Question:

As a member of the design team you are using modelling and simulation to assess the relative performance of various fenestration options for a new multi-purpose building. The design is still in an early phase, and detailed information is not yet available.
Discuss which error sources (internal or external) are likely to be more dominant in this situation, and suggest a procedure or approach which will reduce the impact of the error sources on your advise to the other team members in terms of which fenestration option will be best.

Sample answers:

As there is very little detail about the design, the largest errors will come from EXTERNAL sources:

1. Uncertainty of casual gains from occupants and equipment within the building will be a considerable source of error. This will make it difficult to consider fenestration as a source of solar gain or an aid to heat loss to help offset heating or cooloing loads.
2. Further uncertainty of the actual occupant activity and position will make it difficult to design for the use of natural daylight eg. if the area of the building contained a lot of VDU's for computers then we would have to minimise the amount of natural daylight reaching these areas of work.
3. Another source of error shall come from the actual weather conditions experienced by the building compared to the data contained within the climate databases.
4. Uncertainty over the actual thermo-physical properties (emissivity, reflectance, surface finishes etc.) of the materials forming the internal surfaces, and the position of fittings, makes it difficult to model the extent to which both natural daylight and solar gains would affect the deeper areas of the building.

As for a procedure that would help to minimise any of these errors, my advice would be to keep any modelling as simple as possible ie. to model the effect of window size of natural daylight I would perform a series of tests with varying sizes of windows within a simplified representation of the building area. I would also input various parameters representing different levels of casual gains, internal surfaces and occupant activity. I would then offer these to the other team members as an aid to a final choice of window layout depending on the final choice of activity, occupancy level and equipment contained within that area.
David Forbes, Environmental Engineering, University of Strathclyde, 1997.

- internal errors: - heat & mass transfer modelling errors
                   - coding errors
 
- external errors: - actual weather
                   - actual occupant behaviour
                   - user errors in model definition
                   - (thermophysical) data errors
 
In this situation external errors will be far more
dominant. Best approach to reduce the impact of the
error sources is to using modelling and simulation
in a relative sense, for instance by rank ordering
various design alternatives according to their
predicted performance.The absolute values are not
so interesting. The team just wants to know which
fenestration option is the bettter one.