Two issues exist in the convolutional neural network (CNN) used for asphalt pavement crack detection: balance between accuracy and complexity, and indistinct edges of cracks and asphalt pavement surface. Infrared thermography (IRT) could use the temperature difference between cracks and pavement surface to better distinguish cracks. This work aims to propose a robust crack detection method based on CNN and IRT. An open benchmark dataset was built for crack detection based on three types of images, including visible images, infrared images, and the fusion of visible and infrared images (in short, fusion image). The dataset also considers different conditions and periods, including single, multi, thin, and thick cracks; clean, rough, light, and dark backgrounds, and three periods in a day. Seven CNN segmentation models are trained and evaluated on this dataset. To keep a balance between accuracy and complexity, evaluation metrics (accuracy, and computational and model complexity) are used to have an overall evaluation of models rather than only the accuracy. The results show that the accuracy and predictions of the visible image and fusion image are almost identical for all models, which are much better than that of the infrared image. When the background is rough or cracks are similar to the background, the fusion image is a better choice for crack detection. Compared with the visible image, all segmentation models have a more stable performance for the fusion image. Among segmentation models, Feature Pyramid Networks (FPN) could be the best model because of its high accuracy and low complexity.

3D printing, also known as additive manufacturing, holds immense potential for rapid prototyping and customized production of functional health‐related devices. With advancements in polymer chemistry and biomedical engineering, polymeric biomaterials have become integral to 3D‐printed biomedical applications. However, there still exists a bottleneck in the compatibility of polymeric biomaterials with different 3D printing methods, as well as intrinsic challenges such as limited printing resolution and rates. Therefore, this review aims to introduce the current state‐of‐the‐art in 3D‐printed functional polymeric health‐related devices. It begins with an overview of the landscape of 3D printing techniques, followed by an examination of commonly used polymeric biomaterials. Subsequently, examples of 3D‐printed biomedical devices are provided and classified into categories such as biosensors, bioactuators, soft robotics, energy storage systems, self‐powered devices, and data science in bioplotting. The emphasis is on exploring the current capabilities of 3D printing in manufacturing polymeric biomaterials into desired geometries that facilitate device functionality and studying the reasons for material choice. Finally, an outlook with challenges and possible improvements in the near future is presented, projecting the contribution of general 3D printing and polymeric biomaterials in the field of healthcare.

The effect of basalt fiber on asphalt binder and mastic at low temperatures is investigated in this study. Basalt fibers are dispersed into the asphalt binder and mastic specimens to prepare the fiber-reinforced binding materials. The fiber-reinforced specimens are tested using the direct tension test and a newly developed fatigue test procedure, which is able to directly apply cyclic tensile loading to the asphalt binder and mastic specimens. The reinforcement effects of basalt fiber to the fatigue resistance of asphalt binding materials are evaluated. The direct tension test results show that with an appropriate content, the tensile strength of the asphalt binder is improved with the use of basalt fiber. The basalt fiber also restrains the axial strain and increases the stiffness of both the asphalt binder and mastic specimens. The fatigue test results indicate that the fatigue life of both asphalt binder and mastic specimens is significantly improved by the basalt fibers. The effect of basalt f...

Piezoelectric energy harvesting in pavement is an advanced energy saving technology. It is carried out by laying the piezoelectric material in the pavement structure and converting the mechanical energy into electrical energy. The current energy harvester has difficulty meeting the complex requirements of pavements. In order to develop the pavement piezoelectric energy harvesting technology, in this paper, a stacked mode for a piezoelectric energy harvester is designed. The computer-controlled pressure testing machine (WHY-2000, Shanghai Hualong Test Instruments Corporation, Shanghai, China) was used to test the compressive property and the one–third-scaled accelerated instrument Model Mobile Load Simulator (MMLS-1/3) was used to test the fatigue properties of the piezoelectric transducer. Results showed that the designed piezoelectric transducer could bear loadings up to 150 kN, which can meet road traffic loading requirements. The piezoelectric properties of the transducer remain good after 100,000 cyclic loadings. The indoor laboratory test and the on-site test show that the piezoelectric transducer can work in real pavement in actual traffic conditions. The open circuit voltage can reach 280 V, which can provide enough electricity for sensing systems in the pavements. In all, the proposed new piezoelectric transducer provides a promising future for green energy use in the pavement industry.

Fundamental understanding of micro-mechanical behaviors in bitumen, including phase separation, micro-friction, micro-abrasion, etc., can help the pavement engineers better understand the bitumen mechanical performances at macroscale. Recent researches show that the microstructure evolution in bitumen will directly affect its surface structure and micro-mechanical performance. In this study, the bitumen microstructure and micro-mechanical behaviors are studied using Atomic Force Microscopy (AFM) experiments, Phase Dynamics Theory and Molecular Dynamics (MD) Simulation. The AFM experiment results show that different phase-structure will occur at the surface of the bitumen samples under certain thermodynamic conditions at microscale. The phenomenon can be explained using the phase dynamics theory, where the effects of stability parameter and temperature on bitumen microstructure and micro-mechanical behavior are studied combined with MD Simulation. Simulation results show that the saturates phase, in contrast to the naphthene aromatics phase, plays a major role in bitumen micro-mechanical behavior. A high stress zone occurs at the interface between the saturates phase and the naphthene aromatics phase, which may form discontinuities that further affect the bitumen frictional performance.