A Novel Method to Simultaneously Identify Temperature-Dependent Thermal Properties and Verification

2019 ◽  
Vol 12 (4) ◽  
Author(s):  
Weizhen Pan ◽  
Fajun Yi ◽  
Lijun Zhuo ◽  
Songhe Meng
Keyword(s):  
Thermal Properties ◽  
Measurement Errors ◽  
Temperature Data ◽  
Random Errors ◽  
Temperature Dependent ◽  
Simulation Experiments ◽  
Marquardt Method ◽  
Inverse Heat Transfer ◽  
Novel Method ◽  
Transfer Problems

Abstract A novel method for the identification of thermal conductivity and specific heat capacity simultaneously by solving inverse heat transfer problems (IHTPs) is proposed. The present method uses a new iterative format of the Levenberg–Marquardt method (LMM) and guarantees global convergence by implementing the subsection identification method. Both simulation and real experiments are conducted to prove the validity and practicability of the proposed method. The thermal properties in simulation and real experiments are identified, respectively, by the proposed method. In the simulation experiments, random errors are added into temperature data to survey the effect of measurement errors on the identification; and the deviations of the results are also compared to that in a published literature to show the superiority of the proposed method. The numerical results illustrate that the identification is accurate and stable. And the identification results of the real experiment are compared with measured ones, proving the practicability of the method.

Grain Temperature-Dependent Thermal Properties Estimation Using FI-QPSO Algorithm

2021 ◽  
Author(s):  
Hongmei Xu ◽  
Juan Liu ◽  
Kun Wang ◽  
Songtao Kong ◽  
Yong Shi
Keyword(s):  
Particle Swarm Optimization ◽  
Thermal Properties ◽  
Measurement Errors ◽  
Fuzzy Inference ◽  
Quantum Particle ◽  
Estimation Method ◽  
Particle Swarm ◽  
Temperature Dependent ◽  
Swarm Optimization ◽  
Quantum Particle Swarm Optimization

Abstract A hybrid fuzzy inference-quantum particle swarm optimization (FI-QPSO) algorithm is developed to estimate the temperature-dependent thermal properties of grain. The fuzzy inference scheme is established to determine the contraction-expansion coefficient according to the aggregation degree of particles. The heat transfer process in the grain bulk is solved using the finite element method (FEM), and the estimation task is formulated as an inverse problem. Numerical experiments are performed to study the effects of the surface heat flux, number of measurement points, measurement errors and the individual space on the estimation results. Comparison with the quantum particle swarm optimization (QPSO) algorithm and conjugate gradient method (CGM) is also conducted, and it shows the validity of the estimation method established in this paper.

scholarly journals Application of RC delay time for estimation of thermal properties

2021 ◽  
Vol 2116 (1) ◽  
pp. 012111
Author(s):  
Priyanka Jena ◽  
Rajesh Gupta
Keyword(s):  
Heat Transfer ◽  
Stainless Steel ◽  
Thermal Properties ◽  
Delay Time ◽  
Thermal System ◽  
Inverse Heat Transfer ◽  
Conductivity Range ◽  
Rc Circuit ◽  
Transfer Problems ◽  
Rc Delay

Abstract The analogy between the electrical and thermal system has been extensively used to solve different kinds of direct heat transfer problems. However, this analogy has not been explored much to obtain solutions of inverse heat transfer problems like estimation of thermal properties. This paper presents an approach of estimation of thermal properties using the correspondence between the thermal and electrical domains by exploiting the concept of RC delay time in the resistance-capacitance (RC) circuit. Simulations and experiments have been performed on stainless steel and glass samples to show the applicability of the proposed approach for materials belonging to different conductivity range.

Theoretical Modeling of Cutting Temperature Distribution by Considering the Material Thermal Properties as Functions of Temperature

2011 ◽  
Author(s):  
Zheng Kang ◽  
Xia Ji ◽  
Xueping Zhang ◽  
Steven Y. Liang
Keyword(s):  
Thermal Properties ◽  
Temperature Distribution ◽  
Heat Source ◽  
Cutting Temperature ◽  
Temperature Data ◽  
Temperature Elevation ◽  
Temperature Dependent ◽  
Final Temperature ◽  
Plane Symmetric ◽  
Set Up

To better predict the temperature distribution in the tool and chip, a modified theoretical model by considering material thermal properties as temperature dependent is developed to quantitatively describe the temperature elevation due to the shear and friction at the tool-chip interface. Work’s thermal properties of thermal conductivity and specific heat are modified and considered as functions of temperature. The semi-infinite method is utilized in the model, in which the back of the chip and the shear band are assumed as adiabatic. Temperature distribution in the tool and chip is then determined simultaneously by shear and friction. An imaginary heat source is set up to be plane-symmetric with respect to each original heat source in this approach. The effects of original heat source and imaginary heat source are superimposed to calculate the final temperature elevation in the tool and chip. To determine the ratio of total heat transferred into the chip and the tool, it is assumed that the temperatures in the tool and in the chip are in balance along the tool-chip interface in the stable cutting state. The model is experimentally validated with peak temperature data from previous literature. Results indicate that the model-experiment deviation is less than 10% when thermal properties are considered temperature dependent, and it is more accurate than that by considering the thermal properties as constants. The patterns of temperature distribution in the tool and chip are further analyzed by the model.

Complete Characterization of Thermoelectric Materials by a Combined van der Pauw Approach and the Effect of Radiation Losses

2011 ◽  
Vol 1314 ◽  
Author(s):  
Johannes de Boor ◽  
Volker Schmidt
Keyword(s):  
Thermal Conductivity ◽  
Measurement Errors ◽  
Conductivity Measurement ◽  
Short Review ◽  
Complete Characterization ◽  
Radiative Heat Loss ◽  
Radiation Losses ◽  
Novel Method ◽  
Simple Estimation ◽  
Van Der Pauw

AbstractWe have recently presented a novel method for a complete thermoelectric characterization [J. de Boor, V. Schmidt. Adv. Mater. 22:4303, (2010)]. This method is based on the well-known electrical van der Pauw method and allows measurement of the electrical and thermal conductivity, the Seebeck coefficient and the thermoelectric figure of merit. After a short review of this method we will discuss the systematic measurement errors of the method. It turns out that radiative heat loss can affect the thermal conductivity measurement significantly. We will give a simple estimation for the relative error due to radiation losses and discuss error minimizing strategies.

scholarly journals A Novel Method for the Complex Tube System Reconstruction and Measurement

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2207
Author(s):  
Xiang Guo ◽  
Xin Su ◽  
Yingtao Yuan ◽  
Tao Suo ◽  
Yan Liu
Keyword(s):  
Neural Network ◽  
Minimum Distance ◽  
Technical Difficulty ◽  
Industry Structure ◽  
Tube System ◽  
Simulation Experiments ◽  
Pipe System ◽  
System Reconstruction ◽  
Novel Method ◽  
Assembly Error

Pipe structures are at the base of the entire industry. In the industry structure, heat and vibration are transmitted in each pipe. The minimum distance between each pipe is significant to the security. The assembly error and the deformation of the pipeline positions after multiple runs are significant problems. The reconstruction of the multi-pipe system is a critical technical difficulty in the complex tube system. In this paper, a new method for the multi-pipes structure inspection is presented. Images of the tube system are acquired from several positions. The photogrammetry technology calculates positions, and the necessary coordination of the structure is reconstructed. A convolution neural network is utilized to detect edges of tube-features. The new algorithm for tube identification and reconstruction is presented to extract the tube feature in the image and reconstruct the 3D parameters of all tubes in a multi-pipes structure. The accuracy of the algorithm is verified by simulation experiments. An actual engine of the aircraft is measured to verify the proposed method.

Analysis of Tempering and Rehardening for Grinding of Hardened Steels

1991 ◽  
Vol 113 (4) ◽  
pp. 388-394 ◽  
Author(s):  
O. B. Fedoseev ◽  
S. Malkin
Keyword(s):  
Thermal Properties ◽  
Heat Source ◽  
Hardened Steel ◽  
Temperature History ◽  
Hardness Distribution ◽  
Temperature Dependent ◽  
Thermally Activated ◽  
Reaction Equations ◽  
Rate Controlling Step ◽  
Good Agreement

An analysis is presented to predict the hardness distribution in the subsurface of hardened steel due to tempering and rehardening associated with high temperatures generated in grinding. The grinding temperatures are modeled with a triangular heat source at the grinding zone and temperature-dependent thermal properties. The temperature history, including the effect of multiple grinding passes, is coupled with thermally activated reaction equations for tempering and for reaustenitization which is the rate controlling step in rehardening. Experimental results from the literature are found to be in good agreement with the analytical predictions.

scholarly journals The Effect of Random Error in Exposure Measurement upon the Shape of the Exposure Response

Dose-Response ◽  
2005 ◽  
Vol 3 (4) ◽  
pp. dose-response.0 ◽  
Author(s):  
Kenny S. Crump
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Epidemiological Data ◽  
Epidemiological Studies ◽  
Random Errors ◽  
Exposure Measurement ◽  
Considerable Uncertainty ◽  
Exposure Response ◽  
Log Normal ◽  
Normally Distributed

Although statistical analyses of epidemiological data usually treat the exposure variable as being known without error, estimated exposures in epidemiological studies often involve considerable uncertainty. This paper investigates the theoretical effect of random errors in exposure measurement upon the observed shape of the exposure response. The model utilized assumes that true exposures are log-normally distributed, and multiplicative measurement errors are also log-normally distributed and independent of the true exposures. Under these conditions it is shown that whenever the true exposure response is proportional to exposure to a power r, the observed exposure response is proportional to exposure to a power K, where K < r. This implies that the observed exposure response exaggerates risk, and by arbitrarily large amounts, at sufficiently small exposures. It also follows that a truly linear exposure response will appear to be supra-linear—i.e., a linear function of exposure raised to the K-th power, where K is less than 1.0. These conclusions hold generally under the stated log-normal assumptions whenever there is any amount of measurement error, including, in particular, when the measurement error is unbiased either in the natural or log scales. Equations are provided that express the observed exposure response in terms of the parameters of the underlying log-normal distribution. A limited investigation suggests that these conclusions do not depend upon the log-normal assumptions, but hold more widely. Because of this problem, in addition to other problems in exposure measurement, shapes of exposure responses derived empirically from epidemiological data should be treated very cautiously. In particular, one should be cautious in concluding that the true exposure response is supra-linear on the basis of an observed supra-linear form.

Sign in / Sign up

Export Citation Format

Share Document