a prototype visualization tool for hygrothermal analysis · 2016. 3. 17. · a prototype...
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A Prototype Visualization Tool for Hygrothermal Analysis
Vamshi Gooje, BEMP, CEM, LEED AP BD+C Senior Associate
Building Energy 2016, Boston
March 9, 2016
Lead Computational Designer | CORE
Matthew Naugle
Building Certification
Energy Analysis
Existing Building Sustainability
Sustainability Education & Training
Sustainable Strategies
Sustainability Practice
1. Integration of hygrothermal analysis into early design phases
2. Sequential steps in evaluating hygrothermal failure criteria
3. A novel data visualization tool integrating varied sets of data
Learning Objectives
Basics of
Hygrothermal
Analysis
Hygrothermal Conditions
Reference: “Building Envelope Design” by SAB Magazine
Soil Environment: Temperature, Relative Humidity
Interior Environment: Temperature, Relative Humidity, Air pressure
Solar Radiation
Rain
Wind
Occupant Activities
Mechanical Equipment
Air Leakage
ENVIRONMENTAL LOADS ON THE BUILDING ENVELOPE
Load: Vapor Pressure Difference
Load: Air Pressure Difference
Load: Temperature Difference
Building Envelope
Reference: Whole Building Design Guide
structure external finish
finish support
air barrier
thermal insulation
vapor barrier
interior finish
structure
Large moisture buffer, ease of
wetting and drying
Low to moderate moisture buffers,
wetting and drying process more complicated
Hygrothermal Conditions
Inputs
Simulation
Grid
Material
Properties
Initial
Conditions
Climatic
Data
Surface
Transfer
Parameters
Time
Steps
Update thermal coefficients
Calculate temperature field
Update moisture coefficients
Calculate moisture field
satpp pDt
w
satpp pDt
w
Convergence?
Output Temperature fields
Temperature fluxes
Moisture fields
Moisture fluxes
Yes No
Coupled Transport Equations
Moisture Modeling Using WUFI
Reference: H.M. Künzel, A. Karagiozis, and A. Holm, WUFI Fundamentals
PROCESS
INP
UT
S
OU
TP
UT
S
Material Properties Initial Conditions Climatic Data (Outdoor) Surface Transfer Coefficients Climatic Data (Indoor)
Moisture Content of Component Moisture Content of Assembly Temperature and Dewpoint Limiting Isopleths
Moisture Modeling Using WUFI
Integration of
Hygrothermal Analysis
into Early Design Phases
Integrated Project Delivery Graphic by HOK
LESS EFFECTIVE
MORE EFFECTIVE
Image : HOK
Design Workflow Evolution
18,000
18,200
18,400
18,600
18,800
19,000
19,200
19,400
19,600
19,800
1+Wall R-18 1+Wall R-25 1+Wall R-28 1+Wall R-38
Gas U
se (
in T
herm
s)
Graphic by HOK
PROCESS
OPERATING ENERGY OPTIMIZATION
Disaggregated Data Challenges
HYGROTHERMAL PERFORMANCE
Trending moisture content indicating potential failure of
assembly & individual component
0
10
20
30
40
50
60
70
80
90
18,000
18,200
18,400
18,600
18,800
19,000
19,200
19,400
19,600
19,800
1+Wall R-18 1+Wall R-25 1+Wall R-28 1+Wall R-38
MC
%
Gas U
se (
in T
herm
s)
Graphic by HOK
Challenges in Data Integration
Hygrothermal performance
Energy performance
Sequential Steps in
Evaluating Hygrothermal
Failure Criteria
Graphic by HOK
PROCESS
ASHRAE 160 STANDARD
• 30-day running average (RH<80%, Temperature > 41°F and < 104°F)
• Criteria is evaluated for materials prone to mold.
Failure Criterion 1
(Minimize Surface Mold Growth)
Graphic by HOK
PROCESS Failure Criterion 2
(Moisture Content: Individual Components)
ply
wood
insu
lation
gyp
board
vapor barr
ier
stucc
o p
last
er
This rot/decay applies to wood based products
Graphic by HOK
PROCESS Failure Criterion 3
(Moisture Content: Entire Assembly)
ply
wood
insu
lation
gyp
board
vapor barr
ier
stucc
o p
last
er
The assembly is evaluated to ensure hygric equilibrium is achieved by
the end of study period.
Graphic by HOK
Failure Criterion 4
(Surface Condensation Potential)
ply
wood
insu
lation
gyp
board
vapor barr
ier
stucc
o p
last
er
Material surfaces are evaluated for potential condensation from humid
interior air. Evaluated for potential condensing surfaces
Graphic by HOK
PROCESS Failure Criterion 5
(Isopleths for Mold Growth)
ply
wood
insu
lation
gyp
board
vapor barr
ier
stucc
o p
last
er
Identifies potential mold growth on the interior surfaces. Mold growth is
possible when the conditions lie above the limiting isopleth lines.
Graphic by HOK
PROCESS
• Frost Damage (Primarily for Masonry)
• Fungi Growth (Using WUFI-BIO)
Failure Criterion 6 & 7
A
Data Visualization Tool
Integrating Varied Data Sets
15,000
15,500
16,000
16,500
17,000
17,500
18,000
18,500
19,000
19,500
20,000
1+Wall R-18 1+Wall R-25 1+Wall R-28 1+Wall R-38
Ga
s U
se
(in
Th
erm
s) FC 1
FC 2
FC 3
FC 4
FC 5
FC 6
FC 7
FC 1
FC 2
FC 3
FC 4
FC 5
FC 6
FC 7
FC 1
FC 2
FC 3
FC 4
FC 5
FC 6
FC 7
FC 1
FC 2
FC 3
FC 4
FC 5
FC 6
FC 7
PROCESS
PASS
FAIL
Integrated Data Analysis
Component 1 Outside Inside
Component 2
Component x
Full Assembly
WC
WC
Y1
WC
Temp RH MC DP
Temp RH MC DP
Temp RH MC DP Y2
Y(n)
Potential Total Number of Data Points=
8760 x (Number of Simulation Years) x (1 + 4 x Number of Assembly Components)
E.g. a simulation run for seven years with six components in the assembly would yield approximately
1.5 million data points
Temp RH MC DP
Temp RH MC DP
Temp RH MC DP
Temp RH MC DP
Temp RH MC DP
Temp RH MC DP
Scale of Data
PROCESS Grasshopper
Screenshot showing the
Grasshopper
programming
environment and an
associated visualization
PROCESS
Read file and extract
Temperature & RH data,
along with time steps
Generate visualizations
for results Run analytics
Grasshopper
Import simulation results data
Extract temperature, RH data & total assembly water content
Run analytics for the different failure criteria
FC1
Generate visualizations showing pass/fail in
components
Generate detailed graphs for failures
Import material data
FC 2 FC 3 FC 4 FC 5
Extract material densities, calculate dew point &
moisture content
.asc files
.xml files
Run WUFI simulations WUFI
GRASSHOPPER
Modify simulation parameters if necessary
Proposed Workflow
Wrap Up
PROCESS
• Preliminary testing showed that this visualization tool can effectively
address some of the challenges of post-processing the data from WUFI.
• The visualization style adopted by this tool aims to reduce the complexity of
the data and the associated evaluation criteria into an easily digestible
format that would speed up the evaluation process, and also facilitate for its
integration with other performance criteria.
Key Conclusions
• Carrying out batch runs, for creating a two-way connection from
Grasshopper that would send and receive data.
• Integrate the data from hygrothermal simulations with other design
criteria such as energy performance.
• Converting visualizations into interactive objects, rather than as static
graphs. This would allow the user to manipulate different aspects of the
analysis such as the threshold criteria, and observe the changes that
occur.
Future Work
Copyright Materials
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Reproduction, distribution, display and use of the presentation without written
permission of the speaker is prohibited.
© Thornton Tomasetti Inc. 2016