ABSTRACT
As bitumen oxidizes, material stiffening and embrittlement occur, and bitumen eventually cracks. The use of anti-oxidants, such as lignin, could be used to delay oxidative aging and to extend the lifetime of asphalt pavements. In this study, the chemical and rheological effect of lignin on bitumen was evaluated by using a single dosage organsolv lignin (10 wt.% dosage). A pressure aging vessel (PAV) was used to simulate the long-term aging process after performing the standard short-term aging procedure, and the lignin-modified bituminous binders were characterized by an environmental scanning electron microscope (ESEM), Fourier-transform infrared (FTIR) spectroscopy, and a dynamic shear rheometer (DSR). From the ESEM results, the uniform microstructure was observed, indicating that the addition of lignin did not affect the worm structure of bitumen. Based on the FTIR test results, lignin-modified bitumen showed that a lower number of carbonyl and sulfoxide compounds were generated after aging than for neat bitumen. Based on the linear amplitude sweep (LAS) results, the addition of lignin slightly reduced the fatigue life of bitumen. From the frequency sweep results, it showed that lignin in bitumen acts as a modifier since the physical interaction between lignin and bitumen predominantly affects the material rheology. Overall, lignin could be a promising anti-oxidant due to its economic and environmental benefits.
ABSTRACT
Plant leaf movement is induced by some combination of different external and internal stimuli. Detailed geometric characterization of such movement is expected to improve understanding of these mechanisms. A metric high-quality, non-invasive and innovative sensor system to analyze plant movement is Terrestrial LiDAR (TLiDAR). This technique has an active sensor and is, therefore, independent of light conditions, able to obtain accurate high spatial and temporal resolution point clouds. In this study, a movement parameterization approach of leaf plants based on TLiDAR is introduced. For this purpose, two Calathea roseopicta plants were scanned in an indoor environment during 2 full-days, 1 day in natural light conditions and the other in darkness. The methodology to estimate leaf movement is based on segmenting individual leaves using an octree-based 3D-grid and monitoring the changes in their orientation by Principal Component Analysis. Additionally, canopy variations of the plant as a whole were characterized by a convex-hull approach. As a result, 9 leaves in plant 1 and 11 leaves in plant 2 were automatically detected with a global accuracy of 93.57 and 87.34%, respectively, compared to a manual detection. Regarding plant 1, in natural light conditions, the displacement average of the leaves between 7.00 a.m. and 12.30 p.m. was 3.67 cm as estimated using so-called deviation maps. The maximum displacement was 7.92 cm. In addition, the orientation changes of each leaf within a day were analyzed. The maximum variation in the vertical angle was 69.6° from 12.30 to 6.00 p.m. In darkness, the displacements were smaller and showed a different orientation pattern. The canopy volume of plant 1 changed more in the morning (4.42 dm3) than in the afternoon (2.57 dm3). The results of plant 2 largely confirmed the results of the first plant and were added to check the robustness of the methodology. The results show how to quantify leaf orientation variation and leaf movements along a day at mm accuracy in different light conditions. This confirms the feasibility of the proposed methodology to robustly analyse leaf movements.
