Estimation Of Thermophysical Properties Research Articles

Robust experiment design for the estimation of thermophysical parameters using stochastic algorithms

This numerical study deals with the design of experiments. It aims at optimizing thermocouple positions in order to reduce uncertainties in the estimation of thermophysical properties when an inverse method is applied. The 2D system under investigation is a squared sample of orthotropic material submitted to a constant heat flux on left and bottom edges. The temperature response is given by three sensors. The unknown parameters are the volumetric thermal capacity and the conductivities in the two principal directions. The experiment design is based on an original optimality criterion. Two stochastic algorithms are used to find its minimum and their efficiency is compared to a pure random search algorithm. To deal with the fact that the experiment design depends on the unknowns, a robust optimization approach is proposed.

Predictive methods for the estimation of thermophysical properties of ionic liquids

While the design of products and processes involving ionic liquids (ILs) requires knowledge of the thermophysical properties for these compounds, the massive number of possible distinct ILs precludes their detailed experimental characterization. To overcome this limitation, chemists and engineers must rely on predictive models that are able to generate reliable values for these properties, from the knowledge of the structure of the IL. A large body of literature was developed in the last decade for this purpose, aiming at developing predictive models for thermophysical and transport properties of ILs. A critical review of those models is reported here. The modelling approaches are discussed and suggestions relative to the current best methodologies for the prediction of each property are presented. Since most of the these works date from the last 5 years, this field can still be considered to be in its infancy. Consequently, this work also aims at highlighting major gaps in both existing data and modelling approaches, identifying unbeaten tracks and promising paths for further development in this area.

Estimation of thermophysical properties of dimethyl ether as a commercial refrigerant based on artificial neural networks

In this research, the ability of Multilayer Perceptron Artificial Neural Networks based on back-propagation algorithm has been investigated to estimate dimethyl ether (RE 170) densities and vapor pressures. The best network configuration for this case was determined as a three layers network including 12, 15, 1 neurons in its layers, respectively, using Levenberg–Marquardt training algorithm. The comparisons between results show that there is a good agreement between experimental data and network predictions. As the uncertainties in the presented network for prediction of and saturated liquid, densities are less than 0.04% and 0.16%, respectively. Comparisons among the ANN predictions, several equations of state, and experimental data sets show that the ANN results are in good agreement with the experimental data better than EoSs. Another network for estimation of vapor pressure has been trained with uncertainty less than 0.85%. Results prove that artificial neural network can be a successful tool to represent thermophysical properties effectively, if develops efficiently.

An inverse problem based on genetic algorithm to estimate thermophysical properties of fouling

In the past few decades, the study on how to apply genetic algorithms to problems in the industrial engineering world has aroused a great deal of curiosity of many researchers in the area of management science, industrial operations and engineering systems. This paper shows an experimental process of thermophysical properties estimation of fouling deposited on internal surface of a heat exchanger tube using genetic algorithms. In brief, the deposits on heat exchanger tubes are caused by the presence of inorganic salts, of small quantities of organic materials and products of corrosion in the water. From thermophysical point of view, the deposited fouling has harmful effects on the heat exchanger efficiency. For these reasons the determination of its thermophysical properties became very important. The experimental bench using a photothermal method with a finite width pulse heat excitation is used. The genetic algorithm is used to minimize an objective function containing a calculated and a measured temperature. This last is measured on the rear face of a bi-layer system composed of a section of a heat exchanger and the fouling deposited on during and after a finite width pulse heat excitation on its front face. The calculated temperature, that is a function of the unknown thermophysical properties of the bi-layer system, is calculated by the resolution of the one-dimensional linear inverse conduction problem, and by the use of the thermal quadrupoles formalism. The motivation in using genetic algorithms was their potential to overcome the restriction to the estimation of non-correlated parameters of gradient-based methods, and their powerful ability to work well for many complex problems which are very difficult to solve by conventional techniques. The results of the estimation procedure show on the one hand the efficiency and the stability of the developed genetic algorithm to estimate the thermophysical properties of fouling and the high accuracy of the obtained results on the other hand.

Integrated Process Modeling and Product Design of Biodiesel Manufacturing

Biodiesel, i.e., a mixture of fatty acid methyl esters (FAMEs), produced from reacting triglyceride with methanol by alkali-catalyzed transesterification, has attracted much attention as an important renewable energy source. To aid in the optimization of biodiesel manufacturing, a number of published studies have applied commercial process simulators to quantify the effects of operating conditions on the process performance. Significantly, all of the reported simulation models are design models for new processes by fixing some level of equipment performance such as the conversion of transesterification reaction. Most models assume the feed oil as pure triolein and the biodiesel fuel as pure methyl oleate, and pay insufficient attention to the feed oil characterization, thermophysical property estimation, rigorous reaction kinetics, phase equilibrium for separation and purification units, and prediction of essential biodiesel fuel qualities. This paper presents first a comprehensive review of published lit...

Factual data banks and their application to the synthesis and design of chemical processes and the development and testing of thermophysical property estimation methods

Abstract Factual data banks nowadays play an important role as a source for thermophysical property data for use in chemical process simulation, environmental models, and many other computer-based applications. In this work, the historical developments leading to modern factual data banks, the differences compared to other more bibliographically oriented data banks, and their most important applications and future potential will be discussed by using the example of the Dortmund Data Bank (DDB). As the development of the different predictive models for mixtures is covered in a separate publication, this paper focuses on pure-component property estimation, regression of model parameters, test and verification of model parameters prior to process simulation, and advanced topics in process synthesis such as selection of entrainers and data-mining applications.

Estimation of thermophysical properties using natural signal analysis with heat and moisture transfer model

Conduction heat transfer through opaque envelope components characterizes the thermal performance of buildings and its consequences in terms of energy consumption and thermal comfort. A building envelope can be thermally described by two parameters: thermal conductivity ( λ) and heat capacity ( ρ· c). Estimating these thermal properties in situ allows the characterization of real building elements considering different aspects, such as thermal behavior under specific weather conditions, quality variability in materials, local construction technologies and material deterioration. This paper presents a method to estimate the thermal conductivity and volumetric heat capacity of a homogeneous element using a non-destructive test considering natural oscillations. Surface temperature and heat flow are measured in a concrete sample (with known thermal properties) and the data is treated with a signal processing technique. Estimation is carried out with a heat and moisture transfer model. Measurements were performed on six separate days under different sky conditions within a period of one month, to determine the importance of solar radiation as a heat source. Results gave acceptable estimates (average inaccuracy of 10–14%) of both thermophysical properties.

Estimation of Thermophysical Properties in Massive ZrCoHx System

Thermophysical properties of the complex metal hydride system such as zirconium cobalt hydride, an intermetallic hydride compound, in a massive state were estimated by introducing a crystal lattice structure in a stepwise formation and applying a mixing rule for each property. Experimental data in rarity in metal hydride system was used to calculate and to correlate the consistency of the mixed thermal and physical properties of the complex atomic structure in a unit cell. As a result, the volume expansion of the ZrCoHx was greatly influenced by the hydrogen content and increased to a maximum range of 36% at ZrCoH3 system, but no meaning in the thermal expansion in engineering concept. In consideration of the heat capacity the temperature effect due to the hydrogen—an interstitial heat quantity—in the metal complex formation was mainly attributed, but not much for the hydrogen content (H/ZrCo ratio). In the temperature range between 200K and 600K the heat capacity of hydrogen atom was taken into account to reveal a sharp discrepancy in its non-hydriding property, especially in the lower temperature range. Atomic hydrogen was expected to behave from a gas to a solid property in heat capacity in the temperature ranges from 600K to 200K.

Estimation of thermophysical properties of fouling using inverse problem and its impact on heat transfer efficiency

At high temperature, the circulation of fluid in heat exchangers provides a tendency for fouling accumulation to take place on the internal surface of tubes. In brief, the deposits on heat exchanger tubes are caused by the presence of inorganic salts, of small quantities of organic materials and products of corrosion in the water. From thermophysical point of view, the deposited fouling has harmful effects on the heat exchanger efficiency. Indeed, it increases the thermal resistance which can raise the energy consumption. This study shows an experimental and a theoretical process of estimation of thermophysical properties of the fouling deposited on a section of a heat exchanger and its effects on the heat transfer efficiency. The estimation method is based on the Gauss–Newton algorithm that minimizes the ordinary least squares function comparing a measured temperature and a theoretical one. The temperature response is measured on the rear face of a bi-layer system composed of a section of a heat exchanger and the fouling deposited on during and after a finite width pulse heat flux on its front face. The theoretical temperature, that is a function of the unknown thermophysical properties of the bi-layer system, is calculated by the resolution of the one-dimensional linear inverse conduction problem, and by the use of the quadrupole formalism. The results of the estimation procedure show, on the one hand the efficiency and the stability of the optimization algorithm to estimate the thermophysical properties of the fouling. On the other hand they underline the necessity of the maintenance of fluid circulating tubes at high temperature.

Measurement and estimation of thermophysical properties of nickel based superalloys

Thermophysical properties for the solid and liquid phases of several Ni based superalloys (CMSX-4, CMSX-10, CM186LC, IN 738 and Rene 80) have been measured. The following properties were measured: heat capacity and enthalpy, thermal expansion coefficient and density, thermal diffusivity, viscosity and surface tension. Analysis of these measurements showed that that γ′ phase (Ni3Al) affected the values for the following properties; Cp, enthalpy, electrical resistivity, thermal diffusivity and conductivity. Relationships have been identified between properties and the γ′ phase content (which can be represented by mass% Al in the alloy). These relations were then used to calculate property values of the alloys from chemical composition. Other relations were developed to estimate the viscosities and surface tensions of Ni based superalloys. The predicted property values were found to be in good agreement with the measured values.

Potential Approaches Toward Characterization and Property Estimation of Heavy Petroleum Fluids and Natural Gas Systems

In this article, difficulties in accurate estimation of thermophysical properties of heavy petroleum fluids and natural gas systems through conventional methods are discussed. Potential approaches in characterization of such systems that use direct measurable properties of mixtures are investigated. It is shown that properties such as velocities of sound and light and dipole moment might be appropriate properties to measure for characterization and property estimation of heavy petroleum fluids.

Resolution of an inverse heat conduction problem with a nonlinear least square method in the Hankel space. Application to photothermal infrared thermography

Integral transforms (Laplace, Fourier, Hankel) are widely used to solve the heat diffusion equation. Moreover, it often appears relevant to realize the estimation of thermophysical properties in the transformed space. Here, an analytical model has been developed, leading to a well-posed inverse problem of parameter identification. Two black coatings, a thin black paint layer and an amorphous carbon film, were studied by photothermal infrared thermography. A Hankel transform has been applied on both thermal model and data and the estimation of thermal diffusivity has been achieved in the Hankel space. The inverse problem is formulated as a non-linear least square problem and a Gauss-Newton algorithm is used for the parameter identification.

Estimation of thermophysical properties of fluids under high pressure from speed of sound measurements

The thermophysical properties of pure substances in fluid state as functions of temperature and pressure are of great interest not only for industrial applications (for example in the oil and gas industry), but also for fundamental aspects in view of developing models for an accurate representation of dense fluids. Now these measurements are difficult to perform under pressure, particularly for non single‐phase systems, at atmospheric pressure. An interesting alternative consists in using the ultrasonic velocity which can be determined experimentally with a high degree of accuracy including at high pressures and high temperatures, and which presents the advantage of giving access to various derived properties. This potential, which is specific to ultrasonic velocity in fluids, has been the starting point for the investigation of a large number of pure liquids and gases as well as of several types of mixtures by ultrasonic measurements. In this work we will review the procedures used to evaluate thermophys...

Estimation of thermophysical properties by an inverse method with experimentally determined heating region of a thin-layer heater

This paper deals with the problem of estimation of thermophysical parameters by an inverse method. The thermal conductivity in radial and axial direction of a cylindrical sample and the heat capacity were simultaneously estimated using the Levenberg–Marquardt method of minimizing a mean square functional. As heat sources the thin-layer heater KHR 2/10 of diameter ϕ = 50 mm and thickness 0.20 mm made by OMEGA as well as the Kanthal resistance wire of diameter ϕ = 0.1 mm in a form of semicircle were simultaneously used. The main aim of using these two heaters simultaneously, both placed at one of the sample interfaces, was to generate heat fluxes in axial and additionally in radial direction. However, measurements of temperature distribution on the main surface of the thin-layer heater by using the FLIR Systems (ThermaCAM SC 3000 infrared camera) revealed a spatial heterogeneity of its temperature field, and therefore it was necessary to determine the effective heating region of that heater indispensable for solving of the coefficient inverse problem of heat conduction.

An Efficient Simultaneous Estimation of Temperature-Dependent Thermophysical Properties

In this paper we derive the first-order and second-order one-step GPS applied to the estimation of thermophysical properties. Solving the resultant al- gebraic equations, which usually converges within ten iterations, it is not difficult to estimate the unknown temperature-dependent thermal conductivityand heat ca- pacity simultaneously, if some supplemented data of measured temperature at a time T is provided. When the measured temperature in the conducting slab is contami- nated by noise, our estimated results are also good. The newmethod doesnotrequireany priorinformationon the functional forms of thermal conductivityand heat capac- ity. Numerical examples are examined to show that the new approaches, namely the one-step estimation method (OSEM), have high accuracy and efficiency even there are only few measured data. keyword: One-step Group preserving scheme, Inverse heat conduction problem, Estimation of thermophysical properties.

Estimation of thermophysical properties of moist materials under different drying conditions

This article deals with the solution for the inverse problem of simultaneously estimating moisture content and temperature-dependent moisture diffusivity, together with thermal conductivity, heat capacity, density, and phase conversion factor of a drying body as well as boundary condition coefficients, by using only temperature measurements. Two different physical problems, convective and contact drying, are examined and compared. The present parameter estimation problem is solved with the Levenberg–Marquardt method of minimization of the least-squares norm, by using simulated experimental data. The temperature responses during the drying are obtained with a numerical solution of the non-linear one-dimensional Luikov's equations. As a representative drying body, a mixture of bentonite and quartz sand with known thermophysical properties has been chosen. Analyses of the sensitivity coefficients and of the determinant of the information matrix are presented.

Application of inverse concepts to drying

This paper deals with the application of inverse approaches to estimation of drying body parameters. Simultaneous estimation of the thermo physical properties of a drying body as well as the heat and mass transfer coefficients, by using only temperature measurements, is analyzed. A mathematical model of the drying process has been developed, where the moisture content and temperature fields in the drying body are expressed by a system of two coupled partial differential equations. For the estimation of the unknown parameters, the transient readings of a single temperature sensor located in an infinite flat plate, exposed to convective drying, have been used. The Levenberg-Marquardt method and a hybrid optimization method of minimization of the least-squares norm are used to solve the present parameter estimation problem. An analysis of the influence of the drying air velocity, drying air temperature, drying body dimension, and drying time on the thermophysical properties estimation, that enables the design of the proper experiments by using the so-called D-optimum criterion was conducted. In order to perform this analysis, the sensitivity coefficients and the sensitivity matrix determinant were calculated for the characteristic drying regimes and the drying body dimensions.

An inverse method to estimate thermophysical properties of foods at freezing temperatures: apparent volumetric specific heat

A new approach for the estimation of thermophysical properties of foods at freezing temperatures was explored, analysed and discussed. Semi-empirical formulae were considered for predicting thermophysical properties. Assuming a known function for apparent volumetric specific heat in the freezing temperature range, a simple heat transfer experiment was designed to estimate the unknown parameters. Temperature versus time was recorded at the bottom in the model food undergoing one-dimensional freezing. By solving the partial differential equation with a finite difference scheme coupled with an optimisation technique, parameters were obtained that provide the best least square fit between the experimental and predicted time–temperatures curves. The accuracy of this new methodology was validated using Tylose MH-1000 as a model food. Statistical analysis showed no significant differences between reported and estimated curves. Determined parameters agreed well with values reported in the literature. The determination of thermophysical properties from an inverse method is an attractive technique both from the experimental and methodological point of view.

A new Corresponding States model for the estimation of thermophysical properties of long chain n-alkanes

The interest in phase equilibrium and thermophysical properties of mixtures containing long chain hydrocarbons is increasing. Despite the industrial interest of these systems, the available experimental data are scarce, while new models are required. Corresponding States Theory has been used with success for the estimation of properties of pure components and mixtures of small molecules. This work shows how this theory can be extended to the evaluation of liquid density, vapour pressure and viscosity of long chain molecules in a broad temperature range, based on information of lower members of the same homologous series. Results for the n-alkane series showed that this new model is able to predict liquid density, vapour pressure and viscosity with percent average absolute deviations of 0.44, 0.52, and 3.15%, respectively.

520 生体内部物性値推定に関する逆問題数値シミュレーション

520 生体内部物性値推定に関する逆問題数値シミュレーション