岩石三轴蠕变试验黏弹性解析及参数识别

基于岩石三轴蠕变试验,推导了相应的黏弹性解析解,并对三参量H-K流变模型给出了黏弹性解析解的显式以及流变参数的识别方法. 在此基础上,针对花岗岩及片岩两种岩石的室内蠕变分级加载试验曲线进行了流变参数的识别与反演. 分析表明,同一岩样在不同加载级别下的弹性及黏弹性参数在量值上均有所不同,其中黏弹性模量和黏滞系数的量值随载荷的增加出现损伤衰减,基于试验反演所获参数的解析蠕变曲线与试验蠕变曲线吻合较好.     

T形型钢混凝土柱正截面承载力的计算方法探讨

在总结了型钢混凝土(SRC)柱承载力计算一般方法的基础上,针对T形型钢混凝土柱,结合中国现行规范,分析了此种柱的受力特点和破坏模式,提出T形型钢混凝土柱正截面极限承载力的计算方法,并采用该方法对一T形型钢混凝土柱的承载力进行验算. 结果表明与试验数据吻合较好,说明本文方法具有较好的精确度和适用性.     

Field measurement for superconducting magnets of ADS injector Ⅰ

A superconducting magnet prototype for Accelerator Driven Sub-critical System Injection-Ⅰ had been designed and fabricated, and tested in a new made vertical Dewar in November 2012. Batch magnet production was processed after some major revision from the magnet prototype, they include: removing off the perm-alloy shield, extending the iron yoke, using thin superconducting wire, etc. The first one of the batch magnets was tested in the vertical Dewar at the Harbin Institute of Technologyin in September 2013. A field measurement was carried out at the same time by the measurement platform that was seated on the top of the vertical Dewar,the measurement results met the design requirements. This paper will present the field measurement system design, measurement results and discussion on the residual field from the persistent current effect.     

Goodness-Of-Fit Tests Based on Estimated Expectations of Probability Integral Transformed Order Statistics

New goodness-of-fit tests, based on bootstrap estimated expectations of probability integral transformed order statistics, are derived for the location-scale model. The resulting test statistics are location and scale invariant, and are sensitive to discrepancies at the tails of the hypothesized distribution. The limiting null distributions of the test statistics are derived in terms of functionals of a certain Gaussian process, and the tests are shown to be consistent against a broad family of alternatives. Critical points for all sample sizes are provided for tests of normality. A simulation study shows that the proposed tests are more powerful than established tests such as Shapiro-Wilk, Cramér-von Mises and Anderson-Darling, for a wide range of alternative distributions.     

Asymptotically minimax testing ofr>2 simple hypotheses

In this paper, we consider the problem of asymptotically minimax testing ofr≥2 simple hypotheses when a general stochastic process is observed. We establish general conditions for the exponential decrease of maximal probability errors of minimax tests as the number of observations increases. At the present time, similar results for testing several multinomial schemes were obtained by Salihov [8]. Similar results for testing two simple hypotheses were obtained in [5]. In the proofs of the main results, we use the theory of large deviations ([3], [2]). In Sec. 1, the main result is proved. In Secs. 2–4, we analyze the i.i.d. case, nonhomogeneous Poisson processes, and renewal processes as examples. Published in Lietuvos Matematikos Rinkinys, Vol. 40, No. 3, pp. 313–320, July–September, 2000.     

Investigation of the limitations of saturated fractional factorial experimental designs,with confounding effects for an HPLC ruggedness test

Summary Recently much attention has been directed to the validation of analytical methods. The level of validation will depend on the method application. If a method is developed for general use, for instance by different analysts, instruments or laboratories, then the effect of these changes need evaluation. This is normally referred to as ruggedness testing, where the limitations of the method to changes in the specified conditions are examined.This paper examines the use of Plackett-Burman fractional factorial experiment designs for ruggedness testing in high performance liquid chromatography (HPLC). The ability of these designs to identify confounding effects is applied to the stability indicating analysis of Salbutamol and its major degradation product, AH4045. The results show that confounding effects, proving extremely pertinent to HPLC, can be identified.The assay proved rugged to most tested changes although not to the use of column packing material from different manufacturers.     

Qsar Models for Predicting the Acute Toxicity of Selected Organic Chemicals with Diverse Structures to Aquatic Non-Vertebrates and Humans

Abstract

The linear and non-linear relationships of acute toxicity (as determined on five aquatic non-vertebrates and humans) to molecular structure have been investigated on 38 structurally-diverse chemicals. The compounds selected are the organic chemicals from the 50 priority chemicals prescribed by the Multicentre Evaluation of In Vitro Cytotoxicity (MEIC) programme. The models used for the evaluations are the best combination of physico-chemical properties that could be obtained so far for each organism, using the partial least squares projection to latent structures (PLS) regression method and backpropagated neural networks (BPN). Non-linear models, whether derived from PLS regression or backpropagated neural networks, appear to be better than linear models for describing the relationship between acute toxicity and molecular structure. BPN models, in turn, outperform non-linear models obtained from PLS regression. The predictive power of BPN models for the crustacean test species are better than the model for humans (based on human lethal concentration). The physico-chemical properties found to be important to predict both human acute toxicity and the toxicity to aquatic non-vertebrates are the n?octanol water partition coefficient (Pow) and heat of formation (HF). Aside from the two former properties, the contribution of parameters that reflect size and electronic properties of the molecule to the model is also high, but the type of physico-chemical properties differs from one model to another. In all of the best BPN models, some of the principal component analysis (PCA) scores of the ¹³C-NMR spectrum, with electron withdrawing/accepting capacity (LUMO, HOMO and IP) are molecular size/volume (VDW or MS1) parameters are relevant. The chemical deviating from the QSAR models include non-pesticides as well as some of the pesticides tested. The latter type of chemical fits in a number of the QSAR models. Outliers for one species may be different from those of other test organisms.