A New Technique of High-performance and Fast Tensioning Prestressed Anchorage CableEI北大核心

Research purposes: The large-span transition section tunnel of the Badaling Great Wall station on the Beijing-Zhangjiakou high-speed railway with the maximum excavation width of 32.7 m, and the largest excavation area of 494.4 m 2 , is the world's biggest traffic tunnel in the world with the largest excavation width and excavation area, which has difficult construction and high security risks. The initial support system of tunnel is mainly realized by prestressed bolt, prestressed cable and shotcrete. After test, anchor cable tension using the traditional anchor cable construction technology can't meet the design requirements, at the same time, it takes about 30 days to achieve prestressed tensioning. Therefore, we need to study the high-performance fast tensioning prestressed anchor cable technology, to effectively control surrounding rock deformation, to ensure the safety of construction, improve construction efficiency. Research conclusions:(1) The traditional anchor cable construction technology is adopted. The anchor cable tension value is mainly controlled by the grip force between the anchor rope and grouting body and the cohesive force between grouting body and surrounding rock. (2) The grip force between the anchor rope and the grouting body can be increased by about 2 times by increasing the "barb"; The cohesive force between the grouting body and the surrounding rock can be increased by 1.5 times by 6 ~ 7 MPa high-pressure grouting process. (3) The modified sulphoaluminate cement slurry can reach more than 30 MPa within 1 day of the slurry strength, so as to realize fast anchor cable tension within 1 day after grouting completion. (4)The research results can be used for reference in similar prestressed anchorage cable construction projects. © 2018, Editorial Department of Journal of Railway Engineering Society. All right reserved.     

Research on the Cause and Influential Factors of Tunnel Lining Cracking of Side Wall in Seasonally-frozen RegionsEI北大核心

Research purposes: In recent years, tunnel diseases like lining cracking and water leaking during spring thawing period, caused by frost heaving of surrounding rock, have occasionally occurred in high-latitude seasonally-frozen regions of northwest China and northeast China, which has seriously affected the tunnel structure and operation safety. Taking several railway tunnels in northwest China as an example, this paper investigates the cause and main influencing factors of longitudinal cracking of side wall in winter in seasonal frozen soil area by means of field test, laboratory experiment and numerical simulation. Research conclusions:(1) When the water content of surrounding rock of tunnel built in strongly-weathered sandstone is 12.3% and the frozen depth of surrounding rock is up to 60 cm, the maximum tensile stress of side walls is 2.28 MPa, which is larger than the ultimate tensile strength of C30 concrete, then the horizontal lining cracking will appear on side walls under the effect of continuous negative temperature in winter. If the lining bears part of the surrounding rock load, the longitudinal cracking degree of the side wall will increase. (2) Under the effect of frost heaving loads, the cracking of tunnel lining has its own characteristics of symmetry, seasonality and accumulation, etc. The cracks appear in winter and distribute in the middle of side walls. As the temperature is rising, the crack begins to shrink. (3) The frozen circle thickness and water content of surrounding rock should be used as main indicators during the process of calculation of frost heaving loads of surrounding rock in seasonally-frozen regions. (4) The research results can be used for reference in tunnel design, operation and maintenance in seasonal frozen soil area. © 2018, Editorial Department of Journal of Railway Engineering Society. All right reserved.     

PHOSPHORYLATION OF THE MYELOID ZINC FINGER PRO TEIN MZF－1 IS DIFFERENTIALLY REGULATED DURING MYELOPOIESIS

ＰＨＯＳＰＨＯＲＹＬＡＴＩＯＮＯＦＴＨＥＭＹＥＬＯＩＤＺＩＮＣＦＩＮＧＥＲＰＲＯＴＥＩＮＭＺＦ－１ＩＳＤＩＦＦＥＲＥＮＴＩＡＬＬＹＲＥＧＵＬＡＴＥＤＤＵＲＩＮＧＭＹＥＬＯＰＯＩＥＳＩＳＨｕｉＰｅｉ；ＭａｒｉａＲ．Ｂａｅｒ，ＰｅｔｅｒＧ．Ｂｒａｄｆｏｒ...     

LOSS OF NUCLEUS BASALIS MAGNOCELLULARIS，BUT NOT SEPTAL，CHOLINERGIC NEURONS CORRELATES WITH PASSIVE AVOIDANCE IMPAIRMENT IN RA

ＬＯＳＳＯＦＮＵＣＬＥＵＳＢＡＳＡＬＩＳＭＡＧＮＯＣＥＬＬＵＬＡＲＩＳ，ＢＵＴＮＯＴＳＥＰＴＡＬ，ＣＨＯＬＩＮＥＲＧＩＣＮＥＵＲＯＮＳ　ＣＯＲＲＥＬＡＴＥＳＷＩＴＨＰＡＳＳＩＶＥＡＶＯＩＤＡＮＣＥＩＭＰＡＩＲＭＥＮＴＩＮＲＡＴＳＴＲＥＡＴＥＤ　ＷＩＴ...     

上软下硬地层大直径土压平衡盾构下穿民房建筑群沉降控制北大核心CSCD

依托广州地铁18号线盾构施工,针对其地层分布复杂、软硬差异大及穿越密集民房建筑群等特点,通过注浆加固、现场动态监测、优化掘进参数等一系列主动措施,解决实际工程中掘进参数合理取值与地表建筑沉降变形控制两大难题。研究结果表明:(1)在该类软硬地层中掘进时,刀盘在通过不同岩层断面分界线时扭矩、推力等参数波动较大,总推力与扭矩有良好的相关性,各掘进参数宜控制为:推力30000~35000 kN、扭矩4500~6000 kN·m、推进速度35~45 mm/min;(2)提出的多段式封孔洞内超前注浆工艺可使刀盘前18 m范围内的地表上抬3~5 mm,最大上抬值能达9.02 mm,同时能缓解土体在盾构下穿时及后续固结稳定的沉降趋势;(3)因刀具磨损、掘进参数波动大、螺旋机卡死等引起的临时停机会造成地表建筑日沉降速率超过3 mm/d,在预设停机点位置前采取洞内超前注浆和克泥效工法能有效缓解沉降趋势,在带压开舱期间日沉降速率控制在2 mm/d以下;(4)左右隧道轴线附近的地表建筑沉降基本可分为“微小隆起—沉降较大—逐渐稳定”三个阶段,测点最大沉降值最终稳定在-21.38 mm、-22.49 mm,均小于控制值。     

铁路隧道钻爆法机械化修建设计关键技术北大核心CSCD

隧道钻爆法机械化修建方法是以全工序高效率大型机械配套为基础,用以解决复杂山区长大山岭隧道安全、优质、高效及经济等施工问题的一种技术方法。文章从隧道设计角度论述了钻爆法机械化修建面临的掌子面安全控制与洞身段变形控制两大关键挑战,并总结了以机械化全断面全地质型施工技术、掌子面稳定性评价方法、掌子面超前主动支护技术、掌子面超前支护“定量化”精准设计技术、低预应力锚杆主动支护技术、早高强喷混凝土主动支护技术、初期支护快速成环封闭技术、围岩形变压力计算方法等为核心的隧道钻爆法机械化修建设计关键技术,为推广应用隧道钻爆法机械化修建方法提供技术支撑。     

Fault diagnosis of steam power system based on convolutional neural network北大核心CSCD

[Objectives]In order to improve the fault diagnosis level of marine power systems, this paper studies the real-time fault diagnosis of a marine supercharged boiler based on a convolutional neural network (CNN).[Methods]First, the simulation program of the marine supercharged boiler is developed based on the GSE platform, and the simulation fault data is obtained. The fault diagnosis model of the boiler is then established using the CNN method. Next, through the change trends of temperature, flow and other parameters, combined with a priori knowledge and the machine learning method, fault identification is carried out. Lastly, the performance of the method is evaluated against criteria such as confusion matrix and accuracy. [Results]According to the comparison results between the feature extracted dataset and the original dataset, the stability of the model output results and the generalization ability of the model are optimized and improved, with an overall fault classification accuracy reaching 99.53%.[Conclusion]The results of this study can provide valuable references for the intelligent monitoring of marine power systems. © 2022 Chinese Medical Journals Publishing House Co.Ltd. All rights reserved.