常减压蒸馏装置换热网络的节能优化

利用夹点技术理论对耗能严重的某炼油厂常减压蒸馏装置进行用能诊断分析;并结合热力学原理得到两种优化换热网络,节能效果显著。     

Defect detection in analog and mixed circuits by neural networks using wavelet analysis

An efficient defect-oriented parametric test method for analog & mixed-signal integrated circuits based on neural network classification of a selected circuit's parameter using wavelet decomposition preprocessing is proposed in this paper. The neural network has been used for detecting catastrophic defects in two experimental analog & mixed-signal CMOS circuits by sensing the abnormalities in selected parameters, observed under defective conditions and by their consequent classification into a proper category. To reduce complexity of the neural network, wavelet decomposition is used to perform preprocessing of the analyzed parameter. Moreover, we show that wavelet analysis brings significant enhancement in the correct classification, and makes the neural network-based test method extremely efficient & versatile for detecting hard-detectable catastrophic defects in analog & mixed-signal circuits.     

Experience in testing the Motif interface

The testing and quality assurance of the Motif 1.0 graphical user-interface software are described. The testing goals, which fell into three general categories (code coverage, defect-density, and defect-arrival rate), and a deliverable formal test suite are examined. The three phases of the testing process-evaluation, test development, and regression testing-and the tools used in testing are discussed     

Uniform and optimal schemes for stiff initial-value problems

We formulate a class of difference schemes for stiff initial-value problems, with a small parameter ε multiplying the first derivative. We derive necessary conditions for uniform convergence with respect to the small parameter ε, that is the solution of the difference scheme u_i^h satisfies |u_i^h−u(x_i)| Ch, where C is independent of h and ε. We also derive sufficient conditions for uniform convergence and show that a subclass of schemes is also optimal in the sense that |u_i^h−u(x_i)| C min (h, ε). Finally, we show that this class contains higher-order schemes.     

Galvani's frog: Harbinger of a new era

On 30 October 1786 Luigi Galvani gave the first account, at the Academy of Sciences of Bologna, about his experiments on animal electricity, of which he thought to have obtained evidence from the convulsions shown by a dissected frog, as soon as its hind-limbs were connected with the spinal cord by means of a metallic conductor. The publication of these experiments gave rise to Galvani's controversy with Volta, who denied the existence of animal electricity after discovering that there exists a potential difference between any couple of dissimilar conductors. This was a preliminary step that led Volta to the invention of the voltaic pile. Evidence of animal electricity was given about 1840 by Carlo Matteucci, using the astatic galvanometer invented by Leopoldo Nobili. This fundamental property of living organisms is now a well-advanced field of investigation by electrophysiology and bioelectrochemistry.     

Application of a leakage model to assess exfiltration from sewers.

The exfiltration of wastewater from sewer systems in urban areas causes a deterioration of soil and possibly groundwater quality. Beside the simulation of transport and degradation processes in the unsaturated zone and in the aquifer the analysis of the potential impact requires the estimation of quantity and temporal variation of wastewater exfiltration. Exfiltration can be assessed by the application of a leakage model. The hydrological approach was originally developed to simulate the interactions between the groundwater and surface water, it was adapted to allow for modelling of interactions between groundwater and sewer system. In order to approximate the exfiltration specific model parameters infiltration specific parameters were used as a basis. Scenario analysis of the exfiltration in the City of Dresden from 1997 to 1999 and during the flood event in August 2002 shows the variation and the extent of exfiltration rates.     

An asymptotically efficient ARMA estimator based on sample covariances

An asymptotically efficient autoregressive moving-average (ARMA) spectral estimator is presented, based on the sample covariances of observed time series. The estimate of the autoregressive (AR) part is shown to be identical to the optimal instrumental variable (IV) estimator in [7] although derived here using a different approach. The moving-average (MA) spectral parameter estimate is new.