中国核心期刊scene

中国核心期刊scene

1、受理国家发明专利25项，代表性（10项）如下：（1） 一种应用于复杂地层数字制图的筛分方法，发明专利，授权，专利号：ZL200810028151.2；（2） 一种应用于岩土工程建模的三角网格构建方法，发明专利，授权，专利号：ZL200810028351.8；（3） 一种多功能岩石三轴试验加载系统，发明专利，授权，专利号：ZL200910036624.8；（4） 一种能源自采集与供能系统，实用新型，授权，专利号：ZL200820046924.5；（5） 一种低成本超级运算系统， 实用新型，授权，专利号：ZL200820046916.0；（6） 一种岩土细观力学试验的三轴可调显微观察系统，发明专利，公开实审，申请号：200910036622.9；（7） 一种基于移动设备的无线预警分析系统及其在安全预警平台的应用，发明专利，申请号：200810030147.x；（8） 一种三棱柱体三维地层剖分方法及开挖土方估算方法，发明专利，申请号：200810028150.8；（9） 一种基于摄动-光纤光栅耦合方法的工程岩土体稳定性监测技术，发明专利，申请号：200910039246.9；（10）一种盾构下穿已建隧道的最佳掘进速度控制方法，发明专利，申请号：201010245667.X。2、取得中国版权保护中心软件著作权16项，代表性（10项）如下：（11）2009，长大海底隧道与道路复合结构远程智能监测系统（TRCS-RIMS），中国版权保护中心软件著作权，No.2010SR007607；（12）2009，岩土工程信息仿真与三维开挖分析系统（3D_GIS-EAS），中国版权保护中心软件著作权，No.2010SR007605；（13）2007，基于结构面的三维地层块体构造系统（3DSBS），中国版权保护中心软件著作权，No. 2007SR13681；（14）2006，三维地质体及基坑三维开挖计算系统（3D-GECS），中国版权保护中心软件著作权登记，No. 2006SR12502；（15）2006，三维场景构造系统（3D-Scene），中国版权保护中心软件著作权登记，No.2006SR04519；（16）2006，基于突变论的软土地基填土稳定性分析与判别系统（SFSAJS），中国版权保护中心软件著作权登记，No.2006SR08324；（17）2005，复杂岩土条件下重大工程典型安全问题数字化预警系统（MP－DSWS），中国版权保护中心软件著作权登记，No.2005SR09445；（18）2005，边坡滑动面随机优化搜索与非线性稳定性分析系统（SSNAS），中国版权保护中心软件著作权登记，No.2005SR03786；（19）2005，碎石桩软土复合地基承载力和沉降计算分析系统（CFBSAS），中国版权保护中心软件著作权登记，No.2005SR09444；（20）2005，重大工程复杂地层数字化制图系统（MP-CSDMS），中国版权保护中心软件著作权登记，No. 2005SR01885。发表论文150余篇，其中SCI/EI收录50余篇，代表性论文（10篇）：周翠英，陈恒，朱凤贤，基于渐进演化的高边坡非线性动力学预警研究，岩石力学与工程，2008，27(4): 818-824，EI；周翠英，张乐民，岩石变形破坏的熵突变过程与破坏判据，岩土力学， 2007，28(12): 2506-2510，EI；周翠英，陈恒，朱凤贤，边坡演化的非线性时间序列多元混沌判别，地球科学，2008，33(3):393-398，EI；刘镇，周翠英*，房明，隧道变形失稳过程的非线性动力学分析与破坏判据研究，岩土力学，核心期刊，2010，31（12）：3887-3893，EI；周翠英，牟春梅，软土破裂面的微观结构特征与强度的关系，岩土工程学报，2005，27（10）：1136-1141，EI。

高新波的论文成果

Souleymane Balla-Arabé, X.-B. Gao. A Fast and Robust Level Set Method for Image Segmentation Using Fuzzy Clustering and Lattice Boltzmann Method. IEEE Trans. on Systems, Man and Cybernetics Part B: Cybernetics (IEEE TSMC B), 2013. In PressK.-B. Zhang, X.-B. Gao, et al. Learning Local and Non-Local Priors for Single Image Super-resolution. IEEE Trans. Image Processing (IEEE TIP), Vol.21, No,11, pp.4544-4556, 2012.L.-L. An, X.-B. Gao, et al. Robust Reversible Watermarking via Clustering and Enhanced Pixel-wise Masking. IEEE Trans. Image Processing (IEEE TIP), Vol.21, No.8, pp.3589-3611, 2012.Y. Su, X.-B. Gao, et al. Multivariate Multi-linear Regression. IEEE Trans. on Systems, Man and Cybernetics Part B: Cybernetics (IEEE SMC B), Vol.42, No.6, pp.1560-1573, Dec. 2012.X.-B. Gao, K. Zhang, et al. Image Super-Resolution with Sparse Neighbor em[ant]bedding. IEEE Trans. Image Processing (IEEE TIP), Vol.21, No.7, pp.3149-3205, 2012.Y. Su, Y. Fu, X.-B Gao, Q. Tian. Discriminant Learning through Multiple Principal Angles for Visual Recognition. IEEE Trans. on Image Processing (IEEE TIP), Vol.21, No.3, pp.1381-1390, 2012.X.-B Gao, K.-B. Zhang, et al. Joint Learning for Single Image Super-resolution via Coupled Constraint. IEEE Trans. on Image Processing (IEEE TIP), Vol.21, No.2, pp.469-490, 2012.C.-N. Tian, G. Fan, X.-B. Gao, Q. Tian. Multi-view Face Recognition: From TensorFace to V-TensorFace and K-TensorFace. IEEE Trans. on Systems, Man and Cybernetics Part B: Cybernetics (IEEE TSMC B). Vol.42, No.2, pp.320-333, 2012.X.-B. Gao, N.-N. Wang, et al. Face Sketch-Photo Synthesis and Retrieval Using Sparse Representation. IEEE Trans. on Circuits Systems for Video technology (IEEE TCSVT), Vol.22, No.8, pp.1213-1226, 2012X.-B. Gao, X. M. Wang, et al. Supervised Gaussian Process Latent Variable Model for Dimensionality Reduction. IEEE Trans. on System, Man, and Cybernetics, Part B: Cybernetics (IEEE TSMC B), Vol.41, No.2, pp.518 525, April 2011.X.-B. Gao, B. Wang, et al. A Relay Level Set Method for Automatic Image Segmentation. IEEE Trans. on System, Man, and Cybernetics, Part B: Cybernetics (IEEE TSMC B), Vol.41, No.2, pp.42 434, April 2011.X.-B. Gao, L. L. An, et al. Lossless Data em[ant]bedding Using Generalized Statistical Quantity Histogram. IEEE Trans. on Circuits Systems for Video Technology (IEEE TCSVT), Vol.21, No.8, pp.1061 1070, 2011.K.-B. Zhang, X.-B. Gao, et al. Partially Supervised Neighbor em[ant]bedding for Example based Image Super resolution. IEEE Journal of Selected Topics in Signal Processing, Vol.5, No.5, pp.230 239, 2011.X.-B. Gao, J. Chen, et al. Multi sensor Centralized Fusion without Measurement Noise Covariance by Variational Bayesian Approximation. IEEE Trans. on Aerospace and Electronic Systems (IEEE TAES), Vol.47, No.1, pp.718 722, 2011.X.-B. Gao, Q. Wang, et al. Zernike Moment based Image Super Resolution. IEEE Trans. on Image Processing (IEEE TIP), Vol. 20, No.10, pp.2738 2747, 2011.X.-B. Gao, C. Deng, et al. Geometric Distortion Insensitive Image Watermarking in Affine Covariant Regions. IEEE Trans. on System, Man and Cybernetics, Part C: Applications and Reviews (IEEE TSMC C), Vol.40, No.3, pp.278 286, 2010.X.-B. Gao, Y. Su, et al. A Review of Active Appearance Models. IEEE Trans. on System, Man, and Cybernetics, Part C: Applications and Reviews (IEEE TSMC C), Vol.40, No.2, pp.145 158, 2010.X.-B. Gao, Y. Wang, et al. On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection. IEEE Trans. on Information Technology in Biomedicine (IEEE TITB), Vol.14, No.2, pp.266 273, 2010.B. Wang, X.-B. Gao, et al. A Unified Tensor Level Set for Image Segmentation. IEEE Trans. on System, Man, and Cybernetics, Part B: Cybernetics (IEEE TSMC B), Vol. 40, No.3, pp.857 867, 2010.X.-B. Wang, Z. Li, P. C. Xu, Y. Y. Xu, X.-B. Gao. Spectrum Sharing in Cognitive Radio Networks: An Auction based Approach. IEEE Trans. on Systems, Man and Cybernetics Part B: Cybernetics (IEEE TSMC B), Vol.40, No.3, pp.587 596, June 2010.C. H. Hu, X. B. Wang, Z. C. Yang, J. F. Zhang, Y. Y. Xu, X.-B. Gao. A Geometry Study on the Capacity of Wireless Networks via Percolation. IEEE Trans. on Communications (IEEE TC), Vol.58, No.10, pp.2916 2925, 2010.X.-B. Gao, W. Lu, et al. Image Quality Assessment Based on Multiscale Geometric Analysis. IEEE Trans. on Image Processing (IEEE TIP), Vol.18, No.7, pp.1409 1423, 2009.D. Tao, X. Li, W. Lu, X.-B. Gao. Reduced reference IQA in Contourlet Domain. IEEE Trans. on System, Man, and Cybernetics, Part B: Cybernetics (IEEE TSMC B), Vol.39, No.6, pp.1623 1627, 2009.X.-B. Gao, J. Zhong, J. Li, C. Tian. Face Sketch Synthesis Algorithm Based on E HMM and Selective Ensemble. IEEE Trans. on Circuits and Systems for Video Technology (IEEE TCSVT), Vol.18, No.4, pp.487 496, 2008.X.-B. Gao and X. Tang. Unsupervised Video Shot Segmentation and Model free Anchorperson Detection for News Video Story Parsing. IEEE Trans. on Circuits Systems for Video Technology (IEEE TCSVT), Vol. 12, no. 9, pp.765 776, 2002.X. Tang, X.-B. Gao, J. Z. Liu and H. Zhang. A Spatial temporal Approach for Video Caption Detection and Recognition. IEEE Trans. on Neural Networks (IEEE TNN), Vol.13, No. 4, pp. 961 971, 2002.Z. X. Niu, X.-B. Gao, Q. Tian. Real World Trajectory Extraction for Attack Pattern Analysis in Soccer Video. Pattern Recognition, Vol.45, No.5, pp.1937 1947, 2012.X.-B. Gao, X. Wang, et al. Transfer Latent Variable Model Learning Based on Divergence Analysis. Pattern Recognition (Elsevier), Vol.44, No.10 11, pp.2358 2366, 2011.Y. Wang, D. Tao, X.-B. Gao. Feature em[ant]bedded vector valued contour based level set method with relaxed shape constraint for mammographic mass segmentation. Pattern Recognition (Elsevier), Vol.44, No.9, pp.1903 1915, 2011.X.-B. Gao, B. Xiao, et al. Image categorization: graph edit distance + edge direction histogram. Pattern Recognition (Elsevier). Vol.41, No.10, pp.3179 3191, October, 2008.X.-B. Gao, et al. Shot based Video Retrieval with Optical Flow Tensor and HMM. Pattern Recognition Letters (Elsevier), Vol.30, No.2, pp.140 147, 2009.X. Chen, X.-B. Gao*, et al. 3D Reconstruction of Light Flux Distribution on Arbitrary Surfaces from 2D Multi photographic Images. Optics Express, Vol,18, No.19, pp.19876 19893, 2010.X. Chen, X.-B. Gao, et al. A study of photon propagation in free space based on hybrid radiosity radiance theorem. Optics Express, Vol.17, No.18, pp.16266 16280, 2009X.-B. Gao, R. Fu, et al. Image Segmentation for Aurora Index Extraction. Computer Vision and Image Understanding, Vol.115, No.3, pp.390 402, 2011.X.-B. Gao, Y. M. Yang, et al. Discriminative optical flow tensor for video semantic analysis. Computer Vision and Image Understanding, Vol.113, No. 3, pp.372 383, 2009.K. Zhang, X.-B. Gao, et al. Multi scale Dictionary for Single Image Super resolution. Proceedings of Computer Vision and Pattern Recognition (CVPR2012), Providence, Rhode Island, 16 21 June, 2012, USA.Z. Niu, G. Hua, X.-B. Gao and Q. Tian. Context Aware Topic Model for Scene Recognition. Proceedings of Computer Vision and Pattern Recognition (CVPR2012), Providence, Rhode Island, 16 21 June, 2012, USA.L. H. He, D. Tao, X. Li, X.-B. Gao. Sparse Representation for Blind Image Quality Assessment. Proceedings of Computer Vision and Pattern Recognition (CVPR2012), Providence, Rhode Island, 16 21 June, 2012, USA.Z. X. Niu, G. Hua, X.-B. Gao, Q. Tian. Spatial DiscLDA for Visual Recognition. Proceedings of Computer Vision and Pattern Recognition (CVPR2011), 21 23 June, 2011, Colorado, USA.Z. X. Niu, Q. Tian, X.-B. Gao. Real World Trajectory Extraction for Attack Pattern Analysis in Soccer Video. Proceedings of the ACM International Conference on Multimedia (ACM MM2010), pp.635 638, 25 29 October 2010, Firenze, Italy.W. Ning, J. Li, J. Li, X.-B. Gao. 3D Medical Image Processing and Analyzing System. Demo session of Asian Conference on Computer Vision (ACCV2009), Xian, China, 2009.其它核心期刊及国际会议论文200余篇，其中SCI检索100余篇，EI检索200余篇。

谁能帮我找一篇3000字左右的有关道路工程方面的英文资料或者学术论文并翻译成中文，还要有作者，出版社===

　　沥青玛蹄脂碎石混合料是一种由沥青、纤维稳定剂、矿粉及少量的细集料组成的沥青玛蹄脂，填充间断级配的粗集料骨架间隙而形成的眼挤型密实结构混合料。SMA改性沥青及SMA路面是一种新型的路面结构，改性沥青及SMA混合料冷却后非常坚硬，强度高。本文结合上海城市外环线(浦东段)环南一大道工程的施工，谈谈如何对改性沥青及SMA路面的施工进行控制。

　　一、工程综述

　　本工程北起张扬路立交东至环东一大道，路幅红线宽度100米，为城市Ⅰ级主干道，双向8车道，总长2387米。车行道结构形式为沥青柔性路面，结构层组成为路基+15厘米砂砾垫层+40厘米二灰碎石基层+15厘米三层式沥青混凝土面层。面层组合如下：表面层为改性沥青玛蹄脂碎石混合料（SMA-16）4厘米；中面层为中粒式改性沥青砼（LH-25）6厘米；底面层为粗粒式改性沥青砼（CLH-35）6厘米；下封层1厘米。

　　二、改性沥青施工质量控制的难点

　　1.改性沥青混合料粘度较高，各工序的施工温度均比普通沥青混合料的施工温度要求高，贮存、运输期间的降温不应超过10℃，生产厂至施工现场的距离较长，上海交通繁忙，气候变化大，混合料贮藏温度控制难。

　　2.沥青路面施工质量与摊铺机械的性能密切相关，沥青摊铺机械型号多种，性能不一。如何选择性能良好的施工机械，是工程质量控制的重点。

　　3.沥青摊铺时，必须均匀、连续，工人素质必须高，要能正确判断摊铺界面。

　　三、SMA沥青的拌合及施工

　　1.沥青混合料拌合。由于SMA与普通密级配沥青砼最大不同之处是SMA为间断级配，粗集料粒径单一、量多、细集料很少，矿粉用量多。细集料包括石屑和砂一共只需15%左右，给混合料的供料拌和带来不少困难。为此，料斗、料仓要重新安排，增加粒径为5～10毫米的骨料仓，以保证冷料数量，而细集料用量很少，冷料仓门开启很少，供料过程中要保持细集料干燥，以保证细集料顺利供料。主皮带把粗配料送入滚洞，通过燃烧器对骨料加热，有热电偶检测料温，自动调节燃烧器的风油比，使骨料温度达到190℃～200℃。热料经提升机进入振动筛，把热料按目标配合比的规格要求分筛到不同的热料仓（筛网尺寸可根据要求更换），有计算机控制各热料仓拉门，按输入的生产配合比自动配料、计量，由于SMA粗料粒径单一，细料很少，热料可能会发生粗集料仓经常不足（亏料），而细集料仓经常溢仓的不正常情况，控制室的操作人员不可调整放料的数量，使SMA的配合比不准。然后将木质素纤维加入到搅拌锅与骨料共同进行干拌，再添加经计算机控配比控制计量的石粉及沥青，拌和后，完成成品料的生产。SMA的干拌时间为4秒～5秒，湿拌30秒～45秒。

　　各种材料加热温度控制：沥青加热温度160℃～165℃，现场制作温度165℃～170℃，加工最高温度175℃，集料加热温度190℃～200℃，混合料出场温度175℃～185℃，混合料最高温度（废弃温度）195℃，摊铺温度不低于160℃，初始开始温度不低于150℃，复压最低温度不低于130℃，碾压终了温度不低于130℃，开放交通温度不高于60℃。

　　2.运输。由于SMA沥青混合料的沥青玛蹄脂的粘性较大，运输车的车厢底部要涂较多的油水混合物，而且为了防止运输车表面混合料结成硬壳，运输车运输过程中必须加盖油布，同时车量要适当增加。

　　3.摊铺。沥青必须缓慢、均匀连续不间断地摊铺。摊铺过程中，不得随意变换速度或中途停顿，摊铺速度应根据拌和机产量，施工机械配套情况及摊铺层厚度、宽度确定。摊铺速度为3.5米/分钟。

　　4.碾压。碾压过程是面层施工中的重要环节，碾压SMA的八字方针为“紧跟、碾压、高频、低幅”，并合理地选择压路机组合方式及碾压步骤。

　　5.接缝。

　　（1）纵缝：根据本工程特点，我单位在沥青混合料摊铺过程中采用一台德国产ABG423摊铺机并排摊铺，采用此方式可以一次整幅摊铺，纵缝热接提高了路面的平整度，美化了路面的视觉效果。

　　（2）横缝：SMA路面的接缝处理要比普通混合料困难一些，因此，摊铺时在边部设置挡板，也可以在沥青SMA层每天施工完工后，在其尚未冷却之前，即切割好，并利用水将接缝冲洗干净。第二天涂刷粘层油，即进行摊铺新混合料。

　　沥青混合料施工中容易产生的问题：

　　（1）过碾压：由于SMA路面的集料嵌挤作用，压实程度不大，压实度较易达到，但是随着碾压遍数的增加，集料不断地往下走，玛蹄脂一点点地向上浮，造成构造深度减小。在碾压过程中，特别注意表面构造保持在1～1.5毫米，以便有适宜的构造深度。

　　（2）出现油斑：SMA路面通车后出现油斑也是常见的一种病害，这是由于SMA的纤维拌合不均匀造成的。因此在拌合时，要严格控制纤维的投放数量和投放时间，并延长干拌时间，确保纤维拌合均匀。还要注意储藏期间纤维干燥，防止纤维受潮成团。

　　（3）碾压成型温度不够高是常见的毛病。SMA在130℃碾压的效果就很差了。在低温时碾压，容易出现不平整。在行车过程中出现车辙，是因为碾压不足造成的。

　　Asphalt of Stone Mastic is a mixture of asphalt from the fiber stabilizing agent, slag and a small amount of the fine aggregate composed of lipid Mastic Asphalt, filled with intermittent level of coarse aggregate skeleton space formed by squeezing eye-density Structure mixture. SMA modified asphalt road and SMA is a new type of pavement, and SMA modified asphalt mixture cooled very hard, high strength. Based in Shanghai, Link (Pudong), a South Central Avenue construction project, talk about how the modified asphalt road construction and SMA control.

　　I. Review of projects

　　The project has publicized the North Road interchange east to Central Avenue East a road width of 100 meters pieces of red, as cities Ⅰ-level main road, two-way lane 8, the chief of 2,387 meters. Carriageway of the form of flexible asphalt pavement, structural layer of gravel for the roadbed +15 cm layer of grey rubble +40 cm grassroots +15 cm three asphalt concrete surface. Surface composition is as follows: for the modified asphalt surface layer of Stone Mastic mixture (SMA-16) 4 centimeters of the surface of tablets for-modified asphalt concrete (LH-25) 6 centimeters for the bottom layer Coarse-modified asphalt concrete (CLH-35) 6 centimeters under the closure of one centimeter.

　　Second, the modified asphalt construction quality control difficult

　　1. Modified asphalt mixture viscosity higher, the process of construction than the general temperature of the asphalt mixture of high-temperature requirements, storage, transportation during the cooling should not exceed 10 ℃, manufacturing plant to the construction site of the long distance Shanghai heavy traffic, climate change, mixture storage temperature control difficult.

　　2. Asphalt road paving machinery and construction quality is closely related to the performance, a variety of types of asphalt paving machinery, mixed performance. How to choose the good performance of construction machinery, is the focus of project quality control.

　　3. Asphalt paving, it must uniform, continuous, workers must be of high quality, must be able to correct judgement paving interface.

　　3, SMA asphalt mixing and Construction

　　1. Asphalt mixture mixing. As with the SMA Miji with ordinary asphalt concrete is the biggest difference between the SMA for intermittent graded, coarse aggregate single particle size, quantity, fine aggregate small amount of slag and more. Stone Chip fine aggregate and sand, including a total of only around 15 percent, to the mixture of materials for mixing brought about many difficulties. To this end, the hopper, silo to re-arrangements, to increase the diameter of 5 to 10 mm aggregate positions, to ensure that the expected number of cold, fine aggregate amount of very few, very few cold silo door open for materials to maintain the course of Fine Aggregate drying, to ensure smooth for fine aggregate materials. The main ingredients into the thick belt of the roll-through on aggregate heating burner, a thermocouple detection feed temperature and automatically adjust the oil burner than the wind so that the aggregate temperature reaches 190 ℃ ~ 200 ℃. Heat expected to enter the elevator shaker, thermal materials on target to meet the specifications than the sub-screen to a different thermal bin (screen size can be replaced upon request), a computer control of the Silo flamenco, according to enter the Auto production mix ingredients, measuring, as a single SMA rough material particle size, small little material, thermal materials may be rough sets in less than regular hopper (deficit expected), while small-hopper often overflow warehouse is not the normal situation, control Room operators can not adjust the amount of discharge, the SMA not allowed to mix. Lignin fiber and then added to stir the pot with the aggregate common dry mix, then add the computer-control measures the ratio of powder and asphalt, mixing, the expected completion of the finished product. SMA mix the dry time of four seconds to five seconds, 30 seconds wet mix to 45 seconds.

　　Heating temperature control of various materials: asphalt temperature 160 ℃ ~ 165 ℃, the temperature at the scene produced 165 ℃ ~ 170 ℃, the highest temperature of processing 175 ℃, aggregate heating temperature 190 ℃ ~ 200 ℃, the temperature mixture out 175 ℃ ~ 185 ℃ , The highest temperature mixture (abandoned temperature) 195 ℃, paving the temperature of not less than 160 ℃, the initial starting temperature of not less than 150 ℃, repressing the lowest temperature of not less than 130 ℃, RCC ended temperature of not less than 130 ℃ Open transport temperature no higher than 60 ℃.

　　2. Transportation. As SMA asphalt mixture of asphalt Mastic more viscous resin, the carrier at the bottom of the compartment to the oil-water mixture Tu more, and in order to prevent the carrier surface mixture form a hard shell, the carrier during transport to be decked Tarpaulin, it is necessary to appropriately increase the volume of cars.

　　3. Paver. Asphalt must be slow, even for uninterrupted paver. Paving process, not free to transform the speed or stop half-way, paving the speed of production should be based on mixing, matching and construction machinery paving thickness, width identified. Paving a speed of 3.5 m / min.

　　4. RCC. RCC is the process of construction of an important link in the RCC SMA eight-character principle for the "keeping up, rolling, high-frequency, low-rate" and a reasonable choice roller composition and RCC steps.

　　5. Joints.

　　(1) longitudinal seam: According to the engineering features, I unit in the asphalt paving mixture used in the course of a Germany-ABG423 paver paving side-by-side, this method can be a whole paver, longitudinal seam to increase the heat The smoothness of the road and beautify the road of visual effects.

　　(2) Joints: SMA road handling the joints than ordinary mixture difficult, therefore, paving set at the edge of the baffle, can also SMA layer of asphalt a day after the completion of construction, not yet in its cooling, That is, cutting good, and joint use of water will be clean. The next day Tushua viscosity of the oil, that is paving the new mixture.

　　 asphalt mixture construction of the easy questions:

　　(1) the RCC: As the road aggregate SMA embedded crowded, not degree of compaction, the degree of compaction easier to achieve, but with the RCC to increase the number of times, the aggregate continue to go down, Mastic A little bit of fat to the floating, resulting in reduced structural depth. RCC in the process, with particular attention to the surface structure remained at 1 to 1.5 millimeters in order to have appropriate structural depth.

　　(2) in the oil spot: SMA opening of the road after the oil spot is a common disease, which is due to the SMA fiber caused by uneven mixing. Therefore, in mixing, it is necessary to strictly control the number of fibers running and running time and extended dry mix, to ensure uniform mixing fibers. We must pay attention to storage during the dry fiber to prevent the fibers exposed to moisture into college.

　　(3) RCC forming a high enough temperature is a common illnesses. SMA in the 130 ℃ RCC effect on the poor. In the low temperature at RCC, is not prone to the formation. In the lane in the process of rutting, is inadequate because of the RCC.
　　你可以试下这个《road and bridge》——美刊
　　可以看一些行内的核心期刊，比如《中国公路学报》《力学》等，也可以看看各个学校的学报，比如《同济大学学报》《哈工大学报》《长安大学学报》等，或者有些教材也可以作为参考文献。