不同重力环境下辐射加热材料表面着火特性分析

研究外界辐射加热下，不同重力环境中热薄燃料的着火特性．探讨了重力、环境氧浓度、环境压力及外界辐射强度对着火的影响．结果表明，随着重力的变化，存在不同的着火机制．在微重力和在高的环境氧浓度中，材料的着火延迟时间变短．压力减小，着火延迟时间增大．随着辐射强度的增大，着火延迟时间变小．     

水反常热膨胀特性的简易实验

通过改变带细玻璃管的烧瓶中水的温度导致水位变化来粗略演示水的收缩情况.为较准确测定水最大密度时的温度,将2个温度计放在水下较浅处和较深处,分别测量当温度经由4℃升高时和由4℃降低时两温度计的示数,进而验证水的反常热膨胀特性.     

a-C:F薄膜的热稳定性与光学带隙的关联

以CF4和C6H6的混合气体作为气源,在微波电子回旋共振化学气相沉积(ECRCVD)装置中制备了氟化非晶碳薄膜(aC:F),并在N2气氛中作了退火处理以考察其热稳定性.通过傅里叶变换红外吸收谱和紫外可见光谱获得了薄膜中CC双键的相对含量和光学带隙,发现膜中CC键含量与光学带隙之间存在着密切的关联,在高微波功率下沉积的氟化非晶碳膜具有低的光学带隙和较好的热稳定性. 关键词： 氟化非晶碳膜 光学带隙 退火温度 热稳定性     

Scale Invariance Properties in the Simulated Annealing Algorithm

The Boltzmann distribution used in the steady-state analysis of the simulated annealing algorithm gives rise to several scale invariant properties. Scale invariance is first presented in the context of parallel independent processors and then extended to an abstract form based on lumping states together to form new aggregate states. These lumped or aggregate states possess all of the mathematical characteristics, forms and relationships of states (solutions) in the original problem in both first and second moments. These scale invariance properties therefore permit new ways of relating objective function values, conditional expectation values, stationary probabilities, rates of change of stationary probabilities and conditional variances. Such properties therefore provide potential applications in analysis, statistical inference and optimization. Directions for future research that take advantage of scale invariance are also discussed.     

光纤光栅的温度补偿

提出了一种简单、小型的光纤光栅温度补偿器件，将光纤光栅粘贴在具有负热膨胀系数的材料上，实现了光纤光栅的温度补偿。该器件在-20～44℃温度范围内光栅波长变化0.08m，是未补偿光纤光栅的1／8。     

On effectiveness of wiretap programs in mapping social networks

Snowball sampling methods are known to be a biased toward highly connected actors and consequently produce core-periphery networks when these may not necessarily be present. This leads to a biased perception of the underlying network which can have negative policy consequences, as in the identification of terrorist networks. When snowball sampling is used, the potential overload of the information collection system is a distinct problem due to the exponential growth of the number of suspects to be monitored. In this paper, we focus on evaluating the effectiveness of a wiretapping program in terms of its ability to map the rapidly evolving networks within a covert organization. By running a series of simulation-based experiments, we are able to evaluate a broad spectrum of information gathering regimes based on a consistent set of criteria. We conclude by proposing a set of information gathering programs that achieve higher effectiveness then snowball sampling, and at a lower cost. Maksim Tsvetovat is an Assistant Professor at the Center for Social Complexity and department of Public and International Affairs at George Mason University, Fairfax, VA. He received his Ph.D. from the Computation, Organizations and Society program in the School of Computer Science, Carnegie Mellon University. His dissertation was centered on use of artificial intelligence techniques such as planning and semantic reasoning as a means of studying behavior and evolution of complex social networks, such as these of terrorist organizations. He received a Master of Science degree from University of Minnesota with a specialization in Artificial Intelligence and design of Multi-Agent Systems, and has also extensively studied organization theory and social science research methods. His research is centered on building high-fidelity simulations of social and organizational systems using concepts from distributed artificial intelligence and multi-agent systems. Other projects focus on social network analysis for mapping of internal corporate networks or study of covert and terrorist orgnaizations. Maksim’s vita and publications can be found on Kathleen M. Carley is a professor in the School of Computer Science at Carnegie Mellon University and the director of the center for Compuational Analysis of Social and Organizational Systems (CASOS) which has over 25 members, both students and research staff. Her research combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations. She and her lab have developed infrastructure tools for analyzing large scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining systems for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource and task networks. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces. She is the founding co-editor with Al. Wallace of the journal Computational Organization Theory and has co-edited several books and written over 100 articles in the computational organizations and dynamic network area. Her publications can be found at: http://www.casos.cs.cmu.edu/bios/carley/publications.php     

Numerical simulation of thermally and chemically nonequilibrium flows and heat transfer in underexpanded induction plasmatron jets

The results of numerical simulation are presented for thermally and chemically nonequilibrium air plasma flows in a plasmatron discharge channel and underexpanded dissociated and partially ionized air jets flowing past a cylindrical model with a blunt leading edge and cooled copper surface under the experimental conditions realized in a VGU-4 100 kW induction plasmatron (Institute for Problems in Mechanics of the Russian Academy of Sciences) (see, for example, [1, 2]). The nonequilibrium excitation of the vibrational degrees of freedom of the molecules in the modal approximation and the difference between the electron and translational heavy-particle temperatures are taken into account in the calculations. The calculated data on the heat transfer and pressure at the stagnation point are compared with the results obtained within the framework of the thermally equilibrium model. Comparison with the experimental data obtained in the Institute for Problem in Mechanics of the Russian Academy of Sciences (Laboratory for interaction between plasma and radiation and materials) and kindly provided for comparison purposes gives satisfactory agreement.     

CNx纳米管的制备、结构观察及低场致电子发射性能研究

采用高温热解法，以乙二胺为前驱液，在沉积有铁催化剂的p型硅（111）基底上制备出了定向生长的CNx纳米管.利用扫描电子显微镜、高分辨率透射电子显微镜和拉曼光谱对CNx纳米管进行了形貌观察和表征.CNx纳米管的高度在20?μm左右，直径在50—100nm之间，具有明显的“竹节状”结构，结晶有序度较差.对CNx纳米管薄膜进行低场致发射性能测试：外加电场为1.4V/μm，观察到20?μA /cm2发射电流，外电场升至2.54V/μm时发射电流达到1.280mA/cm2，在较高外电场下，没有发现电流“饱和”.这比 关键词： CNx纳米管 高温热解 “竹节状”结构 场致发射     

激光诱导间质肿瘤热疗的数值模拟和实验研究

本文在考虑生物组织物性动态变化的情况下建立了激光诱导间质肿瘤热疗(LITT)的物理数学模型,采用MonteCarlo方法数值模拟了LITT中激光能量在生物组织内的传输过程,基于Pennes生物传热方程和Arrhenius方程数值求解了组织内的温度分布和热损伤体积的变化,分析了热物性及血液灌注率的动态变化对LITT过程的影响,并与相应的离体实验结果进行了对比。数值模拟结果表明,组织的热物性及血液灌注率的动态变化对于热损伤体积的变化具有重要的影响。因此在激光诱导间质肿瘤热疗的数值模拟中应该考虑热物性及血液灌注率的动态变化以期为临床治疗方案的制定提供更为准确的依据。