Estimation Of Heat Transfer Coefficient Research Articles

Estimation of Multiple Contact Conductances in a Silicon-Indium-Silicon Stack

Estimation of Multiple Contact Conductances in a Silicon-Indium-Silicon Stack

The neural network approach for estimation of heat transfer coefficient in heat exchangers considering the fouling formation dynamic

Routine maintenance for plate heat exchanger (PHE) cleaning improves the effectiveness of heat exchange network operation. Until recently, complex mathematical modelling was used to predict the value of the heat transfer coefficient after a certain period of operation of the heat exchanger, as well as the point in time when the coefficient reached the allowable limit. The applied mathematical tools included the systems of differential equations, matrices of heuristic coefficients, which needed a lot of computer resources. This paper offers an artificial neural network (ANN) technique for forecasting the following values: heat transfer coefficient at any time points during the operating period of PHEs; the time point, when the heat transfer coefficient reaches its lower permitted value. In this method, ANN uses the fuzzy logic techniques to expand the set of training parameters for the model, working with data of industrial measurements and data obtained from the mathematical modelling of the process. It allowed to train the developed feed-forward neural network (FFNN) with the coefficient of determination R2 equal to 0.99 and can predict the thermal resistance in PHE based on measurement data. To adequately predict the time-point to reach the limiting value of the heat transfer coefficient, it was proposed a recurrent neural network (RNN) with a hidden layer of long short-term memory (LSTM), where R2 value came up to 0.89.

A framework for data regression of heat transfer data using machine learning

Machine Learning (ML) algorithms are emerging in various industries as a powerful complement/alternative to traditional data regression methods. A major reason is that, unlike deterministic models, they can be used even in the absence of detailed phenomenological knowledge. Not surprisingly, the use of ML algorithms is being explored also in heat transfer applications. It is of particular interest in systems dealing with complex geometries and underlying phenomena (e.g. fluid phase change, multi-phase flow, heavy fouling build-up). However, heat transfer systems present specific challenges that need addressing, such as the scarcity of high-quality data, the inconsistencies across published data sources, the complex (and often correlated) influence of inputs, the split of data between training and testing sets, and the limited extrapolation capabilities to unseen conditions. In an attempt to help overcome some of these challenges and, more importantly, to provide a systematic approach, this article reviews and analyses past efforts in the application of ML algorithms to heat transfer applications, and proposes a regression framework for their deployment to estimate key quantities (e.g. heat transfer coefficient), to be used for improved design and operation of heat exchangers. The framework consists of six steps: i) data pre-treatment, ii) feature selection, iii) data splitting philosophy, iv) training and testing, v) tuning of hyperparameters, and vi) performance assessment with specific indicators, to support the choice of accurate and robust models. A relevant case study involving the estimation of the condensation heat transfer coefficient in microfin tubes is used to illustrate the proposed framework. Two data-driven algorithms, Deep Neural Networks and Random Forest, are tested and compared in terms of their estimation and extrapolation capabilities. The results show that ML algorithms are generally more accurate in predicting the heat transfer coefficient than a well-known semi-empirical correlation proposed in past studies, where the mean absolute error of the most suitable ML model is 535 [Wm2K-1], compared to the error using the correlation of 1061 [Wm2K-1]. In terms of extrapolation, the selected ML model has a mean absolute error of 1819 [Wm2K-1], while for the correlation is 1111 [Wm2K-1], indicating a disadvantage of the use of semi-empirical models, although the comparison was not entirely suitable, given that the correlation was used as is and no training was done. In addition, feature selection enables simpler models that depend only on features that are potentially most related to the target variable. Special attention is needed however, as overfitting and limited extrapolation capabilities are common difficulties that are encountered when deploying these models.

Estimation of heat transfer coefficient and friction factor with showering of aluminum nitride and alumina water based hybrid nanofluid in a tube with twisted tape insert

Twisted tape is one of the active thermal proficiency boosting technology which has been deeply examined because to consistent efficiency findings and easy implementations. Thermo-hydraulic effectiveness of tubes fitted with twisted tapes is becoming highly significant. Although twisted tapes can cause swirls and disturb boundary layers, this is the most widely used method for improving convection. In the present attempt, to enhance the heat transfer twisted tape is inserted in tube. In the current modern research, the effect of twisted tape, on the enhancement of thermal transport, Nusselt number and friction factor performance of AIN–Al2O3/water hybrid nanofluid is evaluating utilizing CFD and ANSYS-FLUENT software. the consequence of twisted pitch 44 mm, 66 mm, 88 mm, 100 mm and Reynolds numbers 800, 1200, 1600 and 2000 on Nusselt number, heat transfer coefficient and friction coefficient have been computed numerically with 0.01 to 0.04 volume friction of nanopowders. The commercial ANSYS-FLUENT code was used in this analysis utilizing the SIMPLE method for pressure–velocity coupling. The K-ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$K - \\omega$$\\end{document} model and Navier Stokes equations are integrating utilizing finite volume method in ANSYS-FLUENT. It was observed that inserting the twisted tape in tube significantly improves the thermal conductivity as well as friction factor compared with the simple tube without turbulator.

Numerical test bench to evaluate the influence of heat gains on the estimation of Heat Transfer Coefficient under occupied conditions

The estimation of the HTC heat transfer coefficient in real occupancy conditions has a great operational advantage contrary to the measurement in unoccupied conditions, which requires specific measurement protocols. Nevertheless, it presents additional constraints because the gains due to weather conditions and occupancy are poorly controlled. The objective of this work is therefore to quantify the impact of these different gains. A numerical test bench is set up to study the impact of the solar and internal gains by varying different parameters, such as the typology of the building, the meteorological conditions, the scenarios of occupancy. These numerical tests allow to estimate the HTC of a building by calibrating a numerical model from a virtual dataset generated by a detailed model with known and controlled meteorological conditions and usage conditions. They make it possible to determine the share of solar heat gain and internal heat gain in the energy balance of the building and their impact on the estimation of the HTC according to the studied configurations.

Characterisation and analysis of uncertainties in building heat transfer estimates from co-heating tests

In recent years, measurement protocols for the estimation of the total aggregate building heat transfer coefficient (HTC) have provided sufficient empirical evidence to indicate that buildings often do not perform as intended. However, little research has been carried out into the associated uncertainties. Within this context, this paper reviews sources of uncertainty associated with co-heating tests; characterises these uncertainties and their impact on HTC estimates; and devises a method for the calculation of HTC uncertainty. The method proposed was applied to 14 co-heating tests, showing estimated total uncertainty ranging between 2.2-21.1 (or 4.6-26.7% of the measured value) with a mean of 10.1 (or 8.7%). The natural variation of HTC and often-observed inaccuracy of design calculations (the ‘prediction gap’) suggest that more accurate measurements may be of little benefit. Additionally, results suggest that weather conditions, challenging building design and poor experimental technique can all significantly contribute to HTC uncertainty. However, when suitable buildings are tested by experienced technicians and under suitable weather conditions, HTC estimates from the co-heating protocol are likely to provide a useful tool to assess and understand real-world building fabric performance.

The Heat Transfer in Plate Fin Heat Exchanger for Adsorption Energy Storage: Theoretical Estimation and Experimental Verification of the Methodology for Heat Accumulation Process

Adsorption energy storage is a promising resource-saving technology that allows the rational use of alternative heat sources. One of the most important parts of the adsorption heat accumulator is the adsorber heat exchanger. The parameters of heat transfer in this unit determine how fast heat from an alternative energy source, such as the Sun, will be stored. For the design of adsorption heat accumulators, plate fin heat exchangers are mainly used. In this paper, the procedure for the estimation of the global heat transfer coefficient for the adsorber heat exchanger depending on its geometry is considered. The heat transfer coefficient for a LiCl/SiO2 sorbent flat layer under conditions of heat storage stage was measured. Based on these data, the global heat transfer coefficients for a number of industrial heat exchangers were theoretically estimated and experimentally measured for the adsorption cycle of daily heat storage. It was shown that theoretically obtained values are in good agreement with the values of the global heat transfer coefficients measured experimentally. Thus, the considered technique makes it possible to determine the most promising geometry of the plate fin heat exchanger for a given adsorption heat storage cycle without complicated experiments.

Simultaneous estimation of reference temperature and heat transfer coefficient in transient film cooling problems

This paper aims to simultaneously estimate the reference temperature and heat transfer coefficient in film cooling situations from transient temperature measurements. The exist-ing steady-state technique is a tedious process and employs distinct boundary conditions to evaluate each parameters of the film cooling. Applying different boundary conditions may lead to errors in the estimated parameters due to differences in aerodynamic condi-tions. On the other hand, a transient technique can estimate both parameters in a single test by utilizing short-duration transient temperature data. Hence, the present study uses a novel approach for solving transient film cooling problems based on the inverse heat con-duction approach, which can simultaneously estimate heat transfer coefficient and refer-ence temperature. The present method employs an optimization technique known as the Levenberg-Marquardt Algorithm. The objective function for the inverse algorithm is con-structed using the analytical solution of a transient one-dimensional semi-infinite body. The transient surface temperature data required for the present analysis is obtained through a numerical simulation of film cooling arrangement over a flat surface. Laterally averaged effectiveness and heat transfer coefficient for blowing ratios of 0.5, 0.8, and 1.0 are analyzed using the present technique and compared against the steady-state simulation results to demonstrate the methodology. An average deviation of around 7% for the estimated effec-tiveness and 4% for the heat transfer coefficient values are observed between the present IHCP method and the steady state simulation results. The deviation in heat transfer coeffi-cient predominately occurred near the film hole exit of x/d < 5, which might have occurred due to the conjugate solution employed in the present work.

Simultaneous estimation of reference temperature and heat transfer coefficient in transient film cooling problems

This paper aims to simultaneously estimate the reference temperature and heat transfer coefficient in film cooling situations from transient temperature measurements. The exist-ing steady-state technique is a tedious process and employs distinct boundary conditions to evaluate each parameters of the film cooling. Applying different boundary conditions may lead to errors in the estimated parameters due to differences in aerodynamic condi-tions. On the other hand, a transient technique can estimate both parameters in a single test by utilizing short-duration transient temperature data. Hence, the present study uses a novel approach for solving transient film cooling problems based on the inverse heat con-duction approach, which can simultaneously estimate heat transfer coefficient and refer-ence temperature. The present method employs an optimization technique known as the Levenberg-Marquardt Algorithm. The objective function for the inverse algorithm is con-structed using the analytical solution of a transient one-dimensional semi-infinite body. The transient surface temperature data required for the present analysis is obtained through a numerical simulation of film cooling arrangement over a flat surface. Laterally averaged effectiveness and heat transfer coefficient for blowing ratios of 0.5, 0.8, and 1.0 are analyzed using the present technique and compared against the steady-state simulation results to demonstrate the methodology. An average deviation of around 7% for the estimated effec-tiveness and 4% for the heat transfer coefficient values are observed between the present IHCP method and the steady state simulation results. The deviation in heat transfer coeffi-cient predominately occurred near the film hole exit of x/d < 5, which might have occurred due to the conjugate solution employed in the present work.

Performance Analysis of Metaheuristic Optimizers on the Estimation of the Interfacial Heat Transfer Coefficient in Aluminum–Silicon Permanent Mold Casting

Performance Analysis of Metaheuristic Optimizers on the Estimation of the Interfacial Heat Transfer Coefficient in Aluminum–Silicon Permanent Mold Casting

Oil jets piston cooling: A numerical methodology for the estimation of heat transfer coefficients and optimization of the piston temperature field through a genetic algorithm

High-efficiency internal combustion engines need specific methodologies to be developed for the design improvement of the components. Predicting and reducing the thermal loadings on the parts are critical tasks to be addressed. This contribution focuses on the thermal management of the piston through oil jets. The operating temperature of the piston deeply affects its thermo-mechanical behavior, thus possibly jeopardizing the structural integrity of the component. The design of piston cooling jets is usually addressed through Computational Fluid Dynamics, which can guarantee accurate results, usually at a high computational cost. In this contribution, a faster tool is derived to grasp the effect of the cooling jets on the temperature of the piston. Empirical correlations are applied to predict the instantaneous heat transfer coefficients on the piston. The reciprocating motion of the piston is considered since it affects the interaction between the surface and the oil jets. Instantaneous coefficients are cycle-averaged and used to estimate the temperature of the piston through a Finite Element thermal analysis. Finally, an optimization code is developed to find the best jet configuration capable to minimize the temperature of the piston. This methodology is a powerful tool to select the optimal oil jet nozzles for piston cooling.

Estimation of effective thermal conductivity and heat transfer coefficient of lithium orthosilicate pebble bed in carbon dioxide–air medium

ABSTRACT Lithium orthosilicate has the highest absorption capacity among other materials used to capture carbon dioxide (CO2) at a higher temperature. To design a CO2 adsorption system consisting of lithium orthosilicate pebble bed, effective thermal conductivity and heat transfer coefficient data are necessary, and till date, these are not reported in the literature. In the present study, experiments were conducted to estimate the effective thermal conductivity and heat transfer coefficient of lithium orthosilicate pebble bed in CO2–air medium. Effects of CO2 concentration in air, bed temperature, and gas flowrate on the hydrodynamic as well as heat transfer properties of the pebble bed of lithium orthosilicate pebbles were also studied. The effective thermal conductivity and heat transfer coefficients were found in the range of 0.2–0.75 Wm−1K−1 and 14–63 Wm−2K−1, respectively.

Surface heat transfer coefficients in building envelopes: Uncertainty levels in experimental methods

There are several research methods for the on-site assessment of U-values that aim to avoid the use of surface heat flux measurements and rely on tabulated or empirically developed correlations to define this parameter. This works performs a detailed process to estimate indoor surface heat transfer coefficients based on several experimental campaigns over building walls. Data is filtered out to remove periods with large temperature variations and/or unstable convective conditions due to HVAC. A statistical analysis is conducted, and the outcomes used to test the validity of U-value estimation approaches. The outcomes show that the actual surface heat transfer coefficients are in the range of reference works, but variations in the range of up to 2 W/m2 K are found. Uncertainty levels associated to the estimation of surface heat transfer coefficient are in the range 60% for instantaneous values while this is reduced down to 12%–20% for 8-h averages. Variations and uncertainty levels are higher for low temperature gradient situations, which are considered to be very likely for modern insulation levels. It is concluded that methods seeking to avoid the use of surface heat flux measurements need to develop much deeper knowledge in this field to gain accuracy and reliability.

High-precision solidification simulation by estimating heat transfer coefficients through data assimilation

Solidification analysis is important for accurately predicting casting processes. A high-precision casting simulation requires accurate data of the physical properties of materials and heat transfer parameters. In particular, the heat transfer coefficient is a major parameter influencing the casting simulation results. Because the heat transfer coefficient is not uniquely determined by the material, it is typically estimated by trial and error, which requires considerable time for accurate estimations. Therefore, we developed a method to quickly estimate the heat transfer coefficient in a casting process by combining data assimilation and solidification simulations. With this method, the time-dependent heat transfer coefficient can be estimated in an appropriate and easy manner. To reproduce the 3D temperature distribution in a casting with high accuracy, we developed a method to estimate multiple heat transfer coefficients simultaneously by combining data assimilation and 3D solidification simulation. Al–5 mass% Si alloy was cast into a sand mold with a casting size of 30 mm × 30 mm × 100 mm, and the temperature was measured at five points in the casting to obtain a cooling curve. Two cooling curves corresponding to locations of 5 mm from the casting wall were used to estimate the two heat transfer coefficients on the side and bottom surfaces, which were simultaneously estimated by data assimilation. The results confirmed that all the five cooling curves could be reproduced with a high accuracy and that high-precision casting simulation was possible.

Experimental estimation of the local heat transfer coefficient for thin liquid film evaporation in a capillary tube

• Local heat transfer coefficient was estimated for thin liquid film evaporation in a capillary tube. • Temperature infrared measurements were employed as input data of the inverse heat conduction problem. • A robust estimation procedure was adopted. • Procedure validation through the application to both synthetic and experimental data. • Original insight of thin liquid film evaporation was given. Two-phase heat transfer devices consisting of mini and microtubes represent a powerful solution to the continuous reduction of electronic components' dimensions and to the increase of the power to dissipate. Despite many studies on the two-phase heat transfer phenomenon in minitubes, most provided outcomes regarding the average heat transfer coefficient or Nusselt number. A technique to assess the local convective wall heat flux and heat transfer coefficient is proposed, validated, and then applied to the experimental case of thin-film evaporation in a heated capillary tube. The evaporation of the thin film of liquid plays a vital part in the two-phase heat transfer phenomenon inside mini/microtubes. Our study investigated this phenomenon by examining a semi-infinite slug flow. The estimation method used is represented by the inverse heat conduction problem solution in the tube wall, applying the Tikhonov regularisation method. The temperature distributions on the outer surface of the channel measured by an infrared camera were employed as input data for the inverse problem. The estimated heat transfer coefficient distributions confirm the available correlations in average values and provide insight into these complex phenomena in local and instantaneous quantities.

Inverse problem estimation of internal heat transfer coefficients in ducts through a time-dependent reciprocity functional method

Inverse problem estimation of internal heat transfer coefficients in ducts through a time-dependent reciprocity functional method

Local heat flux estimation inside tubes through conjugate gradient method with adjoint operator: application to the pulsating heat pipes case

PurposeThe purpose of this paper is to apply the conjugate gradient (CG) method, together with the adjoint operator (AO) to the pulsating heat pipe problem, including some quite interesting experimental results. The CG method, together with the AO, was able to estimate the unknown functions more efficiently than the other techniques presented in this paper. The estimation of local heat transfer coefficients, rather than the global ones, in pulsating heat pipes is a relatively new subject and presenting a robust, efficient and self-regularized inverse tool to estimate it, supported also by some experimental results, is the main purpose of this paper. To also increase the visibility and the general use of the paper to the heat transfer community, the authors include, as supplemental material, all numerical and experimental data used in this paper.Design/methodology/approachThe approach was established on the solution of the inverse heat conduction problem in the wall by using as starting data the temperature measurements on the outer surface. The procedure is based on the CG method with AO. The here proposed approach was first verified adopting synthetic data and then it was validated with real cases regarding pulsating heat pipes.FindingsAn original fast methodology to estimate local convective heat flux is proposed. The procedure has been validated both numerically and experimentally. The procedure has been compared to other classical methods presenting some peculiar benefits.Practical implicationsThe approach is suitable for pulsating heat pipes performance evaluation because these devices present a local heat flux distribution characterized by an important variation both in time and in space as a result of the complex flow patterns that are generated in this type of devices.Originality/valueThe procedure here proposed shows these benefits: it affords a general model of the heat conduction problem that is effortlessly customized for the particular case, it can be applied also to large datasets and it presents reduced computational expense.

Estimation of heat transfer coefficient in turbulent regime during agitation by two-blade wide paddle impellers

This work proposed a new equation to estimate heat transfer coefficients in a turbulent regime during the agitation by two-blade wide paddle impellers. The equation includes Nusselt number, Prandtl number, Reynolds number based on energy dissipation rate, a ratio of impeller diameter to vessel diameter, and a ratio of blade width to vessel diameter. The representative length related to the heat transfer, proposed by Hiraoka and Ito (1973), was adopted for the equation. The proposed correlation equation successfully estimated the heat transfer coefficient during the agitation by two-blade wide paddle impellers (Maxblend impeller, Fullzone impeller, Sanmeler impeller, MR210, and MR 203). The proposed equation is also applicable for the agitation by conventional impellers (disk turbine, flat paddle, and pitch paddle).

Grey box modeling of supermarket refrigeration cabinets

Aiming to enable robust large-scale fault diagnostics and optimized control for supermarket refrigeration systems, a data-driven grey box model for an evaporator and its surrounding cooling cabinet (or room) is presented. It is a non-linear model with two states: the cabinet temperature and the refrigerant mass in the evaporator. To demonstrate its applicability, data with one-minute sampling resolution from ten evaporators in a supermarket in Otterup (Denmark) was used. The model parameters were estimated using a Kalman filter and the maximum likelihood method. Since the dynamical properties of the cabinets constantly change as goods are added and removed, the parameters were re-estimated for each night, over a period of approximately 2.5 years. The model is validated through a statistical analysis of the residuals and the importance of the ongoing re-estimation of parameters is highlighted. Furthermore, the physical meaning of the estimated parameters is discussed and potential applications for characterization and classification of cabinets are demonstrated, by showing how they can be differentiated as either open- or closed cabinets or rooms, using only the estimated heat transfer coefficients and heat capacities. For a selected case it is shown that the estimated parameter values are close to physics derived values, and that the accuracy measured by the standard errors of the estimates is approximately ±10% relative to the estimated values. The analysis demonstrates that the model is robust, accurate and reliable in terms of estimating physically meaningful parameters and it is therefore appropriate for large-scale implementation.

Non-invasive thermal energy flow rate sensor for turbulent pipe flows

A non-invasive thermal energy flow rate sensor based on a combination of transient heat flux and temperature measurements has been developed. A heat flux sensor and a thin-film thermocouple are covered by a thin-film electric heater and clamped onto the outer surface of a pipe. A one-dimensional transient thermal model is applied before and during activation of the external heater to provide estimates of the fluid heat transfer coefficient and thermal resistance. A parameter estimation code is used to estimate the unknown parameters by using the minimum root mean square error between the analytical and experimental sensor temperature values. The sensor was tested with two different fluids (water and diesel oil) and with two different pipe diameters (d=25.4mm and d=12.7mm). Experiments were completed over a range of Reynolds number from 2000 to 25,000 and a range of fluid temperature from 20 °C to 50 °C. Correlations for the fluid temperature and the fluid velocity were within ±0.13 K and ±5% of the direct measurements. The resulting non-invasive thermal energy flow rate sensor can be used to estimate a fluid velocity and a fluid temperature in heating and cooling pipe applications.