4.0 Introduction
4.1 Parametric studies
4.2 Upgrading strategy
4.3 The issue of cost
4.4 Inovatory design
4.5 Low energy housing
4.6 Re-design
4.7 Critical control
4.8 Feasibility study
4.9 Late design-stage use
4.10 Comfort
4.11 Speculative development
4.12 Training Exemplars
4.12.1 Single office
4.12.1b Additional shading analysis
4.12.2 Simple building
4.12.2b Additional fluid flow analysis
4.12.3 Small house
4.12.4 Large house
4.12.5 Test cells
4.12.6 Special focus
4.12.7 Office block
4.12.8 Plant
Top Prec Next

Section Four

Example applications
of the
ESP-r system

4.0 Introduction

Sections 4.1 through 4.11 presents a number of short case studies of typical and atypical designs as analysed by ESP-r. They have been selected to indicate the possibilities for performance assessment by simulation. The remaining sections describe a number of simulation exercises based on exemplars supplied with the system. These have a dual role: to test the ESP-r program modules on first implementation and to provide training for new users thereafter. The exercises progress from the simple to the more complex and have been designed to test several aspects of ESP-r. Each of the training sessions deals with a basic problem type with variations which explore simulation topics.

Throughout the exercises reference is made to standard ESP-r databases and test files. As explained elsewhere, such files are held in a strict directory structure. In the text that follows the Unix syntax is used so that ~esru/esp-r/climate means sub-directory climate of sub-directory esp-r of the home directory (wherever defined) of esru. Similarly ~esru/esp-r/training/office means sub-directory office of sub-directory training of sub_directory esp-r of the home directory of esru.

4.1 Parametric studies

Parametric analysis of building energy performance is, perhaps, the prerequisite of a more complete understanding of the issues relating to energy efficient building design. The process of simulation can be used to increase the corpus of knowledge upon which future designs can be built. ESP-r has been used as the simulation tool in a number of parametric studies.

In one, different window designs were analysed in terms of their performance in British and Scandinavian climates. Annual simulations were performed for a number of combinations of facade orientation, window size, window type and fabric capacity sampled from the many combinatorial possibilities. Typical occupancy patterns, internal gains and window curtain operation was assumed throughout. The different windows were then analysed in terms of the cost-benefit associated with the provision of varying comfort standards.

In another study, the model was used to generate design guidelines in public buildings by systematically varying the major design parameters such as insulation, capacity, window size, heating system regulation and degree of air permeability.

4.2 Upgrading strategy

Many Government agencies in the UK own housing stock which dates from the early 1950’s. In recent times much of this stock has fallen due for upgrading. Obviously some mechanism must be employed to establish the most productive strategy. ESP-r has been used as such a mechanism.

A sample of houses in any estate are analysed, firstly in their original form, and subsequently with a range of alternative upgrading features formulated on the basis of the initial simulation results. In one case, the prime heat loss path was identified by ESP-r as being through the suspended timber floor. This occurred in a building for which substantial wall insulation was planned. As a result the upgrading proposal was modified and the client’s investment put to better use.

4.3 The issue of cost

ESP-r was once used by a large regional council to investigate the possibilities in a proposed building conversion. The study involved an in-depth investigation into heating demand diversity as affected by alternative zoning strategies, plant control schedules and fabric treatments. Their resulting report included the technical details of the project but went on to raise the following general points.

The total cost incurred by them in the simulation exercise was calculated at half the cost incurred in a parallel exercise which involved only the calculation of zone heat loss by conventional ‘manual’ methods.

The results from the ESP-r exercise allowed a more detailed analysis of both the building and plant performance than would have been possible by other means. In particular, the ability to interactively impose design changes was considered to be extremely useful.

The graphical presentation of results was considered invaluable as a means of conveying information to the design team.

4.4 Inovatory design

ESP-r has also been used to test inovatory design solutions. In one application, the program was used to model a proposed solar wall construction which formed part of a multi-million pound laboratory complex.

The movement of large quantities of air had suggested a design solution in which this air was passed over the entire south-facing building facade and contained within an outer glass skin. ESP-r was used to simulate this solar wall to predict the potential annual pick-up of solar energy and the corresponding reduction of the south facade heat loss due to the insulating effect of the additional glass and air space combination.

Modelling of the system was complicated by the proposed inclusion of ducts within the air space which caused wall shading as well as convective heat pick-up. What was required was a first principle computation method capable of modelling the complexities of the system.

4.5 Low energy housing

In conjunction with a private architectural practice ESP-r was used by the modelling team to develop a specification for a low energy house. Primary objectives were to select a building mass and insulation scheme which, in conjunction with the selected window configuration, would effectively minimise the heating demand. Using real climatic data, initial simulations resulted in decisions on orientation, shape, zoning, window size and window type. Later simulations - assuming real occupancy and plant operational patterns - aided decisions on fabric weight, position of thermal capacity, position of insulation, and effective solar screening to avoid overheating during peak solar times. Issues relating to controlled ventilation and heat distribution between different zones were also examined.

The final scheme was then rigorously analysed over whole year periods and, in this way, efficient energy performance was established.

4.6 Re-design

ESP-r was used to investigate re-design issues in converting a large dockland complex to house departments of a polytechnic. The exercise involved an analysis of the relationship between the existing massive construction and the potential overheating resulting from solar penetration and the introduction of high internal loads. The possible set of conversion solutions were constrained by the existence of a preservation order prohibiting substantive changes to the building facade. The restriction on facade shading devices focused attention on the cost-benefit associated with various glazing types in terms of their ability to minimise solar penetration. ESP-r was used to find a suitable economic solution.

4.7 Critical control

In another new design application ESP-r was used by a central government agency to analyse critical environmental conditions in an astronomical laboratory where control of the thermal environment is crucial to the effective working of the telemetry equipment.

ESP-r was used to select a constructional scheme which would ensure that internal, untreated conditions would remain within Image FIGS/grohtml-12140-1.png 0.1°C of the required condition. The proposed massive concrete construction had a large thermal time constant which had rendered simple predictive techniques unsuitable.

4.8 Feasibility study

A large practice was asked to carry out a feasibility study and produce a development scheme for the comprehensive redevelopment of a narrow but important urban site; the redevelopment had to include two office blocks, each of 100,000 Image FIGS/grohtml-12140-2.png , to be let by the client. The narrowness of the site suggested a narrow floor plan in each office block, one rising to six stories, the other to eight stories. The proposal that one of the blocks should be air conditioned, the other not, suggested to the architect an investigation of a broad range of construction types under ‘artificial’, ‘ambient’, and ‘assisted’, environmental control.

In the event, a two-stage ESP-r analysis was carried out in the context of the non-air conditioned building. In the first stage, office modules on the SW and NE orientations were simulated, respectively, under summer and winter conditions; within a fixed external envelope with 35% glazing. ESP-r was used to explore the implications of achieving shading on the SW facade, increasing the thermal mass of internal partitioning, altering the rate of mechanical ventilation and double-glazing the NE facade. In the second stage, more explicit proposals were generated for the pattern of external glazing, the internal sub-division of space, etc; and a similar series of investigations, using ESP-r, carried out.

4.9 Late design-stage use

The design of a building to house a computer and ancillary activities for a nationalised industry was already well advanced when then the opportunity arose to use ESP-r. The air conditioned building, of approximately 6000 Image FIGS/grohtml-12140-3.png , was to be built on four floors, each 30m wide by 50m long; office accommodation would be housed on the perimeter with rooms of more occasional occupancy in the core.

The stimulus for use of a dynamic energy model came from the late decision to alter the building envelope from a lightweight metal cladding system to brickwork, with an associated increase in glazing from 25% to 40%, differentially arranged in the four floors. The effect of these changes on the variable air volume (VAV) distribution ductwork and on the central air-handling plant needed, as a matter of urgency, to be determined.

The ESP-r analysis was applied to spatial modules sited on all four corners of the building and halfway along each facade. For each module, on each floor, the peak load across the VAV terminals was computed and the accumulative effect on the central plant estimated. In relation to the climate data used the peak load on all space modules was seen to occur on a high air temperature July day and not, as had been previously assumed, within the month of September when solar angles are lower. The ability of ESP-r to model the dynamics of thermal behaviour, hour by hour, showed clearly that the peak load occurred in different space modules at different times throughout the critical day; as a consequence, although individual VAV terminal duties had to be increased, no significant increase in load would be experienced by the central plant.

4.10 Comfort

The first phase of an extension to a University Library comprised a reading room with a floor of bookstacks above. The construction proposed by the architect was dense reinforced concrete with double skin patent glazing angled back from sill to ceiling.

Concern for the environmental conditions focused on the maximum occupancy period of the reading room (May with an estimated 350 readers) and on the mid-summer period (June to August, with an estimated 100 readers); the architect also wished an appraisal of the scheme under winter heating conditions.

Climatic data relevant to the study period were created in accordance with the diurnal range known to prevail at the location of the site. The May analysis received a 24 hour heat input requirement under the proposed 10 air changes per hour ventilation regime; as a result of the analysis the proposed air change rate in the Spring was reduced to a level just sufficient to combat odours and meet ventilation requirements. With 10 air changes per hour in August, the maximum temperature was predicted to be 24°C. Given the slightly lower predicted resultant temperature and the possibility of the 100 readers disposing themselves away from the external wall this was considered to be acceptable. A January analysis of heat flow through the double-glazed envelope revealed acceptable comfort conditions.

4.11 Speculative development

In another exercise ESP-r was used, in the context of speculative office developments, to:

Estimate the relative influence on energy conservation of different external wall constructions and window treatments.

Compare the generated ’best-buy’ solution with other existing schemes.

Ascertain the impact of such an approach to capital expenditure (the developer’s contribution) and running costs (the tenant’s contribution).

The analysis indicated that:

Changes to the fabric alone can result in a +16% or a -24% alteration to the winter heating load relative to the standard.

Double glazing had a similar effect to that of adding a suspended ceiling, namely a 23% saving of winter energy.

Substituting internal fabric blinds for external blinds in winter saves about 12% which is comparable to the thermal benefit of retaining full light output.

There is no apparent advantage in reducing still further the construction U-value.

Peak cooling demands do not show an exactly negative correlation with peak heating load levels, suggesting that a balance in the fabric/services system between winter and summer conditions may be achievable.

From the study, the architect was able to provide a base of relevant data and conclude generally that, ‘if a developer seeks to offer a good level of environment, it may be advantageous to the tenant in terms of running costs to do so by means of design changes to the building rather than by introducing air conditioning’.

4.12 Training Exemplars

The ESP-r system offers a model archiving and browsing facility by which past problems can be maintained and revisited. On delivery, this facility is used to provide a number of exemplar problems which are useful for training support. The following sections relate to some of these on-line exemplar models.

4.12.1 Single office

Figure 4.1.1 gives the geometry, construction and operation details for a single building zone containing office and computing equipment. The user would begin by creating a directory for this problem and moving into it and running ESP-r which contains or allows access to the facilities required to describe the problem, commission simulations and engage in analysis of the results.

The opening display provides a tutorial, database management facility, problem definition, problem simulation and analysis and various support facilities. If the user is a novice it is recommended that some time be spent using the tutorial facility.

When testing ESP-r it is not necessary to create the problem description files since they are supplied. In directory ~esru/esp-r/training/simple, the files cfg/bld_simple.cfg, zones/reception.geo, zones/reception.con, zones/reception.opr and ctl/bld_simple.ctl correspond to the system configuration, zone geometry, zone construction, zone operation and configuration control files respectively. All that is required is to select problem definition and supply the problem name bld_simple.cfg which will then be loaded. At this point the user may explore the details of the problem or commission a simulation. Notes supplied with the problem should be read by selecting problem registration:documentation from within the problem definition, accepting the file bld_simple.log and then reading the text displayed in the text feedback area.

Of course it is also possible to describe this problem from scratch yourself. Although the user may approach this task of in a number of ways, the following sequence is suggested.

The first task is to select database management which allows various databases to be associated with a project. In most cases the defaults provided for climate, pressure distribution, primitive constructions, event profiles, plant components and optical properties will not need to be changed. Indeed some may not be used, but a multi-layered constructions database will need to be defined for the current problem. This database defines the details of wall floor and ceiling constructions - i.e. order, thickness and references to elements in the construction primitives database. To create a new multi-layered constructions database simply supply a new file name and a fresh database with a dummy construction will be created.

For each of the constructions shown in Figure 4.1.1 follow the editing procedures - beginning with the outside face and working in to the layer which faces the zone. You may edit, add or delete an individual layer as necessary. In the case of the double glazing it is necessary to match the properties of the optical database and the best way to do this is to specify the optical properties first and then allow a matching set of layers to be created. It is a good idea to update the database frequently. When you have finished the details should be as in Figure 4.1.2. Note that you can also use any text editor to change this file (test.mlc).

Image FIGS/fig4.1.1.eps.png

Figure 4.1.1 Details of the test1 building

Image FIGS/grohtml-121401.png

Figure 4.1.2 Multi-layer construction database for test1

Exit from the database facility and select problem definition and, after reading the message, supply the new problem name bld_simple.cfg, indicate that you wish to begin with a new geometry from scratch and supply a name for the zone (this name is for reporting and display purposes and is not the file name).

The zone is most easily described as an extruded shape and after you have supplied the floor and ceiling height as well as the coordinates of the various corners and the connections between this corners,
you will be presented with a display similar to that in Figure 4.1.3. Use the geometry-->surface attributes option from the problem definition menu to adapt the (zone)geometry of the problem.

Image FIGS/s4_office.EPS.png

Figure 4.1.3 geometry of bld_simple.cfg.

Note that the surfaces have been given default names. Clarity of presentation is enhanced by replacing the default surface names with names which make sense in the context of a given building. Use the surface attribute selection to accomplish this.

Glazing is representation as a multi-layered construction with additional optical properties. The surface of the glazing can be any polygonal shape, although many users will define glazing as an offset from the lower left corner of an existing surface to the lower left corner of the glazing as well as its width and height.

From the geometry menu some other subjects like solar insolation distribution, obstruction blocks and rotation & transforms can be selected. These options are not relevant to the test case you are working on at this moment; later on, when you have seen some results of this first test, some shading distributions will be added.

At this point the zone will contain information similar to that in Figure 4.1.4.

Image FIGS/grohtml-121402.png

Figure 4.1.4 Zone geometry file.

The next descriptive task is to define the thermophysical properties of the zone. The recommended procedure is to use the surface attribute facility and for each surface select the appropriate construction. In the case of the glazing in the south wall make sure that it is marked as transparent. Having defined these attributes proceed to use the construction browse/ edit facility to create a zone construction file. Since there is a transparent wall in the zone a zone TMC file is required. ESP-r knows about the file structure dependencies and will automatically generate such files. After reading in the geometry (including the surface attributes) ESP-r will attempt to create the necessary files. During the creation process it will ask you to confirm that glz_s is transparent, otherwise the process is automatic. You may browse through any of the surfaces thermophysical properties and unless a change is demanded the data can be merged into the problem. The thermophysical properties are contained in reception.con which is listed below in Figure 4.1.5.

Image FIGS/grohtml-121403.png

Figure 4.1.5 Zone construction file.

The optical properties of the transparent glazing surface are contained in reception.tmc which is listed below in Figure 4.1.6:

Image FIGS/grohtml-121404.png

Figure 4.1.6 Zone TMC file.

To define the infiltration, occupancy, equipment and lighting within the zone select operations and you will be placed into an editing environment which allows each of these to be defined. Normally you will focus on weekdays first and then toggle to Saturdays and Sundays. The operations file reception.opr is listed below in Figure 4.1.8

Image FIGS/grohtml-121405.png

Figure 4.1.8 Zone operation file.

There are several points within ESP-r where information related to the problem topology can be supplied. Within the problem definition menu there is the connection and boundary selection which allows one or more of the connections to be manually edited, topology to be checked and generated via a vertex matching algorithm or topology to be imported from surface attribute boundary specifications. Within the geometry browse & edit facility you may specify boundary conditions as surface attributes or import the connection topology to the surface attributes.

By definition, the initial assumption for the topology of a problem is that all surfaces face the outside. This can be confirmed by exiting to the problem definition menu and consulting the connection and boundary selection. As most of the walls face the outside a quick way to update the surface boundary attributes is to return to the geometry browse & edit and select update topology from problem.

Two surfaces in the zone do not face the outside and this can be defined in two ways:

1)

supply the boundary for the other side of the ’passage’ and the ’floor’ as surface attributes and then exit to the connection and boundary and import this information or;

2)

edit the connection in the connection and boundary display and then move to the geometry browse & edit and import the information.

After updating the problem (system configuration) file simple_office should look like the listing in Figure 4.1.9

Image FIGS/grohtml-121406.png

Figure 4.1.9 Problem definition (system configuration) file.

Now a configuration control file must be created using the building controls & actuation facility. This file contains the control statements to be obeyed by the Simulator at simulation time. This file can be confusing for some users of ESP-r. Previous releases provided only minimal editing facilities, however ESP-r includes a extensive editing and reporting facilities which should ease the process considerably.

To set up a an ideal control with a heating capacity of 1000W max. and 0W min., a cooling capacity of 1000W max. and 0W min. and the following temperature profile:
weekday....
0h00 - 7h00 free floating
7h00 - 9h00 15°C heating setpoint and 100°C cooling setpoint
9h00 - 17h00 20°C heating setpoint and 100°C cooling setpoint
17h00 - 24h00 free floating

Saturday....
0h00 - 24h00 free floating

Sunday....
0h00 - 24h00 free floating

A summary of the meaning of the file as well as the raw file are listed below:

Image FIGS/grohtml-121407.png

Figure 4.1.10 System control information and file.

A simulation is now performed via the Simulator using the climate file ~esru/esp-r/climate/clm67. Two simulations should be performed, saving both in the same results library called, for example, ex1.res. The first should span the period 9th January to 15 January inclusive. The second should span the period 11 July to 17 July inclusive. Both simulations should have a one hour time-step.

Now Results Analysis Module is used to see the results obtained from the simulation. After entering the library name (ex1.res in this case) you can select graph, time-variable and inside air temperature to obtain a common temperature-profile of the inside air. According to these profiles (see figures), the following items can be discussed (you should generate these profiles yourself):

1)

In winter the maximum heating capacity of the actuated control is not satisfactory to achieve the heating setpoint (20°C from 9h00 to 18h00) of the inside air. To perform the next simulation, you can change this maximum heating capacity for instance up to 3000 [W], you will notice that now -during weekdays- the setpoint temperature is reached during the afternoon (figure 4.1.11 and 4.1.13). The new control file is listed below in figure 4.1.12.

2)

In summer the cooling setpoint (100°C from 7h00 to 18h00) never actuates the cooling capacity because this setpoint-temperature never occurs. In the new control file (figure 4.1.11) this setpoint-temperature is adapted to 25°C actuating a cooling capacity of 3000 W. If you generate a temperature-profile now you can see that the inside air temperature is decreased during weekday.

Image FIGS/s4_janur1.EPS.png

Image FIGS/s4_july1.EPS.png

Figure 4.1.11 Temperature profiles for control as listed in fig. 4.1.10.

Image FIGS/grohtml-121408.png

Figure 4.1.12 Listing of the new control file

Image FIGS/s4_janur2.EPS.png

Image FIGS/s4_july2.EPS.png

Figure 4.1.13 Temperature profiles for control as listed in fig. 4.1.12.

4.12.1b Additional shading analysis

In the previous test, only a default insolation distribution has been used (i.e.. all internal surfaces receiving diffuse solar incidence). Before defining the geometry of the first test, we didn’t take any notice of subjects like solar insolation distribution, obstruction blocks and rotation & transforms. These subjects affect the time-series dependent solar incidence.

In order to increase the resolution of the problem (to make the problem more corresponding to reality) a second variant is included called bld_simple_shd.cfg. You may access this by specifying it as the problem name and the relevant information will be loaded. As you can see a large obstruction (for instance a flat-block) is created at the south-side of the office.

If you select obstruction blocks from the geometry-menu you can see in detail that this obstruction is build out of four blocks. In this menu you now can change the geometry of this blocks in order to make it cope with the outdoor situation you wish to simulate. Again don’t forget to update this new situation into the new obstruction file. Obstruction data are listed below in Figure 4.1.14.

Image FIGS/grohtml-121409.png

Figure 4.1.14 Obstruction data

The next action to perform is to go back to the main menu and to start the Shading/ Insolation Module via the shading & insolation option. This program calculates the insolation distribution and it writes the results to a database for use in subsequent simulations.

The results that you will obtain now show no difference in winter. In this period the solar radiation is not remarkable. However in summer (cooling capacity 1000 W, actuated at 25°C) a slight difference occurs as you can see from Figure 4.1.15. Note that in these figures the internal and external surface temperatures of the south wall are drawn instead of the inside air temperature.

Image FIGS/s4_july5.EPS.png

Image FIGS/s4_july6.EPS.png

Figure 4.1.15 Temperature-profiles for summer.

If no shading/insolation database exists, the default insolation distribution of the zone operations file will be used. In this case ESP-r assumes no obstructions so that only the building geometry is needed for calculation of the insolation distribution.

4.12.2 Simple building

We now move to a multi-zone problem and ask what will be the effect on winter heating energy and summer overheating. Again there is no need to generate the zone and configuration files since the data has already been prepared and can be copied from directory ~esru/esp-r/training/basic.

This directory contains several subdirectories including one that contains different problem configurations. A discussion of each of the problems is contained in the files cfg/bld_basic*.log which may be looked at via a text editor or by the facilities provided in the project manager. A summary of these configurations is included below.

Image FIGS/grohtml-1214010.png

Each problem assumes the same building geometry and construction, only different utilities are added. The building geometry is shown below in Figure 4.2.1.

Rather than list each of the different problem files the user is invited to make use of the display facilities within the project manager or the various UNIX file listing facilities. At least you should list the different configuration files to see how the bld_basic.cfg geometry is used for describing different problems.

Now perform the same winter and summer simulations as were performed initially in training session 1 for the base case problem bld_basic.cfg. Using the results analysis program you should now compare your results with the corresponding results for the winter period 9 to 15 January in the following listings (assuming the default climate collection).

Image FIGS/s4_basic.EPS.png

Figure 4.2.1 Simple_building geometry.

Image FIGS/grohtml-1214011.png

Figure 4.2.2 Tabular statistics during winter simulation period.

From this tabular report you can see that during the simulation period, the office requires most heating energy (46 kWh) while the reception looses most energy (160 kWh). The energy statistics table and the causal energy breakdown table show that the reception zone loses most energy due to conduction (total 80 kWh). However the reception zone also suffers a high casual gain from equipment (type 3) so the reception net heat loss is less than the office net heat loss.

If you look to the operation files you will see that a coupled air flow from the reception into the office is defined. In the listed energy statistics you can see that (due to this interzonal airflow) the heat loss from the reception to the office is more or less 10 kWh.

Next you should perform the same simulation for the summer (11-17 July) and generate a tabular report. You will obtain results as listed below.

Image FIGS/grohtml-1214012.png

Figure 4.2.3 Tabular statistics during summer simulation period.

The heat loss due to the conduction through building partitions is less and infiltration & ventilation becomes the greatest heat loss factor. Because of the internal casual gains and the high cooling setpoint-temperature (100°C as you can see from the control file) no heating or cooling energy is required.

For example now it is interesting to run a simulation (winter and summer) to establish the heating and cooling energy required to maintain the zone 1 and 2 air temperatures constant at a setpoint of 24°C during the control period.

Therefore, first you should adapt the control file (or make a new one) to change the capacity and setpoint temperatures of both the heating and cooling plant. You can enter an extremely high capacity in order to be sure that the set-point temperature is reached when the control period starts. You should run the simulations and check the calculated temperature profiles using the Results Analysis Module. Finally, you can find the required energy data from the energy statistics.

When you perform the simulations correctly, you will find 60 and 70 kWh respectively for the reception and the office in winter and 130 and 6 kWh in summer. Due to the high casual gain in the reception less heating energy is required in winter and more cooling energy is required in summer. You can perform the same simulations as has been done for the basic problem configuration, for the other configurations.

4.12.2b Additional fluid flow analysis

At the start of training session 2, a summary of the files bld_basic*.log was given. As you can see, two problem definition files exist in which fluid flows are governed by a flow network. Below, a summary of these problem definition files is included.

Image FIGS/grohtml-1214013.png

The basic building with air movement is restricted to flows via crack openings (under doors and around windows) in the occupied spaces. Separately, the roof is vented by soffit and ridge vents. Use the configuration control file bld_basic.ctl which provides 1kW to the reception and office.

A variation is the base case with the addition of a component ‘door’ between the rooms in the mass flow network and a window which is controlled. Browse and use the configuration control file bld_basic_af2.ctl.

The base case mass flow network is described in bld_basic_af1.afn and contains four boundary nodes (north, east, south, west) and three nodes (roof, recep, offic) which match the thermal zones. Mass flow components (drcrk, wincrk, soffit, roofv) define the flow restrictions. The flow paths are between each zone and the outside via window cracks and between the two occupied rooms via a crack under the door. The roof space has two flow paths to the outside - one through the soffit and one by way of the roof vent.

The mass flow network with window control is bld_basic_af2.afn. The control is made via a configuration control file bld_basic_af2.ctl. A window in the reception is assumed to open if the room temperature rises above 20°C. A similar set of paths is defined for the office.

During a summer simulation the flow is restricted to the cracks in the windows until the room warms. Then the window opens, flow is allowed and then when the temperature drops below 20°C the window closes. In the results analysis you will probably detect a sawtooth pattern as the window opens and closes. The decision to open or close the window is only taken once per timestep and you should experiment with different simulation timesteps to see how this ventilation control changes.

As it is important to check the leakage characteristic of a space, we will first discuss a simple simulation of the fan pressurisation method.

A simple fan pressurisation apparatus consists essentially of a large variable-speed fan with an attached air flow measuring station. The rig is sealed into the doorway of the space under test with internal and external connections taken to a differential micromanometer. The flow rate is measured over a range of pressure differences between 10 and 100 Pascals and the results presented as a curve of volume flow rate against pressure difference. This curve (with leakage parameters k and n) can be fitted by an expression of the form;

Image FIGS/grohtml-1214014.png

In order to simulate fan pressurisation, a mass flow network description as printed in Figure 4.2.4 can be used. Only air leakages (door and window cracks) in the reception zone (space under test) are considered. These air leakages (or flow restrictions) are determined by a thorough investigation of the room partitions. The fan pressurisation apparatus is simulated by a constant mass flow component in the east door. By altering the constant mass flow rate and reading the corresponding pressure differences from the results file, the leakage curve can be calculated (Figure 4.2.5).

Image FIGS/grohtml-1214015.png

Figure 4.2.4 Fluid flow network describing pressurisation

Image FIGS/s4_pressure.EPS.png

n

= 0.53

k

= 3.20 [dm3/s * Pa^1/n]

Qv,10

= 14.0 [dm3/s](NEN 2686, Netherlands)

Figure 4.2.5 Leakage characteristic (simulated) for the reception zone. The graph is drawn by use of copying the predicted flow data to the XVGR tool.

The leakage characteristic as printed above should be compared with data acquired by performing a fan pressurisation (as already explained). In case differences occur between measured data and simulation results, flow restrictions should be altered. For now we assume simulation results to be correct (i.e. more or less in agreement with the measured data). Reading National Standards on pressurisation testing you will find these leakage parameters to be very low and satisfying.

Now, when copying leakage data of various zones to an overall building mass flow network, you are able to perform accurate simulations concerning energy gains and losses due to infiltration and ventilation. Results for a winter’s simulation are printed below in Figure 4.2.6. Comparing these data to the ones printed in Figure 4.2.2 you will find the reception infiltration and ventilation energy loss to be less.

Image FIGS/grohtml-1214016.png

Figure 4.2.6 Tabular energy statistics of winter simulation

In the basic problem configuration, air change rates of infiltration and ventilation were estimated by 0.3 (~ 43 Image FIGS/grohtml-12140-30.png ) and 1.0 (~ 144 Image FIGS/grohtml-12140-31.png ) for the reception zone. If you analyse your mass flow results you will find these rates to be overestimated. With known wind pressure coefficients and wind velocities as boundary conditions, air flows of the reception are in order of magnitude of 10 Image FIGS/grohtml-12140-32.png for both infiltration and ventilation. Note that we already mentioned the leakage parameters to be very low.

Finally two temperature profiles (Figure 4.2.7) are added for the reception and office zone. These profiles show the difference calculated between the basic problem (solid line) and the combination with fluid flow simulation (dashed line).

Image FIGS/s4_temptabel.EPS.png

Figure 4.2.7 Temperature profiles for winter simulations.

4.12.3 Small house

This training session focuses on the training directory house/sun_space which holds the description of a small dwelling proposed for a remote Scottish island. It is designed for high exposure locations. The provision of a unheated but protected space for inclement weather is part of the design brief. Because of site constraints the model is rotated so that the lounge faces south-west. The dwelling is defined with ten thermal zones:
1) combined kitchen and lounge (kitliv)
2) hollow south-west wall (west_space)
3) passage (hall)
4) bathroom (bath)
5) bedroom (bed1)
6) bedroom (bed2)
7) buffer south-west portion (buf_1)
8) buffer north-east portion (buf_2)
9) upper buffer (buf_roof)
10) roof over occupied space (roof)

The dwelling has deep window reveals and its orientation suggests that a detailed treatment of shading and solar penetration is called for. To this end obstruction blocks define the deep window reveals in the bedrooms and kitchen/lounge and correctly limit sunlight entering the dwelling.

The model uses seasonally adjusted mass flow networks to predict air movements. There are timed extract fans in the kitchen and bathroom as well as logic to open the windows during particular hours and if internal temperatures rise above a particular point. This is defined in the configuration control file.

The subdivision of the buffer space into three thermal zones allows warm air to rise into the upper space but for the front and back of the space to evolve different temperatures as a result of solar radiation patterns. This requires that ‘fictitious’ boundaries be used between the zones and project based optical properties and multilayer construction databases have been created.

Of interest is the treatment of the south-west wall of the lounge as a separate thermal zone rather than as a conventional multilayer construction. The reason for this is the large void (300mm) within this wall which, thus described, will have a more detailed treatment of radiant exchanges.

There are two configuration files, house_win.cfg which is used for winter simulations and house_sum.cfg for summer simulations. Similarly there are two mass flow network descriptions (ss_sum.afn and ss_win.afn for summer and winter respectively). The control file ss_win.ctl should be used with winter simulations and ss_sum.ctl with summer simulations.

To browse the fluid flow network associated with a given problem use the appropriate command of the project manager. The winter fluid flow network with the corresponding control functions is listed below.

Image FIGS/grohtml-1214017.png

Figure 4.3.1 Mass flow description for a small house.

By now, you should be able to extract more detailed information about the problem definition from the different problem files.

As an exercise, three different types of occupants use are considered. Those types resulting in respectively lower (E-), normal (N) and higher (E+) energy consumption are printed below in Table 4.3.2.

Table 4.3.2: Control parameters for different types of occupants use for a single family house.

Image FIGS/grohtml-1214018.png

Six simulations were performed; three simulations in which both temperatures and ventilation were controlled according to Table 4.3.2 and three simulations in which only temperatures were controlled and ventilation was governed by the original mass flow description as printed in Figure 4.3.1. January 1967 from the climate file clm67 was taken for the simulation period. The control file for one of these simulations (normal energy consumption) is printed in Figure 4.3.3.

Image FIGS/grohtml-1214019.png

Figure 4.3.3 Control file for simulation of normal occupants use.

The simulation results (i.e. total energy consumption in january) are gathered in Table 4.3.4. Occupants use E- and E+ are of the same frequent occurrence as type N: the simulation shows that energy consumption for this house will vary ~230 kWh (15%) within this range of common occupants use. You can also see that the roof needs extra insulation in order to decrease energy consumption. Besides, the simulations with mass flow description show that the original mass flow description correlates (in terms of energy consumption) with the E+ occupants use.

Table 4.3.4: Calculated total energy consumption in January
for types E-, N and E+.

Image FIGS/grohtml-1214020.png

Succeeding simulations can be performed to determine the variation in summer’s cooling energy.

4.12.4 Large house

Increasing the complexity of the models we now turn to the training directory house/svph which is an example of a moderate size dwelling based on a direct gain house in Milton Keynes. It has become a de facto modelling standard within the UK.

The directory structure, as for other exemplars described above, is an example of using several subdirectories to hold different portions of the problem definition. The benefit of this is that each directory has only a limited number of files.

training/house/svph
‘-----configuration (cfg)
‘-----control (ctl)
‘-----networks
‘-----zones

4.12.5 Test cells

To be completed.

4.12.6 Special focus

There are a number of specialised facilities within ESP-r which are provided for expert users and those who require additional detail in their simulation work. Several examples are given in the exemplars. One example relates to the thermophysical property replacement facility.

It is based on the simple_building problem. The situation modelled in constr/tp_sub is that the conductivity of the glass wool in some of the external walls is increased when the internal air temperature rises above a certain temperature (20°C). This is obviously not a real situation, but a similar situation could occur if the conductivity of a particular constructional material was sensitive to temperature.

An additional entry (glasswool_mod, #282) has been made in the primitives database (tp_subs.pdb). This is similar to glasswool (#211) but with increased conductivity. A new entry has also been made in the multi-constructional database (tp_subc.mlc) which is for ext_wall_mod. This is the same as for the entry for extern_wall except that it uses the modified properties of glasswool.

The control file demonstrates the activation of the replacement constructions. For the space named reception, constructions ’south’, ’east’ and ’north’, and for the office space, constructions ’North_w’ and ’West_w’, use the replacement construction whenever the room temperature exceeds 20°C. In the control file, control function 1 (assigned to the reception) has a ’nested’ control function 3 which gives details of the thermophysical property control. Similarly, control function 2 (for the office) has a ’nested’ control function 4.

4.12.7 Office block

This session switches the focus to full scale commercial buildings with a two level office block located in the north-east of Scotland. The 17-zone model makes use of mass flow simulation and opening of windows to control summer overheating. Images of the problem (in gif format) are included in the images directory.

To access the problem definitions go into the configuration directory. Within the configuration directory is a file office.log which should be viewed via UNIX or project manager facilities.

As this is a large problem it is recommended that simulations be kept to a few days. In summer simulations you will note that the zone temperatures are to some extent a function of wind velocity and direction.

4.12.8 Plant

To be completed.

 

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