关键词：
Pavement engineering;Inductive charging pavement system;Inductive power transfer;Charging efficiency optimization;Sustainability
摘要：
Sustainable transportation development presents a significant challenge for the current transportation industry. Electric vehicles (EVs) have emerged as a key solution to accelerate this transition, but issues surrounding limited driving range and long charging times must be addressed. Inductive power transfer (IPT) systems provide a promising innovative approach by enabling contactless and continuous wireless power transfer (WPT) to EVs in motion. This paper provided a comprehensive review of the latest advancements, challenges, and opportunities in inductive charging pavement technology. It summarized foundational research on IPT systems, including key principles, technological developments, and applications across various fields. Composition, operation principles, and performance parameters of IPT systems were detailed. Strategies for controlling magnetic leakage, optimizing coil structure parameters, and electrical parameters of the IPT system were explored to mitigate the impact of electromagnetic losses on charging efficiency. Key considerations regarding pavement material selection, structural design and the impacts on efficiency were discussed. The potential for inductive charging pavements to enable energy conservation, curb environmental effects, and offer economic benefits was highlighted. Overall, with continued advances in areas such as coil packaging materials, intelligent monitoring technologies and power transfer optimization, inductive charging pavements can play a vital role in facilitating large-scale EVs adoption and realizing greenhouse gas (GHG) emission reductions in the transportation sector.
摘要：
This study aims at developing an efficient and accurate methodology to estimate the resilient modulus of subgrade soils. First, a new resilient modulus model incorporating stress dependence and moisture dependence was proposed. Second, prediction models were developed to conveniently and accurately determine model parameters of SWCC and resilient modulus model. In order to characterise the moisture dependence of subgrade soils, the matric suction was added into the proposed model. The matric suction was measured by the pressure plate test and the soil-water characteristic curve (SWCC) was used to determine the matric suction value at any given moisture contents. In order to develop prediction models for model parameters of SWCC and resilient modulus model, the laboratory experiments and multiple regression analysis were conducted on 22 soil samples. A series of performance-related soil properties were measured and used to develop the coefficients prediction models. The developed coefficients prediction models using the performance-related soil properties have high R-squared values and were validated by comparing the measured and predicted values of resilient modulus. Therefore, when the basic physical properties of soils were obtained, the resilient modulus can be predicted for the subgrade soils at any given matric suctions and stress states.
通讯机构：
[Liang, Chenghao] C;Cent South Univ Forestry & Technol, Sch Civil Engn, Changsha 410004, Peoples R China.
摘要：
<jats:p>Using recycled aggregate from construction and demolition (C&D) wastes as a construction material is a potential method for solving the disposal of C&D wastes, which can reduce the exploitation of natural aggregate. In this study, extensive laboratory tests were carried out to investigate the reliability of the C&D wastes used as road base material. Meanwhile, the gradation design and the dominant aggregate size range were considered, and a physical disposal method was proposed to enhance the structural performance of the recycled material by replacing the skeleton of the recycled aggregate (RA) with high-quality limestone. The test results showed that (1) given the high absorbency and fragility of C&D wastes, its RA was not enough to provide the strength and stability required by the base; (2) the compaction characteristics of the RA are quite different from that of the limestone aggregate, but the final compaction effect is basically the same; (3) the replacement treatment proposed in this study is an effective approach to improve the performance of the recycled granular base because the breakage rate decreased by at least 28.2% and the mechanical properties increased by approximately 50% compared with that of the untreated specimen; and (4) when the limestone content reached 75%, the California bearing ratio and the resilient modulus of the graded B specimen exceeded 120% and 200 MPa, respectively, satisfying the pavement requirement in medium traffic.</jats:p>
摘要：
Although the same compaction degree is achieved in practice, asphalt mixture samples prepared by different compaction methods often have different mechanical properties. In this paper, the air void content (AV) and distribution of aggregates and asphalt mortar in the process of asphalt mixture compaction are traced to capture the meso structural change characteristics of asphalt mixture during compaction. Using the discrete element method (DEM), a numerical technique is developed to simulate the laboratory compaction by taking into account the critical aggregate size and boundary effect. First, the critical aggregate size (CAS) is determined by the 2D and 3D binary particle assembly. Second, DEM simulations of both the Marshall impact compaction (MIC) and static compaction (SC) methods are conducted by the mass-wall and servo boundary, respectively. Third, the applicability of the 2D model is demonstrated through laboratory tests and numerical calculations. Finally, the distribution of aggregates and asphalt mortar are displayed and analyzed. The results show that the variation of CAS presents linear growth approximately with the increase of coarse particle size, less affected by the boundary. The primary control sieve (PCS) is applicable to separate the coarse and fine particles in the 3D assembly, but the CAS is around 0.195 for the 2D assembly, which is obviously less than the PCS. It is verified by two compaction methods and two mixture gradations that the DEM simulation is an effective way to evaluating the compacting effects of the compaction process. By double-sided hammering, coarse aggregates are moved to accumulate more closely, thus the coordination number at the bottom increases. Although a dense specimen can be achieved by compaction method, the size distribution of particles is still uneven in horizontal direction, since the position of large size particles (>16 mm) is difficult to be changed in the compaction process. (C) 2019 Elsevier Ltd. All rights reserved.
期刊：
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2019年12(4):1120-1133 ISSN：1939-1404
通讯作者：
Xiao, Yuelong
作者机构：
[Xiao, Yuelong; Li, Jia; Wu, Lixin; Miao, Zelang] Cent S Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China.;[Xiao, Yuelong; Li, Jia; Wu, Lixin; Miao, Zelang] Cent S Univ, Minist Educ, Key Lab Metallogen Predict Nonferrous Met & Geol, Changsha 410083, Hunan, Peoples R China.;[Shi, Wenzhong] Hong Kong Polytech Univ, Dept Land Surveying & Geoinformat, Hong Kong 999077, Peoples R China.;[He, Yueguang] Changsha Univ Sci Thchnol, Sch Traff & Transportat Engn, Changsha 410083, Hunan, Peoples R China.;[Gamba, Paolo] Univ Pavia, Dept Ind & Informat Engn, I-27100 Pavia, Italy.
通讯机构：
[Xiao, Yuelong] C;Cent S Univ, Sch Geosci & Infophys, Changsha 410083, Hunan, Peoples R China.
关键词：
Impervious surface;one class classification (OCC);open data;satellite image
摘要：
Supervised learning is vital to classify impervious surface from satellite images. Despite its effectiveness, the training samples need to be provided manually, which is time consuming and labor intensive, or even impractical when classifying satellite images at the regional/global scale. This study, therefore, sets out to automatically generate training samples from open data, based on the fact that cities and urban areas are nowadays full of individual geo-referenced data, such as social network data. The proposed method consists of automatic generation of training samples based on a filtering process of open data, satellite image pre-processing, and impervious surface detection using one class classification (OCC). Two Landsat-8 Operational Land Imager images were selected to test the proposed method. The results show that the proposed method is effective in impervious surface with good classification accuracy. The findings in this study shine new light on the applications of open data in remote sensing.
