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Journal articles on the topic 'Thermal parameters identification'

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Author: Grafiati

Published: 13 April 2024

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1

Whalley, R., and D. Mitchell. "The identification of engineering system parameters." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 211, no. 1 (February 1, 1997): 1–14. http://dx.doi.org/10.1243/0959651971539641.

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A procedure enabling the identification of the mass/inertia, damping and stiffness matrices for mechanical systems or the analogous inductance, resistance and capacitance matrices for electrical, fluid or thermal systems from measured results is developed. Analytical constraints that are mandatory are defined. Illustrative examples are provided.

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2

Rose, L., and A. Menzel. "Identification of thermal material parameters for thermo-mechanically coupled material models." Meccanica 56, no. 2 (January 18, 2021): 393–416. http://dx.doi.org/10.1007/s11012-020-01267-2.

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AbstractThe possibility of accurately identifying thermal material parameters on the basis of a simple tension test is presented, using a parameter identification framework for thermo-mechanically coupled material models on the basis of full field displacement and temperature field measurements. Main objective is to show the impact of the material model formulation on the results of such an identification with respect to accuracy and uniqueness of the result. To do so, and as a proof of concept, the data of two different experiments is used. One experiment including cooling of the specimen, due to ambient temperature, and one without specimen cooling. The main constitutive relations of two basic material models are summarised (associated and non-associated plasticity), whereas both models are extended so as to introduce an additional material parameter for the thermodynamically consistent scaling of dissipated energy. The chosen models are subjected to two parameter identifications each, using the data of either experiment and focusing on the determination of thermal material parameters. The influence of the predicted dissipated energy of the models on the identification process is investigated showing that a specific material model formulation must be chosen carefully. The material model with associated evolution equations used within this work does neither allow a unique identification result, nor is any of the solutions for the underlying material parameters close to literature values. In contrast to that, a stable, that is locally unique, re-identification of the literature values is possible for the boundary problem at hand if the model with non-associated evolution equation is used and if cooling is included in the experimental data.

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3

Garmendia, Iñaki, and Eva Anglada. "Thermal parameters identification in the correlation of spacecraft thermal models against thermal test results." Acta Astronautica 191 (February 2022): 270–78. http://dx.doi.org/10.1016/j.actaastro.2021.11.025.

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4

Bouache, T., K. Limam, and W. Bosschaerts. "New thermal parameters identification approach applied to the thermal renovation of buildings." Energy and Buildings 104 (October 2015): 156–64. http://dx.doi.org/10.1016/j.enbuild.2015.06.077.

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5

Monika, Božiková, Hlaváč Petr, Híreš Ľubomír, Hlaváčová Zuzana, Valach Michal, Vozárová Vlasta, and Malínek Martin. "Temperature effect on various biooils physical parameters." Research in Agricultural Engineering 63, No. 4 (December 7, 2017): 145–51. http://dx.doi.org/10.17221/60/2015-rae.

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The article deals with thermal and rheological properties of two selected biooils (PL 64S – sample No. 1, and PL 04N – sample No. 2). For thermal parameters measurements, Hot wire method was used, for detection of rheological parameters rheometer Anton Paar MCR 102 was used and the density was measured by densimeter DM 40. For both biooil samples, two series of thermophysical parameters measurements were made. In the first series thermal conductivity and thermal diffusivity were measured at constant laboratory temperature. The second series was focused on identification of thermophysical parameters changes during temperature stabilisation. The parameters as dynamic viscosity, kinematic viscosity and density were measured in the temperature range (20–50°C). For samples with constant temperature basic statistical characteristics were calculated – standard deviation and probable error in %. For relations of thermal and rheological parameters to temperature nonlinear dependencies were obtained. The polynomial functions of the second degree were used for thermal parameters and exponential functions for rheological parameters.

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6

Ghafiri, Abdelaaziz, Jamal Chaoufi, Claude Vallee, El Hanafi Arjdal, Jean Christophe Dupre, Arnaud Germaneau, Kossi Atchonouglo, and Hassan Fatmaoui. "Identification of Thermal Parameters by Treating the Inverse Problem." International Journal of Computer Applications 87, no. 11 (February 14, 2014): 1–5. http://dx.doi.org/10.5120/15249-3719.

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7

SAKAGAMI, Takahide, Daisuke IMANISHI, and Shiro KUBO. "301 Identification of Defect Parameters by Thermal Response Spectroscopy." Proceedings of The Computational Mechanics Conference 2005.18 (2005): 131–32. http://dx.doi.org/10.1299/jsmecmd.2005.18.131.

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8

Matiašovský, Peter. "The equivalent thermal parameters, their analytical and experimental identification." Solar Energy Materials and Solar Cells 27, no. 2 (July 1992): 119–26. http://dx.doi.org/10.1016/0927-0248(92)90114-5.

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9

Liu, G. R., J. H. Lee, A. T. Patera, Z. L. Yang, and K. Y. Lam. "Inverse identification of thermal parameters using reduced-basis method." Computer Methods in Applied Mechanics and Engineering 194, no. 27-29 (July 2005): 3090–107. http://dx.doi.org/10.1016/j.cma.2004.08.003.

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10

Bondarchuk, Ivan, Valery Perevozkin, Sergey Bondarchuk, and Alexander Vorozhtsov. "Identification of the Kinetic Parameters of Thermal Micro-organisms Inactivation." Applied Sciences 12, no. 22 (November 12, 2022): 11505. http://dx.doi.org/10.3390/app122211505.

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A mathematical model for estimating the characteristics of the process of thermal inactivation of vegetative bacterial cells and their spores is presented. The model relates the change rate of the number of living cells as a nonlinear kinetic dependence of the p-th order, and the temperature constant of their inactivation rate is the Arrhenius function. A method for solving the inverse kinetic problem of identifying the parameters of this model from experimental data is proposed. The method is implemented through the minimization of the original functional, which reduces the number of variable parameters. The solution results of inverse problems for determining the kinetic model parameters based on the experimental data of thermal inactivation of bacterial spores B. subtilis and B. anthracis are presented. The obtained parameters are used to solve the direct problems of the dynamics of micro-organism inactivation. The calculation results represent the dependence on the time of the change number of inactivated micro-organisms, and the thermal exposure time for 99% of their deaths at different temperatures. A comparison of the results with other authors’ calculations and experimental data confirms the adequacy of the model, the high accuracy of the new solution method and the algorithm for its implementation. The developed model of thermal sterilization can be used for the selective deactivation of pathogens in the food products.

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11

De Wit, M. S. "Identification of the important parameters in thermal building simulation models." Journal of Statistical Computation and Simulation 57, no. 1-4 (April 1997): 305–20. http://dx.doi.org/10.1080/00949659708811814.

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12

Atchonouglo, K., M. Banna, C. Vallée, and J. C. Dupré. "Inverse transient heat conduction problems and identification of thermal parameters." Heat and Mass Transfer 45, no. 1 (April 23, 2008): 23–29. http://dx.doi.org/10.1007/s00231-008-0383-7.

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13

Kler, Aleksandr, Vitalii Alekseiuk, and Aleksei Maksimov. "An improved technique for identification of mathematical model parameters of thermal power equipment and assessment of its performance." E3S Web of Conferences 114 (2019): 06009. http://dx.doi.org/10.1051/e3sconf/201911406009.

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The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes a technique improved by the author for identification (adjustment, verification) of mathematical model parameters for complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. An improved technique for identification of mathematical model parameters was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit and an example of the optimization calculation of the real operation condition in order to reduce specific fuel consumption for electricity generation. In addition, the paper discusses an issue of assessing the identification accuracy of mathematical model parameters of thermal power equipment that depends on the accuracy of measurements of control parameters used to adjust the model, as well as on the correctness of the mathematical model construction and the calculation technique applied.

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14

Nissing, Dirk, Arindam Mahanta, and Stefan van Sterkenburg. "Thermal Model Parameter Identification of a Lithium Battery." Journal of Control Science and Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/9543781.

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The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS) take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities) can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.

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15

Alekseiuk, Vitalii. "Improving the Efficiency of the Three-Stage Technique of Mathematical Model Identification of Complex Thermal Power Equipment." E3S Web of Conferences 209 (2020): 03002. http://dx.doi.org/10.1051/e3sconf/202020903002.

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The problems of state estimation of thermal power system operation and identification of mathematical model parameters have not been acceptably solved due to the complexity of studied objects and their mathematical models, and the lack of effective methods, algorithms and computer programs to solve the required mathematical problems. The results of solving the indicated problems are of importance as such, and play a great part in the qualitative solution to the problems of thermal power equipment control, e.g., the problems of optimal load dispatch among thermal power plant units and optimal control of thermal power equipment operation conditions. The paper describes an effective three-stage technique of mathematical model identification of complex thermal power equipment. The technique allows us to more effectively detect gross errors in measurements of control parameters used for identification of the mathematical model of the studied equipment, to evaluate correctness and rectify errors in the mathematical model construction, and to improve identification accuracy. The article presents a new formulation of the optimization problem for more efficient identification of mathematical models of heat power equipment. An effective three-stage technique of mathematical model identification of complex thermal power equipment was tested on a detailed mathematical model of the present-day 225 MW generating unit that was constructed by the author. The paper presents results of solving the identification problem of mathematical model parameters of a generating unit.

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16

Jiang, Dong, Yu Xu, Donghui Zhu, and Zhifu Cao. "Temperature-dependent thermo-elastic parameter identification for composites using thermal modal data." Advances in Mechanical Engineering 11, no. 10 (October 2019): 168781401988416. http://dx.doi.org/10.1177/1687814019884165.

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To accurately determine the temperature-dependent parameters of composites, a thermo-elastic parameter identification approach using thermal modal data is proposed in this article. The investigation is based on two hypotheses: (1) the structure is at steady-state temperature field, which means the temperature distribution is time independent; (2) temperature distribution can be determined in advance of thermo-elastic parameter identification, and thermal-related large deformation is not considered. The thermal-dependent elastic constants and thermal expansion coefficients are expressed as intermediate functions with the independent variable of temperature, perturbation method is adapted to calculate the sensitivity of thermal modal frequencies with respect to the intermediate variables, and variables with high sensitivity are selected as the identifying parameters. By constructing the intermediate function and calculating the relative sensitivity, thermo-elastic parameters are identified by minimizing the residual between experimental and analytical natural frequencies under thermal circumstance. Two different types of composite models are employed to verify the strategies of parameter identification. Results show that on the basis of the intermediate function, the proposed approach can be applied to identify the thermo-elastic parameters effectively.

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17

Allegre, J. M., C. Marchand, and A. Razek. "Identification of thermal parameters in a coupled magnetic-thermal model with the experimental designs method." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 17, no. 3 (1998): 331–36. http://dx.doi.org/10.1108/03321649810203242.

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18

Díaz - Salgado, Jorge, Sandra García - López, Yuridiana R. Galindo - Luna, and R. J. Romero. "Parametric Identification Method for an Absorption Air Conditioning Parabolic Trough Collector Solar Plant." International Journal of Basic and Applied Sciences 9, no. 4 (December 23, 2020): 01. http://dx.doi.org/10.14419/ijbas.v9i4.31273.

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In this work is established a parametric identification method for an absorption air conditioning solar plant. A scaled thermal plant, consisting of a thermal capacitor and a flow line that acts as a capacitor and thermal energy radiator is used. As the mathematical model of the scaled plant is structurally identical to that of the solar plant the first is used to determine the methodology that can be used later for the identification of the PTC solar plant. Parametric identification is a necessary step that allows to determine the unknown parameters of the mathematical model of any solar/thermal plant. This model then can be used to analyze the plant characteristics and design an appropriate control algorithm. Although the system model is nonlinear it can be expressed in the form of a linear regressor in the parameters. This permits to use the least squares method as the identification method. The method is applied to the thermal plant to identify the useful form that the covariance matrix and excitation signals should have to ensure that when applied to the solar plant its unknown parameters can be properly estimated. Once the solar plant parameters are properly estimated model can be used to analyze and simulate the operation of the absorption air conditioning system.

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19

Díaz-Salgado, Jorge, S. García - López, Y. R. Galindo - Luna, and R. J. Romero. "Parametric identification method for an absorption air conditioning parabolic trough collector solar plant." International Journal of Basic and Applied Sciences 12, no. 1 (December 20, 2023): 14–21. http://dx.doi.org/10.14419/k81wh647.

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In this work is established a parametric identification method for an absorption air conditioning solar plant. A scaled thermal plant, consisting of a thermal capacitor and a flow line that acts as a capacitor and thermal energy radiator is used. As the mathematical model of the scaled plant is structurally identical to that of the solar plant the first is used to determine the methodology that can be used later for the identification of the PTC solar plant. Parametric identification is a necessary step that allows to determine the unknown parameters of the mathematical model of any solar/thermal plant. This model then can be used to analyze the plant characteristics and design an appropriate control algorithm. Although the system model is nonlin-ear it can be expressed in the form of a linear regressor in the parameters. This permits to use the least squares method as the identification method. The method is applied to the thermal plant to identify the useful form that the covariance matrix and excitation signals should have to ensure that when applied to the solar plant its unknown parameters can be properly estimated. Once the solar plant parameters are properly estimated model can be used to analyze and simulate the operation of the ab-sorption air conditioning system.

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20

Wang, Xuan, XiaoFeng Zhang, Feng Zhou, and Xiang Xu. "Infrared Technology-Based Sensor Data Analysis for Thermal Fault Identification of Electrical Equipment in Intelligent Substations." Mobile Information Systems 2022 (September 30, 2022): 1–10. http://dx.doi.org/10.1155/2022/1710962.

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The electrical equipment of intelligent substation cannot deal with the problem of load mutation, and the load adjustment is not timely, which leads to the poor performance of thermal fault identification of electrical equipment. Therefore, a study on thermal fault identification of the electrical equipment of intelligent substation based on infrared technology is proposed. First, under the background of infrared technology, according to the thermal fault feature extraction model of substation electrical equipment, the principle of double station cross location is proposed; combined with the sampling results of thermal fault characteristic parameters of electrical equipment in intelligent substation, the thermal fault characteristics are analyzed; through the process of thermal fault identification of electrical equipment in intelligent substation, the preliminary classification structure of thermal fault is obtained and the thermal fault identification is completed. The experimental results show that the designed method has good performance of thermal fault identification, high output stability, better identification effect after optimization, and highly sensitive identification ability.

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21

Božiková, Monika, Peter Hlaváč, Vlasta Vozárová, Zuzana Hlaváčová, Ľubomír Kubík, Peter Kotoulek, and Ján Brindza. "Thermal properties of selected bee products." Progress in Agricultural Engineering Sciences 14, s1 (July 2018): 37–44. http://dx.doi.org/10.1556/446.14.2018.s1.4.

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Knowledge of bee products’ physical properties has a decisive importance for the monitoring of their quality. Thermophysical parameters are very important properties. Thermal conductivity and thermal diffusivity of selected bee products (honey, bee pollen and perga) were measured by two different methods. For identification of thermal conductivity and thermal diffusivity transient methods were used: Hot Wire (HW) and Dynamic Plane Source (DPS) method with an instrument Isomet 2104. The principle of measuring process is based on the analysis of timetemperature relation. In the first series of measurements thermal conductivity and diffusivity at constant laboratory temperature of 20 °C were measured. The second series was focused on identification of the changes in the thermophysical parameters during temperature stabilisation in the temperature range of 5–25 °C. For samples with constant temperature standard deviations and probable errors in % were calculated. For relations of thermal parameters to temperature graphical dependencies were obtained. Two different thermophysical methods were used for improvement of data reliability and data statistics.

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22

Zhang, Y. Z., S. G. Wang, S. Jiang, J. H. Wang, X. Z. Wu, and T. F. Zhang. "Investigation of performance parameters of building thermal battery." E3S Web of Conferences 356 (2022): 01025. http://dx.doi.org/10.1051/e3sconf/202235601025.

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The concept of a building thermal battery refers to storing the supplied heat and releasing it the another time through radiation and convection. The introduction of building thermal battery performance has created a more convenient solution to the problems of building load estimation, control and optimization, building-grid integration, etc. Some literatures have expanded the original definition of building thermal batteries, including PV RE (photovoltaic renewable energy), HVAC and other units. Starting from the building body, this investigation studies a building energy system. With reference to the performance parameters of traditional rechargeable batteries, the corresponding performance parameters of building thermal batteries are developed. The RC model is further used to model the performance parameters of the building thermal battery respectively. Among them, the corresponding parameter values of the RC model are obtained by parameter identification. Finally, the heat storage and heat release characteristics of the building integrated energy system are obtained. It makes the application of buildings as batteries more flexible in the urban energy network.

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23

Majchrzak, Ewa, and Bohdan Mochnacki. "Identification of Thermal Properties of the System Casting-Mould." Materials Science Forum 539-543 (March 2007): 2491–96. http://dx.doi.org/10.4028/www.scientific.net/msf.539-543.2491.

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In the paper the problem of casting and mould thermophysical parameters identification is discussed. So, it is assumed that in the mathematical model describing the thermal processes in the system considered the selected parameter (or parameters) is unknown. On the basis of additional information concerning the cooling (heating) curves at the selected set of points the unknown parameter can be found. The inverse problem is solved using the least squares criterion in which the sensitivity coefficients are applied. On the stage of numerical simulation the boundary element method is used. In the final part of the paper the examples of computations are shown.

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24

NEACȘU, Marian-Iulian. "Optimization of Thermal Treatment Parameters for the Alloy AlZn4.5Mg1." Annals of “Dunarea de Jos” University of Galati. Fascicle IX, Metallurgy and Materials Science 46, no. 4 (December 15, 2023): 31–36. http://dx.doi.org/10.35219/mms.2023.4.05.

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The paper presents the method of finding the optimal variant of thermal processing through artificial aging that is applied to a non-ferrous aluminum-based alloy.The criterion based on which the optimum for the thermal process of artificial aging is obtained is that of the minimum consumption of energy consumed with the heat treatment furnace.With the help of MATLAB, we created a graphic interface for the calculation simulation of the energy consumed by the treatment furnace depending on the process parameters and the identification of the optimal variant.

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25

Nenarokomov, Aleksey V., Leonid A. Dombrovsky, Irina V. Krainova, Oleg M. Alifanov, and Sergey A. Budnik. "Identification of radiative heat transfer parameters in multilayer thermal insulation of spacecraft." International Journal of Numerical Methods for Heat & Fluid Flow 27, no. 3 (March 6, 2017): 598–614. http://dx.doi.org/10.1108/hff-03-2016-0136.

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Purpose The purpose of this study is to optimize multilayer vacuum thermal insulation (MLI) of modern high-weight spacecrafts. An adequate mathematical simulation of heat transfer in the MLI is impossible if there is no available information on the main insulation properties. Design/methodology/approach The results of experiments in thermo-vacuum facilities are used to re-estimate some radiative properties of metallic foil/metalized polymer foil and spacer on the basis of the inverse problem solution. The experiments were carried out for the sample of real MLI used for the BP-Colombo satellite (ESA). The recently developed theoretical model based on neglecting possible near-field effects in radiative heat transfer between closely spaced aluminum foils was used in theoretical predictions of heat transfer through the MLI. Findings A comparison of the computational results and the experimental data confirms that there are no significant near-field effects between the neighboring MLI layers. It means that there is no considerable contradiction between the far-field model of radiative transfer in MLI and the experimental estimates. Originality/value An identification procedure for mathematical model of the multilayer thermal insulation showed that a modified theoretical model developed recently can be used to estimate thermal properties of the insulation at conditions of space vacuum.

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26

Fernández, Antoni Bancells. "Identification of tissue and therapy parameters from surface temperature." Journal of Physics: Conference Series 2444, no. 1 (February 1, 2023): 012015. http://dx.doi.org/10.1088/1742-6596/2444/1/012015.

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Abstract The temperature distribution of human body tissues, when electromagnetic waves are applied, is studied with the help of the bioheat equation, which is characterised by several thermal parameters, such as thermal conductivity, perfusion frequency or metabolic heat. There are also electromagnetic parameters, such as electrical conductivity and dielectric constant. Besides, therapy parameters, such as the applied power should be considered. If the values of all these parameters are known, the time evolution of the temperature can be determined. Some of these values can be found in specialised databases, and others are unknown but approximate values can be obtained by reasonable estimations. The outcome of simulations depends heavily on the parameter values. Surface temperature helps in providing better estimates of the parameter values. Once these parameters are identified, medical analyses can be performed to assess the dosimetry of the radiation so that it does not damage tissues, for example. The surface temperature is obtained from a sequence of thermographic images. Based on these experimental data, an algorithm is applied to find the values of the needed parameters. The model is simulated iteratively, adjusting the parameters at each step, reducing the approximation error between the simulation and the data. This is an optimization problem that belongs to the realm of inverse problems. It can be solved using techniques based on the gradient concept, however, this problem can be ill-conditioned, so probabilistic or evolutionary algorithms are also used. In this paper, the simulation is made using a method based on Legendre wavelets. It is proposed that the subsequent optimization is made using an evolutionary algorithm, that has shown great robustness in the problems where it has been applied. As far as known, it has never been applied to the bioheat equation. This is the aim of this work.

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Gontijo, Danúbia Lucas Meira, Rafael Yuri Medeiros Barbosa, Rodrigo Sislian, and Rubens Gedraite. "Parameters identification associated with artichoke pâté thermal diffusivity via finite volume element method." OBSERVATÓRIO DE LA ECONOMÍA LATINOAMERICANA 22, no. 2 (February 28, 2024): e3522. http://dx.doi.org/10.55905/oelv22n2-247.

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The sterilization operation traditionally used in the food industry has been known for a long time and is still widely used in the conservation of canned food products. Knowledge of the value of the heat transport property thermal diffusivity is very important to define the required heat treatment time and to allow better control of the process in the face of variations in the temperature of the autoclave. This work presents the mathematical model that was developed and tested in the matlab/simulink™ application to estimate the value of thermal diffusivity. The model was used to simulate the temperature behavior of the studied food product based on a value identified for the thermal diffusivity. The results obtained were validated by comparison with those available in the literature and showed good adherence to the latter, with deviations of less than 5ºC in the worst case.

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TSE, OLIVER, RENÉ PINNAU, and NORBERT SIEDOW. "IDENTIFICATION OF TEMPERATURE-DEPENDENT PARAMETERS IN LASER-INTERSTITIAL THERMO THERAPY." Mathematical Models and Methods in Applied Sciences 22, no. 09 (July 31, 2012): 1250019. http://dx.doi.org/10.1142/s0218202512500194.

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Laser-induced thermotherapy (LITT) is an established minimally invasive percutaneous technique of tumor ablation. Nevertheless, there is a need to predict the effect of laser applications and optimize irradiation planning in LITT. Optical attributes (attenuation, absorption, scattering) change due to thermal denaturation. The work presents the possibility to identify these temperature-dependent parameters from given temperature measurements via an optimal control problem. The solvability of the optimal control problem is analyzed and results of successful implementations are shown.

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29

Wang, Xiaoguang, Weiliang He, and Linggong Zhao. "Interval Identification of Thermal Parameters Using Trigonometric Series Surrogate Model and Unbiased Estimation Method." Applied Sciences 10, no. 4 (February 20, 2020): 1429. http://dx.doi.org/10.3390/app10041429.

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Metal-foam materials have been applied in many engineering fields in virtue of its high specific strength and desirable of thermodynamic properties. However, due to the inherent uncertainty of its attribute parameters, reliable analysis results are often ambiguous to obtain accurately. To overcome this drawback, this paper proposes a novel interval parameter identification method. Firstly, a novel modelling methodology is proposed to simulate the geometry of engineering metal foams. Subsequently, the concept of intervals is introduced to represent the uncertainty relationship between variables and responses in heat transfer systems. To improve computational efficiency, a novel augmented trigonometric series surrogate model is constructed. Moreover, unbiased estimation methods based on different probability distributions are presented to describe system measurement intervals. Then, a multi-level optimization-based identification strategy is proposed to seek the parameter interval efficiently. Eventually, an engineering heat transfer system is given to verify the feasibility of the proposed parameter identification method. This method can rapidly identify the unknown parameters of the system. The identification results demonstrate that this interval parameter identification method can quantify the uncertainty of a metal-foam structure in engineering heat transfer systems efficiently, especially for the actual case without sufficient measurements.

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Zaika, Yury V., Nickolay I. Sidorov, and Olga V. Fomkina. "Identification of hydrogen permeability and thermal desorption parameters of vanadium-based membrane." International Journal of Hydrogen Energy 46, no. 18 (March 2021): 10789–800. http://dx.doi.org/10.1016/j.ijhydene.2020.12.176.

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31

Sdid, M. S. N., and M. E. H. Benbouzid. "H-G diagram based rotor parameters identification for induction motors thermal monitoring." IEEE Transactions on Energy Conversion 15, no. 1 (March 2000): 14–18. http://dx.doi.org/10.1109/60.849110.

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32

Imanishi, D., T. Sakagami, and S. Kubo. "810 Identification of Defect Parameters by Thermal Response Spectroscopic Inverse Analysis Scheme." Proceedings of Conference of Kansai Branch 2007.82 (2007): _8–10_. http://dx.doi.org/10.1299/jsmekansai.2007.82._8-10_.

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33

SAKAGAMI, Takahide, Daisuke IMANISHI, and Shiro KUBO. "2834 Identification of Defect Parameters by Thermal Response Spectroscopic Inverse Analysis Scheme." Proceedings of the JSME annual meeting 2006.1 (2006): 317–18. http://dx.doi.org/10.1299/jsmemecjo.2006.1.0_317.

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34

Dilhaire, Stefan, Stéphane Grauby, Wilfrid Claeys, and Jean-Christophe Batsale. "Thermal parameters identification of micrometric layers of microelectronic devices by thermoreflectance microscopy." Microelectronics Journal 35, no. 10 (October 2004): 811–16. http://dx.doi.org/10.1016/j.mejo.2004.06.012.

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Schroeder, Steffen, Bernd Kauschinger, Arvid Hellmich, Steffen Ihlenfeldt, and Damien Phetsinorath. "Identification of relevant parameters for the metrological adjustment of thermal machine models." International Journal on Interactive Design and Manufacturing (IJIDeM) 13, no. 3 (January 29, 2019): 873–83. http://dx.doi.org/10.1007/s12008-019-00529-y.

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Zhou, Mengmeng, Huimin Xie, and Luming Li. "Constitutive parameters identification of thermal barrier coatings using the virtual fields method." Acta Mechanica Sinica 35, no. 1 (August 29, 2018): 78–87. http://dx.doi.org/10.1007/s10409-018-0787-7.

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Han, Zongwei, Biao Li, Changming Ma, Honghao Hu, and Chenguang Bai. "Study on accurate identification of soil thermal properties under different experimental parameters." Energy and Buildings 164 (April 2018): 21–32. http://dx.doi.org/10.1016/j.enbuild.2017.12.067.

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Ma, Han, Zhiyong Tan, Qiang Chen, Yanbin Li, and Qingguo Fei. "Output-only identification of time-varying structural modal parameters under thermal environment." Structures 63 (May 2024): 106338. http://dx.doi.org/10.1016/j.istruc.2024.106338.

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Hu, Yuh-Chung, Ping-Jung Chen, and Pei-Zen Chang. "Thermal-Feature System Identification for a Machine Tool Spindle." Sensors 19, no. 5 (March 9, 2019): 1209. http://dx.doi.org/10.3390/s19051209.

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The internal temperature is an important index for the prevention and maintenance of a spindle. However, the temperature inside the spindle is undetectable directly because there is no space to embed a temperature sensor, and drilling holes will reduce its mechanical stiffness. Therefore, it is worthwhile understanding the thermal-feature of a spindle. This article presents a methodology to identify the thermal-feature model of an externally driven spindle. The methodology contains self-made hardware of the temperature sensing and wireless transmission module (TSWTM) and software for the system identification (SID); the TSWTM acquires the temperature training data, while the SID identifies the parameters of the thermal-feature model of the spindle. Then the resulting thermal-feature model is written into the firmware of the TSWTM to give it the capability of accurately calculating the internal temperature of the spindle from its surface temperature during the operation, or predicting its temperature at various speeds. The thermal-feature of the externally driven spindle is modeled by a linearly time-invariant state-space model whose parameters are identified by the SID, which integrates the command “n4sid” provided by the System ID Toolbox of MATLAB and the k-fold cross-validation that is common in machine learning. The present SID can effectively strike a balance between the bias and variance of the model, such that both under-fitting and over-fitting can be avoided. The resulting thermal-feature model can not only predict the temperature of the spindle rotating at various speeds but can also calculate the internal temperature of the spindle from its surface temperature. Its validation accuracy is higher than 98.5%. This article illustrates the feasibility of accurately calculating the internal temperature (undetectable directly) of the spindle from its surface temperature (detectable directly).

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Jin, Quan Lin, and Yan Shu Zhang. "Parameter Identification of Thermal Visco-Plastic Model Considering Dynamic Recrystallization." Materials Science Forum 561-565 (October 2007): 1869–74. http://dx.doi.org/10.4028/www.scientific.net/msf.561-565.1869.

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A hybrid global optimization method combining the Real-coded genetic algorithm and some classical local optimization methods is constructed and applied to develop a special program for parameter identification. Finally, the parameter identification for both 26Cr2Ni4MoV steel and AZ31D magnesium alloy is carried out by using the program. A comparison of deformation test and numerical simulation shows that the parameter identification and the obtained two sets of material parameters are all available.

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Pokorska-Silva, Iwona, Artur Nowoświat, and Lidia Fedorowicz. "Identification of thermal parameters of a building envelope based on the cooling process of a building object." Journal of Building Physics 43, no. 6 (October 11, 2019): 503–27. http://dx.doi.org/10.1177/1744259119881167.

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Thermal properties of building envelopes are often described using thermal conductivity or thermal resistance. And the opposite task involves the identification of thermal parameters of building envelopes based on the measurements of their cooling process. In this article, the authors proposed a method of identifying thermal parameters of a building envelope based on cooling measurements, using a multiple regression model for this purpose. To satisfy the research objectives, two basic experiments were carried out. The first experiment was performed in laboratory conditions. The research model was a cube of the dimensions of 1.1 m × 1.1 m × 1.1 m. The second experiment was carried out in semi-real conditions, and the used model was a small house of the dimensions of 6.0 m × 4.15 m × 5.2 m. The measurement results were also used to calibrate numerical models made in the ESP-r program. The research studies have demonstrated that the model can be used to identify thermal parameters of a building envelope. Based on the measurements and simulations, the cooling equations of the object were determined and the 95% confidence interval for the heat retention index was estimated. On that basis, using the multiple regression model, such parameters of the model as density, specific heat, and thermal conductivity were estimated. It turned out that using the Gauss–Newton approximation, we obtained the correlation of the measurement results and the analytical model with the correlation coefficient of 0.9971 (for the laboratory scale). And the multiple regression improved not only the correlation between the measurement and the analytical model, but it also allowed to obtain “almost identical” results. Similarly, promising results were obtained for the semi-real scale.

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Du, Hongze, Qi Xu, Lizhe Jiang, Yufeng Bu, Wenbo Li, and Jun Yan. "Stepwise Identification Method of Thermal Load for Box Structure Based on Deep Learning." Materials 17, no. 2 (January 10, 2024): 357. http://dx.doi.org/10.3390/ma17020357.

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Accurate and rapid thermal load identification based on limited measurement points is crucial for spacecraft on-orbit monitoring. This study proposes a stepwise identification method based on deep learning for identifying structural thermal loads that efficiently map the local responses and overall thermal load of a box structure. To determine the location and magnitude of the thermal load accurately, the proposed method segments a structure into several subregions and applies a cascade of deep learning models to gradually reduce the solution domain. The generalization ability of the model is significantly enhanced by the inclusion of boundary conditions in the deep learning models. In this study, a large simulated dataset was generated by varying the load application position and intensity for each sample. The input variables encompass a small set of structural displacements, while the outputs include parameters related to the thermal load, such as the position and magnitude of the load. Ablation experiments are conducted to validate the effectiveness of this approach. The results show that this method reduces the identification error of the thermal load parameters by more than 45% compared with a single deep learning network. The proposed method holds promise for optimizing the design and analysis of spacecraft structures, contributing to improved performance and reliability in future space missions.

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Majchrzak, E., J. Mendakiewicz, and A. Piasecka Belkhayat. "Algorithm of the mould thermal parameters identification in the system casting–mould–environment." Journal of Materials Processing Technology 164-165 (May 2005): 1544–49. http://dx.doi.org/10.1016/j.jmatprotec.2005.02.021.

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Bakkouri, A. El, S. Boussaid, H. Ezbakhe, T. Ajzoul, and A. El Bouardi. "Méthode générale d'identification paramétrique : application a l'étude thermophysique de quelques matériaux locaux utilisés dans la construction au maroc (platre - liège - brique creuse)." Canadian Journal of Civil Engineering 27, no. 4 (August 1, 2000): 628–31. http://dx.doi.org/10.1139/l00-011.

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The research for habitat comfort conditions goes through a better knowledge of the thermal behavior of materials for building surfaces subject to thermal perturbations. This paper presents a general method for the simultaneous identification of the thermal diffusivity a and of the surface transfer coefficients, one for the irradiated face h0 and one for the non-irradiated face he, of a single-layer or multi-layer building surface. The experimental technique used, which is called box method, is based on the exploitation of the experimental thermograph of the non-irradiated face. The results of the identification are given for several construction materials (hollow brick, plaster, cork). The noteworthy influence of the number of parameters to identify is also exposed.Key words: Construction and insulation materials, measure and identification, thermal diffusivity, thermal loss coefficients.

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Strąkowska, Maria, Gilbert De Mey, and Bogusław Więcek. "Identification of the Thermal Constants of the DPL Heat Transfer Model of a Single Layer Porous Material." Pomiary Automatyka Robotyka 25, no. 2 (June 30, 2021): 41–46. http://dx.doi.org/10.14313/par_240/41.

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This paper deals with parameters’ identification of the Dual Phase Lag (DPL) thermal model of a 3D printed porous materials. The experiments were performed for two porous materials with different filling factors. The Laplace transform was applied for the heat transfer equation and together with different optimization methods it allowed to identify the thermal time constants of the DPL model. Several optimization methods were tested with known parameters in order to confirm the correctness of the parameters’ estimation.

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Keshtkar, Najmeh, Johannes Mersch, Konrad Katzer, Felix Lohse, Lars Natkowski, Gerald Gerlach, Martina Zimmermann, Chokri Cherif, and Klaus Röbenack. "Systems Actuated by Shape Memory Alloys: Identification and Modeling." SYSTEM THEORY, CONTROL AND COMPUTING JOURNAL 1, no. 2 (December 31, 2021): 12–20. http://dx.doi.org/10.52846/stccj.2021.1.2.20.

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This paper presents the identification of thermal and mechanical parameters of shape memory alloys by using the heat transfer equation and a constitutive model. The identified parameters are then used to describe the mathematical model of a fiber-elastomer composite embedded with shape memory alloys. To verify the validity of the obtained equations, numerical simulations of the SMA temperature and composite bending are carried out and compared with the experimental results.

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Garcia-Luis, Uxia, Alejandro M. Gomez-San-Juan, Fermin Navarro-Medina, Carlos Ulloa-Sande, Alfonso Yñigo-Rivera, and Alba Eva Peláez-Santos. "Optimizing Space Telescopes’ Thermal Performance through Uncertainty Analysis: Identification of Critical Parameters and Shaping Test Strategy Development." Aerospace 11, no. 3 (March 15, 2024): 231. http://dx.doi.org/10.3390/aerospace11030231.

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The integration of uncertainty analysis methodologies allows for improving design efficiency, particularly in the context of instruments that demand precise pointing accuracy, such as space telescopes. Focusing on the VINIS Earth observation telescope developed by the Instituto de Astrofísica de Canarias (IAC), this paper reports an uncertainty analysis on a thermal model aimed at improving cost savings in the future testing phases. The primary objective was to identify critical parameters impacting thermal performance and reduce overdesign. Employing the Statistical Error Analysis (SEA) method across several operational scenarios, the research identifies key factors, including the Earth’s infrared temperature and albedo, and the spacecraft’s attitude and environmental conditions, as the variables with major influences on the system’s thermal performance. Ultimately, the findings suggest that uncertainty-based analysis is a potent tool for guiding thermal control system design in space platforms, promoting efficiency and reliability. This methodology not only provides a framework for optimizing thermal design and testing in space missions but also ensures that instruments like the VINIS telescope maintain optimal operating temperatures in diverse space environments, thereby increasing mission robustness and enabling precise resource allocation.

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Guo, Fei, Xiaoyu Zhao, Wenqiong Tu, Cheng Liu, Beibei Li, and Jinrui Ye. "Inverse Identification and Design of Thermal Parameters of Woven Composites through a Particle Swarm Optimization Method." Materials 16, no. 5 (February 27, 2023): 1953. http://dx.doi.org/10.3390/ma16051953.

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Designing thermal conductivity efficiently is one of the most important study fields for taking the advantages of woven composites. This paper presents an inverse method for the thermal conductivity design of woven composite materials. Based on the multi-scale structure characteristics of woven composites, a multi-scale model of inversing heat conduction coefficient of fibers is established, including a macroscale composite model, mesoscale fiber yarn model, microscale fiber and matrix model. In order to improve computational efficiency, the particle swarm optimization (PSO) algorithm and locally exact homogenization theory (LEHT) are utilized. LEHT is an efficient analytical method for heat conduction analysis. It does not require meshing and preprocessing but obtains analytical expressions of internal temperature and heat flow of materials by solving heat differential equations and combined with Fourier’s formula, relevant thermal conductivity parameters can be obtained. The proposed method is based on the idea of optimum design ideology of material parameters from top to bottom. The optimized parameters of components need to be designed hierarchically, including: (1) combing theoretical model with the particle swarm optimization algorithm at the macroscale to inverse parameters of yarn; (2) combining LEHT with the particle swarm optimization algorithm at the mesoscale to inverse original fiber parameters. To identify the validation of the proposed method, the present results are compared with given definite value, which can be seen that they have a good agreement with errors less than 1%. The proposed optimization method could effectively design thermal conductivity parameters and volume fraction for all components of woven composites.

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Xu, Yalan, Yu Qian, and Kongming Guo. "Statistical Identification of Parameters for Damaged FGM Structures with Material Uncertainties in Thermal Environment." Complexity 2018 (2018): 1–21. http://dx.doi.org/10.1155/2018/9034865.

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Considering that the statistic numerical characteristics are often required in the probability-based damage identification and safety assessment of functionally graded material (FGM) structures, an stochastic model updating-based inverse computational method to identify the second-order statistics (means and variances) of material properties as well as distribution of constituents for damaged FGM structures with material uncertainties is presented by using measurable modal parameters of structures. The region truncation-based optimization method is employed to simplify the computational process in stochastic model updating. In order to implement the forward propagation of uncertainties required in the stochastic model updating and avoid large error resulting in the nonconvergence of the iteration process, an algorithm is proposed to compute the covariance between the modal parameters and the identified parameters for damaged FGM structures. The proposed method is illustrated by a numerically simulated damaged FGM beam with continuous spatial variation of material properties and verified by comparing with the Monte-Carlo simulation (MCS) method. The influences of the levels and sources of measured data uncertainties as well as the boundary conditions on the identification results are investigated. The numerical simulation results show the efficiency and effectiveness of the presented method for the identification of material parameter variability by using the measurable modal parameters of damaged FGM structures.

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Kuznetsov, V., M. Tryputen, A. Nikolenko, D. Tsyplenkov, V. Kuvaiev, and O. Savvin. "Identification of the thermal process in an induction motor." Collection of Research Papers of the National Mining University 71 (December 2022): 116–30. http://dx.doi.org/10.33271/crpnmu/71.116.

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Purpose: synthesis of a mathematical model of an asynchronous motor, taking into account the impact of changes in the quality of electricity on the processes of heating and heat exchange for an economically justified choice of means of protection. Methodology: Theoretical substantiation of the expediency of using a one-mass thermal model of an asynchronous motor, for the conditions of operation of the latter in conditions of low-quality electricity, in order to determine losses in it. Results: Experimental studies of the operation of an asynchronous motor at nominal load were carried out. The obtained results of the measurements made it possible to determine the parameters of the single-mass thermal model, the heat transfer coefficient of the engine, and the coefficient of its heat capacity.A single-mass thermal model of an induction motor is a mathematical model used to describe the thermal processes occurring in an induction motor. This model is based on the assumption that all motor elements can be combined into one mass that heats up during engine operation. The model assumes that the thermal capacity of the motor is a constant, and the heat flow that is released during the operation of the motor is proportional to the square of the current passing through the motor windings. In addition, the model assumes the presence of thermal conductivity between the mass of the motor and the external environment, which affects the rate of heat dissipation. Scientific novelty: A methodology for determining losses in an asynchronous motor using a synthesized mathematical model is proposed, taking into account the influence of changes in the quality of electricity on the processes of heating and heat exchange in it. Practical significance: The obtained results indicate the adequacy of the proposed thermal model of an asynchronous motor operating in a network with low-quality electricity. Taking into account the fact that for many types of engines in the reference literature,there are no necessary data on the coefficients of heat transfer and heat capacity, and only the thermal time constants for certain types of engines are given, the value of the specified parameters of the model can be obtained on the basis of the methodology presented in the work.A single-mass thermal model can be useful for analyzing the thermal processes occurring in an induction motor and for improving the efficiency of the motor. In particular, it can help determine the optimal operating temperature of the motor, as well as calculate the necessary cooling system to ensure stable operation of the motor under conditions of variable load and temperature conditions.

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