原子荧光光谱法测定萤石中的微量铅

以铁氰化钾–盐酸羟胺体系代替铁氰化钾–草酸体系,建立原子荧光法测定萤石中铅含量的方法。对实验条件进行了优化,在负高压280 V,灯电流65 m A,原子化高度8 mm,还原剂3%硼氢化钾溶液(含0.5%Na OH),载流4%盐酸的工作条件下,铁氰化钾–盐酸羟胺体系有明显的增感作用。样品中Ca~(2+)含量在4 g/L之内不影响铅的测定,溶解阶段通过高氯酸冒烟赶尽HF排除氟离子的干扰,并加入硫氰酸钠–邻菲罗啉消除铁和铜等离子的干扰。测定铅的线性范围为0~80 ng/L,相关系数r=0.999 6,方法检出限为0.187μg/L,测定结果的相对标准偏差为0.25%~1.40%(n=12),加标回收率为97.8%~104.5%。该方法测定结果与电感耦合等离子体原子发射光谱法测定结果相符。原子荧光光谱法快速准确,基体干扰少,灵敏度高。     

天然气稳态运行优化的混合整数模型及其算法

天然气稳态运行优化问题的难点在于网络结构复杂、规模大、目标函数及约束高度非线性.针对其混合整数非线性规划模型,基于网络约简和线性化技术,建立了线性近似模型,并提出一种新的求解算法.将新算法用于优化我国西部天然气管网系统,结果表明所提算法是有效的.     

An efficient multi-objective PSO algorithm assisted by Kriging metamodel for expensive black-box problems

The huge computational overhead is the main challenge in the application of community based optimization methods, such as multi-objective particle swarm optimization and multi-objective genetic algorithm, to deal with the multi-objective optimization involving costly simulations. This paper proposes a Kriging metamodel assisted multi-objective particle swarm optimization method to solve this kind of expensively black-box multi-objective optimization problems. On the basis of crowding distance based multi-objective particle swarm optimization algorithm, the new proposed method constructs Kriging metamodel for each expensive objective function adaptively, and then the non-dominated solutions of the metamodels are utilized to guide the update of particle population. To reduce the computational cost, the generalized expected improvements of each particle predicted by metamodels are presented to determine which particles need to perform actual function evaluations. The suggested method is tested on 12 benchmark functions and compared with the original crowding distance based multi-objective particle swarm optimization algorithm and non-dominated sorting genetic algorithm-II algorithm. The test results show that the application of Kriging metamodel improves the search ability and reduces the number of evaluations. Additionally, the new proposed method is applied to the optimal design of a cycloid gear pump and achieves desirable results.     

A Kriging-based constrained global optimization algorithm for expensive black-box functions with infeasible initial points

In many engineering optimization problems, the objective and the constraints which come from complex analytical models are often black-box functions with extensive computational effort. In this case, it is necessary for optimization process to use sampling data to fit surrogate models so as to reduce the number of objective and constraint evaluations as soon as possible. In addition, it is sometimes difficult for the constrained optimization problems based on surrogate models to find a feasible point, which is the premise of further searching for a global optimal feasible solution. For this purpose, a new Kriging-based Constrained Global Optimization (KCGO) algorithm is proposed. Unlike previous Kriging-based methods, this algorithm can dispose black-box constrained optimization problem even if all initial sampling points are infeasible. There are two pivotal phases in KCGO algorithm. The main task of the first phase is to find a feasible point when there is no feasible data in the initial sample. And the aim of the second phase is to obtain a better feasible point under the circumstances of fewer expensive function evaluations. Several numerical problems and three design problems are tested to illustrate the feasibility, stability and effectiveness of the proposed method.     

A generalized elastic net regularization with smoothed $$\ell _{q}$$ penalty for sparse vector recovery

In this paper, we propose an iterative algorithm for solving the generalized elastic net regularization problem with smoothed \(\ell _{q} (0<q \le 1)\) penalty for recovering sparse vectors. We prove the convergence result of the algorithm based on the algebraic method. Under certain conditions, we show that the iterative solutions converge to a local minimizer of the generalized elastic net regularization problem and we also present an error bound. Theoretical analysis and numerical results show that the proposed algorithm is promising.     

流体力学Petrov-Galerkin有限元法研究进展

详细评述了在流体力学分析中Ｐｅｔｒｏｖ－Ｇａｌｅｒｋｉｎ方法（主要是ＳＵＰＧ方法和ＧＬＳ方法）的研究进展，并提出了今后的发展方向和研究重点。     

多相位激励随机地震响应快速算法

对多支承激励间存在相位差的平稳随机响应分析问题给出了计算各种自谱密度及互谱密度的快速直接算法。此法计入了所有参振振型间的互相关项，以及各激励间的互相关项，是快速、简便、精确的频域分析方法，并可用实振型方便地处理非正交阻尼矩阵。     

用人工产生的拟湍流信号检验相干结构的检测方法

本文利用计算机产生拟湍流脉动信号，将数据进行频谱分析和能谱分析，发现湍流中相干结构不仅包合低频成分还包含一定数量高频成分，因而简单地认为湍流中低频部分是相干结构而高频部分是小尺度脉动，来确定相干结构能量在湍流中所占成分是不科学的；本文还将得到的数据用几种条件采样方法检测相干结构数量和位置，以此判断检测方法的优劣，发现就这类信号而言ＭＵ—ＬＥＶＥＬ法要比ＶＩＴＡ法准确性要高一些。     

轴向移动系统的参数振动问题研究进展

对近二十年来轴向移动系统(移动弦，移动梁和移动带等)的参数振动研究进展进行了详细的评述，特别关注了轴向张紧力和移动速度随时间改变时轴向移动系统的参数振动特性和稳定性等问题。文章首先讨论了所研究问题的控制方程。然后详细说明了目前研究中人们较为关注的几个重点问题，如参数激励的形式，求解方法和所研究的问题等。接着在其后的两节中，分别评述了在张紧力和移动速度随时间变化时，轴向移动弦和轴向移动梁的振动问题近年来的研究进展，详细、深入讨论了模型的类型、张紧力和轴向移动速度随时间变化的形式以及在研究中使用的解题方法和系统的振动特性(振动响应、固有频率和动态稳定性)等；最后给出了在此领域今后研究中应关注的问题。     

香港全风化花岗岩饱和直剪试验中的剪胀问题

通过对全风化花岗岩的慢剪试验,指出了在直剪试验中出现的两种垂直位移变化形式,其对土体的剪胀剪缩性质的 反映与三轴试验是一致的。剪胀的发生与土体的密实程度密切相关;随垂直压力的增大,剪胀发生所需剪应力也增大;剪应 力达到峰值所需要剪位移总是比剪胀发生时所需的剪位移大。