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Gaussian98和Gaussview在结构化学教学中的应用
结合结构化学的特点,在教学中应用Gaussian98和Gaussview这类计算化学软件,使抽象的内容形象化,微观成为宏观,教学过程变得简单、清晰,更有利于教与学.
WANG Jun-min
TANG Ran-xiao
GAO Shu-tao
LIU Shu-jing
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河北农业大学,理学院,河北,保定,071001
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万方数据知识服务平台--国家科技支撑计划资助项目（编号：2006BAH03B01）(C)北京万方数据股份有限公司
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Gaussian03/GaussView在红外光谱教学中的应用
讨论了Gaussian03/GaussView软件在&分析化学&中红外光谱教学中的具体应用,不仅能使抽象的知识形象化、直观化,而且能增强学生的学习兴趣,提高教与学的效率.
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In this paper,the applications of Gaussian03/GaussView in IR spectroscopy teaching are discussed and they are helpful for visualizing the class teaching and enhancing the efficiency of teaching and learning.
XIE Hui-Ding
Guo Yun-Ping
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昆明医学院化学教研室,昆明市人民西路191号,650031
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万方数据知识服务平台--国家科技支撑计划资助项目（编号：2006BAH03B01）(C)北京万方数据股份有限公司
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, December 2004, Pages
View factor for inclined plane with Gaussian source
Faculty of Information Technology, Bond University, Gold Coast 4229, AustraliaThe view factor (angle factor) for a differential inclined plane in the case of a radiating source of radially Gaussian intensity is considered. This information is useful for modelling of solar radiation in certain applications. The view factor is expressed in terms of two integrals, one of which is obtained in closed form in terms of special functions, and the other is approximated. A compact estimate for the view factor is presented which is suitable for machine computation. While the relative error associated with the final estimate is typically less than 0.01%, and in all cases, less than 0.2%, the method is easily extended to yield even greater accuracy.KeywordsSolar radiation; View factor; Gaussian source1. IntroductionView factors for inclined planes for the case of a uniformly radiating source are well-known and can be found in standard texts on radiative transfer, for example
or . The purpose of the present work is to derive an accurate estimate of the view factor for an infinite plane source whose intensity falls off radially in accordance with a Gaussian law and a small differential receiving plane surface inclined at some acute angle to the source plane. The final result is intended to be of use for work on modelling the intensity distribution of the apparent solar disc by the G the receiving plane being the Earth's surface. The Gaussian source assumption follows a suggestion of Peck
in his work on parabolic solar collector design. The paper is organized as follows. We first consider the geometry of the problem and obtain an exact integral expression for the view factor, as a function of the angle of inclination, β, of the differential receiving plane. Following this, some standard estimation techniques are employed to derive a useful approximation to the view factor. Finally, this estimate is used as the basis of a computational model in Microsoft Excel, which computes, tabulates, and graphs the view factor as a function of β.2. Methods of computing view factorsAccording to Modest, view factor evaluation techniques may be classified broadly as follows:1.Direct integration.2.Statistical: sampling with the well-known Monte-Carlo class of methods.3.Special methods.(a)Algebraic: application of symmetry, reciprocity, and other properties.(b)Crossed-string method: applied to long enclosures with constant cross-section.(c)Unit sphere method: used between one infinitesimal and one finite area, such as we have here.(d)Inside sphere method.Direct integration may be accomplished by any of a number of efficient methods, analytical or numerical, with the common Simpson's Rule being very accurate for most shapes, even with modest mesh size. Methods in the Monte-Carlo class are typically poorer cousins to the other, preferred methods, and errors are of order <img class="imgLazyJSB inlineImage" height="17" width="27" alt="Full-size image (<1 K)" title="Full-size image (<img height="17" border="0" style="vertical-align:bottom" width="27" alt="Full-size image (<1 K)" title="Full-size image (, where h is the mesh size. Such techniques should be chosen only when others are, for whatever reason, very awkward to apply. Industry Standard scientific software such as FACET
employs a combination of several of these methods to achieve satisfactory results, in general.The present method falls into category 1, with the integrals here being evaluated partially analytically, and partially estimated. There is no particular nume rather the whole exercise here is primarily one of estimation of semi-tractable integrals in terms of known special functions, and their final estimation using asymptotic techniques. Thus, it makes little sense to compare the present work with some of the more advanced numerical techniques for view factor estimation.3. Net incident intensity for arbitrary source distribution functionWith reference to , the vector ? is the position vector to an arbitrary point P in the plane A1. With respect to the right-handed orthonormal system {i,j,k} emanating from O2, we haveequation(1)<img class="imgLazyJSB inlineImage" height="15" width="123" alt="Full-size image (<1 K)" style="margin-top: -5 vertical-align: middle" title="Full-size image (<img height="15" border="0" style="vertical-align:bottom" width="123" alt="Full-size image (<1 K)" title="Full-size image (The vector ?0 is normal to the plane A1:equation(2)<img class="imgLazyJSB inlineImage" height="15" width="65" alt="Full-size image (<1 K)" style="margin-top: -5 vertical-align: middle" title="Full-size image (<img height="15" border="0" style="vertical-align:bottom" width="65" alt="Full-size image (<1 K)" title="Full-size image (Since P lies in A1, we have y=?0, so Eq.
becomes:equation(3)<img class="imgLazyJSB inlineImage" height="15" width="131" alt="Full-size image (<1 K)" style="margin-top: -5 vertical-align: middle" title="Full-size image (<img height="15" border="0" style="vertical-align:bottom" width="131" alt="Full-size image (<1 K)" title="Full-size image (The angles θ1 and θ2 are respectively the angles of emission from P and incidence at O2 of radiation from the source plane A1. The angle β is the (acute) angle between the normals, respectively n1 and n2, to the planes A1 and dA2.Fig. 1.&#xA0;Geometry.
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No articles found.A Practical View of Suboptimal Bayesian Classification with Radial Gaussian Kernels
1995 Article
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IWANN '96 Proceedings of the International Workshop on Artificial Neural Networks: From Natural to Artificial Neural Computation
June 07 - 09, 1995
Springer-Verlag London, UK
ISBN:3-540-59497-3
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