A calibration method for the energy-integrating function in photovoltaic system monitoring

Solar radiation has an irregularly varying factor due to a basic day and night cycle and climatic conditions. For such conditions a data sampling interval is important to ensure the accuracy of energy monitoring in a photovoltaic system. While treating a system monitoring equipment as a black box. the author has developed the method of calibrating an energy-integrating function. At first for various input waveforms, the relationship between sampling intervals and quasi-integration outputs have been examined by trapezoidal rule. In the numerical simulation the phases of the sampling clock also are considered Then it is concluded that a sampling interval can be inspected through outside observation only by using a rectangular single pulse. By applying the pulse to the energy-integrating process, two kinds of integrated outputs can be obtained for different sampling phases. The calculated difference between both outputs can uniquely give the sampling interval being inspected. Conditions to ensure measuring accuracy are discussed and the validity of this method has been demonstrated experimentally. Practical calibrating procedures also are proposed for the integrating function of PV system monitoring.     

农药残留分析样品前处理技术新进展

介绍了近年来农药残留样品前处理技术的新进展,并对此进行了评述和展望。     

Performance evaluation of an importance sampling technique in a Jackson network

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.     

悬浮液进样-火焰原子吸收光谱法测定茶叶中的微量铬

将茶叶悬浮于琼脂胶体中制成悬浮液 ,直接喷入空气 -乙炔火焰 ,用火焰原子吸收光谱法测定茶叶中的微量铬 ,方法简便、快速、灵敏度和精密度高、测定结果与用灰化法处理样品一致 ,检验表明 ,两种样品前处理方法之间无显著性差异。相对标准偏差为 3.4 %～ 6 .1% ,加标回收率为 95 .7%～ 10 3.8 %。     

Chemical Composition Determination at the Bottom Region of a Recovery Boiler Furnace by Direct Minimization of Gibbs Free Energy

An optimization strategy has been applied to describe the chemical composition at the furnace bottom in the Kraft recovery boiler of a pulp production process. The concentrations of each involved chemical species were calculated through an optimization approach, minimizing the Gibbs free energy of the system. Various systems were proposed and tested, assuming different chemical species and phases number. Because serious initialization problems were found at this stage for some of the proposed systems, an optimization heuristic method (PSO) was used for the first approach to the problem. Once the appropriate phases number and chemical species in the system were determined, the initialization problems disappeared and the use of a deterministic optimization method (SQP) became viable. The proposed approach has shown to be satisfactory to reproduce industrial data and also data reported in the open scientific literature.     

Coordinate descent with arbitrary sampling I: algorithms and complexity†

We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we call ALPHA. Our method at every iteration updates a random subset of coordinates, following an arbitrary distribution. No coordinate descent methods capable to handle an arbitrary sampling have been studied in the literature before for this problem. ALPHA is a very flexible algorithm: in special cases, it reduces to deterministic and randomized methods such as gradient descent, coordinate descent, parallel coordinate descent and distributed coordinate descent—both in nonaccelerated and accelerated variants. The variants with arbitrary (or importance) sampling are new. We provide a complexity analysis of ALPHA, from which we deduce as a direct corollary complexity bounds for its many variants, all matching or improving best known bounds.     

Distribution, relative abundance, and prey demand by double-crested cormorants on Manitoulin Island lakes vs. Lake Huron Coast

An aerial distance sampling survey of double-crested cormorants (Phalacrocorax auritus) was conducted in the northern region of Lake Huron (North Channel; four largest lakes of Manitoulin Island; South Shore of Manitoulin Is. facing the main body of the lake) to assess the relative distribution, abundance and prey demand by cormorants on inland lake vs. coastal habitat. On a per area basis, the density (approx. 1-2 cormorants ? km^− 2) and prey demand (approx. 1.2 kg ha^− 1) of cormorants in the four inland lakes matched that of the North Channel. The South Shore had approximately half the density and prey demand as the other two areas. Cormorants on the inland lakes of Manitoulin Island represented 13% early in the season and a high of 33% of the total population for this region of Lake Huron later in the summer. Estimating regional distributions of cormorants within the Great Lakes basin is important because mapped nest colonies and nest counts are not representative of the actual distribution of foraging cormorants during and after the nesting season. There are two general conclusions to emerge from this survey. First, aquatic productivity from both Great Lakes coast and inland lakes contributes to trends in population and distribution of cormorants in the northern region of Lake Huron and perhaps elsewhere. Second, inland aquatic ecosystems are important throughout a season for foraging cormorants from the Great Lakes and may become more important as Great Lake productivity trends downward.     

Molecular simulation of phase coexistence: Finite-size effects and determination of critical parameters for two- and three-dimensional Lennard-Jones fluids

Abstact The subject of this paper is the investigation of finite-size effects and the determination of critical parameters for a class of truncated Lennard-Jones potentials. Despite significant recent progress in our ability to model phase equilibria in multicomponent mixtures from direct molecular simulations, the accurate determination of critical parameters remains a difficult problem. Gibbs ensemble Monte Carlo simulations with systems of controlled linear system size are used to obtain the phase behavior in the near-critical region for two- and three dimensional Lennard-Jones fluids with reduced cutoff radii of 3, 3.5, and 5. For the two-dimensional systems, crossover of the effective exponent for the width of the coexistence curve from mean field ( = 1/2 in the immediate vicinity of the critical point to Ising-like (= 1/8) farther away is observed. Critical parameters determined by fitting the data that follow Ising-like behavior are in good agreement with literature values obtained with finite-size scaling methods. For the three-dimensional systems, no crossover to mean field-type behavior was apparent. Extrapolated results for the critical parameters are consistent with literature estimates for similar fluids. For both two- and three-dimensional fluids, system size effects on the coexistence curves away from the critical point are small, normally within simulation statistical uncertainties.Invited paper presented at the Twelfth Symposium on Thermophysical Properties, June 19–24, 1994, Boulder. Colorado, U.S.A.     

Efficient conditional probability theorem and importance sampling-based methods for global reliability sensitivity analysis

Global reliability sensitivity (GRS) analysis can measure the effect of random inputs on failure probability (FP). To efficiently solve GRS, two conditional probability theorem (CPT)-based methods are proposed by combining adaptive Kriging (AK) with importance sampling (IS) (CPT-AK-IS) and combining AK with Meta-IS (CPT-AK-Meta-IS) respectively. Firstly, differentiation approximation and CPT are used to convert the estimation of conditional probability density function (PDF), which is required by the existing Bayes theorem-based methods, into that of a series of probabilities. Secondly, GRS can be directly estimated by the failure samples of IS, while the existing Bayes theorem methods based on IS need to transform the failure samples of IS into those of original PDF. Both the first and second strategies can reduce the computational complexity of solving GRS. Thirdly, by selecting a suitable differentiation interval with a proposed adaptive strategy, the estimation of a series of probabilities can be accurately completed as a byproduct of one IS based simulation for solving FP without additional computational cost. Finally, by introducing AK into IS and Meta-IS, it can reduce the number of evaluating performance function and the size of candidate sample pool simultaneously. These novelties are sufficiently verified by the presented examples.