堆内构件异种材料螺钉联接件柔度计算方法

对4种不同直径的螺钉联接结构用有限元分析方法进行了计算和试验研究;对现有螺钉柔度计算方法进行了分析.结果表明,有限元分析计算与试验结果吻合较好;对于被联接件的柔度计算,总结出被联接件长宽比与对柔度的影响β值呈线性关系.     

Scaling of land surface temperature using satellite data: A case examination on ASTER and MODIS products over a heterogeneous terrain area

Land surface temperature (LST) is a key parameter in numerous environmental studies. Surface heterogeneity induces uncertainty in pixel-wise LST. Spatial scaling may account for the uncertainty, however, different approaches lead to differences in scaled values. Satellite-retrieved LST may be representative of the pixel-wise LST and useful for scaling analysis, but the limited accuracy of retrieved values adds uncertainty into the scaled values. Based on the Stefan-Boltzmann (S-B) law, this study proposed scaling approaches for LST over flat and relief areas to explore the combined uncertainties in scaling using satellite-retrieved data. To take advantage of simultaneous, multi-resolution observations at coincident nadirs by the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and the MODerate-resolution Imaging Spectroradiometer (MODIS), LST products from these two sensors were examined for part of the Loess Plateau in China. 90-m ASTER LST data were scaled up to 1 km using the proposed approaches, and variation in the LST was generally reduced after scaling. Amongst the sources of uncertainties, surface heterogeneity (emissivity) and different scaling approaches resulted in very minor differences, with a maximum difference of 0.2 K for the upscaled LST. Terrain features, taken as an areal weighting factor, had negligible effects on the upscaled value. Limited accuracy of the retrieved LST was the major uncertainty. The overall LST increased 0.6 K on average with correction for terrain-induced angular effect and 0.4 K for both angular and adjacency effects over the study area. Accounting for terrain correction in scaling is necessary for rugged areas. With terrain correction, the upscaled ASTER LST achieved an agreement of − 0.1 ± 1.87 K and a root mean square error (RMSE) of 1.87 K overall with the 1-km MODIS LST rectified by Wan et al.'s approach [Wan, Z., Zhang, Y., Zhang Q., Li, Z.-L. (2002b), Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data. Remote Sensing of Environment, 83, 163-180]. Refining the rectification approach resulted in a better agreement of − 0.2 ± 1.57 K and a RMSE of 1.58 K.     

数据库异构模式的消解技术研究

如何解决异构数据的消解是多数据库系统模式中面临的一个重要问题,在对该问题进行研究的基础上,提出了一种利用建立领域概念数据库和实际数据库之间的映射规则来解决数据表示异构问题的方法,并以一个法院案件协查系统为例,详细描述了具体的实现过程。     

On the performance-driven load distribution for heterogeneous computational grids

Load balancing has been a key concern for traditional multiprocessor systems. The emergence of computational grids extends this challenge to deal with more serious problems, such as scalability, heterogeneity of computing resources and considerable transfer delay. In this paper, we present a dynamic and decentralized load balancing algorithm for computationally intensive jobs on a heterogeneous distributed computing platform. The time spent by a job in the system is considered as the main issue that needs to be minimized. Our main contributions are: (1) Our algorithm uses site desirability for processing power and transfer delay to guide load assignment and redistribution, (2) Our transfer and location policies are a combination of two specific strategies that are performance driven to minimize execution cost. These two policies are the Instantaneous Distribution Policy (IDP) and the Load Adjustment Policy (LAP), (3) The communication overhead involved in information collection is reduced using mutual information feedback. The simulation results show that our proposed algorithm outperforms conventional approaches over a wide range of system parameters.     

Sensor deployment based on fuzzy graph considering heterogeneity and multiple-objectives to diagnose manufacturing system

In this paper, a methodology is presented to generate an optimized sensor deployment deciding sensor types, numbers, and locations to accurately monitor fault signatures in manufacturing systems. Sensor deployment to robustly monitor operation parameters is the corner stone for diagnosing manufacturing systems. However, current literature lacks investigation in methodologies that handle heterogeneity among sensor properties and consider multiple-objective optimization involved in the sensor deployment. We propose a quantitative fuzzy graph based approach to model the cause–effect relationship between system faults and sensor measurements; analytic hierarchy process (AHP) was used to aggregate the heterogeneous properties of the sensor–fault relationship into single edge values in fuzzy graph, thus quantitatively determining the sensor's detectability to fault. Finally sensor–fault matching algorithms were proposed to minimize fault unobservability and cost for the whole system, under the constraints of detectability and limited resources, thus achieving optimum sensor placement. The performance of the proposed strategy was tested and validated on different manufacturing systems (continuous or discrete); various issues discussed in the methodology were demonstrated in the case studies. In the continuous manufacturing case study, the results illustrated that compared with signed directed graph (SDG), the proposed fuzzy graph based methodology can greatly enhance the detectability to faults (from SDG's 0.699 to fuzzy graph's 0.772). In the discrete manufacturing case study, results from different optimization approaches were compared and discussed; the detectability of sensors to faults also increased from SDG's 0.61 to fuzzy graph's 0.65. The two case study results show that the proposed approach overcame the qualitative approach such as signed directed graph's deficiency on handling sensor heterogeneity and multiple objectives; the proposed approach is systematic and robust; it can be integrated into diagnosis architecture to detect faults in other complex systems.     

Soybean (Glycine max L. Merrill) Seed Drying in Fixed Bed: Process Heterogeneity and Seed Quality

Soybean (Glycine max (L.) Merr.) is the most important oilseed in the world market. Seed quality has a direct influence on the success of the crop and contributes significantly to productivity levels. The quality of soybean seeds can be influenced by several factors during drying. This study evaluated the drying of soybean seeds in a fixed bed dryer, considering the heterogeneity of the process and the effect of process variables on seed quality. Seed and air temperatures, seed moisture, and seed quality were measured throughout the bed. Empirical equations were obtained relating seed quality indicators, at several bed axial positions, as a function of process variables.     

Identifying crash-prone locations with quantile regression

Identifying locations that exhibit the greatest potential for safety improvements is becoming more and more important because of competing needs and a tightening safety improvement budget. Current crash modeling practices mainly target changes at the mean level. However, crash data often have skewed distributions and exhibit substantial heterogeneity. Changes at mean level do not adequately represent patterns present in the data. This study employs a regression technique known as the quantile regression. Quantile regression offers the flexibility of estimating trends at different quantiles. It is particularly useful for summarizing data with heterogeneity. Here, we consider its application for identifying intersections with severe safety issues. Several classic approaches for determining risk-prone intersections are also compared. Our findings suggest that relative to other methods, quantile regression yields a sensible and much more refined subset of risk-prone locations.     

Design and Analysis of Factorial Experiments Via Interactive Computing in APL

This paper discusses the use of interactive computing in APL for the design and analysis of an ad hoc experiment. As an example, a project involving a 16 × 4 × 2 experiment in 8 blocks of size 8 is reviewed. The desirability of utilizing single-degreeof-freedom pseudo-factors in both the design and analysis phases of such experiments is exhibited, and the detection of and compensation for heterogeneity of variance and outliers are discussed.     

曲流河道砂体内部构成及储集层非均质性的露头研究——以鄂尔多斯盆地东北部延安组露头砂体为例

按大、中、微三种尺度逐层次精细剖析了赵石窑曲流河道砂体的内部构成及储集层非均质性特征.在峭壁断面写实基础上,观测了砂体的空间几何形态、成因相类型、特征及相互配置关系;识别划分了六级界面、十二种储集层岩性相、四种隔挡层,并研究了它们的沉积及分布特征,为建立定量的储集层地质模型提供了重要依据.