Category Archives: BACKGROUND

On the evaluation of visual performances of obstructed glass panes

Michele Zinzi, ENEA Ente Nazionale Energia e Ambiente Giuseppe Rossi, IEN Istituto Tecnico Nazionale Galileo Ferraris Paola Iacomussi, IEN Istituto Tecnico Nazionale Galileo Ferraris Giacomo Zangiacomi, Stazione Sperimentale del Vetro

The glass industry is oriented towards the production of always new materials, sometimes to improve the performances of transparent systems, sometimes to improve their aesthetics and building envelopes. Obstructed glazings can be used for both functions, in fact reducing the amount of solar radiation transmitted by the transparent system, they can avoidoverheating and glare for users, as well as lower cooling loads for the air conditioning. At the same time, they can be used by architects for innovative fagade solutions in buildings.

Even if the light and energy performance must be evaluated according to the relevant European and international standards, some more information should be submitted to the public for a more comprehensive evaluation of the product. One important issue is the obstruction of the view through the transparent system cause by the obstructions, which can be printed on the glass or put down on a plastic layer successively laminated between two glass sheets.

In this paper a complete light and visual characterization of some of such innovative products is presented. In particular the angular hemispherical and the bi-directional transmittance are measured with two experimental facilities. The view-through index, as defined in the REVIS project, is calculated. An innovative method, whose methodology is still at a preliminary stage, to evaluate the quality of vision is then presented. Such method is based on the analysis of images collected by CCD detector and successive mathematical evaluation. If after subjective tests this correlation will be enough accurate an alternative and comparable measurement procedure might be proposed.

O. O. Energiesparverband

The commercial buildings programme is carried out by O. O. Energiesparverband. O. O. Energiesparverband is the regional energy agency of Upper Austria and was established in 1991 by the regional government. Aim of the agency is the promotion of energy efficiency, RES and innovative energy technologies. O. O. Energiesparverband is a central institution for energy information and one of Europe’s largest energy advice and information providers. Services to different target groups, from private households to SME’s and public bodies are offered.

The main services of O. O. Energiesparverband include:

• energy information and awareness raising activities

• energy advice for private households and industry: 15,000 energy advice sessions annually

• international co-operation & European projects: vice-precidency of FEDARENE, member of EUFORES, co-ordinator of the OPET-RES-e network

• management of a sustainable buildings programme which includes energy certification for buildings and the calculation of an energy index for every new single family house (> 30,000 calculations carried out)

• a great number of different training activities (for energy advisors, for installers etc.)

• organisation of conferences, workshops, seminars, competitions

• management of the OEC, the network of green energy businesses.

Conclusions

The example of O. O. Energiesparverband and Upper Austria clearly demonstrates that a lot can be done at a regional level, provided the necessary political backing is given and a comprehensive action plan including information and promotion programmes is carried out.

Thermodynamic Model

These experiments are evaluated by using a thermodynamic model and the comfort criteria according to DIN 1946 [5]. Based on this evaluation, differences between the summer 2002 and the very hot summer 2003 can be evaluated for every building in order to characterise the building physics and weak points in the specific building concept.

The thermodynamic model is based on the specification in EN 832 [6] and focuses on the essential building parameters according to Keller’s approach [7]. The underlying theory can be taken from Baehr’s textbook [8]. The indoor room temperature Ti oscillates periodic around its mean value T, m with the amplitude ATi. Mean temperature and amplitude can be derived from the heat loss coefficient H, the specific heat gain Gm and its amplitude AG and the time constant т or the heat storage C of the room, respectively.

( 1 ) ( 2 )

T(t) = Tm +AT’sin(®-1) with ® = 2n/t0 with t0 = cycle period

with Tm = Tam + — and AT = to -[at, +— | with C/H

l, m am H 1 2-n-z I a H )

Applications

The authors [9] have shown that this simplified model corresponds to a sophisticated building simulation and have applied this method successfully to experiments (with well — known boundary conditions) and field measurements which are associated with uncertainties.

As the thermal performance of a specific building can be discerned accurately by this method, the data model can be practically used

— for data analysis of field measurements (here: passively cooled buildings).

— for quality assurance of the building simulation during the design phase since the complex interactions calculated by the building simulation can be verified with a few concise parameters.

— for measurements during the implementation phase or during the operation to determine the building parameters for advanced control strategies, i. e. predictive controllers.

with an acceptable time effort.

The Summer of 2003

In Germany, the three summer months June, July and August 2003 were significantly too warm. The daily mean temperature was 19.6 °C, 3.4 K above the reference temperature. This extreme summer weather can be predicted by the numerical climate models; summer conditions like those experienced in 2003 should occur statistically every 1,000 years [10], even if the anthropogenic global warming is taken into account. In particular regions (e. g. Freiburg), the mean ambient air temperature was 5 K higher than the reference year.

If the summer 2003 was used as design weather for passive cooling concepts, (almost) every building would need air-conditioning to meet the comfort criteria. Though the summer 2003 is not suitable for design studies, its impact on the design of mechanical and passive cooling systems is discussed intensely.

Experimental study

The experiment carried out in the building from April 25th till May 19th 2003 is analysed.

Various weather data are measured by a local weather station situated close to th< building: global and diffuse horizontal radiation (W/m2), ambient temperature (°C), ai relative humidity (%) and wind velocity (m/s) and direction (°).

The variables recorded inside the building are: air temperature (°C) at different height and locations, air relative humidity (%), heat flux density leaving the room through th< ceiling, south, north and west wall (W/m2K). Description of the monitoring instruments used are summarised in Table 2.

The data-acquisition system sampling rate is 1 second for each channel. Then the dat are integrated over 10 minutes preceding the time of storage in file on the workstation har disk. During the monitoring period, the lighting, heating and cooling systems have beer turned off. During working hours the north window was 1 cm opened. Before use fo analysis the data has been cleaned and filtered by detecting outliers, missing observation and values with not physical signification (commonly due to noise). These data have been repair.

OPTICAL GAIN OF A ROOM

In order to get a realistic analysis of the optical performance of the Photovoltaic modules, a room has been considered where a traditional glass fagade was replaced by a PV fagade made of high visual modules. In that case the solar light was measured before and after the application.

The intervention aimed to increase the comfort in order to increase the control of the direct light entering the windows and to avoid the over heating, particularly in the summertime.

The day light factor method [4,5] has been used to characterise the indoor lighting conditions.

The daylight factor DF is defined as the ratio of the solar lighting in a particular point inside the room E divided for the lighting outside on an horizontal surface facing the hemispherical sky without any obstruction.

A method to have an approximated value of DF is the average day ligh factor DFm defined as

DFm = Eim / Ee, hm x 100

Ei is the average solar lighting on a point inside the room [lux]

Ee, hm is the average lighting on an horizontal plane outside, caused by the whole sky, excluding the direct component [lux]

The room is a part of the CR ENEA building at Portici (Na). It is located at the ground floor,

3.6 mx5 m, for a surface of 18 m2. The fagade facing the South presented a surface of

11. 7 m2 completely glazed and it is the object of the project.

Initially the fagade, 5.01 x2.14 squares meters, in a structure made of reinforced concrete, was divided in four vertical windows, divided with frames. The project intended to keep the original dimensions but has been realized in a different way, with three vertical partitions including two modules each. In conclusion the PV fagade is composed by 6 glass-glass modules realized by Schuco using the SGgPROSOL® technology in a sandwich structure with the two external panes made of heat-strengthened glass (sGGPLANIDUR®) and the solar cells bonded between them by means of an high-transparent resin.

CLIMATIC ZONES’

CLIMATICZONES (№P RESENT ATI VE

STATIONS)

■ ■ r

HOT-MY

HOT — MY

ДДД

BUILDING -11

Подпись: ДДД

System Configuration and Application

Fig. 1 Focusing effect of a glass bar on the incoming direct radiation. The glass bars can be rotated to adjust the reflective layer with respect to the sun’s altitude.

The system is based on the focusing effect of glass bars for parallel sunlight (Fig.1). The incoming light is focused on a line along the inside surface of the bars. In this way direct radiation is separated from diffuse radiation. By applying a reflective layer on the focusing line the direct radiation can be blocked out, while the diffuse part can still enter the room. The reflective layer needs a rotational adjustment mechanism in order to follow the sun’s altitude.

low-e coating

■и

Idir

V

The glass bars are positioned horizontally between two glass panels (Fig.2). The preferred position is either close to the outside window to decrease heat gains in summer, or close to the inside window to raise secondary heat gains in winter. This can be accomplished by horizontally mobile glass bars, even though this will require more mechanical pieces. In this paper we observe the summer case with low heat gains.

Idiff

;>

Isec = Isec heat + Isec dir

+ Is

sec diff

в inside

outside

Ig = I dir + Idiff

Fig. 2 Position of the glass bars inside a double glazing and chosen nomenclature for

irradiances.

The main fields of application are sky lights and fanlights. The cylinders are positioned to almost touch each other. In this case we have a plain translucent element which would keep the direct sunlight out. Optionally, to allow transparency without changing the other properties, we can leave a small gap between the cylinders. In this way, direct sunlight will be able to enter the room but only at very low solar altitude, when it is not disturbing.

Building Energy Simulations

The simulation tool employed in the present study for predicting the energy performance of the SIEEB building is the DOE 2.1 building energy simulation programme developed by Lawrence Berkley Laboratory (1980). Based on preliminary design of SIEEB, the characteristics of building are defined in Table 1.

Table 1. SIEEB characteristics — Preliminary design

Location

Tsinghua University, Beijing (Latitude: 39° 48’ N, Longitude: 116° 28’ E)

Building type

Office building, 10 storeys above ground + 2 storyes underground

Floor area

Total floor area — 15,107 m2 Air-conditioned area — 12,226 m2

Building Envelop

Exterior wall

Plaster+18cm hollow brick+ 6cm insulation+8cm hollow brick+plaster U value = 0.40 W/m2 K

Window

South, East & West

5mm glass (low-e)+22mm air-gap with Venetian blinds+6 mm glass (low-e) U-value = 1.3 W/m2 K, Shading coefficient = 0.63 North & Interior Court

5mm glass (low-e)+15mm gap filled with argon gas +6 mm glass (low-e) U-value = 1.1 W/m2 K, Shading coefficient = 0.63

Roof

1cm ceramic+2cm concrete + 6cm insulation+25cm hollow brick+plaster U-value = 0.42 W/m2 K

Ratio Glazing to total area

South = 42%, East and West = 34% and North = 14%

The preliminary design of the SIEEB is shown in figure 2.

Methods

Basis of the investigated Slurries is microencapsulated paraffin, which is also already used in PCM-Construction-Materials [5, 6, 7]. The diameter of this capsules is down to some ^m and the thickness of the shell is far below 500 nm. Hexadecan with it’s melting point (Tm) of 18°C, Oktadecan (Tm = 28°C) or also Triakontan (Tm = 68°C) are examples for the paraffins, which are encapsulated. Melting points are also adjustable between the melting-temperatures of different Paraffins by mixing them [2].

The PMMA-shell prevents an interaction between the carrier-fluid and the PCM, that’s why in principle no additives are required in the slurry. So it’s relative easy to prepare such a PC-Slurry: The Capsules are delivered by BASF as 50% dispersion, at ISE the slurry is mixed by adding water to the dispersion till a pumpable consistency is reached. At the test-rig capsules concentrations up to 30% have been pumped. This concentration has still a comparatively low viscosity. The dynamic viscosity of a slurry with an amount of 25% capsules reaches from 7 to 8mPa • s1. Values of the kinematic viscosity for slurries with different percentage of microcapsules can be found in literature (cp. table 1).

Table 1: Kinematic Viscosities and density of different Slurries, Shell material: Urea- formaldehyde, from [1]

Slurry

Density

M

Kinematic Viscosity

И

water

997

9.07 • 10-[38]

5% suspension

983

1.04- 10-6

10% suspension

975

1.24- 10-6

15% suspension

966

1.51 • 10-6

20% suspension

957

1.90■ 10-6

A test-rig was built up to check the stability of these slurries. Fig. 1 shows on the left side a schematic of the test-rig. Three different cycles are visible: 1. The cooling-cycle (blue) with a performance of 4 kW, 2. The heating-cycle (red) with a performance of 10 kW and 3. The slurry-cycle (black) with volume-flows up to 1000 l/h and a fluid-capacity of 15 l. The heat is transferred into and out off the slurry by screwed plate heat exchangers. All temperatures are measured by Pt100 thermo-sensors, which are mounted directly on each in — and outlet of both heat exchangers. The volume-flows in each cycle are recorded by magnetic-inductive flow-meter and the pressure losses are measured by relative-pressure-sensors.

The slurries has been pumped for several weeks to verify their stability. Thus at a volume — flow of 500 l/h is adding up to approx. 33 melting — and crystallisation-cycles per hour, that’s about 800 cycles a day. After different periods samples are taken to check their quality by measuring the melting enthalpy by DSC, SEM-pictures are taken to check visually the condition of the shell. The slurry is also visually checked after finishing a test sequence.

і

Conventional components like expansion vessels, breathers and plate heat exchangers are used in the test-rig. It is also proven to run them with the mentioned PCS. Parallel to the thermal and hydraulically characterisation of the slurries it is possible to check also other components in a second test-cycle.

Figure 1: Test-rig to investigate the slurries and components

For the thermal characterisation the volume-flow and the inlet — and outlet-temperatures of each heat exchanger is measured. The primary side of heat exchangers for heating and the secondary side of the heat exhanger for cooling is operated only with pure water. With slurry on the slurry-cycle the heat-capacity (cp) of the capsules fraction is calculated with 2,4 For water the heat flow is computed as follows:

Q pri/seCwater m ‘ CPwater ‘ (Th Tc) (l)

Th and Tc is equal the the heat exchangers hot resp. cold temperature of the inlet resp. outlet. The heatflow on the slurry-side is computed for a slurry with a capsules fraction of

xcapsule to:

Qslurry xcapsule ‘ CPcapsule ■ (Th Tc) + (1 Xcapsule ) ‘ ГП • Cpwater ■ (Th Tc) (2)

Because the measured temperatures are equal to the sensible heat-flow it is necessary to recompute the latent heat by the heat transfer characteristic of the heat exchanger. To do that, first of all the heat transfer characteristic is measured with water also in the slurry — cycle. The heat flow is increased by heating up the inlet water on the primary side step by step. Than the heat flow is calculated for each temperature by equation 1. Since there are no higher heat losses with slurry at equal boundary conditions (same mass-flow and air temper­atures) the heat flow difference between the characterisation with water and measurement with the slurry (eq. 2) must be stored as latent heat:

(3)

Q latent Q slurry—cyclewater Q slurry—cycles

ДИ

capsules

(4)

Q latent

m • (xcapsule )

With the adjusted mass-flow and known capsule-concentration it is possible to compute now the specific heat of fusion and to check, in comparison with the DSC-measurements, the capability of latent heat-storage into the slurry.

AT

(5)

Qsi

urry

xcapsule

Ahcapsule + CP water

area of mealting

0 ■ 0 10 20 30 40 50 60

Temperature [°C]

Slurry 50% — — Slurry 30%————————- Slurry 20% — — Capsules 100%————— Water — —

Figure 2: Enthalpy-Curves for slurries with different amount of capsules and a melting point of approx. 28° C

The capability of such a slurry to store heat is computed with the following equation:

To simulate PCS in different applications the simulation-program COLSIM was extended to compute with variable cp. For the simulation the cp-curve, which was obtained by a DSC — measurement of the pure capsules, was integrated to get the enthalpy-curve as function of the temperature. For slurries with different amounts of capsules the enthalpy-curve is computed with the following formula:

hslurry(0) — h capsuledsc (0) ■ xcapsule + hwater (0) ■ (1 — xcapsule)

Where h is the enthalpy per kg and 0 the temperature in °C. Fig. 2 shows different enthalpy curves for slurries with different amounts of microcapsules. Unlike the cp-curve, the enthalpy curve has the advantage to be a continuous increasing function thus the energy content is well-defined by temperature (cp. 2). The so called enthalpy-method is also used in other models for the simulation of PCM [3]. COLSIM has also the opportunity to compute a fluid system like collector cycles and/or heating-cycles in time-steps down to some seconds. This is the result of COLSIM’s explicit computation without iterations. Due to the small time — steps, the energy-changes from simulation-step to simulation-step are tiny what enables COLSIM to simulate with the finite difference method by inclusion of the results from the last time-step. For the energy content Q of a defined amount of a heat-carrier-fluid m at simulation time t the following simplified equation is essential:

Qt — m ■ ht-1 + Qhains — Qhosses (6)

Data analysis

Free evolution and outdoors weather implicate dynamic testing conditions, as it is clearly seen in the recorded data in Figure 3 to Figure 6, so dynamic testing is suitable for data analysis in this case.

Several references report the use of dynamical tools to estimate the main characteristics of building components from outdoors testing in real buildings (Ralb, 1988) and also using tests cells (SIC 1, 1994), (SIC 2, 1996). Usually these tests impose an optimum testing strategy as previously mentioned.

In this case analysis is complicated as no test strategy was implemented to optimise test sequence regarding analysis, and also because of the low range of some of the available signals due to the high degree of insulation of each wall.

Dynamic ARX multi-output models have been used for data analysis. General mathematical details about the analysis tools are described in (Ljung, 1999). More particular details about the estimation of the physical parameters are reported in (Jimenez et al, 2003). Indoors temperature and heat flux have been considered as output and outdoors temperature has been considered as input.

Taking into account that all walls where very thick, opaque and highly insulating solar radiation was not included into the used model.

Once obtained a suitable model for the dynamical system, U value was obtained taking into account that the obtained dynamical model particularised to the case that all inputs and outputs were constants must coincide with the steady state equation.

Results

The following results have been obtained:

Table 1: Results

Wall

U (W/m2K)*

South

0.13 ± 0.01

North

0.17 ± 0.03

West

0.184 ± 0.006

Ceiling

0.068 ± 0.005

*Only identification errors are included. Higher uncertainty is expected when all measurement contributions were considered.

All results were according to their expectable range, but all walls were found more insulating than expected.

Conclusions

Satisfactory results have been obtained, using non-intrusive measurements, besides testing sequence was not optimum.

Realistic estimations for U value of each wall of the building have been made available for other simulations works to estimate actual heating and cooling loads and also to evaluate the effect of the implemented saving strategies.

Discrepancies regarding values estimated according to the NBE-CT-79 could be due to the faulty sealing in the air chamber into the walls that could lead to produce ventilation phenomena that where not taken into account.