高层建筑消防机器人的机构研究与分析

结合高层建筑火灾现场的特殊条件,介绍了高层建筑消防救灾机器人的整体运作机理以及各主要功能部件的机构组成和工作原理.该机器人可以实现在保持姿态不变的条件下,携带一定数量的救生物品和灭火工具快速运动到壁面目标位置进行破障救生和火情探测,并将探测结果及时传递给处于安全地区的控制系统,便于救灾人员及时采取相应的措施.     

学术自由研究述评

本文主要阐述了有关学术自由这一议题的研究意义、研究现状及其在学理上搭建一个比较合理的理论基础的可能性     

PSZ／Mo功能梯度材料的有限元设计

利用有限元分析的方法，依据拉应力和比应力最小原则对PSZ／Mo功能梯度材料进行了优化设计，确定了FGM的最佳形状分布因子、层数和每一层的厚度。并对最优成分分布FGM在稳态隔热状态下所产生的温度场和热应力进行了计算，得出进行PSZ／Mo功能梯度材料优化设计所需考虑的主要因素。     

激光快速成形Rene′88DT高温合金的时效强化研究

研究了时效时间对激光快速成形后时效硬化镍基高温合金Rene′88DT中沉淀相组织演化和力学性能的影响。发现随时效时间的增加，沉淀相y’略有长大，颗粒之间发生大颗粒吞噬小颗粒的粗化，时效40h后沉淀相颗粒粗化明显。对经不同时间时效后的激光快速成形Rene′88DT试样进行了硬度测试。结果显示，在时效时间为28h时，硬度有一峰值HRC49。在此基础上，采用1165℃，2h固溶、空冷＋760℃，28h时效的热处理工艺对激光快速成形标准拉伸棒样进行了热处理，拉伸结果显示成形件的抗拉强度较激光沉积态提高了400MPa，屈服强度接近同种材料的粉末锻造水平。     

磨削过程中低温磨削液及供液装置的开发及研究

本文针对磨削过程中的过高的磨削温度问题，研制开发了一种新型的低温供液装置，解决了工程中的实际问题。本文还采用有限元方法对采用低温供液装置的进行冷却润滑的磨削温度场进行了分析，通过仿真分析及实验验证了这种低温供液装置可以大大降低磨削区的温度，有效减少磨削烧伤，效果良好。     

基于再制造工程的大型沥青混合料摊铺设备的设计与制造工艺研究

论述了工程机械再制造的意义,分析了当前国内外工程机械再制造的发展现状,对基于再制造工程的大型沥青混合料摊铺设备的设计与制造工艺进行了有益的探索,并针对大型沥青混合料摊铺设备的主要零、部件的材料选择、结构设计、制造与装配工艺设计等进行了研究,对再制造方法的可行性、使用性及经济性进行了评价.     

TiAl合金激光表面原位TiC颗粒增强涂层及高温抗氧化性能

以高纯石墨粉和C Nb混合粉末为原料,对Ti-46Al-2Cr-1．5Nb-1V合金进行了激光表面合金化处理,对激光改性层的显微组织以及成分进行了观察与分析,并对该合金原始组织及经C和C Nb激光表面改性层的高温抗氧化性能进行了对比分析研究。结果表明,C和C Nb激光表面合金化处理后,在合金表面均“原位”形成了TiC颗粒,Nb以固溶原子形式存在于表面改性层中,TiC颗粒的大小,形态及分布强烈取决于激光工艺参数;激光表面处理后的合金的抗氧化性能明显高于未经激光处理的铸态组织,而且在石墨粉中掺杂Nb粉,处理后的合金具有最佳的抗氧化性能。     

Conditional diagnosability and strong diagnosability of shuffle-cubes under the comparison model

The growing size of multiprocessor systems increases the vulnerability to component failures. It is crucial to locate and replace faulty processors to maintain the system's high reliability. Processor fault diagnosis is essential to the reliability of a multiprocessor system and the diagnosabilities of many well-known networks (such as hierarchical hypercubes and crossed cubes [S. Zhou, L. Lin and J.-M. Xu, Conditional fault diagnosis of hierarchical hypercubes, Int. J. Comput. Math. 89(16) (2012), pp. 2152–2164 and S. Zhou, The conditional diagnosability of crossed cubes under the comparison model, Int. J. Comput. Math. 87(15) (2010), pp. 3387–3396]) have been investigated in the literature. A system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly t-diagnosable if it is t-diagnosable and can achieve (t+1)-diagnosability except for the case where a node's neighbours are all faulty. In addition, conditional diagnosability has been widely accepted as a new measure of diagnosability by assuming that any fault-set cannot contain all neighbours of any node in a multiprocessor system. In this paper, we determine the conditional diagnosability and strong diagnosability of an n-dimensional shuffle-cube SQ_n, a variant of hypercube for multiprocessor systems, under the comparison model. We show that the conditional diagnosability of shuffle-cube SQ_n (n=4k+2 and k≥2) is 3n?9, and SQ_n is strongly n-diagnosable under the comparison model.     

The implications of serial correlation and time-lag effects for the impact study of climate change on vegetation dynamics – a case study with Hulunber meadow steppe,Inner Mongolia

Ecological time series data are widely used in ecological research thanks to the development of remote-sensing technologies and fixed ecological research stations. However, the serial correlation issue with time series, which violates the fundamental assumption of independence for traditional statistical models or analysis, is rarely considered by ecologists in vegetation–climate relationship research. In addition, the issue of time lags between climate change and vegetation response is also often ignored. Inadequate consideration of these issues produces misleading results in some cases. In this article, we propose an approach based on the Autoregressive Integrated Moving Average (ARIMA) model and the nonparametric test to address serial correlation issue and distribution requirements for the valid statistical analysis of time series data. With Hulunber meadow steppe as a case, we applied this approach to analyse the role of climate factors in vegetation dynamics based on leaf area index (LAI) data and climatic data. The results showed that the LAI dynamics of Hulunber meadow steppe were mainly related to temperature with the time lag of zero, whereas the impact of precipitation on LAI dynamics was not statistically obvious. The comparison of regression models that deal with serial correlation and residual normality to different extents showed that ignoring the serial correlation issue with time series data likely produces misleading results, highlighting the importance of serial correlation removal. The combination of nonparametric correlation tests with ARIMA-based cross-correlation analysis also proved quite useful in reducing the chance of spurious correlation and time lags resulting from outlier values in ARIMA-based cross-correlation.