Analytical method of predicating the instabilities of a micro arch-shaped beam under electrostatic loading

An arch-shaped beam with different configurations under electrostatic loading experiences either the direct pull-in instability or the snap-through first and then the pull-in instability. When the pull-in instability occurs, the system collides with the electrode and adheres to it, which usually causes the system failure. When the snap-through instability occurs, the system experiences a discontinuous displacement to flip over without colliding with the electrode. The snap-through instability is an ideal actuation mechanism because of the following reasons: (1) after snap-through the system regains the stability and capability of withstanding further loading; (2) the system flips back when the loading is reduced, i.e. the system can be used repetitively; and (3) when approaching snap-through instability the system effective stiffness reduces toward zero, which leads to a fast flipping-over response. To differentiate these two types of instability responses for an arch-shaped beam is vital for the actuator design. For an arch-shaped beam under electrostatic loading, the nonlinear terms of the mid-plane stretching and the electrostatic loading make the analytical solution extremely difficult if not impossible and the related numerical solution is rather complex. Using the one mode expansion approximation and the truncation of the higher-order terms of the Taylor series, we present an analytical solution here. However, the one mode approximation and the truncation error of the Taylor series can cause serious error in the solution. Therefore, an error-compensating mechanism is also proposed. The analytical results are compared with both the experimental data and the numerical multi-mode analysis. The analytical method presented here offers a simple yet efficient solution approach by retaining good accuracy to analyze the instability of an arch-shaped beam under electrostatic loading.

Comparison of wavelet transform methods - The compression of IR spectral data

In this paper, an introduction of wavelet transform and multi-resolution analysis is presented. We describe three data compression methods based on wavelet transform for spectral information,and by using the multi-resolution analysis, we compressed spectral data by Daubechies's compactly supported orthogonal wavelet and orthogonal cubic B-splines wavelet, Using orthogonal cubic B-splines wavelet and coefficients of sharpening signal are set to zero, only very few large coefficients are stored, and a favourable data compression can be achieved.

渤海海域河流相油藏精细描述技术及应用研究

Aiming at the character of Bohaii Sea area and the heterogeneity of fluvial facies reservoir, litho-geophysics experiments and integrated research of geophysical technologies are carried out. To deal with practical problems in oil fields of Bohai area, such as QHD32-6, Southern BZ25-1 and NP35-2 et al., technology of reservoir description based on seismic data and reservoir geophysical methods is built. In this dissertation, three points are emphasized: ①the integration of multidiscipline; ②the application of new methods and technologies; ③the integration of quiescent and dynamic data. At last, research of geology modeling and reservoir numerical simulation based on geophysical data are integrated. There are several innovative results and conclusion in this dissertation: (1)To deal with problems in shallow sea area where seismic data is the key data, a set of technologies for fine reservoir description based on seismic data in Bohai Sea area are built. All these technologies, including technologies of stratigraphic classification, sedimentary facies identification, structure fine characterization, reservoir description, fluid recognition and integration of geological modeling& reservoir numerical simulation, play an important role in the hydrocarbon exploration and development. In the research of lithology and hydrocarbon-bearing condition, petrophysical experiment is carried out. Outdoors inspection and experiment test data are integrated in seismic forward modeling& inversion research. Through the research, the seismic reflection rules of fluid in porosity are generated. Based on all the above research, seismic data is used to classify rock association, identify sedimentary facies belts and recognition hydrocarbon-bearing condition of reservoir. In this research, the geological meaning of geophysical information is more clear and the ambiguity of geophysical information is efficiently reduced, so the reliability in hydrocarbon forecasting is improved. The methods of multi-scales are developed in microfacies research aiming at the condition of shallow sea area in Bohai Sea: ① make the transformation from seismic information to sedimentary facies reality by discriminant analysis; ②in research of planar sedimentary facies, make microfacies research on seismic scale by technologies integration of seismic multi-attributes analysis& optimization, strata slicing and seismic waveform classification; ③descript the sedimentary facies distribution on scales below seismic resolution with the method of stochastic modeling. In the research of geological modeling and reservoir numerical simulation, the way of bilateral iteration between modeling and numerical simulation is carried out in the geological model correction. This process include several steps: ①make seismic forward modeling based on the reservoir numerical simulation results and geological models; ②get trend residual of forward modeling and real seismic data; ③make dynamic correction of the model according to the above trend residual. The modern integration technology of reservoir fine description research in Bohai Sea area, which is developed in this dissertation, is successfully used in (1)the reserve volume evaluation and development research in BZ25-1 oil field and (2)the tracing while drilling research in QHD32-6 oil field. These application researches show wide application potential in hydrocarbon exploration and development research in other oil fields.

基于独立分量分析的地震属性分析方法研究

Conventional seismic attribute analysis is not only time consuming, but also has several possible results. Therefore, seismic attribute optimization and multi-attribute analysis are needed. In this paper, Fuyu oil layer in Daqing oil field is our main studying object. And there is much difference between seismic attributes and well logs. So under this condition, Independent Component Analysis (ICA) and Kohonen neural net are introduced to seismic attribute optimization and multi-attribute analysis. The main contents are as follows: (1) Now the method of seismic attribute compression is mainly principal component analysis (PCA). In this article, independent component analysis (ICA), which is superficially related to PCA, but much more powerful, is used to seismic reservoir characterizeation. The fundamental, algorithms and applications of ICA are surveyed. And comparation of ICA with PCA is stydied. On basis of the ne-entropy measurement of independence, the FastICA algorithm is implemented. (2) Two parts of ICA application are included in this article: First, ICA is used directly to identify sedimentary characters. Combined with geology and well data, ICA results can be used to predict sedimentary characters. Second, ICA treats many attributes as multi-dimension random vectors. Through ICA transform, a few good new attributes can be got from a lot of seismic attributes. Attributes got from ICA optimization are independent. (3) In this paper, Kohonen self-organizing neural network is studied. First, the characteristics of neural network’s structure and algorithm is analyzed in detail, and the traditional algorithm is achieved which has been used in seism. From experimental results, we know that the Kohonen self-organizing neural network converges fast and classifies accurately. Second, the self-organizing feature map algorithm needs to be improved because the result of classification is not very exact, the boundary is not quite clear and the velocity is not fast enough, and so on. Here frequency sensitive principle is introduced. Combine it with the self-organizing feature map algorithm, then get frequency sensitive self-organizing feature map algorithm. Experimental results show that it is really better. (4) Kohonen self-organizing neural network is used to classify seismic attributes. And it can be avoided drawing confusing conclusions because the algorithm’s characteristics integrate many kinds of seismic features. The result can be used in the division of sand group’s seismic faces, and so on. And when attributes are extracted from seismic data, some useful information is lost because of difference and deriveative. But multiattributes can make this lost information compensated in a certain degree.

松辽盆地古龙地区葡萄花油层组沉积成岩相研究

The sediment and diagenesis process of reservoir are the key controlling factors for the formation and distribution of hydrocarbon reservoir. For quite a long time, most of the research on sediment-diagenesis facise is mainly focusing on qualitative analysis. With the further development on exploration of oil field, the qualitative analysis alone can’t meet the requirements of complicated requirements of oil and gas exploreation, so the quantitative analysis of sediment-diagenesis facise and related facies modling have become more and more important. On the basis of the research result from stratum and sediment on GuLong Area Putaohua Oil Layer Group, from the basic principles of sedimentology, and with the support from the research result from field core and mining research results, the thesis mainly makes the research on the sediment types, the space framework of sands and the evolution rules of diagenesis while mainly sticking to the research on sediment systement analysis and diagenetic deformation, and make further quantitative classification on sediment-diageneses facies qualitatively, discussed the new way to divide the sediment-diagenesis facies, and offer new basis for reservoir exploration by the research. Through using statistics theory including factor analysis, cluster analysis and discriminant analysis, the thesis devided sediment-diagenesis facies quantitatively. This research method is innovative on studying sediment-diagenesis facies. Firstly, the factor analysis could study the main mechanism of those correlative variables in geologic body, and then could draw a conclusion on the control factors of fluid and capability of reservoir in the layer of studying area. Secondly, with the selected main parameter for the cluster analysis, the classification of diagenesis is mainly based on the data analysis, thus the subjective judgement from the investigator could be eliminated, besides the results could be more quantitative, which is helpful to the correlative statistical analysis, so one could get further study on the quantitative relations of each sediment-diagenesis facies type. Finally, with the reliablities of discriminant analysis cluster results, and the adoption of discriminant probability to formulate the chart, the thesis could reflect chorisogram of sediment-diagenesis facies for planar analysis, which leads to a more dependable analytic results.According to the research, with the multi-statistics analysis methods combinations, we could get quantitative analysis on sediment-diagenesis facies of reservoir, and the final result could be more reliable and also have better operability.

弱各向异性介质中传播的地震波及其速度重建

We begin our studies to make the best of information of seismic data and carry out the description of cracks parameters by extracting anisotropic information. The researching contents are: (1) velocity and polarization anomaly of seismic wave (qP and qSV wave) in weak anisotropic media; (2) reflection seismic synthetic record in anisotropic media; (3) multiple scattering induced by cracks; (4) anisotropic structure inversion and velocity reconstruction with VSP (Vertical Seismic Profile) data; (5) multi-parameters analysis of anisotropy in time-domain and depth-domain. Then we obtain results as follows: (1) We achieve approximate relation of qP and qSV wave's velocity and polarization property in weak anisotropic media. At the same time, we calculate anisotropic velocity factors and polarization anomaly of several typical sedimentary rocks. The results show there are different anisotropic velocity factors and polarization anomaly in different rocks. It is one of the primary theoretical foundation which is expected to identify lithology; (2) We calculate reflection seismic synthetic record with theoretical model; (3) We simulate scattering induced by cracks with Boundary Element Method. Numerical studies show that in the presence of cracks; spatial and scale-length distributions are important and cannot be ignored in modeling cracked solids; (4) From traveltimes information of VSP data, we study the velocity parameter inversion of seismic wave under isotropic and anisotropic models, and its result indicate that the inversion imaging under anisotropic model will not destroy the original features of isotropic model, but it will bring on some bigger error if we adopt the method of isotropic model for anisotropic model data. Further more, basing on the study we develop the CDP mapping technology of reflecting structure under isotropic and anisotropic models, and we process real data as a trial of the methods; (5) We study the problem of initial model reconstruction of anisotropic parameters structure represented by Anderson parameter in depth domain for surface data.

民众社会风险认知的影响因素及作用机制

Risk perception is one of important subjects in management psychology and cognitive psychology. It is of great value in the theory and practice to investigate the social risk events that the public cares a lot especially in this social transition period. Furthermore, this study explored the factors that influence the risk perception and the results caused by risk perception. A survey including 30 hazards and 8 risk attributes was designed and distributed to about 3, 200 residents of 8 districts, Beijing. The major findings are listed as following： Firstly, combining the methods of system science and psychology, GAE program was used to indentify 7 groups of social risk events, such as national safe, government management, social stability, general mood of society, economic and finance, resources and environment & daily life problems. This study provided substance for the following studies and it was also a new attempt in research method which is of certain reference value for the related researches. Secondly, a scale of societal risk perception was designed and 2 factors were identified (Dread Risk & Unknown Risk). Reliability analysis, EFA and CFA show the reliability and validity of the societal risk questionnaire is good enough. The investigation using this scale showed that older participants and higher socioeconomic status perceived the societal hazards to be more threatening than did younger participants and lower socioeconomic status. However, there is no gender difference. Thirdly, structural equation model was used to analyze the influence factors and mechanism of societal risk perception. Risk taking, government support and social justice could influence societal risk perception directly. Government support moderated the relationship between government trust and societal risk perception. Societal risk perception influenced life satisfaction, public policy preferences and social development belief. Multi-group analysis was used to find out that the participants who have different socioeconomic status express different mechanism. Fourthly, the result of the research was used to explore the risk event of 2008 Olympic game. The results showed that government support and preparation of Olympic game influenced societal risk perception directly. Preparation moderated the relationship between government trust and risk perception. Risk perception influenced worry, effect of Olympic game and belief of successl. This result proved that risk perception could be used as an indicator. The indictor of risk perception was used to identify the characteristics of higher risk perception group. Finally, suggestions to the related decision were provide to the government.

Response Surface Modeling and Optimisation for Reliable Electronic Products

The aim of integrating computational mechanics (FEA and CFD) and optimization tools is to speed up dramatically the design process in different application areas concerning reliability in electronic packaging. Design engineers in the electronics manufacturing sector may use these tools to predict key design parameters and configurations (i.e. material properties, product dimensions, design at PCB level. etc) that will guarantee the required product performance. In this paper a modeling strategy coupling computational mechanics techniques with numerical optimization is presented and demonstrated with two problems. The integrated modeling framework is obtained by coupling the multi-physics analysis tool PHYSICA - with the numerical optimization package - Visua/DOC into a fuJly automated design tool for applications in electronic packaging. Thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and life-time under thermal cycling. Also a thermal management design based on multi-physics analysis with coupled thermal-flow-stress modeling is discussed. The Response Surface Modeling Approach in conjunction with Design of Experiments statistical tools is demonstrated and used subsequently by the numerical optimization techniques as a part of this modeling framework. Predictions for reliable electronic assemblies are achieved in an efficient and systematic manner.

Multiphysics simulation of microwave curing in micro-electronics packaging applications

Purpose – This paper aims to present an open-ended microwave curing system for microelectronics components and a numerical analysis framework for virtual testing and prototyping of the system, enabling design of physical prototypes to be optimized, expediting the development process. Design/methodology/approach – An open-ended microwave oven system able to enhance the cure process for thermosetting polymer materials utilised in microelectronics applications is presented. The system is designed to be mounted on a precision placement machine enabling curing of individual components on a circuit board. The design of the system allows the heating pattern and heating rate to be carefully controlled optimising cure rate and cure quality. A multi-physics analysis approach has been adopted to form a numerical model capable of capturing the complex coupling that exists between physical processes. Electromagnetic analysis has been performed using a Yee finite-difference time-domain scheme, while an unstructured finite volume method has been utilized to perform thermophysical analysis. The two solvers are coupled using a sampling-based cross-mapping algorithm. Findings – The numerical results obtained demonstrate that the numerical model is able to obtain solutions for distribution of temperature, rate of cure, degree of cure and thermally induced stresses within an idealised polymer load heated by the proposed microwave system. Research limitations/implications – The work is limited by the absence of experimentally derived material property data and comparative experimental results. However, the model demonstrates that the proposed microwave system would seem to be a feasible method of expediting the cure rate of polymer materials. Originality/value – The findings of this paper will help to provide an understanding of the behaviour of thermosetting polymer materials during microwave cure processing.

Industrial water pollution in Dhaka, Bangladesh: strategies and incentives for pollution control in small and medium enterprises

The extent and gravity of the environmental degradation of the water resources in Dhaka due to untreated industrial waste is not fully recognised in international discourse. Pollution levels affect vast numbers, but the poor and the vulnerable are the worst affected. For example, rice productivity, the mainstay of poor farmers, in the Dhaka watershed has declined by 40% over a period of ten years. The study found significant correlations between water pollution and diseases such as jaundice, diarrhoea and skin problems. It was reported that the cost of treatment of one episode of skin disease could be as high as 29% of the weekly earnings of some of the poorest households. The dominant approach to deal with pollution in the SMEs is technocratic. Given the magnitude of the problem this paper argues that to control industrial pollution by SMEs and to enhance their compliance it is necessary to move from the technocratic approach to one which can also address the wider institutional and attitudinal issues. Underlying this shift is the need to adopt the appropriate methodology. The multi-stakeholder analysis enables an understanding of the actors, their influence, their capacity to participate in, or oppose change, and the existing and embedded incentive structures which allow them to pursue interests which are generally detrimental to environmental good. This enabled core and supporting strategies to be developed around three types of actors in industrial pollution, i.e., (i) principal actors, who directly contribute to industrial pollution; (ii) stakeholders who exacerbate the situation; and (iii) potential actors in mitigation. Within a carrot-and-stick framework, the strategies aim to improve environmental governance and transparency, set up a packet to incentive for industry and increase public awareness.

Biomonitoring of air pollutants by using lichens (Evernia prunastri) in areas between Kenitra and Mohammedia cities in Morocco.

In this study, Evernia prunastri, a lichen growing in its natural habitat in Morocco was analysed for the concentration of five heavy metals (Fe, Pb, Zn, Cu and Cr) from eleven sites between Kenitra and Mohammedia cities. The control site was Dar Essalam, an isolated area with low traffic density and dense vegetation. In the investigated areas, the concentration of heavy metals was correlated with vehicular traffic, industrial activity and urbanization. The total metal concentration was highest in Sidi Yahya, followed by Mohammedia and Bouznika. The coefficient of variation was higher for Pb and lower for Cu, Zn and Fe. The concentrations of most heavy metals in the thalli differed significantly between sites (p<0.01). Principal component analysis (PCA) revealed a significant correlation between heavy metal accumulation and atmospheric purity index. This study demonstrated also that the factors most strongly affecting the lichen flora were traffic density, the petroleum industry and paper factories in these areas. Overall, these results suggest that the index of atmospheric purity and assessment of heavy metals in lichen thalli are good indicators of the air quality at the studied sites.

Xanthoria parietina as a biomonitor of airborne heavy metal pollution in forest sites in the North East of Morocco

Xanthoria parietina, common foliose lichen, growing in its natural habitat, was analysed for the concentration of five heavy metals (Fe, Cr, Zn, Pb and Cu) from different forest sites of North East of Morocco (Kenitra, Sidi Boughaba, Mkhinza, Ceinture Verte near Temara city, Skhirate, Bouznika and Mohammedia). The quantification was carried out by inductively coupled plasma - atomic emission spectrometry (ICP-AES). Results were highly significant p<0,001. The concentration of metals is correlated with the vehicular activity and urbanization. The total metal concentration is highest at the Kenitra area, followed by Ceinture Verte site near Temara city, which experience heavy traffic throughout the year. Scanning electron microscopy (SEM) of particulate matter on lichen of Xanthoria parietina was assessed as a complementary technique to wet chemical analysis for source apportionment of airborne contaminant. Analysis revealed high level of Cu, Cr, Zn and Pb in samples near roads.  

Understanding online customer repurchasing intention and the mediating role of trust - an empirical investigation in two developed countries

Although e-commerce adoption and customers initial purchasing behavior have been well studied in the literature, repeat purchase intention and its antecedents remain understudied. This study proposes a model to understand the extent to which trust mediates the effects of vendor-specific factors on customers intention to repurchase from an online vendor. The model was tested and validated in two different country settings. We found that trust fully mediates the relationships between perceived reputation, perceived capability of order fulfillment, and repurchasing intention, and partially mediates the relationship between perceived website quality and repurchasing intention in both countries. Moreover, multi-group analysis reveals no significant between-country differences of the model with regards to the antecedents and outcomes of trust, except the effect of reputation on trust. Academic and practical implications and future research are discussed. © 2009 Operational Research Society Ltd.

Predicting intentions to purchase organic food: The role of affective and moral attitudes in the Theory of Planned Behaviour

This study examined the usefulness of integrating measures of affective and moral attitudes into the Theory of Planned Behaviour (TPB)-model in predicting purchase intentions or organic foods. Moral attitude was operationalised Lis positive self-rewarding feelings of doing the right thing. Questionnaire data were gathered in three countries: Italy (N = 202), Finland (N = 270) and UK (N = 200) in March 2004. Questions focussed on intentions to purchase organic apples and organic ready-to-cook pizza instead of their conventional alternatives. Data were analysed using Structural Equation Modelling by simultaneous multi-group analysis of the three Countries. Along with attitudes, moral attitude and subjective norms explained considerable shares of variances in intentions. The relative influences of these variables varied between the Countries, such that in the UK and Italy moral attitude rather than subjective norms had stronger explanatory power. In Finland it was other way around. Inclusion of moral attitude improved the model fit and predictive ability of the model, although only marginally in Finland. Thus the results partially Support the usefulness of incorporating moral measures as well as affective items for attitude into the framework of TPB. (c) 2007 Elsevier Ltd. All rights reserved.