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Building Thermal Analysis Report
Within this report I will create and produce an accurate thermal analysis model using the software IES VE, this is a requirement on behalf of the client. This client brief can be found in Appendix One, when constructing the model based off the brief. it was critical to include the construction data this would be the fundamentals of constraints the model has been based around, this data & guidance can be found in Appendix Two.
When looking at the building thermal analysis, I have been assigned a location for were my building shall be situated, from having this I was then able to assign a weather location for my IES model using the database manager tool.
Within task one the aim of this is to rotate the angle of the building by 45 degrees and see what effect this would have on the two selected rooms With regards to looking at the annual heating energy consumption and the peak summer time temperature. The first room I selected was R013 Student Study Hub, thus being one of the larger rooms then I can assume that this will be one of the worst cases. I also selected R106 Staff Room which is on the complete opposite side, even though these rooms are going to be used for different functions it will give a better difference in results.
R013 – Study Hub
R106 – Staff Room
When making a comparison with both rooms it is clear to see that the building being south facing is going to be the most efficient orientation, this will be due to the fact that the sun has the most impact on a building which is south facing therefore needing less heating to bring the rooms up to temperature.
R013 – Study Hall
R106 – Staff Room
With regards to the study hall it is interesting to see that the biggest temperature difference in summer is also south facing, as opposed to the staff room which would be north facing. I feel this has a lot to do with the area being a larger space thus allowing a lot more heat dispersion.
When comparing the building as a whole it was clear to see that the best orientation for this would be the SE side, this can be shown by the following output data below.
Total Building Boiler Load
Using the optimal orientation I needed to look at what effect different types of solar glazing, one of these need to be reflective and the other absorptive. The reasoning behind this was to look at the effects the different types of glazing would have, this was in relation to the overheating aspect as well as the annual heating energy. Not only were the different types of glazing to look at the thermal analysis of the building but also what impact this would have on the daylighting factor.
For absorptive glazing I used: HD Royal blue
For the reflective glazing I used: SN 70/35
Taken from Guardian Glass
When changing the settings it is key to make sure that all the values match what the manufacturer has specified, when changing the reflectance it can have an adverse effect on the g-value, to make sure we match what has been specified the transmittance can be altered to do this. The main reason for this as IES does not have a setting for absorption, as shown in Appendix Three.
Now the glazing has been selected the next step was to carry out a comparison of what impact this would have on the building itself, as you can see from the graph below looking at the peak day, the absorption type of glass has a clear indication that it reduces the load on the boiler, the reason for this is as it allows the building to store more heat within itself, thus reducing how much the boiler needs to work to get the correct heat output.
Peak Heating Gain – Total Building.
Making a comparison to see what the differences between the two rooms for the peak day in the graph below it is clear to see that the absorption glass still has the lowest solar gain, the tables for these can be found in appendix four.
As shown in appendix five/six it is clear to see that the reflective style of glass has the best effect on both rooms in terms of daylighting factor, ideally 2-5% would be classed as good daylighting. In both rooms this design criteria would have been met. With the other types of glazing allowing in 5%< then the glare factor in these rooms will become high, not only that with a high daylighting factor then the need for artificial light will become less, in some instances this isn’t always the best option as people can find the color of artificial light more appealing.
(CIBSE, Nov 2014)
In task 3 the using the optimal orientation (south east) and the original glazing I needed to investigate what the effects of shading would have on the building and how the building would perform under different orientations. The reasoning behind the construction was in effect to reduce the solar gain, therefore having less of an impact on the boiler, as well as reducing the amount of daylight being intruded though the window.
As you can see because of the orientation compiled with the façade this has a significant effect on the building, I have compiled a list of the results with different orientations, Appendix 7 has the results of the building with the shading added and appendix 8 is the results without
When looking at the results it is clear to see that in both instances the rooms have nearly identical daylighting factor with in most instance the shading slightly reducing the amount of daylighting being let into the room, this is obvious as less daylight gets added in due to the shading. Table 8 in the IES help guides is what I used for the data input on the blinds, this would help me determine how much light absorption is allowed, depending on the material.
As previously said, here is the data which was inputted to IES, the incident radiation then got changed to 400 to lower the blinds and 300 to raise them.
Refer to appendix 9 for solar gain comparison between the different variations of shading, it is clear to see from the results that having the blinds makes quite the impact in reducing the solar gain.
In this section it is clear to outline which is the most beneficial type of solar controls. The key with doing this will be to execute and efficient way of reducing the impacts of daylighting and overheating. I will do this by using the similar methods shown in the previous task either by using blinds or using the façade on top of looking at the different glass materials.
North Side Daylighting
North Side Overheating
East Side Daylighting
East Side Overheating
South Side Daylighting
South Side Overheating
West Side Daylighting
West Side Overheating
Solar Controls Summary
North Façade – the solar controls used here are the absorptive glass with blinds which shall be lowered when the room hits its highest room temperature
East Façade – Using the same controls as the north façade
South Façade – I used the same controls as the north façade, however for some of the rooms this was not enough. In this instance I also applied an external shading which will reduce the solar gain, as for any south facing building the sun will be most active on this side, therefore the external shading will make its greatest impact on the overheating aspect as opposed to the daylighting.
West Façade – Using the same controls as the north façade
Looking at all the information composed together in the charts above, it is clear to see the massive impact having solar controls on the building. In all instances when it comes to the daylighting the use of solar control has always been a better choice, even if the results are the same in certain rooms overall they have a better outcome over the extension of the year.
Now that task 4 has been completed we can use this model to see what effects having a night purge ventilation system would be on the boiler and if it would reduce the overheating risk of the building as well as looking at how efficient the system is.
Looking at the charts it is clear to see that between May to October the building overheats, I decided to run base model without the night purge activated this was to get an indication of to which rooms needed to be looked at in further detail.
I decided to create a range of all the rooms within the model to see which rooms where overheating, it is clear to see from the able above that not all the rooms where overheating, hopefully by using the night purge this can be reduced and help the rooms which are overheating.
By using the night purge which shall be extracted and that data populated by using the apache profile database, it will run a simulation through the summer time alongside the natural ventilation to hopefully reduce the energy used within the building.
The below image is the parameters for the weekly night purge profile.
The chart below is showing one of the typical rooms in the base model without the night purge, this shows how much consumption of heating (kW) of power used in the different months.
Now that I have a general conscious of what the building is using energy wise and the months I can build my yearly night purge profile to assist with this.
Now that profiles have been allocated using the apache profile database the dynamic simulation was re-ran to see what affects this would have on the building.
From examining both of the rooms, it is clear to see the effects that night purge had on the building. It would allow the building to start the day of with a cooler temperature however in terms of actually dropping the peak temperature the difference between the two models is not enough to stop the building from overheating.
To give an idea of how much the building is overheating over the year, I have selected one of my rooms of choice and decided to create a graph outlining this. By looking at this graph I can see the difference in the number of hours how many times the temperature is greater than required temperature of the room and the actual difference using night purge makes.
After completing the night purge below is the list of rooms still exceeding 25 degrees, hopefully by using thermal mass alongside this then these should drastically reduce.
When it comes to reducing the temperature of the building, then the thermal mass could be a different approach to reduce the overheating of the building. By exposing the concrete of the floor/ceiling through the night as the building cools the concrete begins to absorb this, then when the building begins to heat. Up throughout the day the concrete will help reduce the temperature of this by absorbing more heat.
When making a comparison between the two rooms, it is clear to see the actual impact that the thermal mass has on the model, with the cooling being reduced this will have an adverse effect on the boiler. Looking at this will give a good indication as if the thermal mass is the most diverse option.
When concluding how much of an effect thermal mass has on the building, in the charts below it is quite easy to see the impact made by this. Most of the rooms which were overheating before are now not therefore they have been completely removed. Any room which is left the number of hours in which the room exceeds 28 has drastically been reduced.
Before thermal mass
After thermal Mass
Looking at the charts above it is clear to see the boiler loads has drastically increased, nearly a whole 100 Mw/H. The reasoning behind this is that the u-values within the building have increased because of the exposed ceilings, therefore it takes longer for the building to heat up thus driving more load onto the boiler.
Using the results from Task 5 to identify if there are areas of the building for which mechanical cooling is the only realistic solution during the peak summer months (due to excessive overheating) and report on when and how severely they overheat. Activate cooling during the occupied hours in these rooms.
To produce the information in the excel sheet above a TM52 calculation in IES VistaPro needed to take place, from the information provided about each room and the temperatures this would allow allocation for which rooms would pass or fail in accordance with the TM52 document produced by CIBSE.
In the table above R110 was clearly failing, after taking the results from IES and entering them into the TM52 calculator provided by Northumbria University and modifying some of the occupancy & instructions then this room actually passed, these results can be shown on appendix ten. I then carried out completing the same task for the printing hub, the results were compiled and the room passed, these results can also be found in appendix ten.
Looking at the results it is clear to see that they have been excellent in terms of the internal spaces passing, the reasoning behind this is simply to do with the openable areas of the window. Most people would assume the window to be top hung and have a percentage of about 30-50% openable. Looking around there is no physical legislation on this as to what the maximum openable window area is, the main reason this would have an effect would be down to security as it makes it easier for access, I have out linked this in appendix eleven.
In task 7 the idea behind this is to collate all of the information from the previous steps to finalize the project. In section 7 I am going to be carrying out the CIBSE steady state heat loads for each room and the project, on top of this I am going to be looking at the CIBSE intermittent heat for each room. Once this has been completed then the peak summer time temperatures will need to be looked at, this is too see what the maximum temperatures of each room are and to see if this will cause a problem as the room may require cooling. Finally upon completion of all this I will then need to make a comparison between BSRIA rule of thumb and the results shown in the report.
Total steady state heating load for central plant: 36.6kW
Total intermittent heat load for central plant: 70.9kW
Occupied Spaces Table
Circulation Space Table
When looking at which rooms were over heating there would need to be a considerable amount of cooling, with the temperatures rising within these rooms then more cooling needs to be added with the cooling getting added then you run the risk of water vapor condensing. The advantage of this is that the latent heat within these two rooms is low therefor taking less energy required to cool these rooms. The complete model of all rooms can be found in appendix twelve.
In this part of the section I have been tasked with making a comparison between my results and that which has been specified by BSRIA Rule of thumb, I have also included my specific internal gains etc. in appendix thirteen.
BSRIA Rule of Thumb
When looking at the results table above it is clear to see that the heating and cooling loads of the building are very little in comparison with BG9, this will be due to the fact that in the IES model I have shown the building will be naturally ventilated therefore reducing the loads on the heating and cooling. Another anomaly will be the electrical load, given the area of the floor area of the building (2409.64m²) is quite high then there is a larger requirement for this.
When looking at the results of this report, I feel they have met the criteria of the client. He asked to produce a compliant report showing that the building he has specified works with the building regulations and the environment inside this is comfortable. My only main concern would be the internal load of the building itself on the boiler, this seems to be high however passes. In terms of keeping the buildings energy consumption to a minimum I know this has been achieved as previously discussed in the comparison section.
- BSRIA. (2011). Guidlines for Building Services. Rules of Thumb.
- CIBSE. (2013). Limits of thermal comfort. TM52.
- CIBSE. (2015). Enviromental Design. Guide A.
- CIBSE. (Nov 2014). LG10. Daylighting A Guide For Designers, 98.
R013 – Study Hub
R106 – Staffroom Peak Solar Gain
South East with shading (Optimal)
North with shading
North West with Shading
West with Shading
South West with Shading
South with Shading
East with Shading
North East with Shading
South East without Shading (Optimal Orientation)
North without Shading
North West without shading
West without shading
South West without Shading
South without shading
East without Shading
North East without Shading
Guide: CIBSE Guide A – Table 6.6
Information: The computer I have selected is manufacture B with a consumption of 48w
Computers these days are highly efficient.
One person per 6m2 48w + 28w /6 =w/m2 = 12.67w
Computer = 48w
Monitor 19inch = 28w
Student study hub has 6 computers
Guide: CIBSE Guide A – Table 6.2
Information: Using table 6.2 I have selected a number of options.
12w/m2 for the research hub – this area will be used as a more intense study,
Office– will have a 10w/m2
Meeting – 15w/m2
Circulation spaces – will have an 8w/m2 – lack of use no need for intense lighting.
The printing room I have decided instead of this being tied onto an office as they are going to have completely different loads I have selected my own profile for this.
Guide: CIBSE Guide A – Table 6.3
Information: There will be a variation of people in an out the building so an estimate has been made necessary from the internal floor space
Guide: CIBSE Guide A – Table 2.5
Information: For natural ventilation we are going to use macro flow.
To naturally ventilate the space without it clashing with the heating, you can use macro flow.
The WB/DB temperatures have been selected from this.
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