Network-based triple-frequency carrier phase ambiguity resolution between reference stations using BDS data for long baselines

Network-based ambiguity resolution (AR) between reference stations is the prerequisite to realize a precise real-time kinematic positioning service. With the help of BDS triple-frequency signals, we can efficiently deal with the ionospheric delay and tropospheric delay, and achieve rapid and reliable AR. To overcome the inaccurate ionospheric delay estimated by the geometry-free three carrier ambiguity resolution (GF TCAR) technique, which leads to failure in the original ambiguity resolution, we propose an ionospheric-free (IF) TCAR method to resolve the ambiguity between the reference stations over long baselines. Taking full advantage of the known positions of the reference stations, the easily resolved extra-wide-lane (EWL) ambiguity, and the IF phase combinations, we can reliably fix the wide-lane (WL) ambiguity. A Kalman filter is applied to estimate precise IF ambiguities and the original ambiguity is resolved with the fixed WL ambiguity. A numerical analysis with triple-frequency BDS data from three long baselines of a CORS network is provided to compare the AR performance of GF TCAR with that of IF TCAR. The results show that both methods can reliably resolve the WL ambiguity with a remarkable correctly-fixed rate of higher than 99%, and the reliably-fixed rates of the IF TCAR slightly increase from 92.19, 94.67 and 94.61–98.26, 99.54 and 97.51% for the three baselines. Herein “correctly-fixed” and “reliably-fixed” mean the difference between the float ambiguity and the true one are less than ± 0.5 and ± 0.25 cycles, respectively. On the other hand, the AR performance of the original signals with the IF TCAR method is much better than that with the GF TCAR method attaining a 100% correctly-fixed rate, while the GF TCAR method can hardly fix the original ambiguity with the largest bias being as much as 4 cycles because of the amplified systematic bias.     

An improved ionosphere interpolation algorithm for network RTK in low-latitude regions

A traditional interpolation algorithm with the linear interpolation method (LIM) using a fixed number of reference stations is widely used in network RTK to obtain the ionospheric delays for the users. In low-latitude regions, where the ionosphere is relatively active, however, large interpolation errors exist, especially for satellites at low elevation angles. Considering the characteristics of “coinciding ionospheric pierce points (CIPPs)” with a similar nature of ionospheric delays, an improved interpolation algorithm is proposed. In this algorithm, all stations with CIPPs are used to establish the interpolation model; thus, more precise interpolation model is achieved. To validate the performance of the proposed algorithm, data from some reference stations in Guangdong Province of China were used, and the results are compared with those with the traditional interpolation algorithm. Numerical analysis shows that the interpolation accuracy of the proposed algorithm increases by 10–30% compared with the traditional one. Since the number of reference stations is flexible, the proposed algorithm can also balance the model accuracy with the computation burdens. In addition, the proposed algorithm is less affected by the selection of master reference station. In terms of network RTK on-the-fly positioning, the time-to-first-fix is reduced when replacing the traditional interpolation algorithm with the proposed one.     

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.     

双碳背景下我国煤炭资源勘查开发布局研究

随着双碳背景下国家能源结构调整和生态文明建设的要求,本文从保障国家主体能源安全和优化煤炭资源勘查开发布局的角度考虑,阐述了中国煤炭资源分布特点及勘查开发现状;从坚持集约与协调发展、改革与创新发展、绿色与清洁发展的基本原则出发,分析了新时期煤炭资源勘查目标：加强大型煤炭基地资源勘查、推进新增煤层气资源储量、加快煤系矿产资源勘查;从资源禀赋、开发强度、市场区位、环境容量、输送通道等方面出发,阐述了14个大型煤炭基地开发布局方向及建设规模,同时要加快煤层气的开发利用。研究成果对未来一段时期煤炭资源勘查开发及煤炭工业高质量发展具有重要的指导意义。     

Field test research on post-grouting effect for super-long cast-in-place bored pile in thick soft foundation

Geotechnical and Geological Engineering - The field static load test method was adopted for two test piles in a project in Zhejiang area of China, analyze the effect of post-grouting technique on...     

The nonlinear time lag multivariable grey prediction model based on interval grey numbers and its application

Natural Hazards - The linear relationship of the original grey prediction model is too single, and the original grey prediction model does not consider the time delay of the effect of the current...     

盾构超近距离侧穿铁路桥桩保护方案探讨

郑州地铁某盾构区间超近距离侧穿铁路桥梁桩基,受地面空间及隧道与桥桩间净距限制,无法采用隔离桩等常规保护措施.结合工程实际情况提出“盾构通过范围内土体注浆加固”、“桥梁承台加固”以及“注浆+承台加固”三种措施,利用数值模拟手段,对盾构侧穿施工期间,不同保护方案下桥桩的变形规律进行了分析研究.研究结果表明,采用“盾构通过范围内土体注浆加固+承台加固”措施,可使桥面最大沉降值减少约45%,且可减少桥面横桥向不均匀沉降及桥桩水平位移,在很大程度上减少盾构隧道施工对铁路桥梁的不利影响.      

Movement process analysis of the high-speed long-runout Shuicheng landslide over 3-D complex terrain using a depth-averaged numerical model

Landslides - Flow-like landslide is one of the most catastrophic types of natural hazards due to its high velocity and long travel distance. In 2019, a large catastrophic landslide was triggered by...     

静压桩承载力时间效应的研究进展

由于静压桩沉桩后桩周土重塑,静压桩承载力表现出随着休止期的延长而增长的特性。本文从静压桩沉桩后桩周土体内孔隙水消散固结的角度出发,对静压桩承载力时间效应的理论和试验分别进行归纳,结合孔隙水消散路径及固结模型,对桩周土体初始超静孔隙水压力大小及其分布特征进行总结,分析承载力各种测试方法的优缺点,对静压桩承载力的时效性进行深化研究,并探讨了不同地质条件、不同桩的类型对休止期内静压桩承载力的影响,进一步对基于实测数据得出的经验公式进行总结。讨论了基于不同本构关系模型的应力场及位移场解答和沉桩后孔隙水压力消散解答,在此基础上总结了桩基极限承载力理论公式;探讨了黏性土、砂土条件下,考虑超固结比、不排水抗剪强度和塑性指数比对桩基极限承载力系数A的影响,在此基础上归纳了桩基极限承载力经验公式。建议在经验公式基础上设置多重参数,以提升经验公式的精确度,并完善对不同桩、土类型的参数解答;利用BP神经网络,导入静压桩承载力相关参数,以得到针对不同地质条件、桩型、休止期的承载力最优解。