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Smith, Braden James

Publications and source records attributed to Smith, Braden James.

Dual-Image Color Normalization to Enable High-Performance Concentrating Solar Optical Metrology

Concentrating Solar Power (CSP) requires precision mirrors, and these in turn require metrology systems to measure their optical slope. In this project we studied a color-based approach to the correspondence problem, which is the association of points on an optical target with their corresponding points seen in a reflection. This is a core problem in deflectometry-based metrology, and a color solution would enable important new capabilities. We modeled color as a vector in the [R,G,B] space measured by a digital camera, and explored a dual-image approach to compensate for inevitable changes in illumination color. Through a series of experiments including color target design and dual-image setups both indoors and outdoors, we collected reference/measurement image pairs for a variety of configurations and light conditions. We then analyzed the resulting image pairs by selecting example [R,G,B] pixels in the reference image, and seeking matching [R,G,B] pixels in the measurement image. Modulating a tolerance threshold enabled us to assess both match reliability and match ambiguity, and for some configurations, orthorectification enabled us to assess match accuracy. Using direct-direct imaging, we demonstrated color correspondence achieving average match accuracy values of 0.004 h, where h is the height of the color pattern. We found that wide-area two-dimensional and linear one-dimensional color targets outperformed hybrid linear/lateral gradient targets in the cases studied. Introducing a mirror degraded performance under our current techniques, and we did not have time to evaluate whether matches could be reliably achieved despite varying light conditions. Nonetheless, our results thus far are promising.

14 SOLAR ENERGY

Scene Reconstruction User Guide

These instructions show how to use the OpenCSP Scene Reconstruction application. Scene Reconstruction calculates the three-dimensional positions of Aruco markers placed around a scene using photogrammetry. This has multiple applications within OpenCSP; this document is referenced by multiple other OpenCSP documents.

97 MATHEMATICS AND COMPUTING

OpenCSP Camera Calibration: Document Version 1.0

This report provides instructions on how to perform an OpenCSP camera lens calibration, which characterizes the inherent distortion in camera-lens systems. This calibration is necessary for many OpenCSP photogrammetry calculations and should be performed individually for every new camera or after adjusting lens settings.

42 ENGINEERING

SOFAST 2.0 User Guide and Technical Description, Document Version 1.0

This report accompanies Sandia’s deflectometry tool, SOFAST 2.0, providing both a user guide and a basic technical description. SOFAST is a deflectometry tool used to measure surface slope maps of concentrating solar power (CSP) mirrors and collectors. The original SOFAST performed high-resolution measurement of a variety of CSP mirror types. SOFAST 2.0 is a completely new version, re-implemented in Python and including many extensions and improvements.

14 SOLAR ENERGY

OpenCSP Deflectometry Technical Description, Document Version 1.0

This document provides a technical description of algorithms used in the OpenCSP code repository that are common to deflectometry. This document is meant to be a technical reference that describes the internal algorithms of OpenCSP. An example program that uses these algorithms is SOFAST 2.0.

14 SOLAR ENERGY