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1.
以重庆市甄子岩29号危岩体为研究对象,基于现场调查和分析解剖,建立UDEC离散元数值计算模型,对其演化变形过程进行模拟分析。研究表明,在巨大的自重作用下,由于基座岩体岩质软,岩体较破碎,且基座外侧为直立的陡崖,具有完整的临空面,从而使基座岩体易发生压缩流变及剪切流变,进而使危岩体存在滑移垮塌的危险。 相似文献
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大型综合室内亲子乐园属于高大空间,设有游乐设施和游戏的特殊性使得对空间的舒适性要求一致,但是送风气流遇阻严重,室内存在较多气流死角,影响室内空气质量和儿童健康。因此其空调设计不仅需要考虑温度、风速的空间均匀度,还要考虑各点的空气龄和PMV-PPD指标。以天津某亲子乐园为研究对象,利用scSTREAM软件对适用于该房间的辐射供冷加新风、置换通风、混合通风三种空调方式的送风效果进行数值模拟分析,从流场的均匀性、人员的热舒适性等方面对模拟结果进行探讨,研究结果表明辐射供冷加新风方式的空间均匀性和PMV指标最佳,混合通风方式的空气龄最小。 相似文献
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Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety. 相似文献
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Numerical simulation, using SILVACO-TCAD, is carried out to explain experimentally observed effects of different types of deep levels on the capacitance–voltage characteristics of p-type Si-doped GaAs Schottky diodes grown on high index GaAs substrates. Two diodes were grown on (311)A and (211)A oriented GaAs substrates using Molecular Beam Epitaxy (MBE). Although, deep levels were observed in both structures, the measured capacitance–voltage characteristics show a negative differential capacitance (NDC) for the (311)A diodes, while the (211)A devices display a usual behaviour. The NDC is related to the nature and spatial distribution of the deep levels, which are characterized by the Deep Level Transient Spectroscopy (DLTS) technique. In the (311)A structure only majority deep levels (hole traps) were observed while both majority and minority deep levels were present in the (211)A diodes. The simulation, which calculates the capacitance–voltage characteristics in the absence and presence of different types of deep levels, agrees well with the experimentally observed behaviour. 相似文献
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针对流体输送埋地管道泄漏问题,设计了一种利用管道机器人携带封堵气囊进行快速应急封堵修复的埋地管道泄漏内封堵装置。采用矩阵变换方法建立了牵引系统驱动轮过弯方程,利用MATLAB软件对过弯方程进行了验证,同时利用ADAMS软件仿真分析过弯路径与驱动轮转角对牵引系统行走速度的影响。研究结果表明:由两个串联封堵器组成的应急封堵系统可满足复杂工况下的管道泄漏封堵要求;牵引系统驱动轮在弯管内部行走时,单轮速度呈周期性变化,但三个驱动轮整体周期运动特性一致;驱动轮转角在25°~40°时,牵引系统行走速度与驱动轮转角成正比,且转角为30°时驱动效果最好。该内封堵装置的结构设计可为管道泄漏应急封堵领域装备的研发提供重要参考。 相似文献
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This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning
of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed
Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given
visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample
size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive
experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr
and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood
(ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given
sparse data, while CL-AIC should be chosen given moderate or large data sample sizes. 相似文献