Simultaneous estimation of thermal conductivity and volumetric heat capacity for solid foods using sequential parameter estimation technique

2009 ◽  
Vol 42 (2) ◽  
pp. 231-236 ◽  
Author(s):  
Ibrahim O. Mohamed
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Parameter Estimation ◽  
Simultaneous Estimation ◽  
Estimation Technique ◽  
Volumetric Heat Capacity ◽  
Solid Foods

Estimating Two Parameters From Two Complementary Transient Experiments

2017 ◽  
Author(s):  
Robert L. McMasters ◽  
Filippo de Monte ◽  
James V. Beck
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Parameter Estimation ◽  
Estimation Method ◽  
Confidence Regions ◽  
Ordinary Least Squares ◽  
Temperature Measurements ◽  
Temperature History ◽  
Planar Geometry ◽  
Volumetric Heat Capacity

A desirable feature of any parameter estimation method is to obtain as much information as possible with one experiment. However, achieving multiple objectives with one experiment is often not possible. In the field of thermal parameter estimation, a determination of thermal conductivity, volumetric heat capacity, heat addition rate, surface emissivity and convection coefficient may be desired from a set of temperature measurements in an experiment where a radiant heat source is used. It would not be possible to determine all of these parameters from such an experiment; more information would be needed. The work presented in the present research shows how thermal parameters can be determined from temperature measurements using complementary experiments where the same material is tested more than once using a different geometry or heating configuration in each experiment. The method of ordinary least squares is used in order to fit a mathematical model to a temperature history in each case. Several examples are provided using one-dimensional conduction experiments, with some having a planar geometry and some having a cylindrical geometry. The parameters of interest in these examples are thermal conductivity and volumetric heat capacity. Both of these parameters cannot be determined simultaneously from one experiment but the practice of using two complementary experiments allows each of the parameters to be determined. An examination of confidence regions is an important topic in parameter estimation and this aspect of the procedure is addressed in the present work. A method is presented as part of the current research by which confidence regions can be found for results from a single analysis of multiple experiments.

Estimating Two Heat-Conduction Parameters From Two Complementary Transient Experiments

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Robert L. McMasters ◽  
Filippo de Monte ◽  
James V. Beck
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Parameter Estimation ◽  
Estimation Method ◽  
Confidence Regions ◽  
Ordinary Least Squares ◽  
Temperature Measurements ◽  
Temperature History ◽  
Planar Geometry ◽  
Volumetric Heat Capacity

A desirable feature of any parameter estimation method is to obtain as much information as possible with one experiment. However, achieving multiple objectives with one experiment is often not possible. In the field of thermal parameter estimation, a determination of thermal conductivity, volumetric heat capacity, heat addition rate, surface emissivity, and convection coefficient may be desired from a set of temperature measurements in an experiment where a radiant heat source is used. It would not be possible to determine all of these parameters from such an experiment; more information would be needed. The work presented in the present research shows how thermal parameters can be determined from temperature measurements using complementary experiments where the same material is tested more than once using a different geometry or heating configuration in each experiment. The method of ordinary least squares is used in order to fit a mathematical model to a temperature history in each case. Several examples are provided using one-dimensional conduction experiments, with some having a planar geometry and some having a cylindrical geometry. The parameters of interest in these examples are thermal conductivity and volumetric heat capacity. Sometimes, both of these parameters cannot be determined simultaneously from one experiment but utilizing two complementary experiments may allow each of the parameters to be determined. An examination of confidence regions is an important topic in parameter estimation and this aspect of the procedure is addressed in the present work. A method is presented as part of the current research by which confidence regions can be found for results from a single analysis of multiple experiments.

scholarly journals Testing a Gypsum Composite Based on Raw Gypsum with a Direct Admixture of Paraffin and Polymer to Improve Thermal Properties

Materials ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3241
Author(s):  
Krzysztof Powała ◽  
Andrzej Obraniak ◽  
Dariusz Heim
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Thermal Properties ◽  
Phase Change ◽  
Large Scale ◽  
Building Materials ◽  
Residential Buildings ◽  
Energy Performance ◽  
Polymer Content ◽  
Volumetric Heat Capacity

The implemented new legal regulations regarding thermal comfort, the energy performance of residential buildings, and proecological requirements require the design of new building materials, the use of which will improve the thermal efficiency of newly built and renovated buildings. Therefore, many companies producing building materials strive to improve the properties of their products by reducing the weight of the materials, increasing their mechanical properties, and improving their insulating properties. Currently, there are solutions in phase-change materials (PCM) production technology, such as microencapsulation, but its application on a large scale is extremely costly. This paper presents a solution to the abovementioned problem through the creation and testing of a composite, i.e., a new mixture of gypsum, paraffin, and polymer, which can be used in the production of plasterboard. The presented solution uses a material (PCM) which improves the thermal properties of the composite by taking advantage of the phase-change phenomenon. The study analyzes the influence of polymer content in the total mass of a composite in relation to its thermal conductivity, volumetric heat capacity, and diffusivity. Based on the results contained in this article, the best solution appears to be a mixture with 0.1% polymer content. It is definitely visible in the tests which use drying, hardening time, and paraffin absorption. It differs slightly from the best result in the thermal conductivity test, while it is comparable in terms of volumetric heat capacity and differs slightly from the best result in the thermal diffusivity test.

scholarly journals Using CPTs to derive thermal properties of soil

2020 ◽  
Vol 205 ◽  
pp. 04005
Author(s):  
Philip J. Vardon ◽  
Joek Peuchen
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Laboratory Tests ◽  
Field Investigation ◽  
Volumetric Heat Capacity ◽  
Cone Penetration ◽  
Cone Penetration Tests ◽  
Penetration Tests ◽  
Properties Of Soil

A method of utilizing cone penetration tests (CPTs) is presented which gives continuous profiles of both the in situ thermal conductivity and volumetric heat capacity, along with the in situ temperature, for the upper tens of meters of the ground. Correlations from standard CPT results (cone resistance, sleeve friction and pore pressure) are utilized for both thermal conductivity and volumetric heat capacity for saturated soil. These, in conjunction with point-wise thermal conductivity and in situ temperature results using a Thermal CPT (T-CPT), allow accurate continuous profiles to be derived. The CPT-based method is shown via a field investigation supported by laboratory tests to give accurate and robust results.

Effect of timeliness on the thermal properties of paraffin-based Al2O3 nanofluids

2019 ◽  
Vol 33 (05) ◽  
pp. 1950051
Author(s):  
Yangyang Wu ◽  
Baichao Wang ◽  
Dong Li ◽  
Changyu Liu
Keyword(s):  
Thermal Conductivity ◽  
Heat Capacity ◽  
Thermal Diffusivity ◽  
Specific Heat ◽  
Volume Concentration ◽  
Volume Fraction ◽  
Thermal Conversion ◽  
Volumetric Heat Capacity ◽  
Energy Storage Material ◽  
Over Time

Paraffin is an excellent photo-thermal conversion phase change energy storage material, and extensively used in the thermal storage field at the medium-low temperature. However, the low thermal conductivity of paraffin restricts its application in practice. Adding nanoparticles into paraffin is one of the effective methods to improve its thermal conductivity. Nevertheless, the thermal diffusivity, specific heat and volumetric heat capacity of paraffin as well as timeliness were affected after the addition of nanoparticles. In this paper, the influences of volume fraction of Al2O3 nanoparticle and timeliness on these thermal parameters of paraffin were investigated. The results show that the thermal conductivity of paraffin-based Al2O3 nanofluids increases first and then decreases with time, and the maximum thermal conductivity is 0.34 W/[Formula: see text] for volume fraction 1% on third day. The higher volume concentration, the lower specific heat and volumetric heat capacity, all present downtrend over time, until stable in the range of 0.3 MJ/[Formula: see text] and 0.4 MJ/[Formula: see text]. The average enhancement rate of specific heat and volumetric heat capacity are concentrates on −6% to 9%, −10% to 0%, respectively. While increasing the volume concentration, the thermal diffusivity has no obvious regularity, and presents undulatory property over time.

scholarly journals Evaluation of the reliability of building energy performance models for parameter estimation

2019 ◽  
Author(s):  
  Жулиан Берже ◽  
  Денис Дутых
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Capacity ◽  
Parameter Estimation ◽  
Heat Transfer Coefficient ◽  
Diffusion Equation ◽  
Heat Diffusion ◽  
Unknown Parameters ◽  
Heat Diffusion Equation ◽  
The Heat Transfer Coefficient

The fidelity of a model relies both on its accuracy to predict the physical phenomena and its capability to estimate unknown parameters using observations. This article focuses on this second aspect by analyzing the reliability of two mathematical models proposed in the literature for the simulation of heat losses through building walls. The first one, named DF, is the classical heat diffusion equation combined with the DuFort-Frankel numerical scheme. The second is the so-called RC lumped approach, based on a simple ordinary differential equation to compute the temperature within the wall. The reliability is evaluated following a two stages method. First, samples of observations are generated using a pseudo-spectral numerical model for the heat diffusion equation with known input parameters. The results are then modified by adding a noise to simulate experimental measurements. Then, for each sample of observation, the parameter estimation problem is solved using one of the two mathematical models. The reliability is assessed based on the accuracy of the approach to recover the unknown parameter. Three case studies are considered for the estimation of ( i ) the heat capacity, ( ii ) the thermal conductivity or ( iii ) the heat transfer coefficient at the interface between the wall and the ambient air. For all cases, the DF mathematical model has a very satisfactory reliability to estimate the unknown parameters without any bias. However, the RC model lacks of fidelity and reliability. The error on the estimated parameter can reach 40% for the heat capacity, 80% for the thermal conductivity and 450% for the heat transfer coefficient.

Sign in / Sign up

Export Citation Format

Share Document