抽取信号的χ2分布拟合方法

BESⅡ上测量ψ(2S)辐射衰变时, 鉴于本底道的污染非常严重, 提出了一种抽取信号事例数的χ²拟合方法. 大量的蒙特卡罗模拟表明, 信号道与各个本底道的χ²分布形状各不相同. 这些特点提供了从数据的χ²分布中抽出信号道事例数的χ²拟合方法. 从蒙特卡罗模拟的结果来看, χ²拟合方法的误差小于2%.     

Tailoring the absorption distribution in lamp-pumped solid-state lasers with fused silica light-guides

An analysis is made on the absorption distribution within a cylindrical active medium lamp pumped by means of fused silica light-guides. The performances of the proposed pump cavities are analysed through a non-sequential 3D ray-trace program and are compared to those of three reflective chambers: an elliptical cavity, a close-coupled cavity and a diffusive close-wrap cavity. Two light-guides cavities with eight and nine guides, respectively, were built and tested. High coupling efficiency and a reasonable uniform absorption distribution were registered. An overall laser efficiency of 1% was measured. The proposed cavities have permitted the tailoring of the absorption distribution within the laser rod.     

CARS methane spectra: Experiments and simulations for temperature diagnostic purposes

CARS laboratory experiments were done in the 2905–2925 cm⁻¹ range, in the vicinity of the ν₁ band of the methane molecule, for pressures ranging from 1 to 50 bar, and temperatures up to 1100 K. These experiments were carried out in order to retrieve the pressure evolution of the CH₄ spectrum, as well as to confirm its temperature dependance. After a brief recall on the theory used to compute pressure broadening coefficients and relaxation rates, we consider the ν₃ and ν₄ infrared bands of methane for benchmark calculations purposes. Next, we present recent experimental CARS spectra and calculated ones. Lastly, we discuss flame experiments as well as comparisons of temperature retrieval using N₂ and CH₄ as probe molecules.     

Time-frequency analysis of transient dispersive waves: A comparative study

The goal in this work is to investigate the effectiveness of time-frequency representations for analysing dispersive waves by comparing the performance of three different methods. In particular, the smoothed pseudo-Wigner distribution, the continuous wavelet transform and the Hilbert-Huang transform are compared and evaluated in terms of their ability to analyse dispersive elastic waves. The waves under consideration are transient flexural ones generated by an impact in a beam. In view of the results of the comparative study, the advantages and shortcomings of each method are presented and discussed.     

CO2-broadened water in the pure rotation and ν2 fundamental regions

The CO₂-broadened water coefficients (half-widths, line shifts, and temperature dependence of the widths) are predicted using a fully complex Robert-Bonamy formulation for the 937 allowed and forbidden perpendicular type transitions of (000)-(000) between 200 and 900 cm⁻¹ in order to facilitate atmospheric remote sensing of Mars and Venus. In addition, empirical Lorentz line widths and pressure-induced frequency-shifts of CO₂-broadened H₂¹⁶O are obtained at room temperature for 257 perpendicular transitions of the (010)-(000) fundamental. For this, calibrated spectra recorded at 0.0054 cm⁻¹ resolution are measured assuming Voigt line shapes. For transitions between 1287 and 1988 cm⁻¹ with rotational quanta up to J = 13 and K_a = 6, the widths vary from 0.045 to 0.212 cm⁻¹ atm⁻¹ at 300 K; the pressure-shifts are quite large and range from −0.0386 to +0.0436 cm⁻¹ atm⁻¹. For the (010)-(000) band, the RMS and mean observed and calculated differences for CO₂-broadened H₂O half-widths are 12% and −1.9%, respectively, while the RMS and mean ratios of the observed and calculated pressure-induced shift coefficients are 1.6 and 0.79, respectively. For pairs of transitions involving K_a = 0 and 1, such as 2_0 2 ← 3_1 3 and 3_1 3 ← 2_0 2, both the calculated and observed pressure induced shifts in positions are opposite in sign and often similar in magnitude. The data are too limited to characterize vibrational dependencies of the widths, however.     

Multivariate Normal Slice Sampling

By introducing auxiliary variables, the traditional Markov chain Monte Carlo method can be improved in certain cases by implementing a “slice sampler.” In the current literature, this sampling technique is used to sample from multivariate distributions with both single and multiple auxiliary variables. When the latter is employed, it generally updates one component at a time.

In this article, we propose two variations of a new multivariate normal slice sampling method that uses multiple auxiliary variables to perform multivariate updating. These methods are flexible enough to allow for truncation to a rectangular region and/or exclusion of any n-dimensional hyper-quadrant. We present results of our methods and existing state-of-the-art slice samplers by comparing efficiency and accuracy. We find that we can generate approximately iid samples at a rate that is more efficient than other methods that update all dimensions at once. Supplemental materials are available online.     

Multivariate Normal Probabilities: Implementing an Old Idea of Plackett's

This article describes a reduction formula for the computation of multivariate normal probabilities first developed by Plackett. The method is recursive and, despite very promising results, seems not to have been implemented before. Extensive numerical results are given to compare the effectiveness of the approach to other methods from the literature.     

Effect of particle agglomeration and interphase on the glass transition temperature of polymer nanocomposites

In this article, we utilize finite element modeling to investigate the effect of nanoparticle agglomeration on the glass transition temperature of polymer nanocomposites. The case of an attractive interaction between polymer and nanofiller is considered for which an interphase domain of gradient properties is developed. This model utilizes representative volume elements that are created and analyzed with varying degrees of nanoparticle clustering and length scale of interphase domain. The viscoelastic properties of the composites are studied using a statistical approach to account for variations due to the random nature of the microstructure. Results show that a monotonic increase in nanofiller clustering not only results in the loss of interphase volume but also obstructs the formation of a percolating interphase network in the nanocomposite. The combined impacts lead to a remarkable decrease of T_g enhancement of clustering nanofillers in comparison with a well‐dispersed configuration. Our simulation results provide qualitative support for experimental observations that clustering observed at high nanofiller concentrations negatively impacts the effects of the nanofiller on overall properties. © 2011 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2011     

Enthalpy distributions and densities of states in linear polymers

Using polypropylene as an example, we applied a method we have recently developed to calculate the probability distribution of enthalpy from the temperature dependence of the heat capacity. The method involves the use of local temperature expansions of the heat capacity to calculate a set of moments of the enthalpy distribution. Using the maximum‐entropy method, one can then construct the enthalpy distribution for the system. The method is completely model free. The enthalpy distribution so obtained is the analogue of the Maxwell–Boltzmann distribution of kinetic energies for a gas, and like that function, tells one the distribution of enthalpies that an average unit in the polymer chain can have, a quantity that is crucial to understanding the chemical and physical properties of a polymer. Given the enthalpy distribution, one can then calculate the Gibbs free energy and the density of states that correspond to a particular value of enthalpy, thus giving one an expanded thermodynamics of the system in addition to the usual average quantities. We illustrate the fact that the Gibbs free‐energy distribution for this system scales as a simple function of temperature and that the density‐of ‐states function yields a simple empirical partition function for the system giving both the average thermodynamics and the distribution functions. © 2001 John Wiley & Sons, Inc. J Polym Sci Part B: Polym Phys 39: 1513–1518, 2001     

Demand dispersion and logistics costs in one-to-many distribution systems

When an organization decides on which groups of consumers it should target, the locations of these target consumers often play a role. Methods from the field of market segmentation are able to identify target groups with high benefit levels, but the expected costs of supplying products to the target groups are less well understood. These costs can play a large role if the locations of the customers, the demand locations, are geographically widely dispersed. This paper focuses on one-to-many distribution systems in which a central facility serves all demand points. We derive accurate logistics cost estimates from the dispersion of demand points for such systems, enabling a comparison of the expected logistics costs of different candidate target groups. The most accurate measure combines the average distance from the demand locations to a central location and the mutual distances between neighboring demand locations. The average of the distances between all pairs of locations forms a good alternative measure.