# Radiance and Lumen Micro Differences

Does anyone know of any documents/ papers that discuss the differences
between the accuracy of Radiance and Lumen Micro, and the underlying
causes (such as algorithms, geometric capabilities, input flexibility
etc)? I am trying to explain this to someone and would like to read up
the topic.

Thanks.

I can't comment on Lumen Micro. Radiance however has undergone
many validation tests. For an overview of a daylight validation
study:

http://www.iesd.dmu.ac.uk/~jm/pdfs/BRE_IDMP.pdf

Radiance proved to be capable of very accurate predictions.

For a rather more tortuous description of that study, see
Chapters 3 & 4 here:

http://www.iesd.dmu.ac.uk/~jm/zxcv-thesis/

Regards,

-John

···

-----------------------------------------------
Dr. John Mardaljevic
Senior Research Fellow
Institute of Energy and Sustainable Development
De Montfort University
The Gateway
Leicester
LE1 9BH, UK
+44 (0) 116 257 7972
+44 (0) 116 257 7981 (fax)

In general, Radiance is more accurate than other programs if you make extensive use of small patches with mkillum, set the -av parameter to a reasonable value, and use the following parameters:
-ab 5
-as 1024
-ar 5000
-ds .05

If you use -ab 1 instead of 5, your values are typically half of what they should be. If you use -ab 3, they might be 30% too low.

Martin

Martin Moeck, Ph.D., Assistant Professor, ASHRAE, IESNA
The Pennsylvania State University
Department of Architectural Engineering
104 Engineering A
University Park, PA 16802
e-mail: [email protected]
Tel +1 814 863 3555
Fax +1 814 863 4789
http://www.engr.psu.edu/ae/faculty/moeck.htm

Martin,

In general, Radiance is more accurate than other programs if you make
extensive use of small patches with mkillum, set the -av parameter to a
reasonable value, and use the following parameters:
-ab 5
-as 1024
-ar 5000
-ds .05

If you use -ab 1 instead of 5, your values are typically half of what they
should be. If you use -ab 3, they might be 30% too low.

That ar setting is rather on the high side. Also, the high accuracy
that was achieved with the BRE-IDMP dataset relied only on the ambient
calculation - no mkillum. Some tests I carried out at the time (95-97)
showed that accurate pure ambient tended to be faster than comparably
accurate mkillum. For both cases the parameters were gradually refined
until the predictions converged to the measured values (method described
in Chap 6 of RwR). Radiance has changed a bit in the meantime, but I'd
wager that pure ambient is still an effective way to achieve high accuracy.
And maybe even more efficient too. Perhaps I should repeat the tests using
In any case, I'd stick with the method of testing for convergence (Ch 6 RwR).
The "optimum" parameter combination will depend on the scene, and convergence
testing by progressive refinement is the quickest way to get there.
It's the most reliable method too.

-John

···

-----------------------------------------------
Dr. John Mardaljevic
Senior Research Fellow
Institute of Energy and Sustainable Development
De Montfort University
The Gateway
Leicester
LE1 9BH, UK
+44 (0) 116 257 7972
+44 (0) 116 257 7981 (fax)

John:

I agree in general. I was thinking about complex museums with 2000 m2 ands lots of windows and mullions when I recommended my parameters. That's just the museum work that I am exposed to. But ever since 1990, we did tests at Siemens Lighting and it was always the same story: 5 -6 ambient bounces will get you there, even for simpler rooms. I have never found exceptions.

Regards

Martin

···

-----Original Message-----
From: John Mardaljevic [mailto:[email protected]]
Sent: Mon 9/27/2004 11:47 AM
To: [email protected]
Cc:

Martin,

> In general, Radiance is more accurate than other programs if you make
> extensive use of small patches with mkillum, set the -av parameter to a
> reasonable value, and use the following parameters:
> -ab 5
> -as 1024
> -ar 5000
> -ds .05

> If you use -ab 1 instead of 5, your values are typically half of what they
> should be. If you use -ab 3, they might be 30% too low.

That ar setting is rather on the high side. Also, the high accuracy
that was achieved with the BRE-IDMP dataset relied only on the ambient
calculation - no mkillum. Some tests I carried out at the time (95-97)
showed that accurate pure ambient tended to be faster than comparably
accurate mkillum. For both cases the parameters were gradually refined
until the predictions converged to the measured values (method described
in Chap 6 of RwR). Radiance has changed a bit in the meantime, but I'd
wager that pure ambient is still an effective way to achieve high accuracy.
And maybe even more efficient too. Perhaps I should repeat the tests using
In any case, I'd stick with the method of testing for convergence (Ch 6 RwR).
The "optimum" parameter combination will depend on the scene, and convergence
testing by progressive refinement is the quickest way to get there.
It's the most reliable method too.

-John

-----------------------------------------------
Dr. John Mardaljevic
Senior Research Fellow
Institute of Energy and Sustainable Development
De Montfort University
The Gateway
Leicester
LE1 9BH, UK
+44 (0) 116 257 7972
+44 (0) 116 257 7981 (fax)

[email protected]
http://www.iesd.dmu.ac.uk/~jm

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