Net ZEB Design Processes and Tools - Modeling, Design, and Optimization of Net-Zero Energy Buildings - page 210

Several mainstream tools, including eQUEST (based on DOE-2.2) and
EnergyPlus have integrated daylight calculation modules based on
simplified methods like split-flux. Many BPS tools that specialize in
daylighting and electric lighting analysis, including DAYSIM, SPOT, and
ESP-r, use RADIANCE as their daylight simulation engine (Guglielmetti,
Pless,andTorcellini,2010).Thekeylightanddaylightingmetrics,including
for visual comfort, are discussed at length in Chapter 3 .
4.3.3.5 Airflow
Airflowwithinandthroughbuildingenvelopesisoftencriticaltothesuccess
of Net ZEBs. Whether it is naturally or mechanically driven, it has three
main functions: (i) delivering outdoor and filtered air to maintain
contaminants below an acceptable threshold, (ii) thermally conditioning a
space (applicable primarily to forced-air HVAC systems), and (iii) providing
acoolingsensationbyincreasingtherateofsensibleandlatentheattransfer
from occupants to the air.
Modeling airflow is one of the most complex aspects of building physics
and deserves significant attention. The three dominant modeling methods,
in order of ascending resolution and theoretical accuracy, are (i) scheduled
airflow, (ii) airflow networks (a.k.a. zonal methods), and (iii) CFD.
Scheduled airflow simply imposes a certain mass or volume flow rate
between zones, outdoors, and HVAC equipment, such as ducts and air
handling units. It is most suitable for mechanical ventilation because the
airflow rates are approximately known. It can also be used for sensitivity
analysis to determine the effect of airflow rates (e.g., to estimate the size
of window that would be required to achieve a certain level of natural
ventilation). For instance, the NREL RSF case study in Chapter 7 explores
the effect of different nighttime ventilation rates on cooling loads.
Airflow network methods are composed of a collection of nodes that
represent zones, ducts, and outdoor conditions and a network of
connections that represent airflow paths such as windows, cracks, and other
openings. The limitations of airflow networks are that they assume perfectly
mixed zone air within zones, they neglect momentum effects, and
flow-through openings are normally based on empirical pressure-driven
models (Costola, Blocken, and Hensen, 2009). Since the set of conservation
of mass equations for each node are normally nonlinear, the solution for
the system is usually solved numerically. Airflow networks are significantly