Monte Carlo simulations of the S-shaped neutron guides with asymmetric concave and convex surface coatings

• URL: http://arxiv.org/abs/2106.13916v2
• Date: Fri, 8 Oct 2021 17:16:25 GMT
• Title: Monte Carlo simulations of the S-shaped neutron guides with asymmetric concave and convex surface coatings
• Authors: Alexandre P.S. Souza, Luiz P. de Oliveira and Frederico A. Genezini
• Abstract summary: We develop a formalism of construction of a minimal S-shaped guide by only considering the exclusion of the Line-of-Sight. By intending to optimize these guide systems, simulations of this study also consider scenarios that have different supermirrors.
• Score: 68.8204255655161
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: During the last decades, neutron beam transportation has been a well-known and established subject for designing proper neutron guides. However, sometimes unusual adaptation or adjustments are required out of original projects and after operation beginning of facilities. Inter-center transferring of instrument locations also requires a new approach that is not necessarily described in the literature. Inside these situations, the use of S-shaped guides has not been fully discussed in the literature. From a geometrical analysis, we develop a formalism of construction of a minimal S-shaped guide by only considering the exclusion of the Line-of-Sight. We study this guide model through the wavelength cutoff and the neutron transport efficiency analysis. Here, Monte Carlo simulations using MCSTAS software are applied. By intending to optimize these guide systems, simulations of this study also consider scenarios that have different supermirrors. A formalism to determine wavelength cutoff for unique and variable index guide systems is also developed. Simulation results show a good agreement between theoretical and simulated wavelength cutoff values. In addition, we have found specific configurations that combine efficient neutron transport and lower index values on the convex surfaces of curved guides that form the S-shaped guide.

Related papers

• Stable Surface Regularization for Fast Few-Shot NeRF [76.00444039563581]
  We develop a stable surface regularization technique called Annealing Signed Distance Function (ASDF) We observe that the Eikonal loss requires dense training signal to shape different level-sets of SDF, leading to low-fidelity results under few-shot training. The proposed approach is up to 45 times faster than existing few-shot novel view synthesis methods.
  arXiv  Detail & Related papers  (2024-03-29T05:39:47Z)
• A Theoretical Analysis of Noise Geometry in Stochastic Gradient Descent [9.064667124987068]
  Minibatch gradient descent (SGD) is a geometry phenomenon where noise aligns favorably with the geometry of local landscape. We propose two metrics, derived from analyzing how noise influences the loss and subspace projection dynamics, to quantify the alignment strength.
  arXiv  Detail & Related papers  (2023-10-01T14:58:20Z)
• Multielement polynomial chaos Kriging-based metamodelling for Bayesian inference of non-smooth systems [0.0]
  This paper presents a surrogate modelling technique based on domain partitioning for Bayesian parameter inference of highly nonlinear engineering models. The developed surrogate model combines in a piecewise function an array of local Polynomial Chaos based Kriging metamodels constructed on a finite set of non-overlapping of the input space. The efficiency and accuracy of the proposed approach are validated through two case studies, including an analytical benchmark and a numerical case study.
  arXiv  Detail & Related papers  (2022-12-05T13:22:39Z)
• Spin many-body phases in standard and topological waveguide QED simulators [68.8204255655161]
  We study the many-body behaviour of quantum spin models using waveguide QED setups. We find novel many-body phases different from the ones obtained in other platforms.
  arXiv  Detail & Related papers  (2021-06-22T09:44:20Z)
• Learning Generative Prior with Latent Space Sparsity Constraints [25.213673771175692]
  It has been argued that the distribution of natural images do not lie in a single manifold but rather lie in a union of several submanifolds. We propose a sparsity-driven latent space sampling (SDLSS) framework and develop a proximal meta-learning (PML) algorithm to enforce sparsity in the latent space. The results demonstrate that for a higher degree of compression, the SDLSS method is more efficient than the state-of-the-art method.
  arXiv  Detail & Related papers  (2021-05-25T14:12:04Z)
• A Unifying and Canonical Description of Measure-Preserving Diffusions [60.59592461429012]
  A complete recipe of measure-preserving diffusions in Euclidean space was recently derived unifying several MCMC algorithms into a single framework. We develop a geometric theory that improves and generalises this construction to any manifold.
  arXiv  Detail & Related papers  (2021-05-06T17:36:55Z)
• Sinkhorn Natural Gradient for Generative Models [125.89871274202439]
  We propose a novel Sinkhorn Natural Gradient (SiNG) algorithm which acts as a steepest descent method on the probability space endowed with the Sinkhorn divergence. We show that the Sinkhorn information matrix (SIM), a key component of SiNG, has an explicit expression and can be evaluated accurately in complexity that scales logarithmically. In our experiments, we quantitatively compare SiNG with state-of-the-art SGD-type solvers on generative tasks to demonstrate its efficiency and efficacy of our method.
  arXiv  Detail & Related papers  (2020-11-09T02:51:17Z)
• Towards Reflectivity profile inversion through Artificial Neural Networks [0.0]
  The goal of Specular Neutron and X-ray Reflectometry is to infer materials Scattering Length Density profiles from experimental reflectivity curves. This paper focuses on investigating an original approach to the ill-posed non-invertible problem which involves the use of Artificial Neural Networks.
  arXiv  Detail & Related papers  (2020-10-15T10:09:09Z)
• Neutron Guide Building Instruments of the Brazilian Multipurpose Reactor (RMB) Project [58.720142291102135]
  We present a standard design requirement of two primordial instruments, namely Sabi'a and Araponga. They are, respectively, cold and thermal neutron instruments and correspond to a Small-Angle Neutron Scattering (SANS) and High-Resolution Powder Neutron Diffractometer (HRPND) We propose here an initial investigation of the use of simple and split guides to transport neutron beams to two different instruments on the same guide.
  arXiv  Detail & Related papers  (2020-03-11T11:57:55Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.