房间声学系统非线性确定性的替代数据法检测

实际房间声学系统是否具有非线性确定性是声学信号处理中值得研究的问题。采用替代数据法对实际房间声学系统的非线性确定性进行检测,假设实际系统响应是由平稳高斯随机过程经可逆、静态的非线性函数变换而得到,然后对该假设进行检验。由于实际实验所得的假设检验结果不能拒绝该假设,所以在给定实验条件下利用替代数据法不能得出实际房间声学系统具有非线性确定性的结论。对实际房间声学系统非线性确定性的判定可以通过利用其它的非线性分析技术及改善实验条件作进一步研究。     

胎儿心率信号的替代数据分析

利用基于关联维数的振幅调节傅里叶变换的替代数据法对健康的和病态的胎儿心率(Fetal heart rate,即FHR)时间序列进行了分析,给出了胎儿心率时间序列非线性和混沌特性的判定方法,计算结果表明健康的胎儿心率信号的混沌判据S＞2,非线性t检验t＞tαf,说明健康信号具有非线性混沌特性;而病态的胎儿心率信号的混沌判据S＜2,说明病态信号不具有混沌特性.     

Functional barriers in PET recycled bottles. Part I. Determination of diffusion coefficients in bioriented PET with and without contact with food simulants

A major outcome for recycled plastics consists of making food packaging materials. However, any contamination of collected plastics with chemicals may then be of concern for public health. A solution to mind migration is to use a layer of virgin polymer, named functional barrier, intercalated between the recycled layer and the food. This article aims to provide experimental values of diffusion coefficients (D) of model pollutants (surrogates) in poly(ethylene terephthalate) (PET) to be used for modeling migration through functional barriers. Diffusion coefficients of a large set of surrogates at low concentrations in PET were measured in various conditions. A solid‐to‐solid diffusion test was designed to avoid the use of a solvent that may induce plasticizing of the material and partitioning effects at the interface. Using [Log D = f(molecular weight)] correlations, the values of diffusion coefficients and activation energies of the surrogates measured by this method were shown to be consistent with the literature data obtained for gases, in permeation experiments, where no plasticization occurred. Migration from PET into food simulants was then studied. Migration into an aqueous medium is largely influenced by the solubility of the surrogates, the less soluble ones being not detected, despite high D values. With ethanol solvent, there were no partitioning effects, and the high plasticization effect of PET by ethanol considerably increases the apparent diffusion coefficients. The effects of temperature and plasticization on the relationship between diffusion coefficients and molecular weight are discussed. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 92: 2845–2858, 2004     

Overestimated diffusion coefficients for the prediction of worst case migration from PET: application to recycled PET and to functional barriers assessment

This paper defines parameters that can be used to predict worst‐case migration from recycled PET bottles, with and without a functional barrier. Starting with a set of diffusion coefficients determined in well‐defined experimental conditions (temperature, presence or not of a solvent, with and without swelling effect), empirical equations for the diffusion coefficient of a migrant or a pollutant in PET at 40°C are given as a function of its molecular weight. An equation is also derived for migration from PET into water. Surrogates representative of worst‐case migrants are identified and are discussed in terms of molecular weight, structure and interaction with the PET matrix. In the second part of the paper, the empirical equations have been used to simulate the migration from monolayer bottles and from multilayer bottles with different geometries of functional barrier, as a function of the pollutants' molecular weight. Since the diffusion coefficients are overestimated, the calculated migration is also overestimated, which provides a margin of safety. The advantage of the functional barrier technology is compared to the direct food contact route, as a function of food contact time. In the last part of the paper, the effect of testing temperature is investigated. Based on a literature survey, the activation energy of pollutants is shown to increase roughly with their molecular weights. A worst‐case activation energy of 80 kJ/mol is proposed, allowing extrapolation of migration data from a higher temperature (values calculated at 40°C or determined at 60°C) to room temperature. The possible use of this activation energy to design tests for functional barriers is discussed. Copyright © 2004 John Wiley & Sons, Ltd.     

Experimental direct evaluation of functional barriers in PET recycled bottles: comparison of migration behaviour of mono‐ and multilayers

Recycling of used bottles into new bottles is associated with possible migration of pollutants arising from the previous life of the packages. To reduce or delay such migration, the recycled resin is depolluted or a functional barrier layer made of virgin plastics is used. Testing migration from such recycled bottles relies on the use of model pollutants (surrogates). In order to enable modelling of migration kinetics, each step of the use of surrogates is carefully investigated here in the case of PET. First, criteria underlying the selection of surrogates are carefully examined; together with volatility, polarity and diffusion behaviour, it is shown here that their solubility in the food simulant and their chemical stability strongly influence migration results. For aqueous test media, 2,4‐pentanedione and phenol should be used as surrogates. Second, a procedure is developed to impregnate surrogates at very large concentrations (several thousands of mg/kg PET) which are necessary to monitor migration kinetics. This procedure, which uses dichloromethane as solvent, allows a quick and reproducible impregnation, not sensitive to temperatures between 11–23°C, factors which favour its use at a plant scale. Third, flakes impregnated with this procedure are processed into bottles, and their physicochemical properties are compared to those of commercial bottles. Last, monolayer and tri‐layer polluted bottles (model pollutants in inner layer) are tested for migration for more than 1.5 years. With multilayers, the migration lag time of the fastest surrogates is 6 months with 3% acetic acid and 3 months with ethanol as the simulant, due to plasticization of PET by ethanol. The sequence of migration of surrogates is different with monolayer and multilayer bottles, which shows that partition effects (solubility) play an essential role, especially with monolayer materials. Copyright © 2005 John Wiley & Sons, Ltd.     

A novel surrogate-based approach for optimal design of electromagnetic-based circuits

A new geometric design centring approach for optimal design of central processing unit-intensive electromagnetic (EM)-based circuits is introduced. The approach uses norms related to the probability distribution of the circuit parameters to find distances from a point to the feasible region boundaries by solving nonlinear optimization problems. Based on these normed distances, the design centring problem is formulated as a max–min optimization problem. A convergent iterative boundary search technique is exploited to find the normed distances. To alleviate the computation cost associated with the EM-based circuits design cycle, space-mapping (SM) surrogates are used to create a sequence of iteratively updated feasible region approximations. In each SM feasible region approximation, the centring process using normed distances is implemented, leading to a better centre point. The process is repeated until a final design centre is attained. Practical examples are given to show the effectiveness of the new design centring method for EM-based circuits.     

EM‐based yield optimization exploiting trust‐region optimization and space mapping technology

Design centering is a design problem which looks for nominal values of circuit parameters that maximize the probability of satisfying the design specification (yield function). Direct yield optimization of electromagnetic (EM)‐based circuits is obstructed by the high expense of EM simulations required in the yield estimation process. Also, the absence of any gradient information represents an obstacle against the optimization process. In this article, a new approach for design centering and yield optimization of EM‐based circuits is introduced. In the proposed approach, the generalized space mapping (SM) technique is incorporated with a derivative‐free trust region optimization method (NEWUOA). Moreover, a variance reduction sampling technique is implemented in the yield estimation process. Two techniques suitable for the microwave circuit design centering process are introduced. The first technique exploits the surrogate developed using any circuit optimizer, for example, minimax optimizer, in the yield maximization process. While the second technique iteratively constructs and updates an SM surrogate during the yield optimization process. Our novel approach is illustrated by practical examples showing its efficiency. One of the examples is entirely designed within the sonnet em environment. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:474–484, 2015.     

Noise Strategy in Robust Design: What Aspects of Noise Factors are Important in Quality Engineering?

The correlation and variances of noise factors induced during robust design may influence the success of the quality engineering process. A model-based approach is employed to quantify these influences. The results are then checked using two case studies. It was determined that for systems having no significant three-factor interactions, correlation among the noise factors can be safely neglected and it is often helpful to amplify the magnitude of induced noise. Otherwise, noise factors should be used that match the true magnitude and correlation in field conditions. Based on these results, a procedure is suggested for a noise strategy in quality engineering.     

Sparse polynomial surrogates for non-intrusive,high-dimensional uncertainty quantification of aeroelastic computations

This paper is concerned with aircraft aeroelastic interactions and the propagation of parametric uncertainties in numerical simulations using high-fidelity fluid flow solvers. More specifically, the influence of variable operational and structural parameters (random inputs) on the drag performance and deformation (outputs) of a flexible wing in transonic regime, is assessed. Because of the complexity of fluid flow solvers, non-intrusive uncertainty quantification techniques are favored. Polynomial surrogate models based on homogeneous chaos expansions in the random inputs are commonly considered in this respect. The polynomial expansion coefficients are constructed using either structured sampling sets of the input parameters, as Gauss quadrature nodes, or unstructured sampling sets, as in Monte-Carlo methods. In complex systems such as the advanced aeroelastic test case studied here, the output quantities of interest generally depend only weakly on the multiple cross-interactions between the random inputs. Consequently, only low-order polynomials significantly contribute to their surrogates, which thus have a sparse structure in the underlying polynomial bases. This feature prompts to use compressed sensing, or compressive sampling theory for the construction of the polynomial surrogates. The proposed methodology is non-adapted and considers unstructured sampling sets orders of magnitude smaller than the ones required by the usual techniques with structured sampling sets. It is illustrated in the present work for a moderately to high dimensional parametric space.