scholarly journals Identification of thermophysical characteristics of materials using heating probe

2016 ◽  
Vol 5 (1) ◽  
pp. 25 ◽  
Author(s):  
Abdelaziz Nasr ◽  
Abdulmajeed S. Al-Ghamdi ◽  
Mohammad S. Alsoufi
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Inverse Problem ◽  
Heat Capacity ◽  
Heat Transfer Coefficient ◽  
Cylindrical Sample ◽  
Heat Power ◽  
Volumetric Heat Capacity ◽  
Thermophysical Characteristics ◽  
The Heat Transfer Coefficient

This paper investigates the numerical analysis to determine the thermo-physical characteristics of materials. This method is based on a heating probe kept at a constant temperature and maintained in contact with a cylindrical sample. The heat power dissipated in the sample is measured by the probe. The results address to identify simultaneously the thermal conductivity, the volumetric heat capacity and the heat transfer coefficient using the inverse problem.

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.

Thermal Effectiveness of Multiple Shell and Tube Pass TEMA E Heat Exchangers

1988 ◽  
Vol 110 (1) ◽  
pp. 54-59 ◽  
Author(s):  
A. Pignotti ◽  
P. I. Tamborenea
Keyword(s):  
Heat Transfer ◽  
Heat Capacity ◽  
Heat Transfer Coefficient ◽  
Heat Exchangers ◽  
Rate Ratio ◽  
Algebraic Solution ◽  
Tube Heat Exchanger ◽  
Transverse Mixing ◽  
Shell And Tube ◽  
The Heat Transfer Coefficient

The thermal effectiveness of a TEMA E shell-and-tube heat exchanger, with one shell pass and an arbitrary number of tube passes, is determined under the usual symplifying assumptions of perfect transverse mixing of the shell fluid, no phase change, and temperature independence of the heat capacity rates and the heat transfer coefficient. A purely algebraic solution is obtained for the effectiveness as a function of the heat capacity rate ratio and the number of heat transfer units. The case with M shell passes and N tube passes is easily expressed in terms of the single-shell-pass case.

Inverse BEM Method to Identify Surface Temperatures and Heat Transfer Coefficient Distributions at Inaccessible Surfaces

2005 ◽  
Author(s):  
Alain J. Kassab ◽  
Eduardo A. Divo ◽  
Minking K. Chyu ◽  
Frank J. Cunha
Keyword(s):  
Heat Transfer ◽  
Inverse Problem ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Field Variable ◽  
Quadratic Functional ◽  
Two Dimensional ◽  
Additional Information ◽  
Coefficient Distribution ◽  
The Heat Transfer Coefficient

The purpose of the inverse problem considered in this study is to resolve heat transfer coefficient distributions by solving a steady-state inverse problem. Temperature measurements at interior locations supply the additional information that renders the inverse problem solvable. A regularized quadratic functional is defined to measure the deviation of computed temperatures from the values under current estimates of the heat transfer coefficient distribution at the surface exposed to convective heat transfer. The inverse problem is solved by minimizing this functional using a parallelized genetic algorithm (PGA) as the minimization algorithm and a two-dimensional multi-region boundary element method (BEM) heat conduction code as the field variable solver. Results are presented for a regular rectangular geometry and an irregular geometry representative of a blade trailing edge and demonstrate the success of the approach in retrieving accurate heat transfer coefficient distributions.

Forced Convection Heat Transfer of Nanofluids: A Review

2017 ◽  
Author(s):  
Aditya Kuchibhotla ◽  
Debjyoti Banerjee
Keyword(s):  
Heat Transfer ◽  
Experimental Data ◽  
Thermal Conductivity ◽  
Heat Capacity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Specific Heat ◽  
Forced Convection ◽  
Convection Heat Transfer ◽  
Convection Heat

Stable homogeneous colloidal suspensions of nanoparticles in a liquid solvents are termed as nanofluids. In this review the results for the forced convection heat transfer of nanofluids are gleaned from the literature reports. This study attempts to evaluate the experimental data in the literature for the efficacy of employing nanofluids as heat transfer fluids (HTF) and for Thermal Energy Storage (TES). The efficacy of nanofluids for improving the performance of compact heat exchangers were also explored. In addition to thermal conductivity and specific heat capacity the rheological behavior of nanofluids also play a significant role for various applications. The material properties of nanofluids are highly sensitive to small variations in synthesis protocols. Hence the scope of this review encompassed various sub-topics including: synthesis protocols for nanofluids, materials characterization, thermo-physical properties (thermal conductivity, viscosity, specific heat capacity), pressure drop and heat transfer coefficients under forced convection conditions. The measured values of heat transfer coefficient of the nanofluids varies with testing configuration i.e. flow regime, boundary condition and geometry. Furthermore, a review of the reported results on the effects of particle concentration, size, temperature is presented in this study. A brief discussion on the pros and cons of various models in the literature is also performed — especially pertaining to the reports on the anomalous enhancement in heat transfer coefficient of nanofluids. Furthermore, the experimental data in the literature indicate that the enhancement observed in heat transfer coefficient is incongruous compared to the level of thermal conductivity enhancement obtained in these studies. Plausible explanations for this incongruous behavior is explored in this review. A brief discussion on the applicability of conventional single phase convection correlations based on Newtonian rheological models for predicting the heat transfer characteristics of the nanofluids is also explored in this review (especially considering that nanofluids often display non-Newtonian rheology). Validity of various correlations reported in the literature that were developed from experiments, is also explored in this review. These comparisons were performed as a function of various parameters, such as, for the same mass flow rate, Reynolds number, mass averaged velocity and pumping power.

Thermal Tomography Using Experimental Measurement Data

2013 ◽  
Author(s):  
Jussi M. Toivanen ◽  
Ville Kolehmainen ◽  
Tanja Tarvainen ◽  
Janne Huttunen ◽  
Tuomo Savolainen ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Capacity ◽  
Heat Transfer Coefficient ◽  
Experimental Measurement ◽  
Measurement Data ◽  
Surface Heat ◽  
Thermal Tomography ◽  
Surface Heat Transfer Coefficient ◽  
Air Hole

Experimental measurement data is used to test the feasibility of thermal tomography. The 3D distributed thermal conductivity, heat capacity and surface heat transfer coefficient of a mortar target containing an air hole are estimated using measurement data obtained with a prototype thermal tomography measurement device.

Inverse analysis for the determination of heat transfer coefficient

2013 ◽  
Vol 91 (12) ◽  
pp. 1034-1043 ◽  
Author(s):  
Ali Fguiri ◽  
Naouel Daouas ◽  
M-Sassi Radhouani ◽  
Habib Ben Aissia
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Transfer Coefficient ◽  
Source Strength ◽  
Hot Wire ◽  
Source Power ◽  
Heating Source ◽  
The Heat Transfer Coefficient

The parallel hot wire technique is considered an effective and accurate means of experimental measurement of thermal conductivity. However, the assumptions of infinite medium and ideal infinitely thin and long heat source lead to some restrictions in the applicability of this technique. To make an effective experiment design, a numerical analysis should be carried out a priori, which requires a precise specification of the heating source strength and the heat transfer coefficient on the external surface. In this work, a more accurate physical and mathematical modeling of an experimental setup based on the parallel hot wire method is considered to estimate the two above-mentioned parameters from noisy temperature histories measured inside the material. Based on a sensitivity analysis, the heating source strength is estimated first using early time measurements. With such estimated value, determination of the heat transfer coefficient using temperatures measured at later times is then considered. The Levenberg–Marquardt (LM) method is successfully applied using a single experiment for the inverse solution of the two present parameter estimation problems. Estimates of this gradient-based deterministic method are validated with a stochastic method (Kalman filter). The effects of the measurement location, the heating duration, the measurement time step, and the LM parameter on the estimates and their associated confidence bounds are investigated. Used in the traditional fitting procedure of the parallel hot wire technique, the estimated heating source power provides a reasonable agreement between fitted and exact values of the thermal conductivity and the thermal diffusivity.

Steady State Heat Transfer Within a Nanoscale Spatial Domain

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Kirill V. Poletkin ◽  
Vladimir Kulish
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Steady State ◽  
Transfer Coefficient ◽  
Spatial Domain ◽  
Thermal Waves ◽  
Steady State Heat ◽  
Steady State Heat Transfer ◽  
The Heat Transfer Coefficient

In this paper, we study the steady state heat transfer process within a spatial domain of the transporting medium whose length is of the same order as the distance traveled by thermal waves. In this study, the thermal conductivity is defined as a function of a spatial variable. This is achieved by analyzing an effective thermal diffusivity that is used to match the transient temperature behavior in the case of heat wave propagation by the result obtained from the Fourier theory. Then, combining the defined size-dependent thermal conductivity with Fourier’s law allows us to study the behavior of the heat flux at nanoscale and predict that a decrease of the size of the transporting medium leads to an increase of the heat transfer coefficient which reaches its finite maximal value, contrary to the infinite value predicted by the classical theory. The upper limit value of the heat transfer coefficient is proportional to the ratio of the bulk value of the thermal conductivity to the characteristic length of thermal waves in the transporting medium.

Determination of the Thermal Conductivity of Metal-Polymers

2019 ◽  
Vol 973 ◽  
pp. 9-14 ◽  
Author(s):  
Mikhail S. Chepchurov ◽  
Nikolay S. Lubimyi ◽  
Vladimir P. Voronenko ◽  
Daniel R. Adeniyi
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Injection Molding ◽  
Transfer Coefficient ◽  
Cooling System ◽  
Using Data ◽  
Measuring Tool ◽  
The Heat Transfer Coefficient

The use of metal-polymers in the manufacture of mold-forming parts allows for the significant reduction in price and time used in manufacturing of parts. Using data on the thermal conductivity of metal-polymers in calculations of the cooling system of molds allows calculating the optimal cycle of obtaining the product. The authors propose a method of determining the coefficient of heat transfer of metal-polymers based on a die matrix, filled with aluminum. The chosen equipment or measuring tool by them, allows determining the heat transfer coefficient of the material in use. The values of the coefficient of heat transfer of the material in question, obtained in the course of the research can be use in different databases of applications used for modeling production by injection molding. The described method of determining the coefficient of heat transfer may be repeated for samples of metal-polymers.

Intertube Falling-Film Heat Transfer Behavior of Multiwall Carbon Nanotube Suspensions (MWCNT Nanofluids)

2011 ◽  
Author(s):  
Binglu Ruan ◽  
Anthony M. Jacobi
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Heat Transfer Coefficient ◽  
Ethylene Glycol ◽  
Multiwall Carbon Nanotube ◽  
Falling Film ◽  
Water Based ◽  
Film Heat Transfer ◽  
The Heat Transfer Coefficient ◽  
Multiwall Carbon

The thermal conductivity and viscosity of water-based and ethylene-glycol-based multiwall carbon nanotube (MWCNT) suspensions are measured for MWCNT volume concentrations up to 0.24%. The thermal conductivity is found to increase up to 8.6% and 9.3% for water-based and ethylene-glycol-based nanofluids, respectively. The viscosity of the nanofluids increases compared to that of their base fluids, with larger increases for the ethylene-glycol-based nanofluids. Intertube falling-film heat transfer characteristics of these nanofluids are measured and compared to data for the base fluids. The heat transfer coefficient of the water-based nanofluids decreases at low MWCNT concentrations but increases as the concentration increases. The heat transfer coefficient of the ethylene-glycol-based nanofluids decreases with an increase in MWCNT concentration, with a maximum deviation of 30%.

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