[雙語翻譯]--外文翻譯--模糊工程在核研究中的應(yīng)用（原文）

1、Fuzzy Engineering in Nuclear Research Applications D. Ruan: L. Van Den Durpel and P. D’hondt Fuel Research Unit Nuclear Research Centre SCKaCEN Boeretang 200, B-2400 Mol, Belgium Abstract Security, maintenance, monito

2、ring, diagnosis, and environment are all related to humans and their soci- ety, and are the most important and dificult problems of nuclear engineering. These problems are so com- plicated that they can hardly be sol

3、ved without a global approach. Therefore, fuzzy engineering may be one of the most powerful tools available to us. This paper reports on the initial activity of fuzzy engineering at the Belgian Nuclear Research Centr

4、e. It illustrates two applications, namely, nuclear emer- gency decision aiding systems, and inspection of trans- mission lines of nuclear installations with preliminary results, then states a new RtYD project concer

5、ning a fuzzy model-based control of a nuclear reactor giving more practical questions lo do with fuzzy engineering rather than presenting solutions. The paper finally emphasizes that fuzzy engineering is needed for

6、the nuclear research world through the overwhelming re- sponse to the first international FLINS workshop on fuzz# logic and intelligent technologies in nuclear sci- ence, held September 14-16, 1994 in Mol, Belgium. 1

7、 Introduction FLINS is an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science. It started as a new research project, launched in line with the objective of the Belgian Nuclear Research Cen- tre (

8、SCKoCEN) to give young talented people the o p portunity to carry out future-oriented research. Now FLINS has become the name of a new international research forum aiming to promote the theory and a p plications o

9、f fuzzy logic and other novel intelligent technologies in the domain of nuclear science and en- gineering. ‘Correspondence to: Dr. D. Ruan, Fuel Research Unit, SCKaCEN. Boeretann 200. B-2400 Mol. Beldum. fax: +32- N

10、owadays scientists have many models at their dis- posal to treat incomplete and complex information. Undoubtedly, fuzzy set theory is one of the most widely applied of these new models. At the Univer- sity of Ghent,

11、for almost twenty years, fuzzy set theory and its applications have been extensively researched in the Centre for Fuzziness and Uncertainty Modelling under the guidance of Prof. E.E. Kerre. FLINS builds upon a stron

12、g cooperation between SCKoCEN and the University of Ghent. Invented by Prof. L.A. Zadeh at the University of California at Berkeley, U.S.A., in 1965, there have been more than fifteen thousand papers published on bo

13、th theoretical and practical issues of fuzzy set the- ory. However, as Prof. H . J . Zimmermann (ELITE, Germany) points out [21], for almost twenty years, fuzzy methods were confined to universities in most parts of

14、 the world, with the possible exception of some fuzzy logic control applications. This is particularly true in the field of nuclear science and technologies. The best-known work in this area is particularly topi- cal

15、, as it deals with the Chernobyl accident, in which fuzzy human-reliability analyses in man-machine sys- tems has been considered [ 3 , 4 ] .Subsequently, Prof. T. Terano (LIFE, Japan) ad- dressed an important applica

16、tion of fuzzy logic to some of today’s most critical problems. Security, maintenance, monitoring, diagnosis, and environment are all related to humans and their society, and are the most important and difficult prob

17、lems of nuclear engineering. These problems are so complicated that they can hardly be solved without a global approach. Therefore, fuzzy engineering may be one of the most powerful tools available to us [lo]. The c

18、ontinuous increase and remarkable success of various applications of fuzzy logic prompted the foun- dation of the research forum FLINS at the end of 1992. At present FLINS-SCKoCEN consists of sev- eral engineers, mos

19、tly from nuclear science, and sci- entists who are currently working on various projects 14 32 15 29 email: &ns@&bmlackll.bitnk, - for research degrees, postdoctorate studies, or other 0-7803-2461-7/95/$4.00

20、 0 1995 IEEE 21 I Authorized licensed use limited to: WUHAN UNIVERSITY OF TECHNOLOGY. Downloaded on April 26,2010 at 11:49:31 UTC from IEEE Xplore. Restrictions apply. under development for atmospheric dispersion model

21、s. Some of them already give results with acceptable ac- curacy in special but not too complex situations. A direct application of the methods used for probabili- ties assessment of accident consequence is not suitab

22、le, since time consuming calculations are not feasible dur- ing an emergency, and the nature of the uncertainties in a large fraction of the input information and model predictions differs fundamentally. Therefore, t

23、he work [ll] seeks another approach based on fuzzy sets and decision theory to treat uncertain information (incom- plete and inexact). For example, an ambiguous prob- lem of the classification with linguistic values

24、 such as very good, good, middle, bad, and very bad, according to the ratio of predictions and observation data, can be treated with membership functions. Also a simple fuzzy algorithm is designed for the system to p

25、rovide a reasonable solution for practical users, which could propose different solutions within a short time period. The basic idea of the system is built on the follow- ing simple mathematical model: c = FG&$Z(p

26、xp(-&) I = z ( D ) (1) Y = Y ( m In the above equation, C is the concentration of ra- dioactive material, which is dependent of an unknown variable of source term Q, and another unknown vari- able of wind d

27、irection D (x and y are coordinates de- pending on the wind direction D, and the other phys- ical parameters such as ‘U, cry, and U,, are given in this study case). In a real situation, one can on one hand obtain

28、by means of observation (0) measured concentration data denoted as Cg’ for certain points (le E { 1,2,. . . , n } ) , and on the other hand one can cal- culate prediction (P) denoted as Cit!, by the model if the

29、 source term Q and the wind direction D are given for the same points as used in the observation. For each point k, one defines a fuzzy set Fk as where the indexes i, j correspond 1.0 the grids of the wind direction a

30、nd the source term, i.e. d, = d l + ( i - 1)Ad, qJ = Q~ + (j - 1)Aq. The fuzzy set Fk can be interpreted as in a certain point le, the prediction P is the closest to the observation 0. For a 1 1points, using

31、the decision-making theory [1,19,20] one obtains the fuzzy decision set D as: n D = n F k (3) k = l The best source term qo and the best wind direction do can be obtained by using the defiizzification tech- niques.

32、 Practically, one can set the finite grids for wind direction since the range of it is more-or-less known. However there is no idea about the source term. To set a large range of the source yields the computer time-

33、 consuming problem for this simulation. For that rea- son, ratios of $ (prediction over observation) is com- puted, and the situation for which all these ratios (for all measurement points) are as close to 1 as pos

34、sible is being searched with respect to the different member- ship functions. In this way, one gets an approximate value of the source, therefore a more-or-less correct range of it. Several examples have been tested

35、and the method proposed here seems acceptable from the point of view of the practice [9]. 4 Application 2: Inspection of Trans- mission Lines of Nuclear Installa- tions The safety of a nuclear power plant (XPP) and

36、of research reactors has to be dealt in increasingly greater depth. During the construction phase of the NPP, sev- eral safety related solutions can be studied and ideallj implemented. Older installations, at certain

37、 nuclear facilities, require extra safety evaluation. One of the aspects to deal with is the safety of the several trans- mission lines in a nuclear installation, for instance the safety of control, safety against fi

38、re, etc.. The Belgian Nuclear Research Centre has to deal with existing in- stallations, and especially the fire risk anal3sis of elec- trical power cable trays. In this particular case several questions arise: “To w

39、hat extent can those cabinets propagate fire?”, “To what extent can those cables be the source of fire due to their previous service life?”, and “What are the mechanisms observed?”. Clearly a strict answer to those q

40、uestions cannot be obtained since it needs a lot of engineering judgement, and the practical inspection of those cable trays introduces a lot of subjective inputs. Obviously, a survey of all transmission lines agains

41、t several hazards, in the nuclear installation, is an enor- mous task as the following separate steps have to be taken: (1) Each transmission line needs to be checked 213 Authorized licensed use limited to: WUHAN UNI