Alireza Haghighat

Bio: Alireza Haghighat is an academic researcher from Virginia Tech. The author has contributed to research in topics: Monte Carlo method & Neutron flux. The author has an hindex of 14, co-authored 103 publications receiving 970 citations. Previous affiliations of Alireza Haghighat include University of Florida & Pennsylvania State University.

Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function

Abstract: Although the Monte Carlo method is considered to be the most accurate method available for solving radiation transport problems, its applicability is limited by its computational expense. Thus, bia...

Development of new quadrature sets with the "ordinate splitting" technique

Abstract: The Discrete Ordinate Method (SN) is one of the most widely used techniques to solve the linear Boltzmann equation. A commonly used technique for the generation of discrete ordinates and associated weights (quadrature set) is the level-symmetric. However, this technique is limited to order S20. To deal with highly angular dependent situations, we have developed different quadrature techniques including PN-EW, PN-TN and a new angular refinement approach referred to as “ordinate splitting”. We have tested these new quadrature sets using the Kobayashi 3-D problem 3, and demonstrated that PN-TN with ordinate splitting is an effective approach for highly directional problems.

Monte Carlo Methods for Particle Transport

Abstract: Acknowledgments About the Author Introduction History of Monte Carlo Simulation Status of Monte Carlo Codes Motivation for Writing This Book Overview of the Book Recommendations to Instructors Author's Expectation References Random Variables and Sampling Introduction Random Variables Discrete Random Variable Continuous Random Variable Notes on pdf and cdf Characteristics Random Numbers Derivation of the Fundamental Formulation of Monte Carlo (FFMC) Sampling One-Dimensional Density Functions Analytical Inversion Numerical Inversion Probability Mixing Method Rejection Technique Numerical Evaluation Table Lookup Sampling Multidimensional Density Functions Example Procedures for Sampling a Few Commonly Used Distributions Normal Distribution Watt Spectrum Cosine and Sine Function Sampling Remarks References Problems Random Number Generation (RNG) Introduction Random Number Generation Approaches Pseudorandom Number Generators (PRNGs) Congruential Generators Multiple Recursive Generator Testing Randomness x2-Test Frequency Test Serial Test Gap Test Poker Test Moment Test Serial Correlation Test Serial Test via Plotting Examples for PRNG Tests Evaluation of PRNG Based on Period and Average Serial Test via Plotting Remarks References Problems Fundamentals of Probability and Statistics Introduction Expectation Value One-Dimensional Density Function Multidimensional Density Function Useful Theorems Associated with the "True Variance" Definition of Sample Expectation Values Used in Statistics Sample Mean Expected Value of the Sample Variance Precision and Accuracy of a Statistical Process Uniform Distribution Bernoulli and Binomial Distributions Geometric Distribution Poisson Distribution Normal ("Gaussian") Distribution Limit Theorems and Their Applications Corollary to the de Moivre-Laplace Limit Theorem Central Limit Theorem Formulations of Uncertainty and Relative Error for a Random Process General Random Process Special Case of Bernoulli Process Confidence Interval for Finite Sampling Introduction to Student's t-Distribution Determination of Confidence Interval and Application of the t-Distribution Test of Normality of Distribution Test of Skewness Coefficient Shapiro-Wilk Test for Normality References Problems Integrals and Associated Variance Reduction Techniques Introduction Estimation of Integrals Variance Reduction Techniques Associated with Integrals Importance Sampling Correlation Sampling Technique Stratified Sampling Technique Combined Sampling Remarks References Problems Fixed-Source Monte Carlo Particle Transport Introduction Introduction to the Linear Boltzmann Equation Introduction the Monte Carlo Method Determination of Free Flight, i.e., Path-Length Selection of Interaction Type Selection of Scattering Angle A Monte Carlo Algorithm for Estimation of Transmitted Particles Perturbation Calculations via Correlated Sampling Analysis of Monte Carlo Results Remarks References Problems Variance Reduction Techniques in Particle Transport Introduction Effectiveness of Variance Reduction Algorithms Biasing of Density Functions Implicit Capture (or Survival Biasing) Russian Roulette Biasing the Path-Length to the Next Collision Exponential Transformation Forced Collision Splitting Techniques Geometric Splitting with Russian Roulette Energy Splitting with Russian Roulette Angular Splitting with Russian Roulette Weight-Window Technique Application of Combination of Importance Sampling, pdf biasing, and Splitting Technique in Particle Transport Importance (Adjoint) Function Methodology in Deterministic Transport Theory Determination of Detector Response Use of Deterministic Importance (Adjoint) Function for Importance Sampling Remarks References Problems Tallying Introduction Major Quantities in a Particle Transport Simulation Tallying in a Steady-State System Collision Estimator Path-Length Estimator Surface-Crossing Estimator Analytical Estimator Tallying in a Time-Dependent System Tallies in Nonanalog Simulations Estimation of Relative Error Associated Physical Quantities Propagation of Error Remarks References Problems Geometry and Particle Tracking Introduction Discussion on a Combinatorial Geometry Approach Definition of Surfaces Definition of Cells Examples Description of Boundary Conditions Particle Tracking Remarks References Problems Eigenvalue or Criticality Monte Carlo Particle Transport Introduction Theory of Power-Iteration for Eigenvalue Problems Monte Carlo Eigenvalue Calculation Random Variables Associated with a Fission Process Direction of Fission Neutrons Monte Carlo Simulation of a Criticality Problem Estimators for Sampling Fission Neutrons Issues Associated with the Standard Eigenvalue Calculation Procedure Diagnostic Methods for Source Convergence Fission Matrix (FM) Methodology Issues Associated with the FM Method Remarks References Problems Vector and Parallel Processing of Monte Carlo Methods Introduction Vector Processing Vector Performance Parallel Processing Parallel Performance Vectorization of Monte Carlo Methods Parallelization of the Monte Carlo Methods Other Possible Parallel Monte Carlo Algorithms Development of a Parallel Algorithm Using MPI Remarks References Problems Appendices One to Six

Science Case for the Einstein Telescope

Abstract: The Einstein Telescope (ET), a proposed European ground-based gravitational-wave detector of third-generation, is an evolution of second-generation detectors such as Advanced LIGO, Advanced Virgo, and KAGRA which could be operating in the mid 2030s. ET will explore the universe with gravitational waves up to cosmological distances. We discuss its main scientific objectives and its potential for discoveries in astrophysics, cosmology and fundamental physics.

First MR images obtained during megavoltage photon irradiation from a prototype integrated linac-MR system

Abstract: The authors report the first magnetic resonance (MR) images produced by their prototype MR system integrated with a radiation therapy source. The prototype consists of a 6 MV linac mounted onto the open end of a biplanar 0.2 T permanent MR system which has 27.9 cm pole-to-pole opening with flat gradients (40 mT/m) running under a TMX NRC console. The distance from the magnet isocenter to the linac target is 80 cm. The authors' design has resolved the mutual interferences between the two devices such that the MR magnetic field does not interfere with the trajectory of the electron in the linac waveguide, and the radiofrequency (RF) signals from each system do not interfere with the operation of the other system. Magnetic and RF shielding calculations were performed and confirmed with appropriate measurements. The prototype is currently on a fixed gantry; however, in the very near future, the linac and MR magnet will rotate in unison such that the linac is always aimed through the opening in the biplanar magnet. MR imaging was found to be fully operational during linac irradiation and proven by imaging a phantom with conventional gradient echo sequences. Except for small changes in SNR, MR images produced during irradiation were visually and quantitatively very similar to those taken with the linac turned off. This prototype system provides proof of concept that the design has decreased the mutual interferences sufficiently to allow the development of real-time MR-guided radiotherapy. Low field-strength systems (0.2-0.5 T) have been used clinically as diagnostic tools. The task of the linac-MR system is, however, to provide MR guidance to the radiotherapy beam. Therefore, the 0.2 T field strength would provide adequate image quality for this purpose and, with the addition of fast imaging techniques, has the potential to provide 4D soft-tissue visualization not presently available in image-guided radiotherapy systems. The authors' initial design incorporates a permanent magnet; however, other types of magnets and field strengths could also be incorporated. Usable MR images were obtained during linac irradiation from the linac-MR prototype. The authors' prototype design can be used as the functional starting point in developing real-time MR guidance offering soft-tissue contrast that can be coupled with tumor tracking for real-time adaptive radiotherapy.

Science Case for the Einstein Telescope

Abstract: The Einstein Telescope (ET), a proposed European ground-based gravitational-wave detector of third-generation, is an evolution of second-generation detectors such as Advanced LIGO, Advanced Virgo, and KAGRA which could be operating in the mid 2030s. ET will explore the universe with gravitational waves up to cosmological distances. We discuss its main scientific objectives and its potential for discoveries in astrophysics, cosmology and fundamental physics.