- Email: [email protected]
IQ-test—improving quality in testing and evaluation of solar and thermal characteristics of building components
Energy and Buildings 36 (2004) 435–441
IQ-test—improving quality in testing and evaluation of solar and thermal characteristics of building components Paul Baker∗ BRE Scotland, East Kilbride G75 ORZ, UK
Abstract IQ-test is a Thematic Network supported by the European Community under the EESD Programme. The objective of IQ-test is to further the development of common quality procedures at the PASLINK test cell facilities in 12 European countries, for the assessment of the thermal characteristics of building components. This should consolidate the network, integrate the newer test sites and strengthen its common approach of support for new product developments in the field of innovative building components. Round robin tests are underway to assess both the inter-site quality of testing and analytical procedures of the participants. Two components were designed: (1) an opaque, well insulated, homogeneous panel and (2) a window, which is used to replace the central section of the first component. Common test and quality procedures have been implemented at each test site. The data sets generated by each team have been made available for cross-analysis by another team. The results available so far on the first component indicate good agreement between sites. This paper summarises the progress to date. Results are also presented from a training exercise which asked participants to identify the performance characteristics of an unknown component without providing any physical description of the component. © 2004 Published by Elsevier B.V. Keywords: IQ-test; PASLINK; Test cells; Thermal performance
1. Introduction IQ-test is a Thematic Network supported by the European Community under the EESD Programme, which aims to consolidate the work of the network of the PASLINK outdoor test cell facilities in 12 European countries, involved in the energy performance evaluation of the thermal and solar properties of building component. More information may be found on the PASLINK web-site: WWW.PASLINK.ORG. The objective of IQ-test is to further the development of common quality procedures for: • • • •
testing; calibration; data gathering, processing and analysis; interpretation of test results and scaling/replication to real building; and • maintenance of the test infrastructure at the test sites. This should consolidate the network, by integrating the newer test sites and strengthening its common approach of support for new product developments in the field of inno∗ Current address: Centre for Research on Indoor Climate & Health, Glasgow Caledonian University, G4 OBA, UK. E-mail address: [email protected] (P. Baker).
0378-7788/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.enbuild.2004.01.046
vative building components through semi-standardised tests and pragmatic, practicable and affordable but accurate procedures. As part of the work of the Network, round robin tests are being performed as part of a feasibility study for standardisation activities. The objective is to assess both the inter-site quality of testing and analytical procedures of the members, with a view to developing standards for outdoor testing. High quality data for model calibration will also be generated. Two components were designed, incorporating flexibility, in order that the first component could be used as a platform for the second component. The first component is an opaque, homogeneous with a removable central section. The thermal properties of the panel are very well defined. The second component is a window, which is used to replace the central section of the first component. The objective of testing the first component is for each participant to determine the thermal transmission coefficient of the panel by both 1-D heat flux measurements and an energy balance on the test cell. For the second component: the whole wall U-value and solar aperture estimated from the test cell energy balance and the window U-value and solar aperture. Common test procedures have been designed and quality procedures have been implemented at each test site. The
436
P. Baker / Energy and Buildings 36 (2004) 435–441
test work is completed and the data sets generated by each team are being made available for cross-analysis by another team. This paper describes the components and procedures and summarises the results to date, including cross-analysis by other teams on the opaque component. The results of a training exercise are also presented. Data were provided to participants from a test carried out at one of the test sites with another component in the aperture of the opaque wall. The aim was to determine the thermal characteristics of the component, without providing the participants with a physical description or any clues to the type of the “unknown” component.
2. The test components Given the number of organisations involved in the Thematic Network it was decided at the beginning that it was impractical to circulate one component for testing for the following reasons: • variation in the test aperture size of test cells between sites; • high transportation costs; and • likely difficulties in keeping to a strict timetable, given the use of the test cells for other tests. The approach adopted was for each organisation to construct its own component(s) according to strict instructions regarding the selection of materials, manufacture and instrumentation. 2.1. Component 1—the opaque wall The first component is an opaque, homogeneous panel consisting of a sandwich of insulation between plywood, with a replacable central section 1500 mm (h) by 1250 mm (w). The thermal properties of the panel are well defined and the required materials are available in the locality of each participant. Expanded polystyrene (PS30), with a density of 30 kg/m3 and a nominal thermal conductivity of 0.033 W/mK, is used to form an insulating panel of thickness 200 mm. A white exterior finish is used on the plywood. It was agreed that each team should measure the heat flux and temperatures in two profiles through the wall (Fig. 1), with one in the centre of the removable section (A) and the other mid-way between the edge of the wall and the removable panel (B). The objective of testing the first component is for each participant to determine the thermal transmission coefficient (U-value) of the panel by both: 1. 1-D heat flux measurements through profiles A and B; and 2. an energy balance on the test cell.
Heat flux sensors flush mounted in plywood
B
A
Removable central panel
inside Fig. 1. Measurement profiles through the opaque wall.
The latter value will include edge effects, which will vary depending on the test cell and installation of the test wall at each site. 2.2. Component 2—the window The objective of the second component is to introduce a greater degree of complexity by using a window to replace the central section of the first component. The window design incorporates double glazing using ordinary clear float glass in a timber frame. The frames for each participant were produced centrally. Each participant obtained glass from a local supplier and samples were tested centrally to ensure consistency. The spectrophotometric tests have shown that there are differences between the samples in their infrared transmittance, which may give variations in the g-value (solar energy transmittance) of the double glazing between 73.2 and 77.3%. Fig. 2 shows the window installed in the opaque surround. The objectives of the test are to determine: 1. the whole wall U-value and g-value estimated from the test cell energy balance; and 2. the window U-value and g-value (frame and glazing).
Fig. 2. The window installed in the opaque surround at BRE Scotland.
P. Baker / Energy and Buildings 36 (2004) 435–441
437
300 HIGH POWER
Power Level [W]
250
ROLBS
200
150
100
50
LOW POWER
0 0
1
2
3
4
5
6
7
8
9
Day
Fig. 3. A typical heating power sequence with low power = 50 W air circulation fan, high power = 50 W fan power + 200 W resistance heater.
3. The test procedures The procedures are based on the COMPASS Measurement and Data Analysis Procedures [1]. A test sequence was devised to reduce the overall test duration, whilst maximising information. It includes a heating/cooling regime using a Randomly Ordered Logarithmically distributed Binary Sequence (ROLBS). The maximum power level was calculated to ensure that the mean test room temperature difference between the low and high power parts of the test sequence should be at least 10 K, but preferably 20 K, without exceeding the safe operational limits of the test cell. The choice of whether to use heating or cooling depends on the local climatic conditions. In a “heating” climate a maximum power level of 250 W is satisfactory for the window test: the heating sequence is shown in Fig. 3. The air leakage of the test room is also determined by pressurisation testing before and after the test to ensure that the test cell meets a requirement of 0.5 air changes per hour at 50 Pa. It is also recommended that the air leakage is monitored continuously during the test by tracer gas measurements. Formats for reporting and data set descriptions have been developed, including a statement of errors.
Heating Power Test Room Temperature
Solar Radiation
H1-2
H2-3
External Temperature
H3-4
C3
C2
Heat Flux
H4-5
C4
C5
Fig. 4. Lumped parameter model of test cell and component showing data inputs and the RC network.
Testing is now complete and the data have been checked, documented and circulated for the cross-analysis exercise. 4.1. Opaque component The available results for the opaque component are given in Table 1.
Table 1 Available opaque wall results
4. Results The choice of analysis method is open to each team, however identification software such as LORD, developed for the PASLINK EEIG, is widely used and some teams have used MATLAB. Such techniques are required to obtain the steady state performance characteristics from the dynamic climate and test cell data. LORD, for example, solves a user-defined network of conductances and capacitances (analogous to electrical RC-networks) with the measured data as input. An example for an opaque wall and test cell is shown in Fig. 4.
Team providing data
A B C D E F G H I
Opaque wall U-values (W/m2 K) Whole wall
Profile A
0.20 0.19 0.19 0.17 0.19 0.17 0.33 0.18 0.23
0.18 0.18 0.17 0.16 0.17 Not available 0.19 0.18 Not available
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P. Baker / Energy and Buildings 36 (2004) 435–441
Table 2 Whole wall U-value results from cross-validation exercise on opaque wall
re-analyse the data, and a check will be made by a third party.
Team providing data
Whole wall U-value (W/m2 K)
Team performing cross-validation analysis
Whole wall U-value (W/m2 K)
4.2. The window component
A B C E G
0.20 0.19 0.19 0.19 0.33
G H B A F
0.24 0.19 0.19 0.19 0.34
Table 3 Centre of panel (profile A) U-value results from cross-validation exercise on opaque wall Team providing data
Profile A U-value (W/m2 K)
Team performing cross-validation analysis
Profile A U-value (W/m2 K)
A B C E G
0.18 0.18 0.17 0.17 0.19
G H B A F
0.17 0.18 0.17 0.18 0.19
The results so far are under evaluation. The indications are that there is more inter-site variability. A thorough analysis of the environmental boundary conditions under which the tests were carried out is in progress as part of the cross-analysis exercise. For example, Fig. 5 shows the theoretical variation of the U-value of double glazing with wind speed due to the change in the external heat transfer coefficient. 4.3. Training exercise with data from “unknown” component Data were provided by team B from tests carried out on: • the whole opaque wall; and • the opaque wall with the unknown component in the 1250 mm × 1500 mm aperture.
The results indicate that satisfactory agreement on the 1-D centre of panel U-values have been achieved. The difference between the whole wall and the centre of panel U-values indicates the magnitude of the edge effects of the wall. The error estimates for the whole wall and 1-D centre of panel U-values are 13 and 6%, respectively. The cross-analysis was performed as a blind exercise: each cross-analysis team was provided with a full test report and data set, but without the test results or the model used for analysis, by the test team. The results are summarised in Tables 2 and 3. Generally there is good agreement between the results of the data provider and the cross-analysis team. Where the results differ significantly, both teams will
The aim of the exercise was to determine the thermal characteristics of the unknown component after first estimating the properties of the opaque part of the wall from the first part of the test with the whole opaque wall with the removable panel in place. Information regarding measurement errors was also given to the participants. Figs. 6–10 show the result of each participating team. Good agreement between the teams was achieved for the thermal transmission (UA-value) and solar aperture (gA-value) of the unknown component: • The UA range = 2.9–3.1 W/K; and • The gA range = 0.65–0.68 m2 . Excellent agreement was achieved for the UA-value of the opaque wall with the unknown component, with a range of values 3.97–4.04 W/K.
2.9 2.7
U-value [W/m2K]
2.5 2.3 2.1 1.9 1.7 1.5 0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Wind speed [m/s]
Fig. 5. The theoretical variation of double glazing U-value with wind speed.
5
P. Baker / Energy and Buildings 36 (2004) 435–441
439
1.7 1.6 1.5
W/K
1.4 1.3 1.2 1.1 1 A
B
C
D
E
F
G
H
J
K
TEAM
Fig. 6. The identified thermal transmission (UA-value) of the whole opaque wall.
0.2
0.19
2
W/m K
0.18
0.17
0.16
0.15 A
B
C
D
E
F
G
H
J
K
TEAM
Fig. 7. The centre of panel U-value of the removable part of the opaque wall.
4.3 4.2 4.1
W/K
4 3.9 3.8 3.7 3.6 A
B
C
D
E
F
G
H
TEAM
Fig. 8. UA-value of opaque wall with component in aperture.
J
K
440
P. Baker / Energy and Buildings 36 (2004) 435–441 3.4 3.3 3.2
W/K
3.1 3 2.9 2.8 2.7 2.6 A
B
C
D
E
F
G
H
J
K
H
J
K
TEAM
Fig. 9. The UA-value of the unknown component.
0.72
0.7
m
2
0.68
0.66
0.64
0.62
0.6 A
B
C
D
E
F
G
TEAM
Fig. 10. The solar aperture (gA-value) of the unknown component.
Overall, the largest contribution to variation in the estimates of the UA-value of the component is due to the identification of the whole wall UA-value of the opaque wall (range 1.24–1.41 W/K). Table 4 summarises the results on the unknown component. The data were supplied by BRE from tests on roof-light components typically used in industrial roofing systems, carried out as part of a UK Government research programme. Although the U-values of such systems can be calculated using KOBRA, TRISCO, etc. little is known about the solar transmittance. With changes in UK Building Regulations the g-value has become important, in terms of restriction in the allowable area of roof-lights to prevent summertime overheating. The tests were performed to provide validation information for U-value calculations and provide real data on solar apertures. The component
is a triple skin GRP roof-light for a composite cladding system (Fig. 11). The calculated U-value is ∼1.6 W/m2 K, i.e. the UA-value for a 1250 mm × 1500 mm sample is ∼3.0 W/K. Table 4 Summary of results on unknown component
UA-value opaque wall U-value Profile A UA-value opaque wall with component in aperture UA-value of component gA-value of component
Average value
Error
Error (%)
1.32 (W/K) 0.18 (W/m2 K) 3.99 (W/K)
0.18 (W/K) 0.01 (W/m2 K) 0.25 (W/K)
14 8 6
3.01 (W/K) 0.66 (m2 )
0.28 (W/K) 0.04 (m2 )
9 6
P. Baker / Energy and Buildings 36 (2004) 435–441
441
Fig. 11. The triple skin GRP rooflight component mounted in the aperture of the opaque wall at BRE Scotland.
5. Conclusions
Acknowledgements
• The results of the round robin tests and the cross-analysis exercises show that a high standard of testing and analysis has been carried out across the Thematic Network. • Workable standard procedures are in place. • Feedback from the participants indicates that improvements are needed with respect to:
The author acknowledges the support of the European Commission in funding the IQ-test Project.
• Choice of identification models; • Error analysis procedures; and • Test procedures to de-correlate gA and UA-values, for example using a shading screen to give initial estimates of UA.
[1] H.A.L. van Dijk, F.M. Tellez, Measurement and data analysis procedures, Final Report of the JOULE II COMPASS Project (JOU2-CT92-0216), 1999.
Reference
IQ-test—improving quality in testing and evaluation of solar and thermal characteristics of building components Paul Baker∗ BRE Scotland, East Kilbride G75 ORZ, UK
Abstract IQ-test is a Thematic Network supported by the European Community under the EESD Programme. The objective of IQ-test is to further the development of common quality procedures at the PASLINK test cell facilities in 12 European countries, for the assessment of the thermal characteristics of building components. This should consolidate the network, integrate the newer test sites and strengthen its common approach of support for new product developments in the field of innovative building components. Round robin tests are underway to assess both the inter-site quality of testing and analytical procedures of the participants. Two components were designed: (1) an opaque, well insulated, homogeneous panel and (2) a window, which is used to replace the central section of the first component. Common test and quality procedures have been implemented at each test site. The data sets generated by each team have been made available for cross-analysis by another team. The results available so far on the first component indicate good agreement between sites. This paper summarises the progress to date. Results are also presented from a training exercise which asked participants to identify the performance characteristics of an unknown component without providing any physical description of the component. © 2004 Published by Elsevier B.V. Keywords: IQ-test; PASLINK; Test cells; Thermal performance
1. Introduction IQ-test is a Thematic Network supported by the European Community under the EESD Programme, which aims to consolidate the work of the network of the PASLINK outdoor test cell facilities in 12 European countries, involved in the energy performance evaluation of the thermal and solar properties of building component. More information may be found on the PASLINK web-site: WWW.PASLINK.ORG. The objective of IQ-test is to further the development of common quality procedures for: • • • •
testing; calibration; data gathering, processing and analysis; interpretation of test results and scaling/replication to real building; and • maintenance of the test infrastructure at the test sites. This should consolidate the network, by integrating the newer test sites and strengthening its common approach of support for new product developments in the field of inno∗ Current address: Centre for Research on Indoor Climate & Health, Glasgow Caledonian University, G4 OBA, UK. E-mail address: [email protected] (P. Baker).
0378-7788/$ – see front matter © 2004 Published by Elsevier B.V. doi:10.1016/j.enbuild.2004.01.046
vative building components through semi-standardised tests and pragmatic, practicable and affordable but accurate procedures. As part of the work of the Network, round robin tests are being performed as part of a feasibility study for standardisation activities. The objective is to assess both the inter-site quality of testing and analytical procedures of the members, with a view to developing standards for outdoor testing. High quality data for model calibration will also be generated. Two components were designed, incorporating flexibility, in order that the first component could be used as a platform for the second component. The first component is an opaque, homogeneous with a removable central section. The thermal properties of the panel are very well defined. The second component is a window, which is used to replace the central section of the first component. The objective of testing the first component is for each participant to determine the thermal transmission coefficient of the panel by both 1-D heat flux measurements and an energy balance on the test cell. For the second component: the whole wall U-value and solar aperture estimated from the test cell energy balance and the window U-value and solar aperture. Common test procedures have been designed and quality procedures have been implemented at each test site. The
436
P. Baker / Energy and Buildings 36 (2004) 435–441
test work is completed and the data sets generated by each team are being made available for cross-analysis by another team. This paper describes the components and procedures and summarises the results to date, including cross-analysis by other teams on the opaque component. The results of a training exercise are also presented. Data were provided to participants from a test carried out at one of the test sites with another component in the aperture of the opaque wall. The aim was to determine the thermal characteristics of the component, without providing the participants with a physical description or any clues to the type of the “unknown” component.
2. The test components Given the number of organisations involved in the Thematic Network it was decided at the beginning that it was impractical to circulate one component for testing for the following reasons: • variation in the test aperture size of test cells between sites; • high transportation costs; and • likely difficulties in keeping to a strict timetable, given the use of the test cells for other tests. The approach adopted was for each organisation to construct its own component(s) according to strict instructions regarding the selection of materials, manufacture and instrumentation. 2.1. Component 1—the opaque wall The first component is an opaque, homogeneous panel consisting of a sandwich of insulation between plywood, with a replacable central section 1500 mm (h) by 1250 mm (w). The thermal properties of the panel are well defined and the required materials are available in the locality of each participant. Expanded polystyrene (PS30), with a density of 30 kg/m3 and a nominal thermal conductivity of 0.033 W/mK, is used to form an insulating panel of thickness 200 mm. A white exterior finish is used on the plywood. It was agreed that each team should measure the heat flux and temperatures in two profiles through the wall (Fig. 1), with one in the centre of the removable section (A) and the other mid-way between the edge of the wall and the removable panel (B). The objective of testing the first component is for each participant to determine the thermal transmission coefficient (U-value) of the panel by both: 1. 1-D heat flux measurements through profiles A and B; and 2. an energy balance on the test cell.
Heat flux sensors flush mounted in plywood
B
A
Removable central panel
inside Fig. 1. Measurement profiles through the opaque wall.
The latter value will include edge effects, which will vary depending on the test cell and installation of the test wall at each site. 2.2. Component 2—the window The objective of the second component is to introduce a greater degree of complexity by using a window to replace the central section of the first component. The window design incorporates double glazing using ordinary clear float glass in a timber frame. The frames for each participant were produced centrally. Each participant obtained glass from a local supplier and samples were tested centrally to ensure consistency. The spectrophotometric tests have shown that there are differences between the samples in their infrared transmittance, which may give variations in the g-value (solar energy transmittance) of the double glazing between 73.2 and 77.3%. Fig. 2 shows the window installed in the opaque surround. The objectives of the test are to determine: 1. the whole wall U-value and g-value estimated from the test cell energy balance; and 2. the window U-value and g-value (frame and glazing).
Fig. 2. The window installed in the opaque surround at BRE Scotland.
P. Baker / Energy and Buildings 36 (2004) 435–441
437
300 HIGH POWER
Power Level [W]
250
ROLBS
200
150
100
50
LOW POWER
0 0
1
2
3
4
5
6
7
8
9
Day
Fig. 3. A typical heating power sequence with low power = 50 W air circulation fan, high power = 50 W fan power + 200 W resistance heater.
3. The test procedures The procedures are based on the COMPASS Measurement and Data Analysis Procedures [1]. A test sequence was devised to reduce the overall test duration, whilst maximising information. It includes a heating/cooling regime using a Randomly Ordered Logarithmically distributed Binary Sequence (ROLBS). The maximum power level was calculated to ensure that the mean test room temperature difference between the low and high power parts of the test sequence should be at least 10 K, but preferably 20 K, without exceeding the safe operational limits of the test cell. The choice of whether to use heating or cooling depends on the local climatic conditions. In a “heating” climate a maximum power level of 250 W is satisfactory for the window test: the heating sequence is shown in Fig. 3. The air leakage of the test room is also determined by pressurisation testing before and after the test to ensure that the test cell meets a requirement of 0.5 air changes per hour at 50 Pa. It is also recommended that the air leakage is monitored continuously during the test by tracer gas measurements. Formats for reporting and data set descriptions have been developed, including a statement of errors.
Heating Power Test Room Temperature
Solar Radiation
H1-2
H2-3
External Temperature
H3-4
C3
C2
Heat Flux
H4-5
C4
C5
Fig. 4. Lumped parameter model of test cell and component showing data inputs and the RC network.
Testing is now complete and the data have been checked, documented and circulated for the cross-analysis exercise. 4.1. Opaque component The available results for the opaque component are given in Table 1.
Table 1 Available opaque wall results
4. Results The choice of analysis method is open to each team, however identification software such as LORD, developed for the PASLINK EEIG, is widely used and some teams have used MATLAB. Such techniques are required to obtain the steady state performance characteristics from the dynamic climate and test cell data. LORD, for example, solves a user-defined network of conductances and capacitances (analogous to electrical RC-networks) with the measured data as input. An example for an opaque wall and test cell is shown in Fig. 4.
Team providing data
A B C D E F G H I
Opaque wall U-values (W/m2 K) Whole wall
Profile A
0.20 0.19 0.19 0.17 0.19 0.17 0.33 0.18 0.23
0.18 0.18 0.17 0.16 0.17 Not available 0.19 0.18 Not available
438
P. Baker / Energy and Buildings 36 (2004) 435–441
Table 2 Whole wall U-value results from cross-validation exercise on opaque wall
re-analyse the data, and a check will be made by a third party.
Team providing data
Whole wall U-value (W/m2 K)
Team performing cross-validation analysis
Whole wall U-value (W/m2 K)
4.2. The window component
A B C E G
0.20 0.19 0.19 0.19 0.33
G H B A F
0.24 0.19 0.19 0.19 0.34
Table 3 Centre of panel (profile A) U-value results from cross-validation exercise on opaque wall Team providing data
Profile A U-value (W/m2 K)
Team performing cross-validation analysis
Profile A U-value (W/m2 K)
A B C E G
0.18 0.18 0.17 0.17 0.19
G H B A F
0.17 0.18 0.17 0.18 0.19
The results so far are under evaluation. The indications are that there is more inter-site variability. A thorough analysis of the environmental boundary conditions under which the tests were carried out is in progress as part of the cross-analysis exercise. For example, Fig. 5 shows the theoretical variation of the U-value of double glazing with wind speed due to the change in the external heat transfer coefficient. 4.3. Training exercise with data from “unknown” component Data were provided by team B from tests carried out on: • the whole opaque wall; and • the opaque wall with the unknown component in the 1250 mm × 1500 mm aperture.
The results indicate that satisfactory agreement on the 1-D centre of panel U-values have been achieved. The difference between the whole wall and the centre of panel U-values indicates the magnitude of the edge effects of the wall. The error estimates for the whole wall and 1-D centre of panel U-values are 13 and 6%, respectively. The cross-analysis was performed as a blind exercise: each cross-analysis team was provided with a full test report and data set, but without the test results or the model used for analysis, by the test team. The results are summarised in Tables 2 and 3. Generally there is good agreement between the results of the data provider and the cross-analysis team. Where the results differ significantly, both teams will
The aim of the exercise was to determine the thermal characteristics of the unknown component after first estimating the properties of the opaque part of the wall from the first part of the test with the whole opaque wall with the removable panel in place. Information regarding measurement errors was also given to the participants. Figs. 6–10 show the result of each participating team. Good agreement between the teams was achieved for the thermal transmission (UA-value) and solar aperture (gA-value) of the unknown component: • The UA range = 2.9–3.1 W/K; and • The gA range = 0.65–0.68 m2 . Excellent agreement was achieved for the UA-value of the opaque wall with the unknown component, with a range of values 3.97–4.04 W/K.
2.9 2.7
U-value [W/m2K]
2.5 2.3 2.1 1.9 1.7 1.5 0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Wind speed [m/s]
Fig. 5. The theoretical variation of double glazing U-value with wind speed.
5
P. Baker / Energy and Buildings 36 (2004) 435–441
439
1.7 1.6 1.5
W/K
1.4 1.3 1.2 1.1 1 A
B
C
D
E
F
G
H
J
K
TEAM
Fig. 6. The identified thermal transmission (UA-value) of the whole opaque wall.
0.2
0.19
2
W/m K
0.18
0.17
0.16
0.15 A
B
C
D
E
F
G
H
J
K
TEAM
Fig. 7. The centre of panel U-value of the removable part of the opaque wall.
4.3 4.2 4.1
W/K
4 3.9 3.8 3.7 3.6 A
B
C
D
E
F
G
H
TEAM
Fig. 8. UA-value of opaque wall with component in aperture.
J
K
440
P. Baker / Energy and Buildings 36 (2004) 435–441 3.4 3.3 3.2
W/K
3.1 3 2.9 2.8 2.7 2.6 A
B
C
D
E
F
G
H
J
K
H
J
K
TEAM
Fig. 9. The UA-value of the unknown component.
0.72
0.7
m
2
0.68
0.66
0.64
0.62
0.6 A
B
C
D
E
F
G
TEAM
Fig. 10. The solar aperture (gA-value) of the unknown component.
Overall, the largest contribution to variation in the estimates of the UA-value of the component is due to the identification of the whole wall UA-value of the opaque wall (range 1.24–1.41 W/K). Table 4 summarises the results on the unknown component. The data were supplied by BRE from tests on roof-light components typically used in industrial roofing systems, carried out as part of a UK Government research programme. Although the U-values of such systems can be calculated using KOBRA, TRISCO, etc. little is known about the solar transmittance. With changes in UK Building Regulations the g-value has become important, in terms of restriction in the allowable area of roof-lights to prevent summertime overheating. The tests were performed to provide validation information for U-value calculations and provide real data on solar apertures. The component
is a triple skin GRP roof-light for a composite cladding system (Fig. 11). The calculated U-value is ∼1.6 W/m2 K, i.e. the UA-value for a 1250 mm × 1500 mm sample is ∼3.0 W/K. Table 4 Summary of results on unknown component
UA-value opaque wall U-value Profile A UA-value opaque wall with component in aperture UA-value of component gA-value of component
Average value
Error
Error (%)
1.32 (W/K) 0.18 (W/m2 K) 3.99 (W/K)
0.18 (W/K) 0.01 (W/m2 K) 0.25 (W/K)
14 8 6
3.01 (W/K) 0.66 (m2 )
0.28 (W/K) 0.04 (m2 )
9 6
P. Baker / Energy and Buildings 36 (2004) 435–441
441
Fig. 11. The triple skin GRP rooflight component mounted in the aperture of the opaque wall at BRE Scotland.
5. Conclusions
Acknowledgements
• The results of the round robin tests and the cross-analysis exercises show that a high standard of testing and analysis has been carried out across the Thematic Network. • Workable standard procedures are in place. • Feedback from the participants indicates that improvements are needed with respect to:
The author acknowledges the support of the European Commission in funding the IQ-test Project.
• Choice of identification models; • Error analysis procedures; and • Test procedures to de-correlate gA and UA-values, for example using a shading screen to give initial estimates of UA.
[1] H.A.L. van Dijk, F.M. Tellez, Measurement and data analysis procedures, Final Report of the JOULE II COMPASS Project (JOU2-CT92-0216), 1999.
Reference