评过剩吸附量和绝对吸附量关系式的不正确性

页岩吸附气和煤层吸附气都是重要的非常规天然气资源。该资源的评价依赖于在不同压力下等温累积吸附量的计算和等温饱和吸附量的确定。不同压力下的等温累积吸附量,需要通过吸附仪的测试资料,利用有关的计算方法求得。基于1976年Adamson(阿达姆森)提出的固相对气相吸附质量的关系式是不确定的,因此,1998年Donohue和Aranovich引用Adamson的吸附关系式,并提出过剩吸附量和绝对吸附量及其关系式也是不正确的。周理等于2000年发表的文章,确认和引用了Donohue和Aranovich过剩吸附量和绝对吸附量及其关系式同样是不正确的。在2015至2018年间,俞凌杰等沿用周理等的过剩吸附量和绝对吸附量关系式,发表了多篇论文。通过本文的研究,认为过剩吸附量和绝对吸附量是两个缺少物理定义和使用价值的伪名词,两者之间的关系式也是不正确的。利用过剩吸附量和绝对吸附量的关系式根本得不到等温吸附量、等温累积吸附量和等温饱和吸附量。

消除“政治上的不正确”,重拾迷失的文明

从社会存在的对某些职业,残疾人的歧视称呼这两个领域,探讨了汉语中的政治上的不正确性语言,以及其负面影响,并提出一些建议。

Finite element model updating for large span spatial steel structure considering uncertainties

In order to establish the baseline finite element model for structural health monitoring,a new method of model updating was proposed after analyzing the uncertainties of measured data and the error of finite element model.In the new method,the finite element model was replaced by the multi-output support vector regression machine(MSVR).The interval variables of the measured frequency were sampled by Latin hypercube sampling method.The samples of frequency were regarded as the inputs of the trained MSVR.The outputs of MSVR were the target values of design parameters.The steel structure of National Aquatic Center for Beijing Olympic Games was introduced as a case for finite element model updating.The results show that the proposed method can avoid solving the problem of complicated calculation.Both the estimated values and associated uncertainties of the structure parameters can be obtained by the method.The static and dynamic characteristics of the updated finite element model are in good agreement with the measured data.

Correction of Dynamic Error Result from Measurement System Limitations

The main cause of dynamic errors is due to frequency response limitation of measurement system. One way of solving this problem is designing an effective inverse filter. Since the problem is ill-conditioned, a small uncertainty in the measurement will came large deviation in reconstncted signals. The amplified noise has to be suppressed at the sacrifice of biasing in estimation. The paper presents a kind of designing method of inverse filter in frequency domain based on stabilized solutions of Fredholm integral equations of the fast kind in order to reduce dynamic errors. Compared with previous several work, the method has advantage of generalization. Simulations with different Signal-to-Noise ratio （SNR） are investigated. Flexibility of the method is verified. Application of correcting dynamic error is given.

The role of constant optimal forcing in correcting forecast models

In this paper,the role of constant optimal forcing(COF) in correcting forecast models was numerically studied using the well-known Lorenz 63 model.The results show that when we only consider model error caused by parameter error,which also changes with the development of state variables in a numerical model,the impact of such model error on forecast uncertainties can be offset by superimposing COF on the tendency equations in the numerical model.The COF can also offset the impact of model error caused by stochastic processes.In reality,the forecast results of numerical models are simultaneously influenced by parameter uncertainty and stochastic process as well as their interactions.Our results indicate that COF is also able to significantly offset the impact of such hybrid model error on forecast results.In summary,although the variation in the model error due to physical process is time-dependent,the superimposition of COF on the numerical model is an effective approach to reducing the influence of model error on forecast results.Therefore,the COF method may be an effective approach to correcting numerical models and thus improving the forecast capability of models.

Environmental Justice in the Context of Scientific Uncertainty: On the Safety of Genetically Modified Organisms

A foremost issue of our time is our response to risks,especially those arising from scientific uncertainty,such as genetically modified organisms(GMOs).In this context,we need to achieve and maintain environmental justice.This should be based on the corresponding scientific research;essentially,however,it is a kind of social construct.We must maintain a free market mechanism for the development,application,and dissemination of modern technology,including genetically modified biotech and its products.At the same time,the necessary government intervention and legal regulation of the relevant science and technology should be put in place to ensure public safety and the interests of socially disadvantaged groups.

Fuzzy finite element model updating of bridges by considering the uncertainty of the measured modal parameters

It is significant to consider the effect of uncertainty of the measured modal parameters on the updated finite element(FE) model,especially for updating the FE model of practical bridges,since the uncertainty of the measured modal parameters cannot be ignored owing to the application of output-only identification method and the existence of the measured noise.A reasonable method is to define the objective of the FE model updating as the statistical property of the measured modal parameters obtained by conducting couples of identical modal tests,however,it is usually impossible to implement repeated modal test due to the limit of practical situation and economic reason.In this study,a method based on fuzzy finite element(FFM) was proposed in order to consider the effect of the uncertainty of the measured modal parameters on the updated FE model by using the results of a single modal test.The updating parameters of bridges were deemed as fuzzy variables,and then the fuzzification of objective of the FE model updating was proposed to consider the uncertainty of the measured modal parameters.Finally,the effectiveness of the proposed method was verified by updating the FE model of a practical bridge with the measured modal parameters.

A trigonometric interval method for dynamic response analysis of uncertain nonlinear systems

This paper proposes a new non-intrusive trigonometric polynomial approximation interval method for the dynamic response analysis of nonlinear systems with uncertain-but-bounded parameters and/or initial conditions.This method provides tighter solution ranges compared to the existing approximation interval methods.We consider trigonometric approximation polynomials of three types:both cosine and sine functions,the sine function,and the cosine function.Thus,special interval arithmetic for trigonometric function without overestimation can be used to obtain interval results.The interval method using trigonometric approximation polynomials with a cosine functional form exhibits better performance than the existing Taylor interval method and Chebyshev interval method.Finally,two typical numerical examples with nonlinearity are applied to demonstrate the effectiveness of the proposed method.