cg Version

depe = 0.D0end ifdo ntype=1,3do ie=1,50specs(ntype,ie)=specs(ntype,ie)+spec(ntype,ie)spec2s(ntype,ie)=spec2s(ntype,ie)+* spec(ntype,ie)*spec(ntype,ie)spec(ntype,ie)=0.D0end doend doncount = ncount + 1! ========================if(iwatch.gt.0) call swatch(-1,iwatch)! ========================end do! ========================if(iwatch.gt.0) call swatch(-88,iwatch)! ========================! Count total number of actual cases! -----------------------! End of CALL SHOWER loop! -----------------------call plotxyz(99,0,0,0.D0,0.D0,0.D0,0.D0,0,0.D0,0.D0)write(39,fmt="('9')")3.8.1 Statistical uncertainty! Set end of batch for CG ViewThe uncertainty of obtained, x, is estimated using the method used in MCNP in this user code. Assume that the calculation calls for N \incident" particle histories. Assume that x i is the result at the i-th history. Calculate the mean value of x :x = 1 NNXi=1x i (1) Estimate the variance associated with the distribution of x i :s 2 = 1N ; 1NXi=1(x i ; x) 2 ' x 2 ; (x) 2 (x 2 = 1 NNXi=1x 2 i ): (2) Estimate the variance associated with the distribution of x:s 2 x = 1 N s2 ' 1 N [x2 ; (x) 2 ] (3) Report the statistical error as:s x ' [ 1 N (x2 ; x 2 )] 1=2 (4)3.8.2 Output of resultsAfter nishing all histories, obtained results are analyzed and written on output le. Averagevalues and their statistical uncertainty are calculated form the sum of weight and the sum ofweight squared.37