XCO2 - WELL with the VE


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Lindsey Malcolm of XC02 recently explored how using the IES Virtual Environment (IESVE) on two different Indoor Environmental Performance projects could potentially meet the requirements for compliance with the new WELL Building Standard.

Key Facts

  • Potential Credits: 76, 82, 01 and 03
  • Coffee Shop and Restaurant building types

UK Coffee Shop Chain
WELL Area: Comfort
Potential Credits: 76 - Thermal Comfort and 82 - Individual thermal control

This project was originally designed in a conventional way – a two zone model which previously met Part L standards, gained BREEAM credits and complied with CIBSE AM11. However, after some time of the coffee shop being in operation the client received feedback from staff that there were comfort issues. Customers visiting the shop found that the temperature was too cold on hot days due to the air conditioning, whilst staff found it too hot behind the counter.

XC02 took the 2 zone model and divided it into about 18 different zones in plan view and 2 or 3 levels in section view to reflect where occupants, heat sources and HVAC equipment were located. This enabled an assessment of the differences in temperature between the counter, waiting area and seating area. High level gains were modelled where there was lighting and HVAC equipment and low level where there were people, coffee machines, and fridges etc.

Using the IESVE ApacheHVAC application, XC02 set the gains into each of the individual zones so they could monitor the average and peak temperature and covert that into a comfort metric for each zone to see exactly what was happening. They were able to see a temperature set for a particular location, an air intake in one location, and an air supply in another. The fan coil units were located at ceiling level with temperature sensors right next to them, whilst the people were at floor level with the discomfort was behind the counter and at the seats next to the windows.

This information enabled XC02 to get a good idea of the occupant comfort in the different areas of the cafe and analyse possible solutions. These included, relocating kit such as fan coils, looking at where temperature sensors were located, and breaking up the control strategy to ensure fan coils and sensors were more strategically placed to pick up on where people and the primary heat gains were located within the coffee shop. This was all achieved from taking a very basic SBEM model and turning it into something much more complex using IESVE MacroFlo and ApacheHVAC applications.

Lindsey Malcolm, Lead Engineer on this project explains, “Whilst comfort assessments in BREEAM and CIBSE look at space as a single entity, the WELL standard is much more about personal comfort for the individual. Imagine an open plan office for example, we might typically model a perimeter and a core zone, so you might have the seats next to the window as a particular zone and have all the rest of the offices in another. Whereas what we’d actually need to do from a health and wellbeing perspective is look at individual desks; so to have a way of assessing at that level of detail without having a huge headache for geometry creation is key to simulation for the WELL Standard.”

“With the thermal comfort model we found that we could use that greater level of detail in the zone with a greater level of control using the ApacheHVAC application to guide the strategy and give our client some really tangible advice, such as ‘if you implement these three or four different measures you’ll get a much better improvement in comfort both for your staff and for your customers. And that can then be used to guide their designs on new sites and similar projects in different locations going forward.”

WELL Area: Air Quality
Potential Credit: parts of 01 - Air Quality Standards, 03 - Ventilation Effectiveness

For this restaurant project XC02 carried out analysis for a passive design approach. Using ApacheSim and MacroFlo, the team looked at shading, light levels and ventilation within the space to analyse different controls around the façade, windows and roof lights to drive airflow. The starting point was to look at different options on a high level basis, considering bulk temperature within the space to see overall how much of the year it was below 28°C and 32°C in line with the old CIBSE Guide A criteria.

The team then went forward with that design and started to do some CFD work in MicroFlo, looking at typical days to see how the strategy worked with certain prevailing wind conditions and what that meant for wind speeds and temperatures within the space. This was done to check if people were comfortable in different areas and what the temperature gradient was across the space for the prevailing wind conditions.

Lindsey from XC02 commented on the strategy saying, “It was great for getting enough air through the space, looking at the age of air, looking at comfort in terms of people dissatisfied and satisfied, and looking at CO2 levels. However, you realise there’s a bit of a short fall between what we do currently and what we’d want to do for WELL when we start looking at all the things required. In addition to the classic CO2 consideration, WELL looks at things like Volatile Organic Compounds (VOCs), NOx emissions and carbon monoxide, mould and bacterial factors, animal hair, combustion gases, chemical fumes from plants, and cigarette fumes etc. Soon you realise there are a whole host of parameters that aren’t even remotely considered in usual practice and trying to then quantify the performance rating becomes a real challenge.”

“We put some air quality monitoring kit in the space to evaluate its performance and to see how things vary throughout the day and monitor the overall air quality. We looked at things like CO2, VOCs, stale air and dust, however, even the air quality monitoring kit couldn’t pick up on everything that is detailed in the WELL Building Standard. It’s an interesting challenge because things like the VOC levels in the space vary a lot throughout the day, but it’s very much a function of the fixtures, the fittings, the furniture, the paint, and the flooring. All these things omit VOC at a pretty standard rate, so when the space has been unoccupied you see a steady level over the evenings and the weekends, and then when people come into the space there’s lots of fluctuation with people opening windows and moving and things like that. Trying to model that within a software would be incredibly challenging because you’d need to think about not only how many different items of furniture you’ve got but also what level of VOC level’s they omit etc. So the biggest challenge with Air Quality is understanding how we could assess at the design stage what the operational performance model would be and how we could use the Virtual Environment to guide that process. This is the big unknown at this stage and the next steps are going to be interesting to understand what can be done with that.”


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