Continuing FCJ Benalla modelling. My focus in week 3 was refining the base case model, which still had mismatches against the architectural drawings, particularly the wall assembly. I then cross-checked the mechanical drawings to confirm which rooms are conditioned, replacing last week’s assumption-based assignment (done before I had these drawings) with actual specifications. The updated drawings showed the architect had already specified external wall R-values above the NCC Part J4 minimum, so I shifted focus to other performance metrics.
Before touching HVAC efficiency, I explored passive strategies, particularly canopy design. I tested three scenarios: base case canopy, no canopy, and an extended canopy with vertical shading on windows exposed to harsh sun.
Removing the canopy raises cooling demand more than it saves on heating, increasing total HVAC use. The extended canopy cuts cooling well versus “no canopy” but the added heating load means it barely improves on the base case, confirming the original canopy is already close to optimal.
For active systems, I recommended upgrading to an HVAC unit with COP 3.55 / EER 3.65 from previously assumed 3.00 for cooling and 2.50 for heating (which later in week 4, I assumed at 3.00 and 3.2 to align more with the provided mechanical specifications provided), a realistic choice given availability from several manufacturers in Victoria, delivering approx. 30.4% heating and cooling savings versus the original assumed system.
I also optimised thermostat setpoint, widening them in some zones while keeping PMV within comfort limits. This requires the college to adopt season-specific uniform policies (matching the clothing insulation values used in the model). A reminder that ESD recommendations need stakeholder coordination, here with school administration. Temperature setpoint optimisation alone achieved around 17.4% annual HVAC savings, even before the COP upgrade.
Apart from energy, I also looked at integrated water management using Blue Factor that I learned in the previous weeks. The original design already performs really well, with a 20 kL rainwater tank connected to toilet flushing. The base case model gives a Blue Factor score of about 123%, which already complies with BESS requirements. I identified an opportunity to improve the score further, especially in the total gross pollutants category. I tested a small raingarden of 4 m² with a 30 cm substrate depth, fed by runoff from a slightly sloped pavement in the outdoor communal area. This initiative lifted the total gross pollutant score above the target, reaching around 77%, which strengthens the overall water-sensitive urban design.
Overall, through these combined initiatives. I managed to improve the base BESS score from 50% to 64%.
At the end of week 3. I attended a hygrothermal modelling webinar by Darren O’Dea (CEO/developer of Better Building), covering its EnergyPlus HAMT-based tools (validated against HAMSTAD/EN 15026) for assessing mould growth index by wall assembly and orientation. Darren shared practical tips on identifying high mould-risk walls (orientation, rain/drying potential) and reading water content penetration via the built-in graphs, useful for proposing targeted fixes like vapour barriers. I applied this to one of FCJ Benalla’s external wall assemblies, finding a mould growth index staying below 3.00 over 5 years post-construction, a great result.
Week 4
I finalised solutions to push the FCJ Benalla project from the 64% BESS score achieved in Week 3 toward 70% (“Excellence”).
For the innovation section, I claimed 3 points. Notably, one innovation score was already embedded in the architect’s mechanical specifications, the HVAC module turned out to already include a heat recovery module. This underscored the importance of carefully reading service drawings to find gaps that can boost the BESS score. The second point came from improved air permeability: I learned to convert air permeability from m^3/(h⋅m^2) a50 Pa to ACH, needed both for stakeholder clarity and because Better Building requires infiltration input in ACH. The third point was the stretched temperature setpoint already discussed in Week 3.
To reach 70% BESS, I also recommended skylights and additional side windows for better lighting. The building’s daylight factor was already a decent 39%; with these additions, the daylight factor score reaches 60%.
Overall, the base development sits at 55% which already satisfied best practice in the BESS scorecard. Using Better Building and Blue Factor modelling, the project reached 70% BESS (“Excellence”). Looking forward to delivering the assessment to the architect next week :D