1 辽宁工业大学土木建筑工程学院, 锦州 121001
2 中交路桥建设有限公司,北京 100024
3 浙大宁波理工学院土木建筑工程学院, 宁波 315100
为研究高温对混杂纤维混凝土(HFRC)残余强度与微观结构演变规律的影响, 测试了HFRC在不同温度作用后的基本力学性能, 借助扫描电子显微镜研究了纤维-水泥浆体界面的微观结构, 并利用BP神经网络对HFRC在不同温度作用后的抗压强度进行了预测。结果表明: 纤维的混杂效应显著改善了混凝土的耐高温性能, 高温后HFRC的抗压强度和劈裂抗拉强度均高于素混凝土; 当纤维素纤维和玄武岩纤维体积掺量均为0.15%时, HFRC的抗压强度和劈裂抗拉强度均达到最大值; HFRC内部结构密实, 玄武岩纤维填充在孔隙处且与基体的黏结较好, 有效抑制了裂缝的扩展; 基于神经网络的预测数据与试验数据吻合, BP神经网络较好地预测了高温后HFRC的抗压强度。
混杂纤维混凝土 玄武岩纤维 纤维素纤维 力学性能 微观结构 BP神经网络 强度预测 hybrid fiber reinforced concrete basalt fiber cellulose fiber mechanical property microstructure BP neural network strength prediction
1 辽宁工业大学土木建筑工程学院，锦州 121001
2 中国电建集团西北勘测设计研究院有限公司，西安 710100
为研究固体废弃物取代混凝土原材料的适用性及对混凝土性能的影响，对16组粉煤灰-硅锰渣再生混凝土试块进行正交试验，研究当粉煤灰体积取代胶凝材料、硅锰渣体积取代砂、再生骨料质量取代粗骨料时不同取代量对混凝土坍落度、立方体抗压强度和劈裂抗拉强度的影响。结果表明：当粉煤灰取代量为40%(体积分数)时，混凝土坍落度提高率最大，为14.5%，立方体抗压强度和劈裂抗拉强度均降低，降低率分别为7.2%、22.8%；硅锰渣的取代会降低混凝土坍落度，当硅锰渣取代量为80%(体积分数)时，立方体抗压强度和劈裂抗拉强度的降低率最小，分别为0.5%、11.5%；再生骨料的取代会降低混凝土坍落度，当再生骨料取代量为100%(质量分数)时，立方体抗压强度的降低率为1.9%，劈裂抗拉强度的降低率为12.4%。通过优化模型NSGM(1,4)对混凝土立方体抗压强度进行模型预测，模型模拟平均相对误差为0.542%，模型预测平均相对误差为2.727%。
混凝土 粉煤灰 硅锰渣 再生骨料 正交试验 坍落度 强度 concrete fly ash silicon manganese slag recycled aggregate orthogonal test slump strength
1 辽宁工业大学土木建筑工程学院, 锦州 121001
2 中国电建集团西北勘测设计研究院有限公司, 西安 710100
利用海水海砂替代淡水河砂制备混凝土不但能缓解土木工程行业对资源的消耗, 而且对于沿海城市及远海岛礁建设而言, 就地取材节约了大量的运输成本和时间成本, 因此, 对于海水海砂资源化利用的研究变得尤为重要。以海水海砂混凝土为研究对象, 通过对比国内外学者对海水海砂特性的研究, 综合分析了海水海砂混凝土力学性能以及干湿循环和冻融循环下耐久性能以及海水海砂混凝土与纤维增强聚合物(FRP)筋组合结构粘结性能的发展规律。最后对目前海水海砂混凝土研究成果进行了总结, 并对未来的研究内容提出了建议。
海水海砂混凝土 力学性能 干湿循环 冻融循环 FRP筋 侵蚀机理 seawater sea-sand concrete mechanical property dry-wet cycle freeze-thaw cycle FRP bar erosion mechanism
1 Department of Infrastructure Engineering, University of Melbourne, VIC 3010, Australia
2 School of Electrical and Computer Engineering, Royal Melbourne Institute Technology, VIC 3000, Australia
3 Higher Education-Primary Industy, NMIT and Melbourne Polytechnic, NMIT Epping Campus, Victoria 3076, Australia
4 Department of Electrical and Electronic Engineering, University of Melbourne, VIC 3010, Australia
红外与激光工程
2016, 45(9): 902002
1 School of Electrical and Computer Engineering, RMIT University, Australia
2 School of Electronic Science and Engineering,National University of Defense Technology, Changsha 410073, China
Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar (ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error. Effectiveness of the proposed method is also confirmed from real ISAR data experiments.
ISAR imaging ISAR imaging frame theory frame theory frame processing frame processing target rotation rate target rotation rate radar waveforms radar waveforms 红外与激光工程
2016, 45(3): 0302001
