scholarly journals Comparison of Infrared Thermography and Heat Flux Method for Dynamic Thermal Transmittance Determination

Buildings ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 132 ◽  
Author(s):  
Mergim Gaši ◽  
Bojan Milovanović ◽  
Sanjin Gumbarević
Keyword(s):  
Heat Flux ◽  
Infrared Thermography ◽  
Dynamic Method ◽  
Flux Method ◽  
Microsoft Excel ◽  
Experimental Procedure ◽  
Thermal Transmittance ◽  
U Value ◽  
Stationary Heat Transfer

This paper proposes an alternative experimental procedure that uses infrared thermography (IRT) for measuring the surface temperature of building elements, through which it is possible to approximate the thermal transmittance or the U-value. The literature review showed that all authors used similar procedures that require semi-stationary heat transfer conditions, which, in most cases, could not be achieved. The dynamic and the average methods that are given in ISO 9869 were also used with the IRT and the heat flux method (HFM). The dynamic method (DYNM) shows a higher level of accuracy compared to the average method (AVGM). Since the algorithm of the DYNM is more complicated than that of the AVGM, Microsoft Excel VBA was used to implement the algorithm of the DYNM. Using the procedure given in this paper, the U-value could be approximated within 0–30% of the design U-value. The use of IRT, in combination with the DYNM, could be used in-situ since the DYNM does not require stable boundary conditions. Furthermore, the procedure given in this paper could be used for relatively fast and inexpensive U-value approximation without the use of expensive equipment (e.g., heat flux sensors).

scholarly journals Thermal transmittance prediction based on the application of artificial neural networks on heat flux method results

2021 ◽  
Vol 2069 (1) ◽  
pp. 012152
Author(s):  
S. Gumbarević ◽  
B. Milovanović ◽  
M. Gaai ◽  
M. Bagarić
Keyword(s):  
Heat Flux ◽  
Short Term Memory ◽  
Heat Flux Sensor ◽  
Flux Method ◽  
Short Term ◽  
Term Memory ◽  
Thermal Transmittance ◽  
U Value ◽  
Long Short Term Memory ◽  
Artificial Neural

Abstract Deep energy renovation of building stock came more into focus in the European Union due to energy efficiency related directives. Many buildings that must undergo deep energy renovation are old and may lack design/renovation documentation, or possible degradation of materials might have occurred in building elements over time. Thermal transmittance (i.e. U-value) is one of the most important parameters for determining the transmission heat losses through building envelope elements. It depends on the thickness and thermal properties of all the materials that form a building element. In-situ U-value can be determined by ISO 9869-1 standard (Heat Flux Method - HFM). Still, measurement duration is one of the reasons why HFM is not widely used in field testing before the renovation design process commences. This paper analyzes the possibility of reducing the measurement time by conducting parallel measurements with one heat-flux sensor. This parallelization could be achieved by applying a specific class of the Artificial Neural Network (ANN) on HFM results to predict unknown heat flux based on collected interior and exterior air temperatures. After the satisfying prediction is achieved, HFM sensor can be relocated to another measuring location. Paper shows a comparison of four ANN cases applied to HFM results for a measurement held on one multi-layer wall – multilayer perceptron with three neurons in one hidden layer, long short-term memory with 100 units, gated recurrent unit with 100 units and combination of 50 long short-term memory units and 50 gated recurrent units. The analysis gave promising results in term of predicting the heat flux rate based on the two input temperatures. Additional analysis on another wall showed possible limitations of the method that serves as a direction for further research on this topic.

scholarly journals Analysis of Convergence Characteristics of Average Method Regulated by ISO 9869-1 for Evaluating In Situ Thermal Resistance and Thermal Transmittance of Opaque Exterior Walls

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1989 ◽  
Author(s):  
Doo Sung Choi ◽  
Myeong Jin Ko
Keyword(s):  
Thermal Resistance ◽  
Average Method ◽  
Test Duration ◽  
Test Environment ◽  
Building Envelopes ◽  
Thermal Transmittance ◽  
The Third ◽  
U Value ◽  
R Value

In the last few decades, an average method which is regulated by ISO 9869-1 has been used to evaluate the in situ thermal transmittance (U-value) and thermal resistance (R-value) of building envelopes obtained from onsite measurements and to verify the validity of newly proposed methods. Nevertheless, only a few studies have investigated the test duration required to obtain reliable results using this method and the convergence characteristics of the results. This study aims to evaluate the convergence characteristics of the in situ values analyzed using the average method. The criteria for determining convergence (i.e., end of the test) using the average method are very strict, mainly because of the third condition, which compares the deviation of two values derived from the first and last periods of the same duration. To shorten the test duration, environmental variables should be kept constant throughout the test or an appropriate period should be selected. The convergence of the in situ U-value and R-value is affected more by the length of the test duration than by the temperature difference if the test environment meets literature-recommended conditions. Furthermore, there is no difference between the use of the U-value and R-value in determining the end of the test.

scholarly journals Hygrothermal Behaviour of Ventilation Cavities in Highly Insulated Envelopes

2020 ◽  
Vol 172 ◽  
pp. 07003
Author(s):  
Klaus Viljanen ◽  
Xiaoshu Lü ◽  
Jari Puttonen
Keyword(s):  
Heat Flux ◽  
Relative Humidity ◽  
Experimental Studies ◽  
Thermal Transmittance ◽  
The Future ◽  
U Value ◽  
Hygrothermal Behaviour

This article presents long-term experimental studies on the moisture safety in the ventilation cavities of highly insulated (HI) structures. The tested HI-walls had thermal transmittances of 0.11-0.13 W/m2K. A wall with a thermal transmittance of 0.23 W/m2K represented the baseline wall in the test. In addition to walls, an HI-roof of a newly built house with a U-value of 0.08 W/m2K was measured. The results indicate that, in the ventilation cavity, the relative humidity of an HI-wall exceeds 1-7% of the humidity measured from the baseline wall during winter, which coincides with the 0.4-1.5ºC lower temperatures observed in the HI-walls. The mold risk in the ventilation cavities of the walls is low, as the value of the mold index (MI) remains below one, which indicates small amounts of microscopic mold only on surfaces. However, at the bottom of the cavity, the MI value reaches 1.4 due to lower temperatures. In the HI-roof, the MI values are between 1.0 and 2.0 in the middle of the cavity in winter. The reasons for the higher mold risk of the roof are the humid weather, the built-in moisture of the roof and the low heat flux from inside. The study confirms that, in the future, warmer weather and increased humidity can increase moisture risks in the ventilation cavities. The results support the use of materials that are more resistant to mold in the outer parts of structures.

scholarly journals A Novel Approach for U-Value Estimation of Buildings’ Multi-layer Walls Using Infrared Thermography and Artificial Intelligence

2021 ◽  
pp. 35-43
Author(s):  
Arijit Sen ◽  
Amin Al-Habaibeh
Keyword(s):  
Infrared Thermography ◽  
Field Work ◽  
High Accuracy ◽  
The Novel ◽  
Novel Approach ◽  
Wide Range ◽  
Value Estimation ◽  
U Value ◽  
Artificial Neural Network Ann

AbstractEstimating the U-value of walls of buildings is a key process to evaluate the overall thermal performance. Low U-value in buildings is desired in order to keep heat within the envelop and consume less energy in heating. Addressing the limitations in the currently used U-value estimation techniques, this paper proposes a novel approach for estimating the U-value of the envelop of buildings using infrared thermography and Artificial Neural Network (ANN) with the application of a point heat source. The novel system is calibrated by training the ANN in a lab environment using a wide range of samples with multi-layers to be able to estimate the in situ U-value of walls in real buildings during field work with relatively high accuracy.

scholarly journals Measurements of thermal Transmittance of an External massive timber wall in-situ and in the Laboratory

2020 ◽  
Vol 172 ◽  
pp. 14009
Author(s):  
Christoph Geyer ◽  
Andreas Müller ◽  
Barbara Wehle
Keyword(s):  
In Situ Measurement ◽  
Test Results ◽  
Mean Values ◽  
Thermal Transmittance ◽  
University Of Applied Sciences ◽  
Measurement Results ◽  
State Boundary ◽  
U Value ◽  
Massive Timber

The thermal transmittance of an exterior massive timber wall was measured in situ in Appenzell, Switzerland according to the standard ISO 9869-1. The measurements were performed with two different measurement sets in parallel. The measurements started in February and stopped at end of April. The measuring data were analyzed using mean values of the thermal transmittance coefficient and of the thermal resistance following the procedure of ISO 9869-1. In order to clarify if the in-situ measurement results show significant deviations from the measurement results of the thermal transmittance obtained in the laboratory, the thermal transmittance of the identical wall construction was measured in the laboratory of Bern University of Applied Sciences in Biel according to the standard EN ISO 8990 for steady state boundary conditions in a guarded and calibrated hot box. The test results will be presented and the measurement setup will be described. The calculation value of the thermal transmittance coefficient of the massive timber wall according to EN ISO 6946 is U = 0.53 W/(m2K). The test results of the thermal transmittance coefficient, U-value of the wall, measured in the hot box, agreed well within a confidence level of 95 % with the calculated value. The in-situ measurement results of the thermal transmittance coefficient of the two measurement sets differ significantly in the order of 8 % referred to the calculated U-value of the wall as the basic amount. Furthermore, both in situ test results of the U-value of the wall show significant deviations from the calculated U-value up to 27 %.

scholarly journals Application of Multilayer Perceptron Method on Heat Flow Meter Results for Reducing the Measurement Time

2020 ◽  
Vol 2 (1) ◽  
pp. 29
Author(s):  
Sanjin Gumbarević ◽  
Bojan Milovanović ◽  
Mergim Gaši ◽  
Marina Bagarić
Keyword(s):  
Neural Network ◽  
Heat Flux ◽  
Multilayer Perceptron ◽  
Heat Losses ◽  
Measurement Time ◽  
Flux Rate ◽  
U Value ◽  
The Impact ◽  
Building Elements

To reduce the impact on climate change, many countries have developed strategies for the building sector with a goal to reduce the energy demands and carbon emission of buildings. As most buildings that exist today will very likely exist in foreseeable future, many buildings will need to undergo major renovations. One of the most important parameters in determining the transmission heat losses through the building envelope is the U-value, i.e., thermal transmittance, and it is simply the rate of heat transfer per unit temperature. Since the U-value is one of the most important parameters regarding building energy performance, envelope elements that do not perform well in terms of transmission heat losses must undergo a renovation processes. The in-situ U-value of building elements is usually determined by the Heat Flux Method (HFM). One of the issues of current application of the HFM is the measurement duration. This paper explores the possibilities of reducing the measurement time by predicting the heat flux rate using a multilayer perceptron (MLP), a class of artificial neural network. The MLP uses two input layers that are the interior and exterior air temperatures, and the output layer that is the predicted heat flux rate. The predicted value is trained by comparing the predicted heat flux rates with the measured values, and by rearranging the neural network parameters (weights and biases) in corresponding neurons by minimizing the mean squared error defined for trained values (measured versus predicted heat flux rates). The use of MLP shows promising results for predicting the heat flux rates for the analyzed cases (4 days HFM results) when the training is performed on 2/3 or 1/2 of the overall measurement time. The application of the MLP could be in reducing the in-situ measurement time when determining heat losses through building elements in shorter time periods.

scholarly journals Thermal Performance Assessment of a Wall Made of Lightweight Concrete Blocks with Recycled Brick and Ground Polystyrene

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 584
Author(s):  
Hrvoje Krstić ◽  
Ivana Miličević ◽  
Damir Markulak ◽  
Mihaela Domazetović
Keyword(s):  
Heat Flow ◽  
Thermal Performance ◽  
Lightweight Concrete ◽  
Thermal Transmittance ◽  
Building Technology ◽  
Concrete Masonry ◽  
Concrete Blocks ◽  
U Value ◽  
Building Walls

Hollow concrete masonry blocks made of low strength self-compacting concrete with recycled crushed brick and ground polystyrene as an aggregate (RBC-EP blocks), and their expected structural role as masonry infill in steel frames, has been confirmed in previous research studies, thus the extensive investigation of thermal properties is presented in this paper to fully approve their potential application in practice. The Heat Flow and Temperature Based Method was used to conduct in-situ measurements of the wall thermal transmittance (U-value). The experimental U-values of the wall without insulation varied from 1.363 to 1.782 W/m2·K, and the theoretical value was calculated to be 2.01 W/m2·K. Thermal conductivity of the material used for making RBC-EP blocks was measured in a laboratory by using a heat flow meter instrument. To better understand the thermal performance characteristics of a wall constructed from RBC-EP blocks, a comparison with standard materials currently used and found on the market was performed. Walls constructed from RBC-EP blocks show an improvement of building technology and environmentally based enhancement of concrete blocks, since they use recycled materials. They can replace standard lightweight concrete blocks due to their desired mechanical properties, as well as the better thermal performance properties compared to commonly used materials for building walls.

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