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Monte Carlo Simulation in Quantum Science and Applied Physics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Quantum Science and Technology".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 11314

Special Issue Editors

Dr. Davide Bianco

E-Mail Website
Guest Editor
Italian Aerospace Research Centre (CIRA), via Maiorise s.n.c., 81043 Capua, Italy
Interests: nuclear and radiation physics; dosimetry; radioprotection; computational physics; Monte-Carlo radiation transport; radiation in space; nuclear medicine
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Maria Quarto

E-Mail Website
Guest Editor
Department of Advanced Biomedical Science, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
Interests: radiation detection; radiation; radiation protection; metastasis; radioactivity; tumors; cancer cells; Monte Carlo simulation; laser; optics
Special Issues, Collections and Topics in MDPI journals
Dr. Filomena Loffredo

E-Mail Website
Guest Editor
Department of Advanced Biomedical Science, University of Naples Federico II, Via Pansini 5, 80131 Naples, Italy
Interests: radioprotection; ionizing radiation; radioactivity; environmental radiation; radon gas; radiation detection; solid-state detection; space radiation; numerical analysis; Monte Carlo simulation; geostatistical methods; physics education; outreach; health physics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are serving as Guest Editors of a Special Issue of Applied Sciences devoted to the use of Monte Carlo techniques and stochastic approaches in general, and we would like to invite you to contribute with an original research paper or a review article on the subject.

More specifically, this monographic issue of the journal will include studies on radiation and particle transport simulations, with applications including cold reaction chemistry, rarefied gas flows, and ionizing radiation dosimetry. The aim is to present number of papers accounting for, at least, some of the significant applied scientific field which have been impacted by the introduction of stochastic computational approaches.

In the five decades since the seventies, the way of doing science has been revolutionized with the introduction of computers. This is particularly true for those fields which nowadays make extensive use of Monte Carlo techniques—introduced in the forties though only effectively exploited thanks to the exceptional increase in computing power.

The aim is to select some papers for creating a reference publication regarding the state-of-the-art stochastic techniques currently employed within close, nonetheless separate, scientific fields. Hopefully, a large part of the scientific community will benefit from this work, which will provide an account of some of the specific computational strategies and theoretical findings which have been derived on the subject.     

The manuscripts should cover, but are not limited to, the following topics:

  • Radiation transport computational studies exploiting stochastic approaches
  • Monte Carlo methods in cold atomic and molecular physics and chemistry
  • Hybrid methods coupling molecular dynamics and Monte Carlo simulations
  • Review articles on Monte Carlo technique and related stochastic methods
  • Experimental approaches combining measures and Monte Carlo simulation
  • Monte Carlo approaches in fluid flow simulation
  • Direct simulation of transitional flow for hypersonic reentry conditions
  • Monte Carlo techniques for ionizing radiation dosimetry
  • Radiation shielding design with Monte Carlo simulations

Dr. Davide Bianco
Dr. Maria Quarto
Dr. Filomena Loffredo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • stochastic approaches
  • Monte Carlo techniques
  • radiation transport
  • gas flow dynamics

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Published Papers (6 papers)

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Research

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14 pages, 665 KiB  
Article
Groundwater Contaminant Transport Solved by Monte Carlo Methods Accelerated by Deep Learning Meta-Model
by Martin Špetlík and Jan Březina
Appl. Sci. 2022, 12(15), 7382; https://doi.org/10.3390/app12157382 - 22 Jul 2022
Cited by 2 | Viewed by 1585
Abstract
Groundwater contaminant transport modeling is a vitally important topic. Since modeled processes include uncertainties, Monte Carlo methods are adopted to obtain some statistics. However, accurate models have a substantial computational cost. This drawback can be overcome by employing the multilevel Monte Carlo method [...] Read more.
Groundwater contaminant transport modeling is a vitally important topic. Since modeled processes include uncertainties, Monte Carlo methods are adopted to obtain some statistics. However, accurate models have a substantial computational cost. This drawback can be overcome by employing the multilevel Monte Carlo method (MLMC) or approximating the original model using a meta-model. We combined both of these approaches. A stochastic model is substituted with a deep learning meta-model that consists of a graph convolutional neural network and a feed-forward neural network. This meta-model can approximate models solved on unstructured meshes. The meta-model within the standard Monte Carlo method can bring significant computational cost savings. Nevertheless, the meta-model must be highly accurate to obtain similar errors as when using the original model. Proposed MLMC with the new lowest-accurate level of meta-models can reduce total computational costs, and the accuracy of the meta-model does not have to be so high. The size of the computational cost savings depends on the cost distribution across MLMC levels. Our approach is especially efficacious when the dominant computational cost is on the lowest-accuracy MLMC level. Depending on the number of estimated moments, we can reduce computational costs by up to ca. 25% while maintaining the accuracy of estimates. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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15 pages, 2798 KiB  
Article
Uncertainty Quantification for Numerical Solutions of the Nonlinear Partial Differential Equations by Using the Multi-Fidelity Monte Carlo Method
by Wenting Du and Jin Su
Appl. Sci. 2022, 12(14), 7045; https://doi.org/10.3390/app12147045 - 12 Jul 2022
Cited by 1 | Viewed by 1551
Abstract
The Monte Carlo simulation is a popular statistical method to estimate the effect of uncertainties on the solutions of nonlinear partial differential equations, but it requires a huge computational cost of the deterministic model, and the convergence may become slow. For this reason, [...] Read more.
The Monte Carlo simulation is a popular statistical method to estimate the effect of uncertainties on the solutions of nonlinear partial differential equations, but it requires a huge computational cost of the deterministic model, and the convergence may become slow. For this reason, we developed the multi-fidelity Monte Carlo (MFMC) methods based on data-driven low-fidelity models for uncertainty analysis of nonlinear partial differential equations. Firstly, the nonlinear partial differential equations are transformed into ordinary differential equations (ODEs) by using finite difference discretization or Fourier transformation. Then, the reduced dimension model and discrete empirical interpolation method (DEIM) are coupled to construct effective nonlinear low-fidelity models in ODEs system. Finally, the MFMC method is used to combine the output information of the high-fidelity model and the low-fidelity models to give the optimal estimation of the statistics. Experimental results of the nonlinear Schrodinger equation and the Burgers’ equation show that, compared with the standard Monte Carlo method, the MFMC method based on the data-driven low-fidelity model in this paper can improve the calculation efficiency significantly. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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10 pages, 295 KiB  
Article
The New Physics in LILITA_N21: An Improved Description of the Reaction 190 MeV 40Ar + 27Al
by Antonio Di Nitto, Federico Davide, Emanuele Vardaci, Davide Bianco, Giovanni La Rana and Daniela Mercogliano
Appl. Sci. 2022, 12(9), 4107; https://doi.org/10.3390/app12094107 - 19 Apr 2022
Cited by 3 | Viewed by 1215
Abstract
In this paper, light charged particle emission in the evaporation residue channel for the 190 MeV 40Ar + 27Al reaction leading to 67Ga composite nuclei at Ex = 91 MeV and angular momentum up to 46 ℏ has been [...] Read more.
In this paper, light charged particle emission in the evaporation residue channel for the 190 MeV 40Ar + 27Al reaction leading to 67Ga composite nuclei at Ex = 91 MeV and angular momentum up to 46 ℏ has been re-analyzed. The main goal was to study the decay of 67Ga on the basis of an extended set of observables in order to provide a description of the evaporative decay cascades using the multistep Monte Carlo approach. The proton and α-particle energy spectra along with their angular distributions and ratios of differential multiplicities have been considered. The measured observables were compared with statistical model calculations. Having used a single-step Monte Carlo approach and standard parameters decades ago, the model does not provide a good description of the full dataset. Only a subset of the data was reproduced by assuming emitting nuclei with very large deformed shapes in a previous work published in the late 1980s. In the reported analysis, better agreement has been observed. Using the new transmission coefficients from the Optical Model, the parameters of which have recently been derived, the multi-step approach and the introduction of a nuclear shape description based on the nuclear stratosphere allowed us to realize a significant improvement. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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9 pages, 2336 KiB  
Article
Protons Interaction with Nomex Target: Secondary Radiation from a Monte Carlo Simulation with Geant4
by Filomena Loffredo, Emanuele Vardaci, Davide Bianco, Antonio Di Nitto and Maria Quarto
Appl. Sci. 2022, 12(5), 2643; https://doi.org/10.3390/app12052643 - 3 Mar 2022
Cited by 6 | Viewed by 1763
Abstract
The study of suitable materials to shield astronauts from Galactic Cosmic Rays (GCR) is a topic of fundamental importance. The choice of the material must take into account both the secondary radiation produced by the interaction between primary radiation and material and its [...] Read more.
The study of suitable materials to shield astronauts from Galactic Cosmic Rays (GCR) is a topic of fundamental importance. The choice of the material must take into account both the secondary radiation produced by the interaction between primary radiation and material and its shielding ability. The physics case presented here deals with the interaction of a proton beam with a Nomex shield, namely, a target material with a mass thickness of 20 g cm−2. The study was conducted with the simulation code DOSE based on the well-known simulation package Geant4. This article shows the properties of secondary radiations produced in the target by the interaction of a proton beam in an energy range characterizing the GCR spectrum. We observed the production of ions of masses and charges lower than the chemical elements that make up Nomex, and also a significant production of neutrons, protons, and 𝛼 particles. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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10 pages, 2414 KiB  
Article
Estimating Specific Patient Organ Dose for Chest CT Examinations with Monte Carlo Method
by Yang Yang, Weihai Zhuo, Yiyang Zhao, Tianwu Xie, Chuyan Wang and Haikuan Liu
Appl. Sci. 2021, 11(19), 8961; https://doi.org/10.3390/app11198961 - 26 Sep 2021
Cited by 8 | Viewed by 2063
Abstract
Purpose: The purpose of this study was to preliminarily estimate patient-specific organ doses in chest CT examinations for Chinese adults, and to investigate the effect of patient size on organ doses. Methods: By considering the body-size and body-build effects on the organ doses [...] Read more.
Purpose: The purpose of this study was to preliminarily estimate patient-specific organ doses in chest CT examinations for Chinese adults, and to investigate the effect of patient size on organ doses. Methods: By considering the body-size and body-build effects on the organ doses and taking the mid-chest water equivalent diameter (WED) as a body-size indicator, the chest scan images of 18 Chinese adults were acquired on a multi-detector CT to generate the regional voxel models. For each patient, the lungs, heart, and breasts (glandular breast tissues for both breasts) were segmented, and other organs were semi-automated segmented based on their HU values. The CT scanner and patient models simulated by MCNPX 2.4.0 software (Los Alamos National LaboratoryLos Alamos, USA) were used to calculate lung, breast, and heart doses. CTDIvol values were used to normalize simulated organ doses, and the exponential estimation model between the normalized organ dose and WED was investigated. Results: Among the 18 patients in this study, the simulated doses of lung, heart, and breast were 18.15 ± 2.69 mGy, 18.68 ± 2.87 mGy, and 16.11 ± 3.08 mGy, respectively. Larger patients received higher organ doses than smaller ones due to the higher tube current used. The ratios of lung, heart, and breast doses to the CTDIvol were 1.48 ± 0.22, 1.54 ± 0.20, and 1.41 ± 0.13, respectively. The normalized organ doses of all the three organs decreased with the increase in WED, and the normalized doses decreased more obviously in the lung and the heart than that in the breasts. Conclusions: The output of CT scanner under ATCM is positively related to the attenuation of patients, larger-size patients receive higher organ doses. The organ dose normalized by CTDIvol was negatively correlated with patient size. The organ doses could be estimated by using the indicated CTDIvol combined with the estimated WED. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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Review

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15 pages, 565 KiB  
Review
Monte Carlo Simulations in Aviation Contrail Study: A Review
by Davide Bianco, Elisa Marenna, Filomena Loffredo, Maria Quarto, Vittorio Di Vito and Luigi Federico
Appl. Sci. 2022, 12(12), 5885; https://doi.org/10.3390/app12125885 - 9 Jun 2022
Viewed by 2005
Abstract
This article provides a review of the role of stochastic approaches, in particular Monte Carlo calculations, in the study of aviation-induced contrails at different characteristic lengths, ranging from micrometers to the planetary scale. Pioneered in the 1960s by Bird, Direct Simulation Monte Carlo [...] Read more.
This article provides a review of the role of stochastic approaches, in particular Monte Carlo calculations, in the study of aviation-induced contrails at different characteristic lengths, ranging from micrometers to the planetary scale. Pioneered in the 1960s by Bird, Direct Simulation Monte Carlo has for long time been considered unfeasible in extended dispersed-phase systems as clouds. Due to the impressive increase in computational power, Lagrangian Monte Carlo approaches are currently available, even for studying cloud formation and evolution. Some aspects of these new approaches are reviewed after a detailed introduction to the topic of aircraft-induced cloudiness. The role of Monte Carlo approaches in reducing the different source of uncertainty about the contribution of aviation contrails to climate change is introduced. Perspectives on their role in future experimental and theoretical studies are discussed throughout the paper. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Quantum Science and Applied Physics)
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