LA–13709–M Manual

UC abc and UC 700 Issued: March 2000

MCNPTM–A General Monte Carlo N–Particle Transport Code Version 4C

Judith F. Briesmeister, Editor

18 December 2000

i

An Affirmative Action/Equal Opportunity Employer

DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or any agency thereof.

ii

18 December 2000

FOREWORD This manual is a practical guide for the use of our general-purpose Monte Carlo code MCNP. The first chapter is a primer for the novice user. The second chapter describes the mathematics, data, physics, and Monte Carlo simulation found in MCNP. This discussion is not meant to be exhaustive---details of the particular techniques and of the Monte Carlo method itself will have to be found elsewhere. The third chapter shows the user how to prepare input for the code. The fourth chapter contains several examples, and the fifth chapter explains the output. The appendices show how to use MCNP on various computer systems and also give details about some of the code internals. The Monte Carlo method emerged from work done at Los Alamos duringWorld War II. The invention is generally attributed to Fermi,von Neumann, Ulam, Metropolis, and Richtmyer. MCNP is the successor to their work and represents over 450 person-years of development. Neither the code nor the manual is static. The code is changed as the need arises and the manual is changed to reflect the latest version of the code. This particular manual refers to Version 4C. MCNP and this manual are the product of the combined effort of many people in the Diagnostics Applications Group (X-5) in the Applied Physics Division (X Division) at the Los Alamos National Laboratory. The code and manual can be obtained from the Radiation Safety InformationComputational Center (RSICC), P. O. Box 2008, Oak Ridge, TN, 37831-6362 J. F. Briesmeister Editor 505-667-7277 email: [email protected]

18 December 2000

iii

COPYRIGHT NOTICE FOR MCNP VERSION 4C Unless otherwise indicated, this information has been authored by anemployee or employees of the University of California, operator of the Los Alamos National Laboratory under Contract No. W-7405--ENG--36 with the U.S. Department of Energy. The U.S. Government has rights to use, reproduce, and distribute this information. The public maycopy and use this information without charge, provided that this Notice and any statement of authorship are reproduced on all copies. Neither the government nor the University makes any warranty, express or implied, or assumes any liability or responsibility for the use of this information.

iv

18 December 2000

TABLE OF CONTENTS CHAPTER 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. MCNP AND THE MONTE CARLO METHOD. . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. Monte Carlo Method vs Deterministic Method . . . . . . . . . . . . . . . . . . . . . . . . 2 B. The Monte Carlo Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 II. INTRODUCTION TO MCNP FEATURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 A. Nuclear Data and Reactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 B. Source Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 C. Tallies and Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 D. Estimation of Monte Carlo Errors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 E. Variance Reduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 III. MCNP GEOMETRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 A. Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 B. Surface Type Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 C. Surface Parameter Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 IV. MCNP INPUT FOR SAMPLE PROBLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 A. INP File. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 B. Cell Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 C. Surface Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 D. Data Cards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 V. HOW TO RUN MCNP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 A. Execution Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 B. Interrupts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 C. Running MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 VI. TIPS FOR CORRECT AND EFFICIENT PROBLEMS . . . . . . . . . . . . . . . . . . . . 36 A. Problem Setup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 B. Preproduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 C. Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 VII. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 CHAPTER 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. History. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 B. MCNP Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 C. History Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 II. GEOMETRY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 A. Complement Operator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 B. Repeated Structure Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

18 December 2000

v

III.

IV.

V.

VI.

VII.

VIII.

IX.

vi

C. Surfaces. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 CROSS SECTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 A. Neutron Interaction Data: Continuous-Energy and Discrete-Reaction . . . . . 18 B. Photon Interaction Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 C. Electron Interaction Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 D. Neutron Dosimetry Cross Sections. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 E. Neutron Thermal S(α,β) Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 F. Multigroup Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 PHYSICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 A. Particle Weight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 B. Particle Tracks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 C. Neutron Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 D. Photon Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 E. Electron Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 TALLIES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 A. Surface Current Tally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 B. Flux Tallies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 C. Track Length Cell Energy Deposition Tallies . . . . . . . . . . . . . . . . . . . . . . . . 80 D. Pulse Height Tallies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 E. Flux at a Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 F. Additional Tally Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 ESTIMATION OF THE MONTE CARLO PRECISION . . . . . . . . . . . . . . . . . . . 99 A. Monte Carlo Means, Variances, and Standard Deviations . . . . . . . . . . . . . . . 99 B. Precision and Accuracy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 C. The Central Limit Theorem and Monte Carlo Confidence Intervals . . . . . . 103 D. Estimated Relative Errors in MCNP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 E. MCNP Figure of Merit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 F. Separation of Relative Error into Two Components. . . . . . . . . . . . . . . . . . . 109 G. Variance of the Variance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 H. Empirical History Score Probability Density Function f(x) . . . . . . . . . . . . . 113 I. Forming Statistically Valid Confidence Intervals. . . . . . . . . . . . . . . . . . . . . 119 J. A Statistically Pathological Output Example . . . . . . . . . . . . . . . . . . . . . . . . 123 VARIANCE REDUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 A. General Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 B. Variance Reduction Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 CRITICALITY CALCULATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 A. Criticality Program Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 B. Estimation of keff Confidence Intervals and Prompt Neutron Lifetimes . . . 162 C. Recommendations for Making a Good Criticality Calculation . . . . . . . . . . 178 VOLUMES AND AREAS114. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181 A. Rotationally Symmetric Volumes and Areas . . . . . . . . . . . . . . . . . . . . . . . . 181 B. Polyhedron Volumes and Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182

18 December 2000

X. XI. XII.

XIII.

C. Stochastic Volume and Area Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 PLOTTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 PSEUDORANDOM NUMBERS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 PERTURBATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 A. Derivation of the Operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 B. Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 C. Accuracy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

CHAPTER 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. INP FILE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. Message Block . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 B. Initiate-Run . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 C. Continue−Run . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 D. Card Format . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 E. Particle Designators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 F. Default Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 G. Input Error Messages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 H. Geometry Errors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 II. CELL CARDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 A. Shorthand Cell Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 III. SURFACE CARDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 A. Surfaces Defined by Equations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 B. Axisymmetric Surfaces Defined by Points . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 C. General Plane Defined by Three Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 D. Surfaces Defined by Macrobodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 IV. DATA CARDS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 A. Problem Type (MODE) Card . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 B. Geometry Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 C. Variance Reduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 D. Source Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 E. Tally Specification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 F. Material Specification Cards. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 G. Energy and Thermal Treatment Specification . . . . . . . . . . . . . . . . . . . . . . . 116 H. Problem Cutoff Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 I. User Data Arrays. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 J. Peripheral Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 V. SUMMARY OF MCNP INPUT FILE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 A. Input Cards . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 B. Storage Limitations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

18 December 2000

vii

CHAPTER 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. GEOMETRY SPECIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. COORDINATE TRANSFORMATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 A. TR1 and M = 1 Case: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 B. TR2 and M = −1 Case: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 III. REPEATED STRUCTURE AND LATTICE EXAMPLES . . . . . . . . . . . . . . . . . 20 IV. TALLY EXAMPLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 A. FMn Examples (Simple Form) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 B. FMn Examples (General Form) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 C. FSn Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 D. FTn Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 E. Repeated Structure/Lattice Tally Example . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 F. TALLYX Subroutine Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 V. SOURCE EXAMPLES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 VI. SOURCE SUBROUTINE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 VII. SRCDX SUBROUTINE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 CHAPTER 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. DEMO PROBLEM AND OUTPUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. TEST1 PROBLEM AND OUTPUT. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 III. CONC PROBLEM AND OUTPUT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 IV. KCODE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 V. EVENT LOG AND GEOMETRY ERRORS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 A. Event Log . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 B. Debug Print . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 APPENDIX B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. SYSTEM GRAPHICS INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. X–Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 II. THE PLOT GEOMETRY PLOTTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 A. PLOT Input and Execute Line Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 B. Plot Commands Grouped by Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 C. Geometry Debugging and Plot Orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 III. THE MCPLOT TALLY AND CROSS SECTION PLOTTER . . . . . . . . . . . . . . . 10 A. Input for MCPLOT and Execution Line Options . . . . . . . . . . . . . . . . . . . . . . 11 B. Plot Conventions and Command Syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 C. Plot Commands Grouped by Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 D. MCTAL Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 E. Example of Use of COPLOT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 APPENDIX C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. INSTALLING MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

viii

18 December 2000

II.

III.

IV.

A. On Supported Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 B. VMS System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 C. On Other Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 MODIFYING MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 A. Creating a PRPR Patch File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 B. Creating a New MCNP Executable . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 MCNP VERIFICATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 A. On Supported Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 B. On VMS System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 CONVERTING CROSS-SECTION FILES WITH MAKXSF . . . . . . . . . . . . . . . 14

APPENDIX D. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. PREPROCESSORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. PROGRAMMING LANGUAGE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 III. SYMBOLIC NAMES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 IV. SYSTEM DEPENDENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 V. COMMON BLOCKS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 VI. DYNAMICALLY ALLOCATED STORAGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 VII. THE RUNTPE FILE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 VIII. C FUNCTIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 IX. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 APPENDIX E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. DICTIONARY OF SYMBOLIC NAMES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. SOME IMPORTANT COMPLICATED ARRAYS . . . . . . . . . . . . . . . . . . . . . . . 32 A. Source Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 B. Transport Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 C. Tally Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 D. Accounting Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 E. KCODE Arrays. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 F. Alpha Arrays. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 G. Universe Map/ Lattice Activity Arrays for Table 128 . . . . . . . . . . . . . . . . . . 48 H. Weight Window Mesh Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 I. Perturbation Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 J. Macrobody and Identical Surface Arrays . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 APPENDIX F . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. Data Types and Classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. XSDIR— Data Directory File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 III. Data Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 A. Locating Data on a Type 1 Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 B. Locating Data on a Type 2 Table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

18 December 2000

ix

IV. V. VI. VII. VIII. IX.

C. Locating Data Tables in MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 D. Individual Data Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Data Blocks for Continuous–Energy and Discrete Neutron Transport Tables. . . . 12 Data Blocks for Dosimetry Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Data Blocks for Thermal S(α,β) Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Data Blocks for Photon Transport Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Format for Multigroup Transport Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Format for Electron Transport Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52

Appendix G. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. ENDF/B REACTION TYPES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 II. S(a,b) DATA FOR USE WITH THE MTm CARD . . . . . . . . . . . . . . . . . . . . . . . . 5 III. MCNP NEUTRON CROSS–SECTION LIBRARIES. . . . . . . . . . . . . . . . . . . . . . . 6 IV. MULTIGROUP DATA FOR MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 V. DOSIMETRY DATA FOR MCNP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 VI. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Appendix H. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 I. CONSTANTS FOR FISSION SPECTRA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 A. Constants for the Maxwell fission spectrum (neutron-induced). . . . . . . . . . . . 1 B. Constants for the Watt Fission Spectrum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 II. FlUX-TO-DOSE CONVERSION FACTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 A. Biological Dose Equivalent Rate Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 B. Silicon Displacement Kerma Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 III. REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Appendix I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Appendix J . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

x

18 December 2000

MCNP–A General Monte Carlo N–Particle Transport Code Version 4C Diagnostics Applications Group Los Alamos National Laboratory

ABSTRACT MCNP is a general-purpose Monte Carlo N–Particle code that can be used for neutron, photon, electron, or coupled neutron/photon/electron transport, including the capability to calculate eigenvalues for critical systems. The code treats an arbitrary three-dimensional configuration of materials in geometric cells bounded by first- and second-degree surfaces and fourth-degree elliptical tori. Pointwise cross-section data are used. For neutrons, all reactions given in a particular cross-section evaluation (such as ENDF/B-VI) are accounted for. Thermal neutrons are described by both the free gas and S(α,β) models. For photons, the code takes account of incoherent and coherent scattering, the possibility of fluorescent emission after photoelectric absorption, absorption in pair production with local emission of annihilation radiation, and bremsstrahlung. A continuousslowing-down model is used for electron transport that includes positrons, k x-rays, and bremsstrahlung but does not include external or self-induced fields. Important standard features that make MCNP very versatile and easy to use include a powerful general source, criticality source, and surface source; both geometry and output tally plotters; a rich collection of variance reduction techniques; a flexible tally structure; and an extensive collection of cross-section data.

18 December 2000

xi

CHAPTER 2 INP File

NOTES:

xii

18 December 2000

MCNP –A General Monte Carlo N–Particle Transport ...

Dec 18, 2000 - Reference herein to any specific commercial product, process, or service by trade name, trademark ... 505-667-7277 email: [email protected] ...

23KB Sizes 6 Downloads 57 Views

Recommend Documents

MCNP –A General Monte Carlo N–Particle Transport ...
Dec 18, 2000 - G. Universe Map/ Lattice Activity Arrays for Table 128 . . . . . . . . . . . . . . . . . . 48. H. Weight Window Mesh Parameters .

a monte carlo study
Mar 22, 2005 - We confirm this result using simulated data for a wide range of specifications by ...... Federal Reserve Bank of Kansas City and University of Missouri. ... Clements M.P., Krolzig H.$M. (1998), lA Comparison of the Forecast ...

Monte Carlo Simulation
You are going to use simulation elsewhere in the .... If we use Monte Carlo simulation to price a. European ...... Do not put all of your “business logic” in your GUI.

Sequential Monte Carlo multiple testing
Oct 13, 2011 - can be reproduced through a Galaxy Pages document at: ... Then, in Section 3, we show on both simulated and real data that this method can ...

Introduction to Monte Carlo Simulation
Crystal Ball Global Business Unit ... Simulation is the application of models to predict future outcomes ... As an experimenter increases the number of cases to.

Sequential Monte Carlo multiple testing
Oct 13, 2011 - An example of such a local analysis is the study of how the relation ... and then perform a statistical test of a null hypothesis H0 versus. ∗To whom ... resampling risk (Gandy, 2009), and prediction of P-values using. Random ...

A Non-Resampling Sequential Monte Carlo Detector for ... - IEEE Xplore
SMC methods are traditionally built on the techniques of sequential importance sampling (SIS) and resampling. In this paper, we apply the SMC methodology.

Hamiltonian Monte Carlo for Hierarchical Models
Dec 3, 2013 - eigenvalues, which encode the direction and magnitudes of the local deviation from isotropy. data, latent mean µ set to zero, and a log-normal ...

Introduction to Monte Carlo Simulation - PDFKUL.COM
Monte Carlo Simulation Steps. • Following are the important steps for Monte Carlo simulation: 1. Deterministic model generation. 2. Input distribution identification. 3. Random number generation. 4. Analysis and decision making ..... perform output

A novel approach to Monte Carlo-based uncertainty ...
Software Ltd., Kathmandu, Nepal, (3) Water Resources Section, Delft ... was validated by comparing the uncertainty descriptors in the verification data set with ... The proposed techniques could be useful in real time applications when it is not ...

A quasi-Monte Carlo method for computing areas ... - Semantic Scholar
Our method operates directly on the point cloud without any surface ... by counting the number of intersection points between the point cloud and a set of.

A Sequential Monte Carlo Method for Bayesian ...
Sep 15, 2002 - to Bayesian logistic regression and yields a 98% reduction in data .... posterior, f(θ|x), and appeal to the law of large numbers to estimate.

Quasi-Monte Carlo Image Synthesis in a Nutshell
With re- spect to computer graphics, consistency guarantees image synthesis without persis- ... Bias is defined as the difference of the desired result and the expectation. In fact, .... is a classic reference available for free on the internet, and

Monte Carlo simulations for a model of amphiphiles ...
Available online at www.sciencedirect.com. Physica A 319 (2003) .... many sites. The amphiphiles possess internal degrees of freedom with n different states.

monte carlo procedures. a problem for multiple ...
30 Jun 2007 - Given a reference system x' y' z' for incident radiation propagating in the z ' direction, we now consider the case of a rotational ellipsoid with mayor axis. A in the plane x' z', making an angle θ with the x' axis. The two equal. (mi

Statistical Modeling for Monte Carlo Simulation using Hspice - CiteSeerX
To enable Monte Carlo methods, a statistical model is needed. This is a model ..... However, it is difficult to determine the correlation without a lot of statistical data. The best case .... [3] HSPICE Simulation and Analysis User Guide. March 2005.

Sonification of Markov chain Monte Carlo simulations
This paper illustrates the use of sonification as a tool for monitor- ... tional visualization methods to understand the important features of Ф. When. , however ...

Bayes and Big Data: The Consensus Monte Carlo ... - Semantic Scholar
Oct 31, 2013 - posterior distribution based on very large data sets. When the ... and Jordan (2011) extend the bootstrap to distributed data with the “bag of little ...

Using the Direct Simulation Monte Carlo Approach for ...
The viability of using the Direct Simulation Monte Carlo (DSMC) approach to study the blast-impact ... by computing load definition for two model geometries - a box and an 'I' shaped beam. ... On the other hand, particle methods do not make the conti

Bayes and Big Data: The Consensus Monte Carlo ... - Rob McCulloch
Oct 31, 2013 - The number of distinct configurations of xij in each domain is small. ...... within around 11,000 advertisers using a particular Google advertising.