1. AR 4322 – Building Simulation and Analysis
Fall 2009
Huang Yi Chun
SDE
Tel:
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

2. Lecture 4 – Trends in Simulation
Automation
Reading List
Huang, Yi Chun; Khee Poh Lam and Gregory Dobbs(2008). A Scalable Lighting Simulation Tool for Integrated Building Design. Proceedings of The Third National Conference of IBPSA-USA (SimBuild 2008), 30 July – 1 August 2008, San Francisco, USA. Pp
Huang, Yi Chun, and Khee Poh Lam (2008). Automated Calculation of Lighting Regulations. Proceedings of the First International Conference on Building Energy and Environment (COBEE 2008), July 2008, Dalian, China.
Biswas, Tajin, Tsung-Hsien Wang and Ramesh Krishnamurti (2008) Integrating Sustainable Building Rating Systems with Building Information Models. Proceedings of the 13th International Conference on Computer Aided Architectural Design Research in Asia (CADDRIA 2008), 9-12 April 2008, Chiang Mai, Thailand. Pp
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

3. Automatic Calculation of Lighting Regulations
Huang, Yi Chun; Khee Poh Lam and Gregory Dobbs(2008). A Scalable Lighting Simulation Tool for Integrated Building Design. Proceedings of The Third National Conference of IBPSA-USA (SimBuild 2008), 30 July – 1 August 2008, San Francisco, USA. Pp
Slide 1: Title (please keep)
Slides 2-9: Introduction of project, problem statement and objectives
Slide 10: Summary of application features
Slides 11-16: Demo 1 Lighting simulations in 3 mouse clicks
Slide 17: Addition features of application
Slides 18-22: LEED Credit 8.1 (Glazing Factors) Calculator
Slides 23-24: LEED Credit 8.2 (View Out) Calculator
Slide 25: rgbe visualizer
Slide 26-28: External data libraries

4. Context and Motivation
Performance benchmarks in building design
1. Benefits of performance-based design and performance benchmarks
- High performance buildings (integration, sustainability)
- Vision, goals, objectives, tracking, assessments
- Lindsey, 2003; Hitchcock, 2003; Deru, 2004
2. Lighting regulations (standards) as performance benchmarks
- Fundamental (ir)radiance calculations might not provide operative information
- Lighting regulations (standards) as performance benchmarks
- Logistical effort in acquiring parameters
- Time and effort in calculation procedures
3. Automated calculation of lighting regulations
- Dual purposes: reduction in calculation and documentation effort
- Market demand
- Prevalence of BIM, opportunity for automation
- Need to formulate calculation procedures as computable
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 4

5. Context and Motivation
Performance benchmarks in building design
2. Lighting regulations (standards) as performance benchmarks
- Fundamental (ir)radiance calculations might not provide operative information
- Lighting regulations (standards) as performance benchmarks
USGBC LEED Rating System
EQ 8.1 & 8.2 – Daylight and Views
Provide for the building occupants a connection between indoor spaces and the outdoors through the introduction of daylight and views into the regularly occupied areas of the building.
EQ 8.1 (Opt 1) – Achieve a minimum glazing factor of 2% in a minimum of 75% of all regularly occupied areas
EQ 8.2 – Achieve direct line of sight to the outdoor environment via vision glazing between 2’6” and 7’6” above finish floor for building occupants in 90% of all regularly occupied areas.
Voluntary rating system
Widespread use by both governmental and private industry (Landman, 2005)
2 lighting performance benchmarks
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 5

6. Context and Motivation
Performance benchmarks in building design
2. Lighting regulations (standards) as performance benchmarks
- Fundamental (ir)radiance calculations might not provide operative information
- Lighting regulations (standards) as performance benchmarks
- Logistical effort in acquiring parameters
- Time and effort in calculation procedures
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 6

7. Context and Motivation
Performance benchmarks in building design
3. Automated calculation of lighting regulations
- Dual purposes: reduction in calculation and documentation effort
- Market demand
- Prevalence of BIM, opportunity for automation
- Need to formulate calculation procedures as computable
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 7

8. Objectives Integration with Design Support Tool
Availability of performance benchmarks throughout design process
Reduction of time and effort
Formulation of benchmarks as computable
Formulation of calculation procedures as computable problems that can be evaluated by a computer automatically
Resources required must be within the constraints of typical design practices
Improvements
Formulation of procedures as algorithms allows insight into benchmarks, and how they might be improved
LEED benchmarks, like most regulatory metrics typically calculated post-design due to logistical and resource burdens.
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 8

9. Framework New Lighting Simulation Tool – Version 0.5
Implemented as part of CMU Lighting Simulation Tool – part of effort to reduce effort & resources
LEED automation – tracking performance during design iterations, documentation effort
LEED Credit EQ 8.1. Glazing Factors
Revit Model
Material Properties Inspection and Editing
LEED Credit EQ 8.2. View-out Availability
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

10. Formulation as Computable
LEED EQ 8.1 (Opt 1) – Daylight Availability
Achieve a minimum glazing factor of 2% in a minimum of 75% of all regularly occupied areas
Mainly logistical task, variable values retrieved from BIM, minimal computation
Algorithm
Step 1: Find list of occupied spaces
Step 2: Find list of windows in each space
Step 3: Determine window type
(subdivide window if necessary)
Step 4: Retrieve Tvis and calculate GF for all windows
Step 5: Tabulate GFs in each space (check if >2%)
Step 6: Tabulate eligible floor area (check if ≥75%)
Analysis
O(nlogn) retrieval of lists and values from BIM
Step 3: O(nlogn) retrieve window geometry
O(n) orientation and height determination
O(n) subdivision
O(n) GF calculations and tabulation
LINEARITHMIC TIME PERFORMANCE
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 10

11. Formulation as Computable
LEED EQ 8.1 (Opt 1) – Daylight Availability
Real-time implementation, dynamic update as building model is modified
Parameters Inspection in Lighting Tool, no user intervention
Automated Calculation of Lighting Regulations – Y.C. Huang
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 11

12. Formulation as Computable
LEED EQ 8.1 (Opt 1) – Daylight Availability
Real-time implementation, dynamic update as building model is modified
Real-time calculation of LEED EQ 8.1
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 12

13. Formulation as Computable
LEED EQ 8.1 (Opt 1) – Daylight Availability
Real-time implementation, dynamic update as building model is modified
Tabulation for LEED EQ 8.1 submittal
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 13

14. Formulation as Computable
LEED EQ 8.2 – External Views
Achieve direct line of sight to the outdoor environment via vision glazing between 2’6” and 7’6” above finish floor for building occupants in 90% of all regularly occupied areas.
Determine the area with direct line of sight by totaling the regularly occupied square footage that meets the following criteria:
- In plan view, the area is within sight lines drawn from perimeter vision glazing
- In section view, a direct sight line can be drawn from the area to perimeter vision glazing
Line of sight may be drawn through interior glazing.
For private offices, the entire square footage of the office can be counted if 75% or more of the area has direct line of sight to perimeter glazing. If less than 75%, actual compliant area is counted.
For multi-occupant spaces, the actual square footage with direct line of sight to perimeter glazing is counted.
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 14

15. Formulation as Computable
LEED EQ 8.2 – External Views
2 step graphical calculation procedure (2D line-of-sight projections, 2nd pass confirmation)
Implicit checks for internal wall openings
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 15

16. Formulation as Computable
LEED EQ 8.2 – External Views
Formularization as computable, possible finite-element approach
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 16

17. AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation17

18. AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation18

19. AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation19

20. Formulation as Computable
LEED EQ 8.2 – External Views
Dynamic implementation, fast update as building model is modified
Imported building model, no user intervention
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 20

21. Formulation as Computable
LEED EQ 8.2 – External Views
Dynamic implementation, fast update as building model is modified
Dynamic calculation of LEED EQ 8.2
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 21

22. Formulation as Computable
LEED EQ 8.2 – External Views
Dynamic implementation, fast update as building model is modified
Tabulation for LEED EQ 8.2 submittal
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 22

23. Summary of Results Formulation of LEED EQ 8.1 & 8.2 as computable
- Interoperability
- Ray tracing
- CMU Lighting Tool
Algorithm optimization – data structures
Benchmark clarification – steradians (computing speed-up)
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 23

24. Modified Photon Mapping
Huang, Yi Chun (2009). “Implementation of a new simulation engine”. An Integrated Scalable Lighting Simulation Tool, Chapter 3. Unpublished manuscript.
Slide 1: Title (please keep)
Slides 2-9: Introduction of project, problem statement and objectives
Slide 10: Summary of application features
Slides 11-16: Demo 1 Lighting simulations in 3 mouse clicks
Slide 17: Addition features of application
Slides 18-22: LEED Credit 8.1 (Glazing Factors) Calculator
Slides 23-24: LEED Credit 8.2 (View Out) Calculator
Slide 25: rgbe visualizer
Slide 26-28: External data libraries

25. Lighting Models (Backwards) Raytrace and Photon Mapping
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

26. Lighting Models Raytracing might under-estimate ambient radiance
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

27. Photon Mapping Separating rendering equation into 4-components Direct
Specular
Indirect
Caustics
Radiance of Point A as sum of direct, specular, indirect and caustics components
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 27

28. Photon Mapping Separating rendering equation into 4-components Direct
Specular
Indirect
Caustics
2-maps, check for duplicate paths
Reflected caustics might be neglected
Radiance of as sum of direct, specular, indirect and caustics components
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 28

29. Modified Photon Mapping
Separating rendering equation into 3-components
Direct
Indirect
Caustic
No longer split into diffuse or specular terms, taken care of (and pre-computed) by BRDF
No need to check for duplicate paths
Diffused caustics accounted for
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 29

30. Modified Photon Mapping
Accuracy of area estimation
Disc Vs. Sub-sampling
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 30

31. Modified Photon Mapping
Accuracy of area estimation
Disc Vs. Sub-sampling
Direct visualization of photon map to show effect of approximated area (left), corrected area (right)
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 31

32. Modified Photon Mapping
Progressive accuracy
Scalability
Use number of photons rather than samples
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 32

33. Modified Photon Mapping
Power-based priority-queue
Conventional Russian Roulette (left), power-prioritized technique (right)
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 33

34. Modified Photon Mapping
Direct sampling
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 34

35. A Scalable Lighting Simulation Tool For Integrated Building Design
Huang, Yi Chun, and Khee Poh Lam (2008). Automated Calculation of Lighting Regulations. Proceedings of the First International Conference on Building Energy and Environment (COBEE 2008), July 2008, Dalian, China.
Slide 1: Title (please keep)
Slides 2-9: Introduction of project, problem statement and objectives
Slide 10: Summary of application features
Slides 11-16: Demo 1 Lighting simulations in 3 mouse clicks
Slide 17: Addition features of application
Slides 18-22: LEED Credit 8.1 (Glazing Factors) Calculator
Slides 23-24: LEED Credit 8.2 (View Out) Calculator
Slide 25: rgbe visualizer
Slide 26-28: External data libraries

36. Objective 1 Reduce resources required to conduct lighting simulation
Conducting a lighting simulation is time consuming, too many software to buy and learn.
Drawings
Documentation
Etc.
Geometry
Modeling
Variables Definition
E.g. Materials & Location
Simulation Parameters
Definition
Simulation
Results processing
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 36

37. Objective 1 Reduce resources required to conduct lighting simulation
Reducing time and effort required to prepare for simulations (applicable to all domains)
Drawings
Documentation
Etc.
Geometry
Modeling
Variables Definition
E.g. Materials & Location
Simulation Parameters
Definition
Why should we spend time on this?
Simulation
Results processing
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 37

38. Automated Processing Objective 1
Reduce resources required to conduct lighting simulation
Reducing time and effort required to prepare for simulations (applicable to all domains)
Automated
Processing
Automatic
XML-Based
Parser
Automatic
Default
Values
Automatic
Engine
Selection
Drawings
Documentation
Etc.
Automatic
Simulation
Files Creation
Improved
Analysis
Features
User-editable Input
Results processing
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 38

39. Objective 1 Reduce resources required to conduct lighting simulation
Definition of appropriate simulation parameters require much training and tacit knowledge
Time consuming
Finite element Radiosity parameters
Backward Ray-trace parameters
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 39

40. Objective 2 Efficiency and consistency in defining BIM and assumptions
New information created in individual domain is updated to the BIM
Objective 2
Efficiency and consistency in defining BIM and assumptions
Externalizing project shared information
Shared
Building
Information
Model
Shared
Construction
Properties
Database
Shared
Location
Information
Database
Conflict?
Information Update?
SHARED OBJECT MODEL
Conflict?
Information Update?
LIGHTING SIMULATION
ASSUMPTIONS
-geometry abstractions
-material properties
(reflectance, specularity, etc)
-luminare specification
-schedules
ENERGY SIMULATION
ASSUMPTIONS
-geometry abstractions
-material properties
(conductivity, specific heat, etc.)
-lighting design level
-schedules
Building Modeler
Lighting Tool
Energy Tool
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

41. Lighting Simulation Tool
Objective 2
Efficiency and consistency in defining BIM and assumptions
Externalizing project shared information
Shared
Construction
Properties
Database
Shared
Location
Information
Database
Other domain apps
Shared
Building
Information
Model
Parser
Parser
Lighting Simulation Tool
Parser
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 41

42. Objective 3
Obtaining Operative Information for Design Decisions
Lighting simulations address low-level objectives, not higher-level questions typical of primary design inquiries.
Typical Lighting Simulation
Lighting
Simulation
3. Formulating objectives solvable by lighting simulation
Simulation Results
(Illuminance data)
What is the illuminance distribution in this space?
4. Analysis of results
Is there sufficient illuminance on workplane in all occupied spaces?
Check all occupied spaces if
illuminance > threshold
on workplane
Is there lighting sufficient in this building?
2. Formulating well-formed problem by considering context and making relevant assumptions.
Check if number of satisfactory spaces compliant with regulations
SOLUTION
5. Operative Information for design decision
1. Design Question
AR 4322 – Building Simulation and Analysis – Lecture 1 - Introduction

43. Objective 3 Obtaining Operative Information for Design Decisions
Providing post-processing analysis toolkit
Tone-mappers
Luminance data inspection and false-color analyses
Luminance ratios calculator
Data comparisons
LEED rating system Credit 8.1 & 8.2 calculators
Tabulation of results
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 43

44. Results CMU Lighting simulation Tool – Version 0.5
Java based application – ease of prototyping
General Parser – Revit-exported gbXML files & extended XML schema
Radiance engine integration – automatic simulation files generator
External Libraries – Location & Construction complete, rule based context recognition
Visualizations – HDRI support, False-color, Inspector, Comparator, Luminance Ratios
Post-processing – LEED Credit EQ 8.1 & 8.2 calculators and tabulations
Step 1 – User selects input file (as exported from Revit)
Step 2 – Missing information such as sky data and camera positions are set automatically
Step 3 – Default values are highlighted in red. User can edit values if necessary
Prototype of 2007 CMU Lighting Application v.0.5. The 3-step process to saving time.
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

45. Change Management System*
New Lighting Tool
Building
Information Model
<<include>>
Import BIM
Form
Complete Model
Read/Write
BIM
<<include>>
Construction
Database
Access
Database
Edit BIM
Location
Database
Domain
Object Model
GUI
Perform
Lighting Simulation
User
Read/Write
Simulation Results
Simulation
Results
Visualize
Simulation Results
Change Management System*
Shared Object Model*
*External System
Calculate
LEED Benchmarks
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

46. AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

47. Lighting Simulation Results
Demo 1
Dramatic reduction in effort to conduct lighting simulation
Revit Model
Export as gbXML file
Lighting Simulation Results
The following slides will demonstrate how a lighting simulation is obtained in just 3 mouse clicks
Automatic processing by
CMU Lighting Application
Generated Radiance Batch File
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation

48. Demo 2 Parametric Studies 48
The following slides will demonstrate how a lighting simulation is obtained in just 3 mouse clicks
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 48

49. Demo 3 Design investigations and analyses 49
Automatic Radiance Batch Files
Revit Model
Automatic processing by
CMU Lighting Application
Results Analysis
The following slides will demonstrate how a lighting simulation is obtained in just 3 mouse clicks
Comparison between design changes
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 49

50. Demo 4 Calculating LEED credits, tracking during design investigations
LEED Credit EQ 8.1. Glazing Factors
Revit Model
Material Properties Inspection and Editing
LEED Credit EQ 8.2. View-out Availability
The following slides will demonstrate how a lighting simulation is obtained in just 3 mouse clicks
AR 4322 – Building Simulation and Analysis – Lecture 4 – Trends in Simulation 50

51. Sustainable Building Information Model (SBIM) Sponsored by: Autodesk® Revit Professor Ramesh Krishnamurti Tajin Biswas Tsung-Hsien Wang Yi Chun Huang School of Architecture Pittsburgh, Pennsylvania

52. Approach (Integrating rating systems with design software via a framework)
Evolutionary benchmarks
-different rating systems
Rating_1
Protocols
Rating System Evaluation
Direct Data
Performance Data
BIM
Simulation Tools
External Data
request
Sustainable Framework
Rating_2
Rating_n
Design
Representation
software
Missing information
In a broad sense, a framework is a “conceptual structure used to solve or address complex issues” ( Dec 2008). In sustainable design it is seen and used mainly in the form of matrixes, (Weerasinghe, et al 2007, Hassan, 2008 and Gething, 2007). In this paper the characteristics associated with a framework will be used more specifically as a structure to map rating system requirements to their comprising elements; identify processes involved; identify missing information and manage changes in rating systems in a cohesive way.
Implicit in the task of putting together a complete set of data are the following:
Formulation of a comprehensive and general ontology that: a) can accommodate and classify all informational requirements of the different rating systems; and b) lends itself easily to computation.
2. Identification of protocols required for carrying out specific processes for such evaluation.
3. Mapping rating system requirements to elements in a BIM, for example, Revit™ to [a)] find missing capabilities in the BIM, which will help identify the necessary external data that [b)] needs to be accommodated. Figure depicts the system flow.
Multiple goals and constraints
at different phases of design-
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

53. Building Information Model Design and Interaction with General Framework
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

54. Framework Categorization
……..
C1.5 Integrity of building envelope
C 1.6 HVAC Systems
C 1.7 Service Water Heating
C 1.8 Power Distribution Systems
C 1.9 Other Systems
C 1.10 Lighting Systems
C 1.11 Adaptability of systems
......
F 1.1 Energy efficiency
F 1.2 On site renewable energy
F 1.3 Alternative Green Energy
Sub Categories
Major Categories
Owner
Designer ……
Major Phases
Lifecycle of Project
Feasibility Study-Pre design
Site
Building
Material
Indoor Environment
Energy
Design
Construction Management/Planning
Construction
Operation and maintenance
Pre Construction
Decommissioning
Construction
Commissioning
Service and support
How does the framework of measures cater to different rating systems
An exhaustive list of requirements from all the systems…?
Approach –to find the most commonly used attributes and parameters
Source and disposal
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

55. Framework Objects Mapping to Ratings (energy)
……..
C1.5 Integrity of building envelope
C 1.6 HVAC Systems
C 1.7 Service Water Heating
C 1.8 Power Distribution Systems
C 1.9 Other Systems
C 1.10 Lighting Systems
C 1.11 Adaptability of systems
......
F 1.1 Energy efficiency
F 1.2 On site renewable energy
F 1.3 Alternative Green Energy
Sub Categories ID
Object Name
return type
Ex ref
BIM ref
LEED
BREEAM
Gr Star
C 1.5.1
Insulation
yes/no
ref
material
EA Preq2
EA 1-10
C 1.6.2
HVACType (enum 8types)
ref
ref sec 6.4
Ene-Pre
Ene-1
C 1.7.1
ServiceWaterHeating
 ref
equip
Wat-3
C 1.8.1
PowerDistSystems
ref sec 8.4
Ene-2
C 1.8.2
Electrical Submetering(enum lighting, fan, cooling tower, humidification..)
ref (SIBSE)
Ene02
C 1.9.1
OtherEquipment(motors)
ref sec 10.4 C
Lighting(exterior, signs, grounds, parking)
ref sec 9.4
Ene04
Mat-10 C
LightFixtureType
string
light
SS8
Pol 07
Emi-8 C
LightPowerDensity
number
 process
Ene-3 C
FixturePower C
NumberOfLuminare ID
Object Name
return type
Ex ref
BIM ref
LEED
BREEAM
Gr Star
F 1.1.1
ReductionOfEnergyFromBase
number
ref
EA 1-10
Ene01
Ene 05
Mat-10
Ene-1
F 1.1.2
EnergySimulation
yes/no
Ref/process
Ene-Pre
F 1.1.3
SimulationNumber
How does the framework of measures cater to different rating systems
An exhaustive list of requirements from all the systems…?
Approach –to find the most commonly used attributes and parameters
Mapping of sub categories to objects that are required by different rating systems
Exhaustive list of attributes?
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

56. Framework Objects Mapping to Simulation Model
……..
C1.5 Integrity of building envelope
C 1.6 HVAC Systems
C 1.7 Service Water Heating
C 1.8 Power Distribution Systems
C 1.9 Other Systems
C 1.10 Lighting Systems
C 1.11 Adaptability of systems
......
F 1.1 Energy efficiency
F 1.2 On site renewable energy
F 1.3 Alternative Green Energy
Sub Categories ID
Object Name
C 1.5.1
Insulation
C 1.6.2
HVACType (enum 8types)
C 1.7.1
ServiceWaterHeating
C 1.8.1
PowerDistSystems
C 1.8.2
Electrical Submetering(enum lighting, fan, cooling tower, humidification..)
C 1.9.1
OtherEquipment(motors) C
Lighting(exterior, signs, grounds, parking) C
LightFixtureType C
LightPowerDensity C
FixturePower C
NumberOfLuminare
Baseline Model for Simulation
Building & Location Info
Building Geometry
Building Envelope
Service Hot Water
Power
Lighting
Other Loads
HVAC ID
Object Name
F 1.1.1
ReductionOfEnergyFromBase
F 1.1.2
EnergySimulation
F 1.1.3
SimulationNumber
How does the framework of measures cater to different rating systems
An exhaustive list of requirements from all the systems…?
Approach –to find the most commonly used attributes and parameters
Mapping of objects that are required for simulation
Exhaustive list of attributes?
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

57. Application Data Manager
Application Design
Event Detector
General Framework GF
External Simulation Engine
SQL
Query
Request
Demo-Dec (cont.)
Application
GUI
External Database
System Updates
Application Data Manager
GBXML
BIM
Database
Revit S Craig
1,2
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

58. Databases to Application via SQL
External Databases
Revit
Collect building element
info
Generate Data Table
Populate defaults
Others
(e.g.Rain fall Rates)
Building Information Database
Application
Result
Evaluation (LEED, GREENSTAR)
Material
Properties
Simulation (Energy, Lighting)
Measure Databases
General Framework
LEED
GreenStar
BREEAM
SQL
Mdb Database
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

59. Case Study 407 S Craig St, PA (Back)
407 S Craig St, PA (Front), LEED silver
407 S Craig St, PA (Back)
LEED certified building, 407 S Craig St , Pittsburgh
Previously we tested on random models which were not certified just to get test the ability to extract required information
Now we are validating the results of a real building to see how many credits can be calculated and if we can arrive at the same results
Some achieved credits/points:
Site density, alternative transportation (targeted by our application)
Energy reduction, onsite renewable energy (solar panels on roof)
Reused structure and materials inside (targeted and achieved)
Storage for recyclable materials (targeted)
Water efficient fixtures (targeted)
Skylights before
Redesigned: Northern light and solar panels
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

60. Model and Application Main Information Display Navigation Status
Build Revit model and inputting information related to LEED certification.
Build site mass model as well as materials in details
Status
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

61. Calculating building and material reuse from model (LEED)
Testing is done using LEED 3.0 for material reuse MR 1.1 and MR 1.2
Building structure and façade is existing
Using these material properties we are able to calculate credits for building material reuse
Potential Credits: MRp1 and MR4.1
By placing storage bins we are able to calculate if it meets the requirements for recycling the buildings waste (paper, glass, cardboard, etc)
Steel framing using recycled steel content, to determine if it fulfils requirements of MR 4.1
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

62. Calculating building and material reuse from model (Green Star)
This shows using Green Star on same building to determine which credits it satisfies:
In this case it fulfils requirements of Mat2 and Mat 3
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

63. Calculating number of parking and bicycle racks (Green Star)
Testing done with LEED shows that Cyclist facilities are adequate
In this particular step we start to check if it qualifies for Green Star requirements of the number of bicycle racks which does not qualify
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

64. Calculating LEED SS 2 (Site Density)
On going experimentation of calculating site density through the following steps:
Superimposing site map with plan to identify and build mass model for site density calculation for LEED
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

65. Calculating LEED SS 2 (Finding Density Radius)B C M N K L J
350’ I O H P D E
Calculating density radius according to the specified requirements
Density radius(LF) = 3 * (Property Area (sft)
All the properties that intersect the line have to be calculated
The radius starts at the center of the building and is drawn to include the properties that fall into it for density calculation F F G
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

66. Calculating LEED SS 2 (Calculating Development Density)B A N M L K D
Development Density E J I O P F G H
Number of floors added to the mass to calculate total floor areas, using site area, site density is calculated and evaluated
The density (sft/acre = gross building (sft)/Project site area (acres)
For Example
Building Space (sft) Area(Acres) A
B 87,
C 6,
……………………………………………………………………………….
Total building area (X)
Total site area (Y)
Average Density = (X/Y) sft/Acre > 60,000 sft/Acre so it meets the requirements
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

67. Calculating LEED EA 1.1~1.10 Energy Optimization
Sustainable Evaluation of Buildings – T. Biswas & T.S. Wang

68. Energy Simulation to quantify energy improvement
Appendix G – Information requirements
Originally intended for rating energy efficiencies of building designs that exceed the requirements of ASHRAE  There exists some proposed design, compare to baseline.
Our objective  Generating baseline model from architectural model (no M&E specifications).
Proposed Design
Proposed Design Model
Energy Simulation to quantify energy improvement
Energy Usage Reports
Baseline Model
ASHRAE 90.1 Compliant
Building & Location Info
Building Geometry
Building Envelope
HVAC
Service Hot Water
Power
Lighting
Other Loads
Lights
Internal Eqpt Loads
Service Water Heating
Space Heating
Space Cooling
Heat Rejection
Fans
Other HVAC Eqpt
Appendix G stipulates modeling requirements, especially the differences between the 2 models.
Performance benchmarks are highlighted, NOT an exhaustive listing of attributes.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

69. Processes and Artifacts
Revit file
Contains
All info
Weather files
Populate defaults
Generate idf file
Ground
Calcs
Sizing Run
Overview of processes and artifacts involved in the objective of automating the generation of Appendix-G baseline EnergyPlus input models
Has
Ground slab
idf file
(prep0)
idf file
(prep1)
idf file
(base)
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

70. Processes Generate idf file
Processes will complete the idf file. May not be 1:1 mapping
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

71. Processes Generate idf file ERROR DONE Zones Is there HVAC Zoning? Yes
Are the zones well-formed? No
Is queue empty? Process next zone
Yes
Yes
Are there Room elements?
Yes No No
ERROR
DONE No
Are there external walls?
Should the zone be subdivided?
Yes
Yes
Form bounded zones from surfaces
Subdivide zone, add new geometry. No No
Add zones to unprocessed queue
Zone processing complete. Remove from queue.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

72. Appendix G – EnergyPlus (idf) file
Baseline Model
Building & Location Info
Building Geometry
Building Envelope
Service Hot Water
Power
Lighting
Other Loads
HVAC
Basic Objects
 Required in all models
HVAC Objects
 Varies among models
How does Appendix G translate as an EnergyPlus model?
- General Categories listed here
- HVAC ontology varies depending on required system type
Can we formulate an exhaustive list of attributes? Sure, the entire E+ list of objects.
Mapping of general categories
HVAC ontology varies
Exhaustive list of attributes?
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

73. Appendix G – EnergyPlus (idf) file  Basic Objects
EnergyPlus Model
Simulation Parameters
Location
Schedules
Reports
Appendix G – EnergyPlus (idf) file  Basic Objects
Surface Construction Elements
Geometry
Airflow
Internal Gains
Design
Node Branch Management
Plant Condenser Loops
Plant Condenser Control
Plant Condenser Flow Control
System Availability Managers
Air Distribution
Set Point Managers
Controllers
Zone Equipment
Zone Controls and Thermostats
Air Distribution Equipment
Air Path
Plant Equipment
Pumps
Fans
Coils
Simulation Parameters
Surface Construction Elements
Schedule
Version
Building
Timestep in hour
Inside Convection Algorithm
Outside Convection Algorithm
Solution Algorithm
Run Control
Schedule Type
Schedule: Compact
Material: Regular
Material: Regular-R
Material: Air
Material: Window Glass
Material: Window Gas
Construction
Internal Gains
People
Lights
Electric Equipment
Location
Geometry
Run Period
Location
Design Day
Ground Temperatures
Water Mains Temperatures
Zone
Surface Geometry
Surface: Heat Transfer
Surface: Heat Transfer: Sub
Surface: Shading: Attached
Air Flow
Infiltration
Reports
Report Variable
Report Meter
How does Appendix G translate as an EnergyPlus model?
Color Key
Class
Leaf
Convention : Class attributes might be other classes. Leaf is used here to refer to attributes that require values that do not reference other objects. Conceptually, a model is complete once all leaves(typically numerical or Boolean) are acquired.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

74. Appendix G – EnergyPlus (idf) file  HVAC Objects
EnergyPlus Model
Simulation Parameters
Location
Schedules
Reports
Appendix G – EnergyPlus (idf) file  HVAC Objects
VAV w/PFP Boxes (System 8)
Surface Construction Elements
Geometry
Airflow
Internal Gains
Design
Node Branch Management
Plant Condenser Loops
Plant Condenser Control
Plant Condenser Flow Control
System Availability Managers
Air Distribution
Set Point Managers
Controllers
Zone Equipment
Zone Controls and Thermostats
Air Distribution Equipment
Air Path
Plant Equipment
Pumps
Fans
Coils
Design
Plant Condenser Flow Ctrl
Controllers
Sizing Parameters
Zone Sizing
System Sizing
Plant Sizing
Splitter
Mixer
Controller: Simple
Controller: Outside Air
Air Distribution
Zone Equipment
Air Primary Loop
Controller List
Air Loop Equipment List
Outside Air System
Outside Air Node
Outside Air Inlet Node List
Outside Air Mixer
Controlled Zone Equip. Config.
Zone Equip. List
Air Distribution Unit
Node Branch Management
Plant Equipment
Node List
Branch List
Connector List
Branch
Pipe
Boiler: Simple
Chiller: Electric
Air Distribution Equipment
Single Duct: VAV: Reheat
Pumps
Plant Condenser Loops
System Availability Managers
Pump: Variable Speed
Zone Ctrls and Thermostats
Plant Loop
SAM List
SAM: Scheduled
SAM: Low Temp. Turn Off
Zone Control: Thermostatic
Single Heating Setpoint
Single Cooling Setpoint
Dual Setpoint with Deadband
Coils
Plant Condenser Control
Coil: Water: Cooling
Coil: Water: Simple Heating
The comprehensive idf schema would be the entire E+ documentation.
Plant Operation Schemes
Cooling Load Range-based Op
Heating Load Range-based Op
Plant Equipment List
Set Point Managers
SPM: Scheduled
SPM: Mixed Air
Air Path
Fans
Zone Supply Air Path
Zone Return Air Path
Zone Return Plenum
Zone Splitter
Fan: Simple: Variable Volume
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

75. Color Key Class Leaf Only the basic objects
Simulation Parameters
Version
Run Period
Material: Regular
Zone
People
Infiltration
Version
Building
Timestep in Hour
Inside Conv. Algorithm
Outside Conv. Algorithm
Solution Algorithm
Run Control
Version Identifier
Run Period Start
Run Period End
Start Day
Use Weather File Holidays
Use Weather File DLS
Apply Weekend Rule
Weather File Rain Ind.
Weather File Snow Ind.
Name
Roughness
Thickness
Conductivity
Density
Specific Heat
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Zone Name
Relative North
X Origin
Y Origin
Z Origin
Type
Multiplier
Ceiling Height
Volume
Name
Zone Name
Num People Sch Name
Num People Calc Method
Num People
Fraction Radiant
Activity Level Sch Name
Name
Zone Name
SCHEDULE Name
Design Volume Flow Rate Calculation method
Design Volume Flow Rate
Flow per Zone Area
Flow per Ext Surface Area
Air Changes Per Hour
Constant Term Coefficient
Temp. Term Coefficient
Velocity Term Coefficient
Velocity Squared Term Coefficient
Building
Building Name
North Axis
Terrain
Loads Convr Tolerance
Temp. ConvrTolerance
Solar Distribution
Warm-up Days
Location
Lights
Location
Run Period
Location
Design Day
Ground Temperatures
Water Mains Temp.
Material: Regular-R
Surface Geometry
Name
Zone Name
Schedule Name
Design Level Calc Method
Lighting Level
Return Air Fraction
Fraction Radiant
Fraction Visible
Fraction Replaceable
End-Use Subcategory
Location Name
Latitude
Longitude
Time Zone
Elevation
Timestep in Hour
Name
Roughness
Thermal Resistance
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Surface Starting Position
Vertex Entry
Coordinate System
Timestep in Hour
Surface Const. Elements
Inside Conv Algorithm
Surface: Heat Transfer
Design Day
Material: Regular
Material: Regular-R
Material: Air
Material: Window Glass
Material: Window Gas
Construction
Inside Conv Algorithm
Surface Name
Surface Type
Construction Name
Zone Name
Outside Face Environment
Outside Face Env Object
Sun Exposure
Wind Exposure
View Factor to Ground
Num of Surface Vertex
Vertex Coordinate
Design Day Name
Max Dry Bulb Temperature
Daily Temperature Range
Humidity Ind. Conditions
Barometric Pressure
Wind Speed
Wind Direction
Sky Clearness
Rain Indicator
Snow Indicator
Day of Month
Month
Day Type
DLS Indicator
Humidity Indicating Type
Material: Air
Outside Conv Algorithm
Name
Thermal Resistance
Electric Equipment
Outside Conv Algorithm
Name
Zone Name
Schedule Name
Design Level Calc Method
Design Level
Fraction Latent
Fraction Radiant
Fraction Lost
Solution Algorithm
Material: Window Glass
Geometry
Solution Algorithm
Name
Optical Data Type
Solar Transmittance
Solar Reflect.: Front Side
Solar Reflect.: Back Side
Visible Transmittance
Visible Reflect.: Front Side
Visible Reflect.: Back Side
IR Transmittance
IR Emissivity: Front Side
IR Emissivity: Back Side
Conductivity
Zone
Surface Geometry
Surface: Ht Transfer
Surface: Ht Transfer: Sub
Surface: Shdi: Attached
Run Control
Run Control
Surface: Ht Transfer: Sub
Surface Name
Surface Type
Construction Name
Base Surface Name
View Factor to Ground
Multiplier
Num of Surface Vertex
Vertex Coordinate
Schedule
Schedule Type
Schedule: Compact
Schedule Type
Ground Temperatures
Internal Gains
Schedule Type Name
Range
Numeric Type
Monthly Grd Temp.
Material: Window Gas
People
Lights
Electric Equipment
Name
Gas Type
Thickness
Surface: Shd: Attached
Schedule: Compact
Surface Name
Base Surface Name
TransSchedShadowSurf
Num of Surface Vertex
Vertex Coordinate
Report Variable
Air Flow
Name
Schedule Type
Week Schedule
Day Schedule
Construction
Report Name
Reporting Frequency
Infiltration
Only the basic objects
Name
Outside Layer
Layer
Reports
Report Meter
Report Variable
Report Meter
Meter Name
Reporting Frequency
Color Key
Class
Leaf
Convention : Class attributes might be other classes. Leaf is used here to refer to attributes that require values that do not reference other objects. Conceptually, a model is complete once all leaves(typically numerical or Boolean) are acquired.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

76. Example of object links
Simulation Parameters
Version
Run Period
Material: Regular
Zone
People
Infiltration
Version
Building
Timestep in Hour
Inside Conv. Algorithm
Outside Conv. Algorithm
Solution Algorithm
Run Control
Version Identifier
Run Period Start
Run Period End
Start Day
Use Weather File Holidays
Use Weather File DLS
Apply Weekend Rule
Weather File Rain Ind.
Weather File Snow Ind.
Name
Roughness
Thickness
Conductivity
Density
Specific Heat
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Zone Name
Relative North
X Origin
Y Origin
Z Origin
Type
Multiplier
Ceiling Height
Volume
Name
Zone Name
Num People Sch Name
Num People Calc Method
Num People
Fraction Radiant
Activity Level Sch Name
Name
Zone Name
SCHEDULE Name
Design Volume Flow Rate Calculation method
Design Volume Flow Rate
Flow per Zone Area
Flow per Ext Surface Area
Air Changes Per Hour
Constant Term Coefficient
Temp. Term Coefficient
Velocity Term Coefficient
Velocity Squared Term Coefficient
Building
Building Name
North Axis
Terrain
Loads Convr Tolerance
Temp. ConvrTolerance
Solar Distribution
Warm-up Days
Location
Lights
Location
Run Period
Location
Design Day
Ground Temperatures
Water Mains Temp.
Material: Regular-R
Surface Geometry
Name
Zone Name
Schedule Name
Design Level Calc Method
Lighting Level
Return Air Fraction
Fraction Radiant
Fraction Visible
Fraction Replaceable
End-Use Subcategory
Location Name
Latitude
Longitude
Time Zone
Elevation
Timestep in Hour
Name
Roughness
Thermal Resistance
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Surface Starting Position
Vertex Entry
Coordinate System
Timestep in Hour
Surface Const. Elements
Inside Conv Algorithm
Surface: Heat Transfer
Design Day
Material: Regular
Material: Regular-R
Material: Air
Material: Window Glass
Material: Window Gas
Construction
Inside Conv Algorithm
Surface Name
Surface Type
Construction Name
Zone Name
Outside Face Environment
Outside Face Env Object
Sun Exposure
Wind Exposure
View Factor to Ground
Num of Surface Vertex
Vertex Coordinate
Design Day Name
Max Dry Bulb Temperature
Daily Temperature Range
Humidity Ind. Conditions
Barometric Pressure
Wind Speed
Wind Direction
Sky Clearness
Rain Indicator
Snow Indicator
Day of Month
Month
Day Type
DLS Indicator
Humidity Indicating Type
Material: Air
Outside Conv Algorithm
Name
Thermal Resistance
Electric Equipment
Outside Conv Algorithm
Name
Zone Name
Schedule Name
Design Level Calc Method
Design Level
Fraction Latent
Fraction Radiant
Fraction Lost
Solution Algorithm
Material: Window Glass
Geometry
Solution Algorithm
Name
Optical Data Type
Solar Transmittance
Solar Reflect.: Front Side
Solar Reflect.: Back Side
Visible Transmittance
Visible Reflect.: Front Side
Visible Reflect.: Back Side
IR Transmittance
IR Emissivity: Front Side
IR Emissivity: Back Side
Conductivity
Zone
Surface Geometry
Surface: Ht Transfer
Surface: Ht Transfer: Sub
Surface: Shdi: Attached
Run Control
Run Control
Surface: Ht Transfer: Sub
Surface Name
Surface Type
Construction Name
Base Surface Name
View Factor to Ground
Multiplier
Num of Surface Vertex
Vertex Coordinate
Schedule
Schedule Type
Schedule: Compact
Schedule Type
Ground Temperatures
Internal Gains
Schedule Type Name
Range
Numeric Type
Monthly Grd Temp.
Material: Window Gas
People
Lights
Electric Equipment
Name
Gas Type
Thickness
Surface: Shd: Attached
Schedule: Compact
Surface Name
Base Surface Name
TransSchedShadowSurf
Num of Surface Vertex
Vertex Coordinate
Report Variable
Air Flow
Name
Schedule Type
Week Schedule
Day Schedule
Construction
Report Name
Reporting Frequency
Infiltration
Example of object links
Name
Outside Layer
Layer
Reports
Report Meter
Report Variable
Report Meter
Meter Name
Reporting Frequency
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

77. Attributes available in REVIT model
Simulation Parameters
Version
Run Period
Material: Regular
Zone
People
Infiltration
Version
Building
Timestep in Hour
Inside Conv. Algorithm
Outside Conv. Algorithm
Solution Algorithm
Run Control
Version Identifier
Run Period Start
Run Period End
Start Day
Use Weather File Holidays
Use Weather File DLS
Apply Weekend Rule
Weather File Rain Ind.
Weather File Snow Ind.
Name
Roughness
Thickness
Conductivity
Density
Specific Heat
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Zone Name
Relative North
X Origin
Y Origin
Z Origin
Type
Multiplier
Ceiling Height
Volume
Name
Zone Name
Num People Sch Name
Num People Calc Method
Num People
Fraction Radiant
Activity Level Sch Name
Name
Zone Name
SCHEDULE Name
Design Volume Flow Rate Calculation method
Design Volume Flow Rate
Flow per Zone Area
Flow per Ext Surface Area
Air Changes Per Hour
Constant Term Coefficient
Temp. Term Coefficient
Velocity Term Coefficient
Velocity Squared Term Coefficient
Building
Building Name
North Axis
Terrain
Loads Convr Tolerance
Temp. ConvrTolerance
Solar Distribution
Warm-up Days
Location
Lights
Location
Run Period
Location
Design Day
Ground Temperatures
Water Mains Temp.
Material: Regular-R
Surface Geometry
Name
Zone Name
Schedule Name
Design Level Calc Method
Lighting Level
Return Air Fraction
Fraction Radiant
Fraction Visible
Fraction Replaceable
End-Use Subcategory
Location Name
Latitude
Longitude
Time Zone
Elevation
Timestep in Hour
Name
Roughness
Thermal Resistance
Absorptance: Thermal
Absorptance: Solar
Absorptance: Visible
Surface Starting Position
Vertex Entry
Coordinate System
Timestep in Hour
Surface Const. Elements
Inside Conv Algorithm
Surface: Heat Transfer
Design Day
Material: Regular
Material: Regular-R
Material: Air
Material: Window Glass
Material: Window Gas
Construction
Inside Conv Algorithm
Surface Name
Surface Type
Construction Name
Zone Name
Outside Face Environment
Outside Face Env Object
Sun Exposure
Wind Exposure
View Factor to Ground
Num of Surface Vertex
Vertex Coordinate
Design Day Name
Max Dry Bulb Temperature
Daily Temperature Range
Humidity Ind. Conditions
Barometric Pressure
Wind Speed
Wind Direction
Sky Clearness
Rain Indicator
Snow Indicator
Day of Month
Month
Day Type
DLS Indicator
Humidity Indicating Type
Material: Air
Outside Conv Algorithm
Name
Thermal Resistance
Electric Equipment
Outside Conv Algorithm
Name
Zone Name
Schedule Name
Design Level Calc Method
Design Level
Fraction Latent
Fraction Radiant
Fraction Lost
Solution Algorithm
Material: Window Glass
Geometry
Solution Algorithm
Name
Optical Data Type
Solar Transmittance
Solar Reflect.: Front Side
Solar Reflect.: Back Side
Visible Transmittance
Visible Reflect.: Front Side
Visible Reflect.: Back Side
IR Transmittance
IR Emissivity: Front Side
IR Emissivity: Back Side
Conductivity
Zone
Surface Geometry
Surface: Ht Transfer
Surface: Ht Transfer: Sub
Surface: Shdi: Attached
Run Control
Run Control
Surface: Ht Transfer: Sub
Surface Name
Surface Type
Construction Name
Base Surface Name
View Factor to Ground
Multiplier
Num of Surface Vertex
Vertex Coordinate
Schedule
Schedule Type
Schedule: Compact
Schedule Type
Ground Temperatures
Internal Gains
Schedule Type Name
Range
Numeric Type
Monthly Grd Temp.
Material: Window Gas
People
Lights
Electric Equipment
Name
Gas Type
Thickness
Surface: Shd: Attached
Schedule: Compact
Surface Name
Base Surface Name
TransSchedShadowSurf
Num of Surface Vertex
Vertex Coordinate
Report Variable
Air Flow
Name
Schedule Type
Week Schedule
Day Schedule
Construction
Report Name
Reporting Frequency
Infiltration
Attributes with values obtainable from Revit model
Name
Outside Layer
Layer
Reports
Report Meter
Report Variable
Report Meter
Meter Name
Reporting Frequency
Attributes available in REVIT model
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

78. Design
Sizing Parameters
Node List
Plant Condenser Control
Air Primary Loop
SAM List
Zone Equip. List
Sizing Parameters
Zone Sizing
System Sizing
Plant Sizing
Sizing Factor
Time Steps in Averaging Win.
Node List Name
Node_ID
PlantOperationSchemeName
Control Scheme
Control Scheme Name
Control Scheme Schedule
Primary Air Loop Name
Name: Controller List
Name: SAM List
Primary Air Design Vol. FR
Air Loop Branch List Name
ReturnAir AirLoop Inlet Node
ZoneEquipGroup Outlet Node
SupplyAirPath ZEG InletNodes
AirLoop Outlet Node
Name
SAM Type
SAM Name
Name
Zone Equipment Type
Type Name
Zone Sizing
Branch List
SAM: Scheduled
ControlledZone Equip.Config.
NodeBranchManagement
Name of a zone
Cooling Design Sup. Air Temp.
Heating Design Sup. Air Temp.
Cooling Design Sup. Air HumR
Heating Design Sup. Air HumR
Outside Air Method
Outside Air Flow per Person
Outside Air Flow p. Zone Area
Outside Air Flow per Zone
Zone Sizing Factor
CoolingDesign Air Flow Meth.
HeatingDesign Air Flow Meth.
Branch List Name
Branch Name
Cooling Load Rangebased Op
Name
Schedule Name
Zone Name
List Name: Zone Equipment
Zone Air Inlet Node(s)
Zone Air Exhaust Node(s)
Zone Air Node Name
Zone Return Air Node Name
Node List
Branch List
Connector List
Branch
Pipe
Name
Load Range Lower Limit
Load Range Upper Limit
Priority Control Equip List Nm.
Connector List
Controller List
SAM: Low Temp. Turn Off
Connector List Name
Type of Connector
Name of Connector
Name
Sensor Node
Temperature
Applicability Schedule Name
Heating Load Rangebased Op
Name
Controller Type
Controller Name
Plant Condenser Loops
Air Distribution Unit
Branch
Name
Load Range Lower Limit
Load Range Upper Limit
Priority Control Equip List Nm.
Plant Loop
Air Distribution Unit Name
AirDistUnit Outlet NodeName
System Component Type
Component Name
Air Loop Equipment List
Plant Condenser Control
Branch Name
Maximum Branch Flow Rate
Comp Type
Comp Name
Comp Inlet Node Name
Comp Outlet Node Name
Comp Branch Control Type
Plant Sizing
Name
KEY—System Component
Component Name
SPM: Scheduled
Plant Operation Schemes
Cooling Load Range-based Op
Heating Load Range-based Op
Plant Equipment List
Plant Equipment List
Name of a Plant Loop
Loop Type
Design Loop Exit Temperature
Design Loop Delta T
Name
Control Variable
Schedule Name
Name of the set point Node
Equip List Name
KEY—Plant Equip
Equip Name
Outside Air System
Single Duct: VAV: Reheat
Plant Condenser Flow Ctrl
System Sizing
Pipe
Name
Name: Controller List
Name of Air Loop Equip List
Name of a SAM List
Name of the System
System Available Schedule
Damper Air Outlet Node
Unit Air Inlet Node
Maximum Air Flow Rate
Zone Minimum Air Flow Fraction
Control node
Reheat Component Object
Name of Reheat Component
Max Reheat Water Flow
Min Reheat Water Flow
Unit Air Outlet Node
Convergence Tolerance
Damper Heating Action
SPM: Mixed Air
Splitter
Mixer
NameofAir Primary Loop Obj.
Type of Load to Size on
Design (min) Outside A.V. FR.
Min System Air Flow Rate
Preheat Design Temperature
Preheat Design Humidity Rt
Precool Design Temperature
Precool Design Humidity Rt
Cen.Cool Design Sup.AirTemp
Cen.Heat Design Sup.AirTemp
Sizing Option
Cooling 100% Outside Air
Heating 100% Outside Air
Cen.CoolDesg Sup.Air.Hum.Rt
Cen.HeatDesg Sup.Air.Hum.Rt
Cooling Design Air Flow Meth.
Cooling Design Air Flow Rate
Pipe Name
Inlet Node Name
Outlet Node Name
Splitter
Name
Control Variable
Reference SP Node Name
Fan Inlet Node Name
Fan Outlet Node Name
Name of the Set Point Node
Air Distribution
SplitterName
Inlet Branch Name
Outlet Branch Name
Outside Air Node
Air Primary Loop
Controller List
Air Loop Equipment List
Outside Air System
Outside Air Node
Outside Air Inlet Node List
Outside Air Mixer
Node Name
Height Above Ground
Plant Loop
Mixer
Plant Loop Name
Fluid Type
Plant Op. Scheme List Name
Loop Temp. SP Node Name
Maximum Loop Temperature
Minimum Loop Temperature
Maximum Loop Vol. FlowRate
Minimum Loop Vol. FlowRate
Plant Side Inlet Node Name
Plant Side Outlet Node Name
Plant Side Branch List Name
Plant Side Connector List Nm.
DemandSide Inlet NodeNm.
DemandSide Outlet NodeNm.
DemandSide Branch List Nm.
DemandSide Con. List Nm.
Load Distribution Scheme
System Available Manager List
Outside Air Inlet Node List
MixerName
Outlet Branch Name
Inlet Branch Name
Node Name
Controller: Simple
Outside Air Mixer
Name
Control Variable
Action
Actuator variable
Control_Node
Actuator_Node
Contr. Convergence Tolerance
Max Actuated Flow
Min Actuated Flow
System Availability Managers
Name
Mixed_Air_Node
Outside_Air_Stream_Node
Relief_Air_Stream_Node
Return_Air_Stream_Node
SAM List
SAM: Scheduled
SAM: Low Temp. Turn Off
Set Point Managers
SPM: Scheduled
SPM: Mixed Air
Controller: Outside Air
Controllers
Name
Economizer Choice
ReturnAir TempLimit
ReturnAir EnthalpyLimit
Lockout
Minimum Limit
Control_Node
Actuated_Node
Min outside air flow rate
Max outside air flow rate
Temperature Limit
Temperature lower limit
Relief_Air_Outlet_Node
Return_Air_Node
Min Outside Air Sch Name
Controller: Simple
Controller: Outside Air
Going back to the exhaustive idf list of attributes (case system 8). This 2 pages list HVAC objects and attributes.
Zone Equipment
Controlled Zone Equip. Config.
Zone Equip. List
Air Distribution Unit
Air Distribution Equipment
Single Duct: VAV: Reheat
Color Key
Class
Leaf
Convention : Class attributes might be other classes. Leaf is used here to refer to attributes that require values that do not reference other objects. Conceptually, a model is complete once all leaves(typically numerical or Boolean) are acquired.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang

79. Zone Ctrls and Thermostats
Zone Control: Thermostatic
Zone Supply Air Path
Boiler: Simple
Pump: Variable Speed
Coil: Water: Cooling
Fan: Simple: Variable Volume
Zone Control: Thermostatic
Single Heating Setpoint
Single Cooling Setpoint
Dual Setpoint with Deadband
Thermostat Name
Zone Name
Control Type Schedule Name
Control Type
Control Type Name
Supply Air Path name
Supply Air Path Inlet Node
Key: System Component Type
Component Name
Boiler Name
Fuel Type
Nominal Capacity
Theoretical Boiler Efficiency
Design Water Outlet Temp
Max Design Boiler Water FR
Minimum Part Load Ratio
Maximum Part Load Ratio
Opt Part Load Ratio
Coefficient
Boiler_Water_Inlet_Node
Boiler_Water_Outlet_Node
Temp Upper Limit Water Outlet
Boiler Flow Mode
Pump Name
Inlet_Node
Outlet_Node
Rated Volumetric Flow Rate
Rated Pump Head
Rated Power Consumption
Motor Efficiency
Fraction of Motor Inefficiencies to Fluid Stream
Coefficient
Min Flow Rate
Pump Control Type
Pump Flow Rate Schedule
Coil Name
Available Schedule
Design Water Flow Rate of Coil
Design Air Volume Flow Rate
Design Inlet Water Temp
Design Inlet Air Temp
Design Outlet Air Temp
Design Inlet Air Humidity Rt
Design Outlet Air Humidity Rt
Coil_Water_Inlet_Node
Coil_Water_Outlet_Node
Coil_Air_Inlet_Node
Coil_Air_Outlet_Node
Type of Analysis
Heat Exchanger Configuration
Fan Name
Available Schedule
Fan Total Efficiency
Delta Pressure
Max Flow Rate
Min Flow Rate
Motor Efficiency
Motor In Airstream Fraction
Fan Coefficienct
Fan_Inlet_Node
Fan_Outlet_Node
Air Path
Zone Return Air Path
Single Heating Setpoint
Zone Supply Air Path
Zone Return Air Path
Zone Return Plenum
Zone Splitter
Return Air Path name
Return Air Path Inlet Node
Key: System Component Type
Component Name
Name
Setpoint Temp. Sch. Name
Single Cooling Setpoint
Plant Equipment
Zone Return Plenum
Name
Setpoint Temp. Sch. Name
Boiler: Simple
Chiller: Electric
Zone Plenum name
Zone name
Zone Node name
Outlet_Node
Inlet_Node
Chiller: Electric
Coil: Water: Simple Heating
DualSetPoint with Deadband
Pumps
Chiller Name
Condenser Type
Nominal Capacity
COP
Plant_Side_Inlet_Node
Plant_Side_Outlet_Node
Condenser Side_Inlet_Node
CondenserSide_Outlet_Node
Minimum Part Load Ratio
Maximum Part Load Ratio
Opt Part Load Ratio
Temp Design Condenser Inlet
Temp Rise Coefficient
Temp Design Evap Outlet
Design Evap Vol Water FR
Coefficient
Temp Lower Limit Evap Outlet
Chiller Flow Mode
Coil Name
Available Schedule
UA of the Coil
Max Water Flow Rate of Coil
Coil_Water_Inlet_Node
Coil_Water_Outlet_Node
Coil_Air_Inlet_Node
Coil_Air_Outlet_Node
Performance Input Method
Nominal Capacity
Design Inlet Water Temp
Design Inlet Air Temp
Design Outlet Water Temp
Design Outlet Air Temp
Name
Heating SP Temp. Sch. Name
Cooling SP Temp. Sch. Name
Pump: Variable Speed
Zone Splitter
Coils
Splitter name
Inlet_Node
Outlet_Node
Coil: Water: Cooling
Coil: Water: Simple Heating
Fans
Fan: Simple: Variable Volume
Color Key
Class
Leaf
Convention : Class attributes might be other classes. Leaf is used here to refer to attributes that require values that do not reference other objects. Conceptually, a model is complete once all leaves(typically numerical or Boolean) are acquired.
Sustainable Evaluation of Buildings – T. Biswas, Y.C. Huang & T.S. Wang