外文翻译---数值模拟中岩体力学特性的工程与实验关系

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1、PDF外文：http:/ 3090字  出处： International Journal of Rock Mechanics and Mining Sciences, 1997, 34(2): 289-297 The Relation Between In situ and Laboratory RockProperties Used in Numerical Modelling Mohammad N, Reddish D J, Stace L R INTRODUCTION Numerical models are being used increasingly for rockm

2、echanics design as cheaper and more efficient softwareand hardware become available. However, a crucial stepin modelling is the determination of rock massmechanical properties, more precisely rock stiffness andstrength properties. This paper presents the results of a review ofnumerical modelling sti

3、ffness and strength properties used to simulate rock masses. Papers where laboratoryand modelling properties are given have been selectedfrom the mass of more general modelling literature.More specifically papers that have reduced stiffnessand/or strength parameters from laboratory to fieldvalues ha

4、ve been targeted. The result of the search hasbeen surprising: of the thousands of papers on numericalmodelling, a few hundred mention laboratory and rockmass properties, and of those, only some 40 appear toapply some kind of reduction. The papers that apply areduction have been used to produce the

5、graphs thatconstitute the main content of this paper. Rock stiffnessproperties have been separated from those of strength inthe analysis and this has illustrated interestingdifferences in their respective average reduction factors. METHODOLOGY The review conducted has studied case histories andback

6、analysis examples of numerical modelling for awide range of rock structures. Each reviewed paper hasbeen databased in terms of laboratory measured rockproperties and numerical modelling rock mass inputproperties plus other relevant quantitative data 1-37.The vast majority of papers have provided inc

7、ompletedata either omitting key parameters or synthesizingparameters. Some papers have given laboratory andmass properties, and a few papers have explained theprocess by which laboratory properties have beenadjusted to the rock mass by use of rock mass ratings.One can only conclude that this is rela

8、ted to the originof the models or modellers, being from environmentswhere materials like steel have no scale effects. Therewould be few rock mechanics specialists who would notacknowledge that even the strongest rock types needsome adjustment of their rock mass properties. Thegraphs and data provide

9、d in this paper have thereforeconcentrated on papers where reductions have beenapplied. A list of the most valid and relevant numericalpapers is included at the end of the paper. RESULTS Figure 1 presents the Young's modulus results forlaboratory tests plotted with those used in the model.Each c

10、ase is numbered against its source. There is asimple trend in these data and if a straight line is fitted,model stiffness is on average 0.469 of the laboratorystiffness (Fig. 2). The data can alternatively be plotted asreduction factors as in Fig. 3. Here a trend of increasedreduction factors for lo

11、w stiffness rock types becomesapparent. A number of very high reduction factors canalso be seen for very low stiffness rocks.Figure 4 shows the uniaxial compressive strengthresults for laboratory tests plotted against those used inthe model. Each case is numbered against its source.There is a simple

12、 trend in these data and, if a straightline is fitted, model strength is on average 0.284 of thelaboratory strength (Fig. 5). The data can alternativelybe plotted as reduction factors as in Fig. 6. Here, a trendof increased reduction factors for weak rock typesbecomes apparent. Figure 7 illustrates

13、the trend for tensile strength,indicating that the laboratory values are reduced by afactor of almost two and Fig. 8 shows the trend forPoisons ratio with no significant conclusions to bedrawn. TECHNIQUES OF REDUCTION A number of authors have presented relations betweenlaboratory and in situ propert

14、ies. Some have includedrock mass ratings in their relations. The widely usedtechnique to derive deformation moduli is equation (1)presented by Bieniawski 38 for rocks having a RockMass Rating (RMR) greater than 50 with a predictionerror of 18.2%. However, when the RMR is less than orequal to 50, the

15、 Bieniawski formula is not applicable asit leads to values of deformation moduli less than orequal to zero. Serafim and Pereira 39 using theBieniawski Rock Mass Classification system (RMR)derived an alternative expression, equation (2), for theentire range of RMR. 2 1 0 0 ( )mE R M R G P a（ 1）  

16、;10401 0 ( )R M RmE G P a （ 2）  Figure 9 shows both the expressions plotted againstthe stiffness data from the review. A double x axis hasbeen used to compare these data. This has required theRMR to be related to laboratory E. A simple linearrelation has been used over the typical full of bothp

17、roperties. (RMR = 0-100 and E = 0-120 GPa.)Nicholson and Bieniawski 40, have developed anempirical expression for a reduction factor, equation (3).This factor is calculated in order to derive deformationmoduli for a rock mass using its RMR and a laboratoryYoung's modulus. 2i n t0 . 0 0 2 8 0 . 9

18、 e x p ( )2 2 . 8 2rmE R M RR F R M RE （ 3）  Mitri et al. 33 used the following equation (4) to derivethe modulus of deformation of the rock mass and scaleddown the Hoek-Brown parameters to represent an insitu situation using the RMR. i n t0 . 5 1 c o s ( )100rmE R M RRF E （ 4）    Fig

19、. 1. (a) Young's modulus from case histories for laboratory tests and numerical modelling input (range 0-120 GPa). (b)Young's modulus from cast histories for laboratory tests and numerical modelling input (range 0-28 GPa).  Fig. 2. Young's modulus from case histories for laboratory

20、tests and numerical modelling input.  20000    0    0 20000 40000 60000 80000 100000 120000400006000080000100000120000152714 141362166221631163021 21212114211432 142424321427619 273223162121 2130303329Model E(MPa)L a bor a tor y E ( M Pa )5000 10000 15000 20000 2500000500010

21、0001500020000L a bor a tor y E ( M Pa )Model E(MPa)1717919112711 17 2610222220121711232323141423 1215 1424 24121212121251824141913141171310241718242471224131913252577810241811710191724 221724171716111014221710101320 00 0    0    0 20 00 0 40 00 0 60 00 0 80 00 0 10 00 0 0 12 00 0

22、 040 00 060 00 080 00 010 00 0 012 00 0 0Model E(MPa)L a bo ra tory  E ( M P a )    0    0 20 00 0 40 00 0 60 00 0 80 00 0 1000 0 0 1200 0 0Reduction Factor for Model E(MPa)La bo rato ry E(M P a )    5   1 0    1 5    2 0    2 5    3 0    3 5    4 0    4 5    5 0y= 5.18 01 e -1E -05xR 2 =0 .075 4