Optimal Choice of Parameters for Exponential Biasing in Monte Carlo

Dubi, A.; Dudziak, D.J.

doi:10.13182/nse79-a18922

Cited by 16 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dubi's work was focused on exponential transform [45,46] and importance splitting [47][48][49][50][51][52]. Burn extended Dubi's importance splitting work in generality [53,54] and to other variance-reduction techniques [55,56].…”

Section: Dubi and Burnmentioning

confidence: 99%

Cost-optimized Automated Variance Reduction for Highly Angle-dependent Radiation Transport Analyses [Dissertation]

2023

View full text Add to dashboard Cite

I appreciate Ms. Peggy Jo Gramer's and Dr. Garnette Roberts's ceaseless work to ensure that all needs, academic and personal, were addressed during my time as a doctoral student.My gratitude also goes to mentors from earlier in my career, Mr. Stan Anderson, Mr. Arnie Fero, and Dr. Gianluca Longoni, for instilling strong engineering principles and for encouraging me to follow a path that lead me to this point.

show abstract

Section: Dubi and Burnmentioning

confidence: 99%

Cost-optimized Automated Variance Reduction for Highly Angle-dependent Radiation Transport Analyses [Dissertation]

2023

View full text Add to dashboard Cite

show abstract

“…For example, using too low next event probability, p s , (see section 2.2) leads to shifting of the history length probability distribution towards emphasizing low terms in the Neumann series [1] of the target calculation while reducing the probability of appearance of high terms with higher importance. The "sawtooth" phenomenon, in which a wrong result is supported by a seemingly low variance [6], appears when the number of histories is such that artificially reduced important regions in the phase space are not sampled. Thus an elaborate study of such biasing methods and their impact on the phase space of each specific problem must be carried out in order to avoid erroneous results.…”

Section: Phase Space Splittingmentioning

confidence: 99%

A Note on Variance Reduction Methods in Monte Carlo Applications to Systems Engineering and Reliability.

Khazen¹,

Dubi²

1999

Monte Carlo Methods and Applications

View full text Add to dashboard Cite

Monte Carlo analysis of the time behavior of complex modern systems is rapidly becoming a commonplace tool in the design and life cycle control. This is due to the inherent complexity of such systems both in terms of their multiple dimensions and interactive stochastic behavior. Predictions of system characteristics such as reliability, availability, spare parts requirements, maintenance scheduling etc. are essential at the earliest stages of design in order to achieve optimal system performance at the lowest possible cost. The applications of Monte Carlo methods to this field are the only effective approach. Within this area the estimation of rare events (with significant consequences) is a most difficult problem. Variance Reduction Methods (VRM) are, therefore, important.Although a vast amount of effort has been invested in the development of variance reduction methods in the transport of neutral particles and a large variety of such methods exist, their transfer into the area of systems engineering is not at all trivial. This, mainly, due to the profound differences in the phase space and the addition of the "aging" phenomena in the case of systems transport.In this work a number of variance reduction methods is considered. The method of forced events is applied to the time crossing estimator and to the event type estimator. The latter case is shown to yield a method parallel to the leakage estimation method. Also, geometrical splitting is considered. The questions of splitting surface and 'distance to detector', which are essential for this method, are discussed and an approach that accounts for these elements is suggested. In each case it is shown that the VRM method is unbiased and numerical examples are presented to demonstrate the efficiency of each method.

show abstract

“…The different efficient methods used by various authors to solve the problem have resulted in a whole range of different numerical calculational schemes (Foderaro and Obenshain, 1956;Jaeger, 1968;Atomic Energy Society of Japan, 1988;Ezure, 2002;Ghassoun et al, 2000;Dubi and Dudziak, 1979;Mine, 1994). Ezure using Monte Carlo method discusses several useful calculation approximations to the simplified gamma-ray shielding formulas which are valid for various values of the parameters (Ezure, 2002).…”

Section: Introductionmentioning

confidence: 99%