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Computing light reflection from rough surfaces is an important topic in computer graphics. Reflection models developed based on geometric optics fail to capture wave effects such as diffraction and interference, while existing models based on physical optics approximations give erroneous predictions under many circumstances (e.g. when multiple scattering from the surface cannot be ignored). We present a scalable 3D full-wave simulator for computing reference solutions to surface scattering problems, which can be used to evaluate and guide the development of approximate models for rendering. We investigate the range of validity for some existing wave optics based reflection models; our results confirm these models for low-roughness surfaces but also show that prior rendering methods do not accurately predict the scattering behavior of some types of surfaces. Our simulator is based on the boundary element method (BEM) and accelerated using the adaptive integral method (AIM), and is implemented to execute on modern GPUs. We demonstrate the simulator on domains up to 60 × 60 × 10 wavelengths, involving surface samples with significant height variations. Furthermore, we propose a new system for efficiently computing BRDF values for large numbers of incident and outgoing directions at once, by combining small simulations to characterize larger areas. Our simulator will be released as an open-source toolkit for computing surface scattering.
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Surface Alfven Wave Reflection as the Slow Wind Formation Mechanism in the Alfven Wave Driven Solar Atmosphere Model
The heating near the coronal hole boundary is included into the AWSoM model via the Alfven wave interaction with the boundary between the closed and open field lines. Although the excessive heating on the Alfven surface wave is possible (Evans et al 2012), we chose to parameterize the surface effect in terms of excessive nonlinear reflection proportional to the transverse gradient of density. The efficiency of such reflection is derived analytically and compared with the solar wind observation data at 1 AU.
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- Award ID(s):
- 1836821
- PAR ID:
- 10220235
- Date Published:
- Journal Name:
- 2020 Fall AGU Meeting
- Issue:
- Paper SH032-07
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
