Laminar burning velocity measurements of liquid fuels at elevated pressures and temperatures with combustion residuals

The laminar burning velocity is a fundamental property of a fuel that affects many aspects of its combustion behaviour. Experimental values are required to validate kinetic simulations, and also to provide input for models of flashback, minimum ignition energy and turbulent combustion.A constant volume vessel (rated at 3.4 MPa) in conjunction with a multi-zone model was used to calculate burning velocity from pressure and schlieren data, allowing the user to select data uncorrupted by heat transfer or cellularity. Using the pressure rise data allows measurements to be derived for much higher pressures and temperatures than when the constant pressure data are used. A 12 term correlation for burning velocity was fitted to the data.n-Heptane, iso-octane, toluene, ethylbenzene and ethanol were tested over a wide range of initial pressures (50, 100, 200 and 400 kPa), temperatures (310, 380 and 450 K) and equivalence ratios (0.7–1.4), along with tests using combustion residuals at mole fractions of up to 0.3. The results compared favourably with the limited data already published, especially at high pressures. Conditions at the onset of cellularity are given for iso-octane.     

任意四边形薄板自然频率的加权残值法计算

本文采用变换的办法解决了加权残值法在计算任意四边形薄板问题时边界条件不易处理的困难,拓广了加权残值法在处理非规则外型固体力学问题方面的应用范围,使工程人员更易掌握板的自然频率的计算。     

Topics in the Theory of Random Noise. Vol. 1. General Theory of Random Processes. Non-Linear Transformations of Signals and Noise

Residuals from fit are often examined in regression analysis. A test suggested by Ellenberg [5] and Prescott [7] for the largest residual being an outlier is implemented through table development. Tables of critical valltes for tests at levels (α ≤ 0.10, 00.5, and 0.01 are included.     

Generating a Variable from the Tail of the Normal Distribution

The performance of three rules for dealing with outliers in small samples of size n from the normal distribution N(μ, σ²) is investigated when the primary objective of sampling is to obtain an accurate estimate of σ². It is assumed that at most one observation in the sample may be biased, arising from either N(μ + aσ, σ²) or N(μ, (1 + b) σ²). Performance of each rule is measured in terms of “Protection”, the fractional decrease in MSE obtained by using the rule when a biased observation actually is present in the sample. Numerical results have been obtained for n 5 ≤ 11 when μ is known and n = 3 when μ is unknown.     

Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems

This paper proposes a nonlinear system identification using parallel linear-plus-neural network models that provide more accurate predictions on the process behavior even on extrapolated regions. For this purpose, a residuals-based identification algorithm using parallel integration of linear orthonormal basis filters (OBF) and neural networks model is developed and analyzed under range extrapolations. Results on the van de Vusse reactor case study show enhanced extrapolation capability when compared to the conventional neural network (NN) and the series Wiener-NN models.     

Distribution-Free Life Test Sampling Plans

This paper describes life test sampling plans which assume only that the life distribution has increasing or decreasing failure rate. Tables are presented showing the minimum number of items necessary to assure a specified mean life or percentile life when the experiment time is fixed in advance.     

The Use of Partial Residual Plots in Regression Analysis

This paper defines partial residuals in multiple linear regression. The ith partial residual vector can be thought of as the dependent variable vector corrected for all independent variables except the ith variable. A plot of the ith partial residuals vs values of the ith variable is proposed as a replacement for the usual plot displaying ordinary residuals vs the ith independent variable. This partial residual plot shows the extent and direction of linearity, while displaying deviations from linearity, such as outliers, inhomogeneity of variance, and curvilinear relationships. Some alternative definitions of partial residuals are described.     

Degrees of freedom for the residuals of a principal component analysis — A clarification

Various conflicting proposals for degrees of freedom associated with the residuals of a principal component analysis have been published in the chemometrics-oriented literature. Here, a detailed derivation is given of the ‘standard’ formula from statistics. This derivation intends to be more accessible to chemometricians than, for example, the impeccable, but condensed proof that was published by John Mandel in a relatively unknown paper (J. Res. Nat. Bur. Stand., 74B (1970) 149–154). The derivation is presented in the form of a two-stage recipe that also appears to apply to more complex multiway models like the ones considered by Ceulemans and Kiers (Br. J. Math. Stat. Psych., 59 (2006) 133–150).     

Elements of Probability Theory

Graphical methods are useful for examining residuals after a model is fitted to data. In particular, probability plots can be used to identify peculiar observations and to assess whether a proposed distribution and regression relationship adequately fit the data. A simple extension of probability plotting methods is presented for regression problems where data on the dependent variable are censored on the right. Such data arise, for example, in life tests where the data are analyzed before all test units have failed. The methods are illustrated with censored data from an accelerated life test.