电流引线迫流冷却传热分析

如何降低电流引线向低温环境的漏热,是超导电力技术领域的一项重要课题.文中概述了电流引线研究进展,建立了电流引线迫流冷却传热模型,并分析了氮气迫流冷却作用,推导了电流引线温度分布和最优长度-横截面积比(ORLA)函数式.自然蒸发迫流冷却对最优长度-横截面积比(ORLA)影响较小.     

Experimental implementation of a fixed-point duality quantum search algorithm in the nuclear magnetic resonance quantum system

In this work, we demonstrated a fixed-point quantum search algorithm in the nuclear magnetic resonance (NMR) system. We constructed the pulse sequences for the pivotal operations in the quantum search protocol. The experimental results agree well with the theoretical predictions. The generalization of the scheme to the arbitrary number of qubits has also been given.     

利用DSP底层结构提高MPEG-4编码的实时性

由于利用TMS320C6000系列的DSP底层结构可以提高图像压缩的实时性,本文在TMS320C6416平台上针对DSP底层结构对MPEG-4视频编码进行了优化,包括对8个运算单元能并行执行的特性进行汇编。针对DSP芯片两级高速缓存的工作特点,对编码器中代码和数据所占用的内存空间进行优化。利用EDMA级联特性在内存开辟双缓冲区,同时完成视频数据编码和传输的工作,从而有效地改善编码效率。实验结果表明：该编码器可以对512 pixel×512 pixel大小的灰度图像,以30 frame/s帧频进行压缩,实现了对视频图像的实时编码。     

基于改进粒子群优化算法的氩原子团簇结构优化

采用改进粒子群优化算法(IPSO)结合Lennard-Jones势对氩原子团簇结构进行优化,得到了氩原子团簇的稳态结构能量。以氩原子团簇Arn（n = 2-14）为例,验证了该方法的有效性。结果表明,应用本文提出的方法可得到对称性良好的团簇结构。与基本粒子群优化算法(BPSO)及遗传算法(GA)相比,改进粒子群优化算法具有更好的收敛特性,能较快地得到氩原子团簇结构的最优解。     

激光诱导击穿光谱实验装置的参数优化研究

为了使激光诱导击穿光谱(LIBS)实验装置中的多个关键参数达到最优化设置,以便更好地服务于煤质分析,实验中对这些参数与煤粉等离子体中待测元素发射谱线信噪比间的关系进行了详细研究,并根据信噪比大小来进行最优化参数的选择.实验结果表明,对于本LIBS实验装置,其最优化参数设置是将激光脉冲能量设为120 mJ·Pulse-1...     

高场超导MRI系统铁磁屏蔽的几何优化

磁共振成像（MRI）系统是一种重要的医学影像诊断设备,它根据核磁共振原理对处于静磁场中的人体器官进行成像,具有清晰度高和任意层面成像等优点,在医学检查和诊断方面有着重要的作用,与低场MRI相比,高场MRI系统可提高质子的磁化率,增加图像的信噪比,缩短MRI信号采集时间,从而使脑功能成像的信号变化更为明显;但是较高的背景...     

条件非线性最优扰动方法在陆面过程模式参数优化中的扩展应用初探

本文旨在探讨条件非线性最优扰动(CNOP)方法在陆面过程模式的参数优化工作方面的扩展应用.使用通用陆面模式(CoLM)和CEOP地面基准站——吉林通榆站退化草地2006年生长季的资料,针对土壤颜色、砂土比例和叶面积指数等关键模式参数,使用感热通量、潜热通量和浅层土壤温湿度作为检测变量,设计了单参数和多参数优化试验.结果表明,CONP扩展方法得到的优化参数提高了CoLM对检测变量的模拟能力,并且多参数的优化结果明显优于单参数的优化结果,在模式模拟偏差较大的土壤湿度方面改进尤为显著,此外,使用了差异进化算法( 关键词： 条件非线性最优扰动(CNOP) 陆面过程模式 参数优化     

Desarrollo de un algoritmo de optimización global en colonias de hormigas con selección de región factible para espacios continuos

This study introduces a new algorithm for the ant colony optimization (ACO) method, which has been proposed to solve global optimization problems with continuous decision variables. This algorithm, namely ACO-FRS, involves a strategy for the selection of feasible regions during optimization search and it performs the exploration of the search space using a similar approach to that used by the ants during the search of food. Four variants of this algorithm have been tested in several benchmark problems and the results of this study have been compared with those reported in literature for other ACO-type methods for continuous spaces. Overall, the results show that the incorporation of the selection of feasible regions allows the performing of a global search to explore those regions with low level of pheromone, thus increasing the feasibility of ACO for finding the global optimal solution.     

A multi-period stochastic portfolio optimization model applied for an airline company in the EU ETS

This paper aims to set up and solve a multi-period stochastic portfolio optimization model from an airline company’s point of view, considering all the specific European Union Emissions Trading Scheme (EU ETS) regulatory, managerial and trading constraints (i.e. physical constraints). Our contribution to existing academic literature is multiple. As the first ever case, we apply this technique to the aviation sector, a newly included sector within the EU ETS. More than mainly incorporating physical and technical (‘engineering’) features and focusing on short-term planning issues, we particularly address financial features and focus on mid-term planning issues. Therefore, instead of using spot prices, we run Monte Carlo simulations of correlated geometric Brownian motions (GBM) for traded futures prices of various emission allowance types for different CO₂ delivery time periods. We thereby specifically refer to the existing exchange-traded emission allowance types EU Emission Allowance (EUA) and Certified Emission Reduction (CER). By implementing actually valid and real-world-oriented regulatory constraints for EU ETS, namely managerial and trading constraints, our model implies a real-life application. We also highlight the possibility of banking and borrowing of emission allowances between CO₂ compliance periods, which is a crucial regulatory feature of EU ETS.     

Non-conflicting ordering cones and vector optimization in inductive limits

Let (E, ξ)= ind (E_n, ξ_n) be an inductive limit of a sequence (E_n, ξ_n)_{n∈ N} of locally convex spaces and let every step (E_n, ξ_n) be endowed with a partial order by a pointed convex (solid) cone S_n. In the framework of inductive limits of partially ordered locally convex spaces, the notions of lastingly efficient points, lastingly weakly efficient points and lastingly globally properly efficient points are introduced. For several ordering cones, the notion of non-conflict is introduced. Under the requirement that the sequence (S_n)_{n∈ N} of ordering cones is non-conflicting, an existence theorem on lastingly weakly efficient points is presented. From this, an existence theorem on lastingly globally properly efficient points is deduced.