ETA 2021 Strategic Plan - Flipbook - Page 14
Finally, we must identify the most effective
pathways for widescale adoption of resilience
solutions in the existing building stock. What
policies will stimulate uptake, and complement
private sector efforts? What is the role of
voluntary and mandatory standards? And how
can we value and assess the trade-offs between
diverse adaptation strategies and their cobenefits with improvements such as energy
efficiency?
Metrics and Measurement
To inform resilience metrics development
we will define specific resilience objectives,
such as infrastructure service restoration and
maintenance (productivity), habitability or
survivability (health), and resistance to failure
(structural). For each stressor of interest, a
scenario mapping methodology can be applied
to identify a set of relevant constituent metrics.
For example, consider a case in which the
stressor is wildfire in close proximity. Evacuation
is likely, making service maintenance and
survivability less applicable, and elevating the
importance of resistance to failure. Existing
simulation tools and empirical datasets could
enable identification of the parameters to which
the constituent metrics are most sensitive.
For example, smoke and wildfire propagation
models integrated with city-scale building
simulations can isolate the parameters (e.g.,
building loads; locations; construction material;
heating, ventilation and air-conditioning
(HVAC) systems; and window configurations)
that correlate with the highest satisfaction of
the resilience targets. Additional analysis can
identify relationships between those high-impact
parameters to determine a unified metric.
When addressing the questions posed for
metrics and measurement, the first step involves
conducting a review of empirical and analytical
methods used in other fields, to establish
baseline performance and key performance and
outcome indicators. This review will cover datarich domains such as medicine and health, as
well as data-poor domains, including events that
are severe but rare.
Building upon the metrics for each stressor of
interest, and the modeling outputs that were
used to derive them, cost and performance
targets may be set for a suite of “resilience
sensors.” For example, traditional sensors
located inside buildings, such as temperature
or occupancy sensors, could be complemented
with new types of sensors that give a more
complete picture of building operations when
Detailed Approach
The three core focus areas are interrelated.
Metrics and Measurement form the foundation
of the work and will inform Modeling, Prediction
and Simulation. These two areas will then drive
the development of solutions for Technologies
and Processes at Scale. The work undertaken
in each focus area is not sequential but rather
will include parallel development and feedback
loops.
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the various data streams are fused into a single
operational view. Likewise, new forms of remote
collection using sensors on vehicles, drones,
or satellites may provide a more complete
assessment of urban vulnerabilities and
resilience opportunities. Finally, “virtual” sensors
that provide data about human activities related
to urban resiliency, such as health impacts
tracked by hospital admissions, are yet another
independent input for our resiliency metrics
and models. To make use of all these data
will require developments in data fusion and
analysis, as well as techniques for preserving
privacy of sensitive data.
For each stressor of interest, optimal spatial
configurations, sampling frequency, and
communications and storage architectures must
be determined so that monitoring solutions
may be synthesized and tested for each of the
primary stressors of interest. An important
consideration will be the system’s maintainability
and accessibility.
Modeling, Prediction, and Simulation
Modeling, Prediction and Simulation will provide
computational tools to simulate the impact
of hazards on buildings and infrastructure,
quantify the impact with the developed metrics,
and support evaluation of technologies and
processes to improve infrastructure resilience.
Our starting point comprises a rich body of
research and simulation tools for both physical
infrastructure and environmental systems.
The first step in our approach to develop
new solutions for resilience-focused impact
assessment and technology development will be
to identify the gaps in these existing modeling
approaches. Gaps will be defined from the
perspective of the metrics we seek to evaluate
from the Metrics and Measurement focus area.
These gaps might relate to time scales (multiyear
versus sub-hourly), spatial scales (from meters
to kilometers), resolution (multi-building versus
component level), or performance (accuracy and
uncertainty).
Gaps also will be defined from the perspective
of the resilience scenarios and decisions that
the models are designed to address. That is, the
needs and gaps of models used to better inform
which segments of the grid should be subject
to public safety power shutoffs for wildfire risks
will be quite different from those used to value
new materials solutions based on the 30-year
insurance risk of flood-induced mold damage.
Once the gaps are identified, target models and
prediction approaches will be extended, and
further developed in response. For instance, a
key challenge in coupling urban microclimate
models and building energy models is the
mismatch of spatial and temporal resolutions. To
align these dimensions, we will develop a data
exchange framework and conduct simulation
studies (starting at the neighborhood scale) to
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