One-dimensional Distribution Research Articles

Feasibility study of one-dimensional imaging with an optical fiber for radiation dose-rate monitoring system in the decommissioning process

Real-time dose-rate monitoring system under the high dose-rate situation is required for the decommissioning of Fukushima Daiichi Nuclear Plants to remove the debris remaining inside the plants. We have proposed a dose-rate monitor consisting of a scintillator, over 100-m long optical fiber and CCD spectrometer. Some noises with a dominant emission wavelength of below 550 nm originating from the optical fiber itself must be separated from the signal from the scintillator, and the signal region has been defined as 650–1000 nm to use significant data, up to now. In this paper, we investigated if the noise region defined as below 550 nm can be supporting data for the monitoring system, because such noises are expected to include position information through the fiber. In the emission spectrum, the intensities of the noise emission or absorption band are expected to depend on the position of the fiber, and we demonstrated such dependence, “one-dimensional dose-rate distribution”, with 20 m-long optical fiber and CCD spectrometer. Optical fiber was placed around a 60Co source with an activity of approximately 60 TBq, and emission spectra of the fiber were acquired with different dose-rate conditions from 10 to 700 Gy/h. The noise intensities were well fitted with the power function as a function of the product of fiber length and dose rate, and we found that fiber noise has rate information in one-dimensional imaging.

Modelling and fault analysis of APROS-based moisture separation reheater

A modular modelling approach was adopted to build a dynamic simulation model of the moisture separation reheater on a high-precision APROS real-time platform to investigate the dynamic operating characteristics of the moisture separation reheater. The model was subjected to steady-state and step dynamic tests at different loads. The results show that the established model can correctly reflect the steam flow and heat transfer properties and can meet the requirements of the simulation. Using the one-dimensional distribution of the model, the effect of a small breakage failure in the heat exchanger bundle was further investigated. The results showed that the heat transfer tube bundle had leaks, reducing the heat transfer capacity and affecting the quality of the steam used to work in the low-pressure turbine. Simultaneously, the effect on steam outlet parameters increased with the degree of leakage in the heat exchanger.

Binning high-dimensional classifier output for HEP analyses through a clustering algorithm

Binning high-dimensional classifier output for HEP analyses through a clustering algorithm

Experiment and simulation of LNG self-pressurization considering temperature distribution under varying liquid level

For LNG-fueled ships, estimating the rate of self-pressurization is critical because the pressure limit of an LNG storage tank and the specifications of the boil-off gas processing system depend on the pressure rise rate. However, estimation using a non-equilibrium model exhibits deviated prediction on the pressure increase when thermal stratification is occurred in LNG. Therefore, in this study, a new numerical model is proposed for estimating the self-pressurization of LNG by considering the nonuniform one-dimensional fluid temperature distribution at varying LNG levels. The suggested model was verified using a pilot-scale experiment with a 150 m3 LNG tank capacity. The results show that the proposed model can explain the limited evaporation at a higher level and the vigorous evaporation at a lower level. Furthermore, the suggested model exhibits that the temperature profile in LNG can be determined by the evaporation at the liquid surface according to different levels and can successfully predict the increasing rate of pressure by excluding the assumption of a homogeneous LNG temperature.

Numerical modelling and analysis of current induced stresses in REBCO coil stacks

This study reports the effect of the radial, axial, and hoop electromagnetic stresses caused by the large current density and the self-field (screening current-induced magnetic field) on REBCO superconducting coil stacks. A two-dimensional numerical model is used to study the stress distribution of a superconducting coil stack under current. The electromagnetically homogenized coil stack is assumed to be composed of four equally spaced coils with rectangular cross-section. Initially, the verification of the model is done by comparing the analytical calculations (which were in good agreement) of stress distributions of a superconducting slab exposed to a variable magnetic field and in a superconducting strip exposed to a variable current. Then, the two-dimensional model is used to obtain the components of stress that occurred in the coil stack under sinusoidal varying currents. The stress component distributions are calculated at different time intervals, currents, frequencies, and coil distances. Besides, one-dimensional stress distributions are plotted to show how the stress distributions change while the current increases. The upper and lower coils have much higher magnetic stress than the inner coils. Results obtained from the one-dimensional stress distribution calculations show that the stress occurring in the radial direction is lower than the stress in the z-direction in the coil stack. The stress distributions do not show a significant change as the frequency of the applied current changes. The stresses in both the radial and axial directions decrease as the distance between coils increases. All results are presented, and the possible reasons are explained.

Properties of Various Entropies of Gaussian Distribution and Comparison of Entropies of Fractional Processes

We consider five types of entropies for Gaussian distribution: Shannon, Rényi, generalized Rényi, Tsallis and Sharma–Mittal entropy, establishing their interrelations and their properties as the functions of parameters. Then, we consider fractional Gaussian processes, namely fractional, subfractional, bifractional, multifractional and tempered fractional Brownian motions, and compare the entropies of one-dimensional distributions of these processes.

On a time-changed variant of the generalized counting process

AbstractIn this paper, we time-change the generalized counting process (GCP) by an independent inverse mixed stable subordinator to obtain a fractional version of the GCP. We call it the mixed fractional counting process (MFCP). The system of fractional differential equations that governs its state probabilities is obtained using the Z transform method. Its one-dimensional distribution, mean, variance, covariance, probability generating function, and factorial moments are obtained. It is shown that the MFCP exhibits the long-range dependence property whereas its increment process has the short-range dependence property. As an application we consider a risk process in which the claims are modelled using the MFCP. For this risk process, we obtain an asymptotic behaviour of its finite-time ruin probability when the claim sizes are subexponentially distributed and the initial capital is arbitrarily large. Later, we discuss some distributional properties of a compound version of the GCP.

Search for a possible quasi-periodic structure based on data of the SDSS DR12 LOWZ

ABSTRACT We carry out a statistical analysis of the spatial distribution of galaxies at cosmological redshifts 0.16 ≤ z ≤ 0.47 based on the SDSS DR12 LOWZ catalogue. Our aim is to search and study possible large-scale quasi-regular structures embedded in the cosmic web. We calculate projections of the Cartesian galaxy coordinates on different axes (directions), densely covering certain regions in the sky to look for special directions along which 1D distributions of the projections contain significant quasi-periodic components. These components appear as peaks in the power spectra and lie in a narrow range of wave numbers 0.05 < k < 0.07. Particular attention is paid to the evaluation of the significance of the peaks. It is found that the significance of the dominant peaks for some selected directions exceeds (4–5)σ. In order to reduce possible selection effects, we create a mock homogeneous catalogue of spatial distribution of galaxies by adding a random set of artificial objects (points) to the real galaxies under study. The power spectrum of this cumulative model data also demonstrates significant peak corresponding to approximately the same scale. As a result we assume the existence of an anisotropic cosmological quasi-periodic structure with characteristic scale (116 ± 10) h−1 Mpc.

Adiabatic wall temperature in the supersonic flow of moist air with spontaneous condensation

The expansion of moist air in supersonic nozzles is accompanied by spontaneous condensation of water vapor due to a sharp decrease in flow temperature and pressure. However, in the near-wall boundary layer due to the viscous dissipation, moist air temperature decreases slightly in comparison with initial one. This leads to the fact that the vapor remains overheated in the near-wall region and condensation does not spread to its entire depth. Droplets formed in the core flow as a result of condensation can penetrate into the near-wall region due to turbulent diffusion and evaporate due to higher temperature in the near-wall region. This process causes cooling of the near-wall gas layers and, consequently, a decrease in the adiabatic wall temperature. A decrease in the adiabatic wall temperature relative to the stagnation temperature leads to a decrease in aerodynamic heating and, consequently, in the heat flux from the gas to the body. In this paper, measurements of the adiabatic temperature of the supersonic nozzle wall for moist air flow with condensation are presented. Temperature measurements were made using an infrared thermal imager. Initial moisture content varied in the range of 1.5–20.2 g/(kg. dry air) and initial relative humidity in the range 20–90%. It is shown that in the region behind the zone of spontaneous condensation (“condensation shock”), adiabatic wall temperature depends on the initial moisture content and can be either greater or less than the value of a single-phase (dry air) flow with identical initial flow parameters. Estimates of the flow parameters behind the condensation region are obtained using one-dimensional diabatic flow equations and experimental static pressure distributions along the nozzle length. The correlation between the initial moisture content, the average droplet size and the temperature recovery factor is shown.

A Generalized Approach to Model One-Dimensional Nonmonotonous Distributions Using Renyi Entropy Theory with Applications to Open-Channel Turbulent Flows

A Generalized Approach to Model One-Dimensional Nonmonotonous Distributions Using Renyi Entropy Theory with Applications to Open-Channel Turbulent Flows

Mathematical modeling of diagnostics of residual stresses in a layered medium

The work is devoted to the use of mathematical modeling in the framework of the problems of non-destructive testing of structural materials. A mathematical formulation of a three-dimensional problem of diagnostics for elastic layered medium is constructed, which makes it possible to determine the spatial distribution of residual stresses from the values of displacements measured on the surface of a layered half-space, which arose as a result of a specially initiated wave process. Under the assumption of weak inhomogeneity and anisotropy of the layers, a transition is made to a linearized (which is ill-posed) problem, the procedure for solving which is constructed using the method of stationary basic processes. As an example, the case of diagnosing a one-dimensional (depending only on the distance to the surface) distribution of residual stresses is considered.

Coded meta-materials drivened by impedance-mismatch: Ultra-broadband anti-reflection and scattering field manipulation

The inability of existing electromagnetic wave absorbing materials (EAMs) to manipulate electromagnetic waves in multiple dimensions leads to the failure to satisfy the demands placed on electromagnetic (EM) defense technology by the current complex EM environment. To break this dilemma, this study focuses on the impedance properties of EAMs, conferring additional ability to disperse and deflect reflected waves by encoding EAMs with opposite phase responses in different impedance mismatch modes. Due to the synergy of both absorption and scattering mechanisms, the developed scattering metamaterial absorber exhibits excellent anti-reflection performance, with reflectivity below 0.1 in the 7.8–16.7 GHz at 2 mm thickness. Furthermore, a genetic algorithm is employed to tailor the desired scattering field to meet the stealth requirements of specific environments, allowing for the directional transmission of EM energy in the one-dimensional or homogeneous distribution in the three-dimensional. The proposed scattering metamaterial absorber constructed by coded EAMs exhibited excellent anti-reflection properties and environmental stealth adaptability, opening up new possibilities for the development of advanced EM defense technology.

A study on the approximated angular averaging of distribution functions obtained from the Ornstein–Zernike theory for diatomic solutes consisting of fused Lennard-Jones particles immersed in a Lennard–Jones monatomic solvent

We propose an approximate method to obtain an angular averaged distribution function around an atom of a diatomic solute molecule consisting of fused Lennard–Jones (LJ) particles solvated in an LJ monatomic solvent. Our method employs the Ornstein–Zernike and closure equations for the correlation function between a single-centered solute and solvent by assuming spherical symmetry for the potential interaction. In setting the potential along the radial direction, the interaction between the solvent and solute atom that is covalently bonded to the atom located at the origin is also considered, as is typical in interaction site models. The proposed method accurately describes the angular averaged distribution function between a solvent and a solute atom that is completely buried inside the other atom in the solute, where the term “buried” indicates that the sum of the radius of one atom and the bond length is less than the radius of the other atom. The obtained angular-dependent one-dimensional distribution function is also reasonable for buried solute atoms. Thus, the proposed method is superior to the reference interaction site model (RISM) theory. However, our method failed to correctly describe the distribution function for an unburied atom of the solute, for which the RISM theory would be better than the proposed method. Furthermore, we demonstrated that sigma enlarging bridge (SEB) correction [T. Miyata, Bull. Chem. Soc. Japan, 90 (2017) 1095] is applicable to the proposed method. The combination of the method proposed in this study and SEB correction improves both the first rising region of the angular averaged distribution function and the solvation free energy.

A Numerical Analysis of Pulsed-Field Magnetization Characteristics of REBCO Bulk Magnets When Using Various Soft-Iron Yokes

We aim to improve the magnetizing efficiency while maintaining the trapped magnetic field of REBCO bulk magnets activated by pulsed-field magnetization (PFM). Recently, we performed numerical analysis using a 3D simulation model based on our bulk PFM system and estimated the magnetizing characteristics when using disk-, ring-, and cross-shaped yokes. In this paper, a detailed analysis model that accounts for the inhomogeneity of the REBCO bulk is created, and the magnetizing properties are evaluated at different temperatures and applied fields. Comparison of the experimental and numerical results for the dependence of the total magnetic flux on the applied magnetic field shows a similar trend of change. From the results of the time variation of the one-dimensional magnetic field distribution in the ascent and descent processes of the applied field, we can reproduce the experimentally confirmed fact that the magnetic flux enters from the GSR and is trapped in the GSR by considering the difference in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">J_c</i> of the GSB and the GSR in the analysis. Furthermore, it was confirmed not only in the previous experiment but also in the present analysis that the GSB arrangement of the cross-type yoke enables efficient magnetization.

Theoretical Analyses of Interaction Forces Acting between Solid Surfaces Considering One-Dimensional Periodic Material Distribution: Radial Effects of Spherical Surface

Theoretical Analyses of Interaction Forces Acting between Solid Surfaces Considering One-Dimensional Periodic Material Distribution: Radial Effects of Spherical Surface

Network feature-based phenotyping of leaf venation robustly reconstructs the latent space.

Despite substantial variation in leaf vein architectures among angiosperms, a typical hierarchical network pattern is shared within clades. Functional demands (e.g., hydraulic conductivity, transpiration efficiency, and tolerance to damage and blockage) constrain the network structure of leaf venation, generating a biased distribution in the morphospace. Although network structures and their diversity are crucial for understanding angiosperm venation, previous studies have relied on simple morphological measurements (e.g., length, diameter, branching angles, and areole area) and their derived statistics to quantify phenotypes. To better understand the morphological diversities and constraints on leaf vein networks, we developed a simple, high-throughput phenotyping workflow for the quantification of vein networks and identified leaf venation-specific morphospace patterns. The proposed method involves four processes: leaf image acquisition using a feasible system, leaf vein segmentation based on a deep neural network model, network extraction as an undirected graph, and network feature calculation. To demonstrate the proposed method, we applied it to images of non-chemically treated leaves of five species for classification based on network features alone, with an accuracy of 90.6%. By dimensionality reduction, a one-dimensional morphospace, along which venation shows variation in loopiness, was identified for both untreated and cleared leaf images. Because the one-dimensional distribution patterns align with the Pareto front that optimizes transport efficiency, construction cost, and robustness to damage, as predicted by the earlier theoretical study, our findings suggested that venation patterns are determined by a functional trade-off. The proposed network feature-based method is a useful morphological descriptor, providing a quantitative representation of the topological aspects of venation and enabling inverse mapping to leaf vein structures. Accordingly, our approach is promising for analyses of the functional and structural properties of veins.

Super-resolution Reflection Microscopy via Absorbance Modulation.

In recent years, fluorescence microscopy has been revolutionized. Reversible switching of fluorophores has enabled circumventing the limits imposed by diffraction. Thus, resolution down to the molecular scale became possible. However, to the best of our knowledge, the application of the principles underlying super-resolution fluorescence microscopy to reflection microscopy has not been experimentally demonstrated. Here, we present the first evidence that this is indeed possible. A layer of photochromic molecules referred to as the absorbance modulation layer (AML) is applied to a sample under investigation. The AML-coated sample is then sequentially illuminated with a one-dimensional (1D) focal intensity distribution (similar to the transverse laser mode TEM01) at wavelength λ1 = 325 nm to create a subwavelength aperture within the AML, followed by illumination with a Gaussian focal spot at λ2 = 633 nm for high-resolution imaging. Using this method, called absorbance modulation imaging (AMI) in reflection, we demonstrate a 2.4-fold resolution enhancement over the diffraction limit for a numerical aperture (NA) of 0.65 and wavelength (λ) of 633 nm.

Stochastic Levenberg–Marquardt Neural Network Implementation for Analyzing the Convective Heat Transfer in a Wavy Fin

The present research examines the steady, one-dimensional thermal distribution and heat transfer of a wavy fin. This heat transfer analysis considers convective effects as well as temperature-dependent thermal conductivity. Furthermore, a novel implementation of a neural network with backpropagated Levenberg–Marquardt algorithm (NN-BLMA)-based machine learning intelligent strategies is provided to interpret the heat transfer analysis of a convective wavy fin. The non-linear ordinary differential equation (ODE) of the study problem is converted into its non-dimensional form using the similarity transformation technique. The dimensionless equation obtained is then numerically explored via the Runge–Kutta–Fehlberg scheme. A data set for varying the pertinent parameters is generated, and an artificial neural network model is designed to estimate the heat transfer behavior of the wavy fin. The effectiveness of the proposed NN-BLMA is subsequently endorsed by analyses using a regression model, mean square error, and histograms. The findings of comprehensive computational parametric studies illustrate that the presented technique, NN-BLMA is an effective convergent stochastic numerical solver employed for the heat transfer model of the convective wavy fin. The wavy fin’s temperature dispersion optimizes as the thermal conductivity parameter rises. Heat transfer rate is higher in wavy fin compared to rectangular fin.

Safe and Efficient Dynamic Window Approach for Differential Mobile Robots With Stochastic Dynamics Using Deterministic Sampling

We propose an efficient and safe dynamic window approach (DWA) by using deterministic sampling. When the system dynamics have uncertainty, the control input includes errors, so that the DWA objective function becomes a random variable. When a random-choice algorithm with a finite number of samples is used to estimate the objective function, it may miss collisions during prediction. In this work, we approximate the end-state distribution as a one-dimensional distribution for each input candidate in advance and generate sample paths deterministically to eliminate the misses to achieve safe control. Numerical experiments have shown that this method is approximately three times as efficient as the Monte Carlo method in most indoor environments.

Identity breeds inequality: Evidence from a laboratory experiment on redistribution

Politics is increasingly driven by identity cleavages, which also affect the discussion about inequality and redistribution. Typically, redistribution is meant to reduce inequality, implying that redistribution neither makes the rich richer nor the former poor the new rich. However, if identity affects redistribution, these limits might no longer be binding, and redistribution could further increase existing inequalities (making the rich richer) or reverse the income ordering to favor the once-poor (which can even be inequality increasing if redistribution is strong). In a laboratory experiment, we investigate redistribution via a novel smooth one-dimensional distribution mechanism that also allows for an increase or reversal of inequality. Decision-makers receive information about the recipients' political orientation, nationality, or seat number during the experiment, and we vary the structure and source of income inequality (income is either earned, random, or unfair). We find most choices of the decision-makers involve redistribution, with only 8 % of choices sticking with the status quo. While most redistribution choices reduce inequality, a larger share—(18 %)—increase inequality by making the rich richer, 13 % of choices reduce overall inequality but make the poor the new rich, and 9 % increase inequality by making the poor very rich. Thus, 40 % of decisions are redistributions that are typically unobserved in common redistribution designs. Ingroup favoritism is a strong motive for redistribution in general, and it is the most important motive for redistribution to increase or reverse inequality. Indeed, 85 % of the inequality-increasing or reversing decisions favor the ingroup. Complementary eye-tracking data show that decision-makers’ attention to information about the recipients’ groups and to poor outliers are related to higher levels of redistribution.