies. Model calculations assumed a heat source term derived from the decay of 26Al (justification is provided). Differences from the previous model include: varying the thermal diffusivity parameter with increasing temperature (and decreasing porosity), using variable physical and thermal parameters to provide end member models, and incorporating a shortened thermal history of 60 Ma (obtained from new Pb‐Pb chronology of phosphates) rather than 100 Ma. Times of isotopic closure in chondrite phosphates overlap the thermal model estimates, and postmetamorphic cooling rates from the model approximately coincide, in both trend and magnitude, with metallographic and fission track cooling rate data. Model calculations attempt to match peak metamorphic conditions in the central portions of these bodies and yield accretion ages between 1.4 to 3.1 Ma after calcium‐aluminum inclusion (CAI) formation. Model calculations also predict that both the H and the L chondrite parent asteroids consisted of ∼80% equilibrated and 20% unequilibrated chondritic material and that their original radii ranged from 80 to 95 km.

A NEURAL NETWORK APPROACH FOR THERMAL PROCESSING APPLICATIONS

The use of a neural network approach in thermal processing applications is presented. A four layer neural network with 3 inputs and 3 outputs was trained using a back-propagation algorithm. A finite difference computer program was used to predict nodal temperature responses of conduction heating model foods under thermal processing conditions. Equivalent lethality processes were obtained for a range of input variables (can size, food thermal diffusivity and kinetic parameters of quality factors) for sterilization temperatures between 110 and 134C (at 2C intervals). the computed optimum conditions and their associated quality changes were used as input variables for training and evaluation of the neural network. the trained network was found to predict optimal sterilization temperatures with an accuracy of ± 0.5C and other responses with less than 5% associated errors.