自进式中空注浆锚杆在班多水电站施工中的应用

水利工程及各类地下工程中普遍存在着软弱围岩、断层破碎带等复杂地质条件,给岩锚施工带来了极大的困难,特别是在塌孔严重和需要特长锚杆的情况下,普通的砂浆锚杆施工难度大。文章结合班多水电站导流明渠边坡开挖支护施工,阐述了自进式中空注浆锚杆在岩石破碎、黏土岩等复杂地质条件下替代普通砂浆锚杆,能够克服普通砂浆锚杆施工进度缓慢、无法插杆、塌孔等问题,保证围岩的整体稳定。     

Developing a Higher-Cycled Product Design CAE Model： The Evolution of Automotive Product Design and CAE

To help corporations survive amidst worldwide quality competition, the authors have focused on the strategic development of a higher-cycled product design CAE model employing a highly reliable CAE analysis technology component model. Their efforts are part of principle-based research aimed at evolving product design and CAE development processes to ensure better quality assurance. To satisfy the requirements of developing and producing high quality products while also reducing costs and shortening development times, the effectiveness of this model was verified by successfully applying it to the technological problems of loosening bolts and other product design bottlenecks at auto manufacturers.     

Temporal persistence and stability of surface soil moisture in a semi-arid watershed

Satellite soil moisture products, such as those from Advanced Microwave Scanning Radiometer (AMSR), require diverse landscapes for validation. Semi-arid landscapes present a particular challenge to satellite remote sensing validation using traditional techniques because of the high spatial variability and potentially rapid rates of temporal change in moisture conditions. In this study, temporal stability analysis and spatial sampling techniques are used to investigate the representativeness of ground observations at satellite scale soil moisture in a semi-arid watershed for a long study period (March 1, 2002 to September 13, 2005). The watershed utilized, the Walnut Gulch Experimental Watershed, has a dense network of 19 soil moisture sensors, distributed over a 150 km² study region. In conjunction with this monitoring network, intensive gravimetric soil moisture sampling conducted as part of the Soil Moisture Experiment in 2004 (SMEX04), contributed to the calibration of the network for large-scale estimation during the North American Monsoon System (NAMS). The sensor network is shown to be an excellent estimator of the watershed average with an accuracy of approximately 0.01 m³/m³ soil moisture. However, temporal stability analysis indicated that while much of the network is stable, the soil moisture spatial pattern, as represented by mean relative difference, is not replicated by the network mean relative difference pattern. Rather, the network is composed of statistical samples. Geophysical aspects of the watershed, including topography and soil type are also examined for their influence on the soil moisture variability and stability. Soil type, as characterized by bulk density, clay and sand content, was responsible for nearly 50% of the temporal stability. Topographic effects were less important in defining representativeness and stability.     

Influence of Heat Input on Microstructure and Mechanical Properties of Laser Welding GH4169 Bolt Assembly—Numerical and Experimental Analysis

By conducting the numerical and experimental analysis, the influence of heat input on the microstructures and mechanical properties of laser welding GH4169 bolt assembly is systematically investigated. The weld formation, temperature field, and residual stress distribution during laser welding by using the finite element modeling are consistent with experimental results. The numerical simulation results show that the increase of heat input imparts lower residual stresses and higher temperature gradient. During the process of laser welding, the steepest temperature gradient and the peak residual stress arise in the fusion zone (FZ). In addition, the dissolution of γ″ and γ′ toward the fusion line increases in heat affected zone (HAZ), but only Laves phase is observed in FZ. With increasing heat input from 24 to 48 J mm⁻¹, the ultimate tensile strength of welded joints decreases. Both the lowest microhardness values and tensile failure of GH4169 alloy laser welded joint are in FZ. Herein, it is that the relationship among the heat input, microstructures, and mechanical properties of GH4196 bolt assembly in laser welding is systematically established, which will be of guiding significance for the selection of welding parameters in aerospace.     

Ultraschallbasierte in situ Vorspannkraftermittlung an Schrauben ohne Referenzmessung im nicht verspannten Zustand durch Kombination von Longitudinal- und Transversalwellen

Ultrasonic based bolt preload evaluation is commonly performed using the mono-wave method. This method works by measuring the time of flight of longitudinal waves. Here, a reference measurement in the unloaded condition is necessary for each bolt. In this publication the longitudinal wave is complemented by another type of ultrasonic wave - the transverse wave. This method does not require a reference measurement in the unloaded condition for each bolt. Moreover, an analytic method for determining the bolt-specific K-value is introduced, which is needed for the ultrasonic bolt preload determination. The analytically calculated K-values are compared with experimental K-values from tensile tests. The influence of material, bolt property class and surface protection system were determined with cylindrical specimens. In component tests, the bolt preload was evaluated using the bi-wave method, a possible influence of the bolt assembly method was investigated and the results were interpreted regarding their accuracy.     

锚杆锚索载荷数据采集及分析系统设计

针对目前锚杆、锚索载荷数据采集与分析方法存在的准确性低、读数困难、效率低等问题,研发了一种新的锚杆、锚索载荷数据采集及分析系统。该系统利用无线传输技术采集载荷数据,并借助计算机软件对采集的数据进行数字化分析研究,提高了数据分析的准确性,为判断巷道支护的安全性提供了更为科学的依据。     

Benchmarking classifiers to optimally integrate terrain analysis and multispectral remote sensing in automatic rock glacier detection

The performance improvements that can be achieved by classifier selection and by integrating terrain attributes into land cover classification are investigated in the context of rock glacier detection. While exposed glacier ice can easily be mapped from multispectral remote-sensing data, the detection of rock glaciers and debris-covered glaciers is a challenge for multispectral remote sensing. Motivated by the successful use of digital terrain analysis in rock glacier distribution models, the predictive performance of a combination of terrain attributes derived from SRTM (Shuttle Radar Topography Mission) digital elevation models and Landsat ETM+ data for detecting rock glaciers in the San Juan Mountains, Colorado, USA, is assessed. Eleven statistical and machine-learning techniques are compared in a benchmarking exercise, including logistic regression, generalized additive models (GAM), linear discriminant techniques, the support vector machine, and bootstrap-aggregated tree-based classifiers such as random forests. Penalized linear discriminant analysis (PLDA) yields mapping results that are significantly better than all other classifiers, achieving a median false-positive rate (mFPR, estimated by cross-validation) of 8.2% at a sensitivity of 70%, i.e. when 70% of all true rock glacier points are detected. The GAM and standard linear discriminant analysis were second best (mFPR: 8.8%), followed by polyclass. For comparison, the predictive performance of the best three techniques is also evaluated using (1) only terrain attributes as predictors (mFPR: 13.1-14.5% for best three techniques), and (2), only Landsat ETM+ data (mFPR: 19.4-22.7%), yielding significantly higher mFPR estimates at a 70% sensitivity. The mFPR of the worst three classifiers was by about one-quarter higher compared to the best three classifiers, and the combination of terrain attributes and multispectral data reduced the mFPR by more than one-half compared to remote sensing only. These results highlight the importance of combining remote-sensing and terrain data for mapping rock glaciers and other debris-covered ice and choosing the optimal classifier based on unbiased error estimators. The proposed benchmarking methodology is more generally suitable for comparing the utility of remote-sensing algorithms and sensors.     

Identification and sizing of the entirely visible rocks from a 3D surface data segmentation of laboratory rock piles

Once segmentation of 3D surface data of a rock pile has been performed, the next task is to determine the visibility of the surface rocks. A region boundary-following algorithm that accommodates irregularly spaced 3D coordinate data is presented for determining this visibility. We examine 3D surface segmentations of laboratory rock piles and determine which regions in the segmentation correspond to entirely visible rocks, and which correspond to overlapped or partially visible rocks. This is a significant distinction as it allows accurate size determination of entirely visible rocks, separate handling of partially visible rocks, and prevents erroneous bias resulting from mishandling partially visible rocks as smaller entirely visible rocks. Literature review indicates that other rock pile sizing techniques fail to make this distinction. The rock visibility results are quantified by comparison to manual surface classifications of the laboratory piles and the size results are quantified by comparison to the sieve size.     

Bolt support mechanism based on elastic theory

Mechanical model of anchorage surrounding rock considering tray effect was established based on elastic theory, in order to study the mechanism of bolt supporting. Elastic solutions of normal force at point in the interior of a semi-infinite solid were obtained by means of classical displacement function method in elasticity. The factors which influence stress of bolted surrounding rock, such as the length of bolt and tray effect, were analyzed. The absolute value of stress along bolt axes decreased rapidly with an increase in radical distance and the maximum appeared near ends of bolt. With increasing radical distance, the value of radical stress changed from positive to negative roughly and then increased to zero, with maximum at the middle of bolt. The evolution of hoop stress as radical distance increasing was similar with stress along bolt axes. With an increase in depth, the radical effect ranges of all normal stress components were reduced. These suggest that the effect from tray on stress along bolt axes of bolted surrounding rock could be neglected, except near surface of surrounding rock.     

Selection of regression models for predicting strength and deformability properties of rocks using GA

Recently, many regression models have been presented for prediction of mechanical parameters of rocks regarding to rock index properties. Although statistical analysis is a common method for developing regression models, but still selection of suitable transformation of the independent variables in a regression model is difficult. In this paper, a genetic algorithm (GA) has been employed as a heuristic search method for selection of best transformation of the independent variables (some index properties of rocks) in regression models for prediction of uniaxial compressive strength (UCS) and modulus of elasticity (E). Firstly, multiple linear regression (MLR) analysis was performed on a data set to establish predictive models. Then, two GA models were developed in which root mean squared error (RMSE) was defined as fitness function. Results have shown that GA models are more precise than MLR models and are able to explain the relation between the intrinsic strength/elasticity properties and index properties of rocks by simple formulation and accepted accuracy.