Mo Tian
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Mo Tian has a total of 23 co-authors. Here are the top co-authors by number of shared publications:
Daniel Small
4 shared publications- Yu Yao
Arizona State University
4 shared publications - Neel Desai
Arizona State Univ., Tempe, AZ (United States)
3 shared publications - Randolph Brost
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
3 shared publications - Zubair Ebne Rafique
Arizona State University
3 shared publications - David G. Novick
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2 shared publications
Latest Publications
- 5 March 2026
- Published by Elsevier in Solar Energy
- Vol. 310
A polarimetry-based field-deployable non-interruptive mirror soiling detection method
- 5 March 2026
- Published by Elsevier in Solar Energy
- Vol. 310
A polarimetry-based field-deployable non-interruptive mirror soiling detection method
- 3 December 2025
- Published by Elsevier in Solar Energy
- Vol. 304
Heliostat optical error inspection with polarimetric imaging drone
- 3 December 2025
- Published by Elsevier in Solar Energy
- Vol. 304
Heliostat optical error inspection with polarimetric imaging drone
- Open Access
- 19 January 2024
- Published by TIB Open Publishing in SolarPACES Conference Proceedings
- Vol. 1
Field Deployable Mirror Soiling Detection Based on Polarimetric Imaging
Heliostat mirror soiling is one of the significant factors for reduced optical efficiency of Concentrated Solar Power (CSP) fields. However, it remains challenging to determine the mirror soiling patterns across the large area of the CSP field. Here we propose a fast and field deployable inspection method to measure the heliostat mirror soiling levels based on polarization images in regular daylight settings without additional light sources. Under sunny and clear sky conditions, we have demonstrated accurate measurement of reflection efficiency (error ~1%) for mirrors with different soiling levels.
- 19 January 2024
- Published by TIB Open Publishing in SolarPACES Conference Proceedings
- Vol. 1
Open AccessField Deployable Mirror Soiling Detection Based on Polarimetric Imaging
Heliostat mirror soiling is one of the significant factors for reduced optical efficiency of Concentrated Solar Power (CSP) fields. However, it remains challenging to determine the mirror soiling patterns across the large area of the CSP field. Here we propose a fast and field deployable inspection method to measure the heliostat mirror soiling levels based on polarization images in regular daylight settings without additional light sources. Under sunny and clear sky conditions, we have demonstrated accurate measurement of reflection efficiency (error ~1%) for mirrors with different soiling levels.
- Open Access
- 20 December 2023
- Published by TIB Open Publishing in SolarPACES Conference Proceedings
- Vol. 1
Toward Autonomous Field Inspection of CSP Collectors With a Polarimetric Imaging Drone
We developed a polarimetric imaging drone to perform field inspections of heliostats and carried out field tests at Sandia’s National Solar Thermal Test Facility (NSTTF). The preliminary results show that Degree of Linear Polarization (DOLP) and Angle of Polarization (AOP) images greatly enhanced the edge detection results compared with the conventional visible images, supporting fast and accurate detection of heliostat mirror edges and cracks. The system holds the promise to enable future automated detection of heliostats optical errors and mirror defects.
- 20 December 2023
- Published by TIB Open Publishing in SolarPACES Conference Proceedings
- Vol. 1
Open AccessToward Autonomous Field Inspection of CSP Collectors With a Polarimetric Imaging Drone
We developed a polarimetric imaging drone to perform field inspections of heliostats and carried out field tests at Sandia’s National Solar Thermal Test Facility (NSTTF). The preliminary results show that Degree of Linear Polarization (DOLP) and Angle of Polarization (AOP) images greatly enhanced the edge detection results compared with the conventional visible images, supporting fast and accurate detection of heliostat mirror edges and cracks. The system holds the promise to enable future automated detection of heliostats optical errors and mirror defects.