Since its observation in 1985 nuclear resonant scattering of synchrotron radiation has become an excellent tool to study hyperfine
interactions in solids. It combines the advantages of both local probe experiments and scattering techniques and gives valuable
information on magnetic and electronic structures in case of NFS experiments. Experiments benefit from the outstanding beam
quality of 3rd generation synchrotron radiation sources, as the small beam size and divergence.
This revised version was published online in August 2006 with corrections to the Cover Date. 相似文献
Two types of Equations of State (EoS), which are characterized here as “simple” and “complex” EoS, are evaluated in this study. The “simple” type involves two versions of the Peng–Robinson (PR) EoS: the traditional one that utilizes the experimental critical properties and the acentric factor and the other, referred to as PR-fitted (PR-f), where these parameters are determined by fitting pure compound vapor pressure and saturated liquid volume data. As “complex” EoS in this study are characterized the EoS derived from statistical mechanics considerations and involve the Sanchez–Lacombe (SL) EoS and two versions of the Statistical Associating Fluid Theory (SAFT) EoS, the original and the Perturbed-Chain SAFT (PC-SAFT).
The evaluation of these two types of EoS is carried out with respect to their performance in the prediction and correlation of vapor liquid equilibria in binary and multicomponent mixtures of methane or ethane with alkanes of various degree of asymmetry. It is concluded that for this kind of systems complexity offers no significant advantages over simplicity. Furthermore, the results obtained with the PR-f EoS, especially those for multicomponent systems that are encountered in practice, even with the use of zero binary interaction parameters, indicate that this EoS may become a powerful tool for reservoir fluid phase equilibria modeling. 相似文献
We study a linear discrete-time partially observed system perturbed by a white noise. The observations are transmitted to
the estimator via communication channels with irregular transmission times. Various measurement signals may incur independent
delays, arrive at the estimator out of order, and be lost or corrupted. The estimator is given a dynamic control over the
sensors by taking part in producing the signals to be sent via the channels. The minimum variance state estimate and the optimal
sensor control strategy are obtained. Ideas of model predictive control are applied to derive a nonoptimal but implementable
in real time method for sensor control
This work was supported by the Australian Research Council. 相似文献
State space methods have proved to be powerful theoretical and computational tools in a number of areas of applications, in particular filtering and control theory. In this paper we advocate the use of state space methods for the study of discrete probability densities on the set {0,1,2,…}. The fundamental approach is to consider the class
of all discrete probability densities that can be represented as the impulse response/convolution kernel of a finite dimensional discrete time state space system. We show that all standard operations such as the calculation of moments, convolution, scaling, translation, product, etc. can be carried out using system representations. 相似文献