Ran Tao
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Ran Tao has a total of 85 co-authors. Here are the top co-authors by number of shared publications:
- Gilles Lubineau
Mechanics of Composites for Energy and Mobility Lab, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
32 shared publications - Arief Yudhanto
Department of Mechanical Engineering Baylor University Waco Texas USA
8 shared publications - Ruslan Melentiev
Centre of Micro/Nano Manufacturing Technology (MNMT-Dublin), School of Mechanical & Materials Engineering, University College Dublin, Dublin 4, Ireland
7 shared publications Xiaole Li
7 shared publications- Marco Alfano
Dipartimento di Scienze e Metodi dell’Ingegneria, Università degli Studi di Modena e Reggio Emilia, Via Amendola 2, 42122 Reggio Emilia, Italy
5 shared publications - Sofia Teixeira de Freitas
Delft University of Technology
5 shared publications
Latest Publications
- Open Access
- 29 September 2026
- Published by Elsevier in Polymer Testing
- Vol. 163
Cure-dependent thermal-mechanical and mode I fracture behavior of a low-Tg bio-based epoxy
- 29 September 2026
- Published by Elsevier in Polymer Testing
- Vol. 163
Open AccessCure-dependent thermal-mechanical and mode I fracture behavior of a low-Tg bio-based epoxy
- Open Access
- 8 August 2026
- Published by Elsevier in Composites Part B: Engineering
- Vol. 326
2D bio-inspired reinforcement mesh for toughening composite bonded joints: Effect of orientation and adhesion patterning
- 8 August 2026
- Published by Elsevier in Composites Part B: Engineering
- Vol. 326
Open Access2D bio-inspired reinforcement mesh for toughening composite bonded joints: Effect of orientation and adhesion patterning
- Open Access
- 11 December 2025
- Published by Elsevier in Composites Part B: Engineering
- Vol. 312
Mode I toughening of bio-based epoxy adhesive through 3D-printed biomimetic reinforcements
- 11 December 2025
- Published by Elsevier in Composites Part B: Engineering
- Vol. 312
Open AccessMode I toughening of bio-based epoxy adhesive through 3D-printed biomimetic reinforcements
- Open Access
- 16 September 2025
- Published by Elsevier in Composites Science and Technology
- Vol. 272
Bio-inspired overlapping curl structures for toughening bio-based epoxy: A study on the fracture phenomena
- 16 September 2025
- Published by Elsevier in Composites Science and Technology
- Vol. 272
Open AccessBio-inspired overlapping curl structures for toughening bio-based epoxy: A study on the fracture phenomena
- Open Access
- 17 October 2024
- Published by Elsevier in Materials & Design
- Vol. 247
Biomimetic toughening design of 3D-printed polymeric structures: Enhancing toughness through sacrificial bonds and hidden lengths
- 17 October 2024
- Published by Elsevier in Materials & Design
- Vol. 247
Open AccessBiomimetic toughening design of 3D-printed polymeric structures: Enhancing toughness through sacrificial bonds and hidden lengths
- Open Access
- 21 February 2024
- Published by Elsevier in Journal of Materials Research and Technology
- Vol. 29, 4384-4393
Characterizing ABS–copper chemistry-dependent adhesion: From the atomic to macro level
- 21 February 2024
- Published by Elsevier in Journal of Materials Research and Technology
- Vol. 29, 4384-4393
Open AccessCharacterizing ABS–copper chemistry-dependent adhesion: From the atomic to macro level
- 1 August 2023
- Published by SPIE-Intl Soc Optical Eng
- Vol. 12747, 76-169
UNet++ for estimating physical parameters from Newton’s rings
Newton’s rings pattern is frequently encountered in optical interferometry, and by extracting the phase contained in it, the measured physical parameter information can be obtained. According to the purpose of point-to-point mapping of the image to be analyzed, a method based on UNet++ to extract the phase of Newton’s rings is proposed. Once the network training is completed, the continuous phase including the curvature radius and ring’s center coordinate can be directly predicted from a single Newton’s rings pattern immediately. The relative error of the curvature radius obtained by parameter fitting the phase is less than 0.83%, and the error of ring’s center coordinate is close to 0 pixel. In order to further improve the results of curvature radius estimation, the parameter estimation results obtained by UNet++ are taken as the initial value and corrected by the least-squares fitting method. Experimental results show that for the Newton’s rings pattern containing -5 dB Gaussian noise, the relative error of the corrected curvature radius is no higher than 0.31%.
- 1 August 2023
- Published by SPIE-Intl Soc Optical Eng
- Vol. 12747, 76-169
UNet++ for estimating physical parameters from Newton’s rings
Newton’s rings pattern is frequently encountered in optical interferometry, and by extracting the phase contained in it, the measured physical parameter information can be obtained. According to the purpose of point-to-point mapping of the image to be analyzed, a method based on UNet++ to extract the phase of Newton’s rings is proposed. Once the network training is completed, the continuous phase including the curvature radius and ring’s center coordinate can be directly predicted from a single Newton’s rings pattern immediately. The relative error of the curvature radius obtained by parameter fitting the phase is less than 0.83%, and the error of ring’s center coordinate is close to 0 pixel. In order to further improve the results of curvature radius estimation, the parameter estimation results obtained by UNet++ are taken as the initial value and corrected by the least-squares fitting method. Experimental results show that for the Newton’s rings pattern containing -5 dB Gaussian noise, the relative error of the corrected curvature radius is no higher than 0.31%.