[Radiance-general] BSDF xml into Radiance

[Daniel C. Glaser]

Dear Greg,
   Thank you for letting us know about the -c option.  I am going to try 
it with rtcontrib (sensors) and wanted to ask for advice on how to setup 
the points for averaging.  For example, if I choose 4 for -c, do I send 
in the same point 4 times or is there a heuristic for perturbing or 
regularly spacing these points for improving results?
   Thanks for creating this feature!

- Dan

On 7/25/2012 10:44 AM, Greg Ward wrote:
> Hi Lars,
>
> Andy probably is the right person to respond to this, but as he's on a vacation until the end of the month, I thought I'd offer a couple of comments (inline).
>
> Cheers,
> -Greg
>
>> From: "Lars O. Grobe" <grobe at gmx.net>
>> Date: July 25, 2012 1:18:42 AM PDT
>>
>> Hi Andy, hi list-subscribers,
>>
>> I just came across this recent message about the usability of the bsdf
>> material type with patch-based models of the sky including direct sun
>> and complex fenestration. To avoid misunderstandings, I will try a short
>> summary for others to comment on available options for annual
>> simulations with complex glazing:
>>
>>
>> 1) classic radiance tools (rpict, rtrace), complemented by mkillum to
>> relax ambient setting.
>>
>> Advantages: low noise, validated.
>>
>> Disadvantages: very slow for annual simulations, no support when
>> non-planar specular reflective surfaces are involved.
> More specifically, non-planar, specular reflectors run into trouble for insolation.  Cloudy skies or sunless skies are no problem.
>
>> 2) rtcontrib and patch-based model.
>>
>> Advantages: faster for annual simulations.
>>
>> Disadvantages: noise, nice images require high (slow) -ad and cannot be
>> optimized using mkillum, limitations about specular non-planar
>> reflectors apply.
> The accuracy of non-planar, specular reflectors is actually better than #1, but the results are somewhat noisy.  A new -c option to vwrays (coupled with the rtcontrib -c option) is a good way to reduce noise that is available in the latest HEAD.  This is a better way to reduce noise than increasing -ad, and less costly.
>
>> 3) rtcontrib and patch-based model, bsdf.
>>
>> Advantages: support for non-planar reflectors, should be slightly faster
>> than 2) as the fenestration system does not have to be traced internally
>> - did anyone compare?
>>
>> Disadvantages: still high -ad settings required leading to extended
>> rendering times and still no way to get mkillum in, tends to
>> underestimate direct sun (according Andy's message).
>>
>>
>> 4) three-phase-method.
>>
>> Advantages: very fast, can also be used with non-planar specular
>> reflectors as bsdf data is supported.
>>
>> Disadvantages: requires quite a lot of set-up work, e.g. subdivisions to
>> reflect external obstructions. Patches visible in the results,
>> fenestration geometry is not visible.
> Andy has proposed an improved annual simulation method, which we hope to work on next year, to remedy the direct solar sampling difficulties in the 3-phase method.  It should also alleviate problems with external facade geometry and reduce the need to subdivide windows.
>
>> 5) pmap.
>>
>> Advantages: can be used with non-planar reflectors and multi-peak
>> transmission.
>>
>> Disadvantages: unknown status (any news?), not integrated with rtcontrib
>> (contributions would need to be rendered manually).
>>
>>
>> So if I need a way to generate images with visible fenestration
>> geometry, the only reliable option would be 2), which requires very
>> hight settings for -ad and thud will still be rather time-consuming, if
>> noise is to be controlled.
>>
>> Cheers, Lars.
>>
>> On Tue, 2012-06-12 at 08:43 -0700, Andrew McNeil wrote:
>>
>>> Though I've found that the BSDF material doesn't work well for
>>> daylight coefficient based annual simulations (I'm assuming dds.bash
>>> is a dynamic daylight simulation script).  Putting the solar radiance
>>> into skypatches relies on probabilistic sampling to find patches
>>> containing the sun, and if you don't have much direct transmission
>>> from the direction of the sun, you aren't likely to find the sun.  Not
>>> finding the sun causes big errors.
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