LiQuID: Lighting Quality In Design
James Peng1, Ben Liao1, Daniel Glaser1, John Canny1, Ellen Yi-Luen Do2
1
2
University of California, Berkeley
University of Washington, Seattle
Primary contact address: jpeng9999@hotmail.com
Oftentimes, architects and lighting designers do not fully utilize natural daylight when
designing buildings and lighting systems. Buildings with artificial lighting systems are
simpler to design and analyze. However, doing so would forgo some of the ecological,
social, and economical benefits of daylight. Current simulation tools for predicting visual
quality and energy use of architectural lighting systems are not very informative or useful
when concerning the use of daylight. Photorealistic renderings produced by a number of
simulation systems are only relevant for a specific set of variables, including time,
season, and sky condition. For instance, the distribution, intensity, and angle of daylight
can change rapidly during the day. Also, lighting quality depends upon viewer direction
and location within a room, and current tools provide little assistance for managing
multiple viewpoints. Tools that aggregate these results do so only at the expense of
compromising fine-grained analysis details.
LiQuID is an analytical tool for evaluating a comprehensive set of lighting data to
account for the complex nature of daylight. The program is designed to generalize large
collections of lighting data by performing automatic classification, lighting quality
analysis, and a summary component. Automatic classification is a data-driven method for
identifying and organizing sets of data, based on similarities in light intensity and
distribution. Lighting quality analyses are based on the normative lighting characteristics
defined in industry standard handbooks (e.g.(Illuminating Engineering Society et al.
2000; Benya et al. 2001)). These sources contain guidelines on evaluating architectural
models for factors like direct glare and light distribution. A summary module integrates
with a user interface for a building designer to review.
LiQuID works in conjunction with a modeler, simulation program and visualization
toolkit. Initially, an architectural design is created with a modeler or CAD program. The
three-dimensional geometry is broken down into wall, ceiling, and floor surfaces.
Designers can also define viewpoints within the room to evaluate a viewer's actual
perspective. Next, a high quality simulation package (such as in (Ward 1994)) is used to
generate illuminance and luminance data for the given planes and viewpoints, for a
variety of temporal and sky conditions. After the lighting quality analysis, the
visualization toolkit displays the results of automatic classification and statistical
evaluation. This can enhance existing methods for display of daylight data (Cheng and
Pat-Yak Lee 2001; Glaser and Ubbelohde 2002; Papamichael 2002) to also include
statistical trends.
Through automatic classification, LiQuID detects the major patterns in shape and
intensity of lighting within the building design. Classification utilizes a k-means
algorithm, which takes large quantities of simulated lighting data and groups them into
clusters based on similar patterns. Within each cluster is the subset of all lighting data
most similar to one another. Instead of analyzing all the output from the simulation
program, these clusters can be examined for their normative lighting characteristics.
Examples include point-by-point analysis of lighting intensity and the comparison of
adjacent surfaces and perspectives for discontinuities. After classification and lighting
quality analysis, LiQuID can present the evaluation of the architectural model. Reports of
problematic lighting, such as high glare or low ambient lighting, are accompanied by
relevant information, such as frequency or the reasons for occurrence. In addition, the
program may give suggestions on improving the lighting quality of the model, like
installing shading devices to reduce glare.
By analyzing numerous lighting simulations across multiple variables, LiQuID will
extract useful lighting information from an architectural model. LiQuID aims to relieve
architects and lighting designers from the tedious work required to analyze countless
potential lighting situations. Also, it aims to remove some of the oversimplifications and
generalizations about daylight that are utilized when evaluating lighting systems.
Therefore by doing careful analysis of a comprehensive amount of simulations, LiQuID
aims to provide reliable, accurate and legible feedback to building designers to encourage
them to incorporate lighting, energy, and economic concerns of daylighting into their
designs.
REFERENCES:
Benya, J., L. Heschong, T. McGowan, N. Miller and F. Rubinstein, Eds. (2001).
Advanced Lighting Guidelines. White Salmon, WA, New Buildings Institute.
Cheng, N. and E. Pat-Yak Lee (2001). Depicting Daylighting: Types of Multiple Image
Display. Proceedings of the Association for Computer Aided Design in
Architecture (ACADIA '01), Buffalo, New York. 282-291
Glaser, D. and S. Ubbelohde (2002). "Techniques for Managing Planar Daylight Data."
Building and Environment 37(8-9): 825-831.
Illuminating Engineering Society, M. S. Rea and Illuminating Engineering Society of
North America (2000). The IESNA lighting handbook : reference & application.
New York, N.Y., Illuminating Engineering Society of North America.
Papamichael, K. (2002). A Web-based Virtual Lighting Simulator. Proceedings of the
Association for Computer Aided Design in Architecture (ACADIA '02), Pomona,
CA. 269-277
Ward, G. (1994). "The radiance lighting simulation system." Computer Graphics 28(7):
459-72.
LiQuID
Lighting Quality In Design
James Peng1, Ben Liao1, Daniel Glaser1
John Canny1, Ellen Yi-Luen Do2
1University
of California, Berkeley 2University of Washington, Seattle
http://iolanthe.cs.berkeley.edu/~peng
simulation tools for predicting visual quality and energy use of
Problem: Current
architectural lighting systems are not very informative or useful.
P1. Photorealistic images are easy to understand,
but only describe a single moment of time in
simulation space, thus requiring many images to
account for all possible conditions.
Jun 21st
9am
Sky Condition:
Clear
Dec 21st
9am
Dec 21st
12pm
Sky Condition:
Overcast
Sky Condition:
Clear
P2. Lighting quality also varies by viewer
perspective. Current tools provide little
assistance for selecting a comprehensive set of
viewpoints.
East View
N
South View
Sample Images from Lawrence Berkeley National Laboratory Virtual Lighting Simulator
Solution:
Automatic classification can help users quickly understand lighting
problems and characteristics of their architectural designs.
S1. Cluster the vast amounts of time-varying
lighting data according to normative lighting
characteristics (such as glare level or minimum
illuminance) to identify significant trends.
GROUP: very dim lighting
GROUP: fair lighting
S2. Create representative slices of the
architectural model based on automated and
user-specified conditions of location and viewer
perspective.
GROUP: high glare lighting
3D Model
Surface Lighting Data
Lighting
Configuration #3
Day: Dec 21
Time: 12:00 pm
Sky Condition:
clear
Surface Slices
Insert Viewpoints
Perspective Lighting Data
Perspective
Slices
1
1
Will require excessive electric lamps
to light most of the year
Efficient daylighting – saves
energy during springtime
These clusters were generated with LiQuID
2
Shading
devices
recommended for early
morning
2
Wall 1
Illuminance
-5 fc (min
- ...
Future:
We are currently:
• Prototyping interfaces to summarize
lighting
characteristics
and
suggest
recommendations
• Generating appropriate slices and views
• Refining normative lighting characteristics
• Integrating
with
existing
research
programs LightSketch and Scythe & Sew
• Testing user interface with professionals
Jan
Dec
9am
Low Ambient Lighting
- Winter: 66% Fall: 45%
- 9am: 55%
High Glare
- Summer: 55% Fall: 35%
12pm: 40% 3pm: 25%
Predicted Energy Usage
– 3 kw/ft2 (excessive)
Recommendation:
Install Lightshelf
on south window
6pm
Average Ambient
Lighting
- 10 footcandles
Conceptual sketch of LiQuID integrating with Scythe and Sew