scholarly journals Sequential binary decay of light nuclear systems: An assessment of statistical model codes

2020 ◽  
Vol 15 ◽  
pp. 83
Author(s):  
N. G. Nicolis
Keyword(s):  
Monte Carlo ◽  
Statistical Model ◽  
Sequential Decay ◽  
Model Code ◽  
Charge Distributions ◽  
Final Mass ◽  
Nuclear Systems ◽  
Nucleon Emission ◽  
Excited Nuclei ◽  
Complete Dissociation

The sequential decay of excited nuclei is described as a succession of binary processes involving fragments in their ground, excited-bound and unbound states. Primary together with secondary decays lead to the final mass and charge distributions. Asymmetric mass splittings involving nucleon emission up to symmetric binary ones are treated within the Weisskopf evaporation formalism, in a unified manner. This procedure was imple- mented in the Monte-Carlo multi-step statistical model code MECO (Multisequential Evaporation COde). We study the evolution of the calculated final mass and charge distributions from 40Ar* as a function of the excitation energy, up to complete dissociation. Our results are compared with the predictions of statistical evaporation codes based on different assumptions for the compound nucleus decay.

SEQUENTIAL BINARY DECAY OF HIGHLY EXCITED NUCLEI

2008 ◽  
Vol 17 (08) ◽  
pp. 1541-1556 ◽  
Author(s):  
N. G. NICOLIS
Keyword(s):  
Rate Equations ◽  
Stage Theory ◽  
Mass Distributions ◽  
Model Code ◽  
Decay Products ◽  
Final Mass ◽  
Initial Excitation ◽  
Nucleon Emission ◽  
Excited Nuclei ◽  
Complete Dissociation

The decay of highly excited nuclei is described as a sequence of binary processes involving emission of fragments in their ground, excited-bound and unbound states. Primary together with secondary decay products lead to the final mass distributions. Asymmetric mass splittings involving nucleon emission up to symmetric binary ones are treated according to a generalized Weisskopf evaporation formalism. This procedure is implemented in the Monte-Carlo multi-step statistical model code MECO (Multisequential Evaporation COde). We examine the evolution of the calculated final mass distributions in the decay of a light compound nucleus, as the initial excitation energy increases towards the limits of complete dissociation. Comparisons are made with the predictions of the transition-stage theory, as well as a consistent Weisskopf treatment in which the decay process is described by rate equations for the generation of different fragment species.

scholarly journals Variational methods and speed-up of Monte Carlo perturbation computations for optimal design in nuclear systems

2019 ◽  
Vol 34 (3) ◽  
pp. 211-221
Author(s):  
Zafar Koreshi ◽  
Hamda Khan ◽  
Muhammad Yaqub
Keyword(s):  
Monte Carlo ◽  
Variational Methods ◽  
Nuclear Reactor ◽  
Critical Mass ◽  
Reactor Core ◽  
Radiation Shielding ◽  
Optimization Simulation ◽  
Nuclear Systems ◽  
Optimal Mix ◽  
Optimal Material

Seeking optimal material distribution in a nuclear system to maximize a response function of interest has been a subject of considerable interest in nuclear engineering. Examples are the optimal fuel distribution in a nuclear reactor core to achieve uniform burnup using minimum critical mass and the use of composite materials with an optimal mix of constituent elements in detection systems and radiation shielding. For such studies, variational methods have been found to be useful but, they have been used for standalone analyses often restricted to idealized models, while more elaborate design studies have required computationally expensive Monte Carlo simulations ill-suited to iterative schemes for optimization. Such an inherent disadvantage of Monte Carlo methods changed with the development of perturbation algorithms but, their efficiency is still dependent on the reference configuration for which a hit-and-trial approach is often used. In the first illustrative example, this paper explores the computational speedup for a bare cylindrical reactor core, achievable by using a variational result to enhance the computational efficiency of Monte Carlo design optimization simulation. In the second example, the effect of non-uniform material density in a fixed-source problem, applicable to optimal moderator and radiation shielding, is presented. While applications of this work are numerous, the objective of this paper is to present preliminary variational results as inputs to elaborate stochastic optimization by Monte Carlo simulation for large and realistic systems.

scholarly journals Reliability of internal column-slab connection under punching according to NBR 6118:2014

2018 ◽  
Vol 11 (5) ◽  
pp. 931-948
Author(s):  
G. R. SILVA ◽  
A. CAMPOS FILHO ◽  
M. V. REAL
Keyword(s):  
Monte Carlo ◽  
Statistical Analysis ◽  
Reliability Index ◽  
Ansys Software ◽  
Model Code ◽  
Flat Slabs ◽  
Target Reliability Index ◽  
The Monte Carlo Method ◽  
Model Code 2010 ◽  
Brazilian Standard

Abstract This article presents a study on the reliability of internal column-slab connection under punching, designed according to the Brazilian Standard NBR 6118:2014. The evaluation of reliability was made by comparing the reliability index β with the target reliability index recommended by the fib Model Code 2010. The reliability indexes were calculated through statistical analysis of the data obtained with numerical simulations using the Monte Carlo method, with Latin Hypercube sample, through ANSYS software. The results showed that, for most slabs, the indexes of reliability β presented satisfactory results. However, some of the tested slabs presented results below the assumed limits. Therefore, this article suggests that the Brazilian Standard NBR 6118:2014 is appropriate for most flat slabs without shear reinforcement.

BINARY AND TERNARY FISSION WITHIN THE STATISTICAL MODEL

2008 ◽  
Vol 17 (10) ◽  
pp. 2014-2019 ◽  
Author(s):  
GURGEN G. ADAMIAN ◽  
ALEXANDER V. ANDREEV ◽  
NIKOLAI V. ANTONENKO ◽  
WERNER SCHEID
Keyword(s):  
Statistical Model ◽  
Nuclear Fission ◽  
Binary Fission ◽  
Ternary Fission ◽  
Scission Point ◽  
Fission Fragments ◽  
Charge Distributions

The binary and ternary nuclear fission are treated within the statistical model. At the scission point we calculate the potentials as functions of the deformations of the fragments in the dinuclear model. The potentials give the mass and charge distributions of the fission fragments. The ternary fission is assumed to occur during the binary fission.

scholarly journals A Bayesian spatial random effects model characterisation of tumour heterogeneity implemented using Markov chain Monte Carlo (MCMC) simulation

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2082 ◽  
Author(s):  
Martin D. King ◽  
Matthew Grech-Sollars
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Statistical Model ◽  
Spatial Heterogeneity ◽  
Random Effects ◽  
Random Effects Model ◽  
Tumour Heterogeneity ◽  
Spatial Random Effects ◽  
Mcmc Simulation

The focus of this study is the development of a statistical modelling procedure for characterising intra-tumour heterogeneity, motivated by recent clinical literature indicating that a variety of tumours exhibit a considerable degree of genetic spatial variability. A formal spatial statistical model has been developed and used to characterise the structural heterogeneity of a number of supratentorial primitive neuroectodermal tumours (PNETs), based on diffusion-weighted magnetic resonance imaging. Particular attention is paid to the spatial dependence of diffusion close to the tumour boundary, in order to determine whether the data provide statistical evidence to support the proposition that water diffusivity in the boundary region of some tumours exhibits a deterministic dependence on distance from the boundary, in excess of an underlying random 2D spatial heterogeneity in diffusion. Tumour spatial heterogeneity measures were derived from the diffusion parameter estimates obtained using a Bayesian spatial random effects model. The analyses were implemented using Markov chain Monte Carlo (MCMC) simulation. Posterior predictive simulation was used to assess the adequacy of the statistical model. The main observations are that the previously reported relationship between diffusion and boundary proximity remains observable and achieves statistical significance after adjusting for an underlying random 2D spatial heterogeneity in the diffusion model parameters. A comparison of the magnitude of the boundary-distance effect with the underlying random 2D boundary heterogeneity suggests that both are important sources of variation in the vicinity of the boundary. No consistent pattern emerges from a comparison of the boundary and core spatial heterogeneity, with no indication of a consistently greater level of heterogeneity in one region compared with the other. The results raise the possibility that DWI might provide a surrogate marker of intra-tumour genetic regional heterogeneity, which would provide a powerful tool with applications in both patient management and in cancer research.

Sign in / Sign up

Export Citation Format

Share Document