bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparison of particle and fluid models for positive streamer discharges in air
Authors: Wang Zhen , Sun Anbang , Teunissen Jannis 
Published: December 2021

Abstract
Both fluid and particle models are commonly used to simulate streamer discharges. In this paper, we quantitatively study the agreement between these approaches for axisymmetric and 3D simulations of positive streamers in air. We use a drift–diffusion–reaction fluid model with the local field approximation and a particle-in-cell, Monte Carlo collision particle model. The simulations are performed at 300 K and 1 bar in a 10 mm plate–plate gap with a 2 mm needle electrode. Applied voltages between 11.7 and 15.6 kV are used, which correspond to background fields of about 15–20 kV cm−1. Streamer properties like maximal electric field, head position and velocity are compared as a function of time or space. Our results show good agreement between the particle and fluid simulations, in contrast to some earlier comparisons that were carried out in 1D or for negative streamers. To quantify discrepancies between the models, we mainly look at streamer velocities as a function of streamer length. For the test cases considered here, the mean deviation in streamer velocity between the particle and fluid simulations is less than 4%. We study the effect of different types of transport data for the fluid model, and find that flux coefficients lead to good agreement whereas bulk coefficients do not. Furthermore, we find that with a two-term Boltzmann solver, data should be computed using a temporal growth model for the best agreement. The numerical convergence of the particle and fluid models is also studied. In fluid simulations the streamer velocity increases somewhat using finer grids, whereas the particle simulations are less sensitive to the grid. Photoionization is the dominant source of stochastic fluctuations in our simulations. When the same stochastic photoionization model is used, particle and fluid simulations exhibit similar fluctuations.
Bell nonlocality in networks
Authors: Tavakoli Armin , Pozas-Kerstjens Alejandro , Luo Ming-Xing , Renou Marc-Olivier 
Published: December 2021

Abstract
Bell’s theorem proves that quantum theory is inconsistent with local physical models. It has propelled research in the foundations of quantum theory and quantum information science. As a fundamental feature of quantum theory, it impacts predictions far beyond the traditional scenario of the Einstein-Podolsky-Rosen paradox. In the last decade, the investigation of nonlocality has moved beyond Bell's theorem to consider more sophisticated experiments that involve several independent sources which distribute shares of physical systems among many parties in a network. Network scenarios, and the nonlocal correlations that they give rise to, lead to phenomena that have no counterpart in traditional Bell experiments, thus presenting a formidable conceptual and practical challenge. This review discusses the main concepts, methods, results and future challenges in the emerging topic of Bell nonlocality in networks.
Characterizing the stress and electrical properties of superconducting molybdenum films
Authors: Wang Yeru , Liang Yajie , Ding Jiao , Chen Naihui , Chen Yanling , Cui Wei , Huang Rui , Li Chengzhe , Li Fajun , Liu Jiejia , Jin Hai , Wang Guole , Wang Sifan , Zhang Yuning 
Published: December 2021

Abstract
In the process of minimizing stress in sputtered molybdenum (Mo) films for fabricating transition-edge sensor devices, we have investigated correlations between the stress and film deposition parameters. At a fixed sputtering power, the tensile stress of our film samples decreases toward both low and high ends of Ar pressure, suggestive of two physical mechanisms at work: an ‘atomic peening’ effect at low Ar pressure and the development of voids at high Ar pressure. We have also carried out correlative studies of the stress and electrical properties (including superconducting critical temperature and residual resistivity) of the film samples, and found that the results are complex. We have made extensive comparisons with the published results, and attempted to explain the discrepancies in terms of film deposition techniques, sample preparation and treatment, and dynamical ranges of measurements. It is fairly clear that the microscopic properties, including porosity and disorder, of Mo films may have significant impact on the correlations.
Investigating the reason for high FF from ternary organic solar cells
Authors: Li Danqin , Zeng Yihan , Chen Zeng , Leng Shifeng , Xiao Zuo , Xue Qifan , Hao Tianyu , Lv Meng , Wu Hongbo , Lin Lina , Yang Jianming , Ma Zaifei , Chen Jinquan , Huang Rong , Liu Feng , Zhu Haiming , Liu Xianjie , Ding Liming , Fahlman Mats , Bao Qinye 
Published: December 2021

Abstract
Power-law distribution found in city-scale traffic flow simulation
Authors: Umemoto Daigo , Ito Nobuyasu 
Published: December 2021

Abstract
Origin of a power-law in traffic-volume distribution found in traffic simulations of Kobe city was studied. The traffic distribution which was obtained from a shortest path search with randomized OD (origin-destination) set in Kobe city digital map obeys power-law. The toy model that Cayley tree is embedded in the network is also verified. It is theoretically shown that the traffic distribution with all possible OD set in a Cayley tree obeys power-law like distribution. With randomized OD set, the distribution is diffused from the theoretical point sets. Relationship between these facts and the origin of power-law is discussed.
Intelligent Vehicle Design based on PaddlePaddle and Deep Learning
Authors: He Song , Xue Hao , Guo Lejiang , Chen Xin , Hu Jun 
Published: December 2021

Abstract
ABSTRACT.In order to visualize the applications of deep learning based intelligent vehicle in the real field vividly, especially in the unmanned cases in which it realizes the integration of various technologies such as automatic data acquisition, data model construction, automatic curve detection, traffic signs recognition, verification of the unmanned driving, etc. A M-typed Model intelligent vehicle that is embedded with a high-performance board from Baidu named Edge Board is adopted by this study. The vehicle is trained under the PaddlePaddle deep learning frame and Baidu AI Studio Develop platform. Through the autonomous control scheme design and the non-stop study on the deep learning algorithm, an intelligent vehicle model based on PaddlePaddle deep learning is here. The vehicle has the function of automatic driving on the simulated track. In addition, it can distinguish several traffic signs and make feedbacks accordingly.
Research on load balancing of parallel component programs based on quantum particle swarm optimization algorithm
Authors: Peng Yunfeng , Gao Guowei , Shi Congming , Liu Hai , Wang Jianan 
Published: December 2021

Abstract
Parallel component applications are often deployed on heterogeneous clusters. Load balancing is very important for their performance requirement. Existing load balancing methods have high performance cost and poor balance effect. Based on the analysis of structures of parallel component applications, we established the mathematical model of load balancing for parallel components on heterogeneous clusters. We use the quantum particle swarm optimization algorithm to search the optimal solution of the proposed mathematical model and determine the best load balancing scheme. Comparing with the methods based on real-time detection and other swarm intelligence optimization algorithms, our method has lower balance cost, less number of iterations and better performance.
An Interval Type-2 Possibilistic C-Means Clustering Algorithm and Its Application
Authors: Xing Haihua , Chen Huannan , Lin Hongyan , Wu Xinghui 
Published: December 2021

Abstract
In this paper, we aim at the fuzzy uncertainty caused by noise in pattern data. The advantages of PCM algorithm to deal with noise and interval type-2 fuzzy sets to deal with high-order uncertainties are used, respectively. An interval type-2 probability C-means clustering (IT2-PCM) based on penalty factor is proposed. The performance of the algorithm is evaluated by two sets of data sets and two groups of images segmentation experiments. The results show that IT2-PCM algorithm can assign proper membership degrees to clustering samples with noise, and it can detect noise points effectively, and it has good performance in image segmentation.
Research on Security Protocol Analysis Tool SmartVerif
Authors: Lu Siqi , Han Qingdi , Miao Xuyang , Liu Yubo 
Published: December 2021

Abstract
Security protocols have been designed to protect the security of the network. However, many security protocols cannot guarantee absolute security in real applications. Therefore, security tests of the network protocol become particularly important. In this paper, firstly, we introduce SmartVerif, which is the first formal analysis tool to automatically verify the security of protocols through dynamic strategies. And then, we use SmartVerif to verify the pseudo-randomness of the encapsulated key of the Two-Pass AKE protocol, which was proposed by Liu’s in ASIACRYPT in 2020. Finally, we summary our work and show some limitations of SmartVerif. At the same time, we also point out the direction for future improvement of SmartVerif.
The l-good-neighbor edge connectivity of graphs
Authors: Zhang Shumin , Li Yalan , Ye Chengfu 
Published: December 2021

Abstract
The l -good-neighbor edge connectivity is an useful parameter to measure the reliability and tolerance of interconnection networks. For a graph H with order p and an integer l (l ≥ 0), an edge subset X ⸦ E(H) is called a l-good-neighbor edge-cut if H − X is disconnected and the minimum degree of every component of H − X is at least £. The order of the minimum l-good-neighbor edge-cut of H is called the l-good-neighbor edge connectivity of H, denoted by λ
l
(H). In this paper, we show λ(H) ≤ λ
l+1(H), obtain the bounds of λl
(H) when 0 ≤ l ≤ [p-2/2], character some graphs with the small λl
(H) and get some results about the Erdös-Gallai-type problem about λl
(H).
Electric-field-tunable linear unipolar magnetic switch based on a spin-valve multiferroic heterostructure
Authors: Liu Mengli , Du Wei , Su Hua , Liu Bo , Meng Hao , Tang Xiaoli 
Published: December 2021

Abstract
This work reports an energy-efficient strategy for realizing linear unipolar giant magnetoresistance (GMR) switch by using electric fields (E-fields). Herein, a modified spin-valve (SV) structure of double antiferromagnetic (AFM) pinning layers was adopted. Since the magnetization direction of ferromagnetic (FM) layer can be controlled via the strain-mediated magnetoelectric (ME) effect, a multiferroic heterostructure of SV/PMN-PT was fabricated. By applying an E-field on the PMN-PT substrate, an effective magnetic field Heff
was produced along the [1-10] direction of PMN-PT. It can turn the magnetic moments of FM layer toward [1-10] direction. Accordingly, a linear GMR curve with a wide sensing field range was achieved. This E-field-induced linear magnetic switch can satisfy the demand for different switching field ranges in the same application system.
An Electric Equipment Analysis Method based on Knowledge Reasoning
Authors: Zhang Xinjie , Wang Yao , Lin Run , Zhang Yuze , Li Xu , Wang Jian 
Published: December 2021

Abstract
Facing the increasingly complex power grid architecture and high equipment failure risk, a comprehensive equipment condition analysis method based on knowledge reasoning is proposed in this paper, mainly using the large amount of characteristic information to realize the condition evaluation, fault detection and early warning. Firstly, it statistically analyzes the historical data, extracts the characteristic information of equipment health status and builds a knowledge mapping library of key factors for equipment-centered status analysis; secondly, it establishes an intelligent early warning library of equipment index data, and gets the probability of equipment defects and fault risks through induction-based knowledge reasoning method; finally, it gets the equipment status rating through logic and rule-based knowledge reasoning method and the closed-loop system of equipment status evaluation is established. The reasonableness of the evaluation method is verified by the examples, which realizes supervision equipment operation status mining early warning, sensing equipment operation status in advance and reducing potential operation risk of power grid.
Intervention analysis with autoregressive integrated moving average models for time series of urban air pollutants
Authors: Manco-Perdomo L A , Pérez-Padilla L A , Zafra-Mejía C A 
Published: December 2021

Abstract
The objective of this paper is to show an intervention analysis with autoregressive integrated moving average models for time series of air pollutants in a Latin American megacity. The interventions considered in this study correspond to public regulations for the control of urban air quality. The study period comprised 10 years. Information from 10 monitoring stations distributed throughout the megacity was used. Modelling showed that setting maximum emission limits for different pollution sources and improving fuel were the most appropriate regulatory interventions to reduce air pollutant concentrations. Modelling results also suggested that these interventions began to be effective between the first 4 days-15 days after their publication. The models developed on a monthly timescale had a short autoregressive memory. The air pollutant concentrations at a given time were influenced by the concentrations of up to three months immediately preceding. Moving average term of the models showed fluctuations in time of the air pollutant concentrations (3 months - 14 months). Within the framework of the applications of physics for the air pollution control, this study is relevant for the following findings: the usefulness of autoregressive integrated moving average models to temporal simulate air pollutants, and for its suitable performance to detect and quantify regulatory interventions.
Numerical analysis of a tire shredder machine to produce rubber particulate material
Authors: García-León R A , Jaramillo H Y , Gómez-Camperos J A 
Published: December 2021

Abstract
The main objective of this work is to develop a numerical analysis of a shredder machine to generate rubber particulate material for its implementation in different sectors such as construction, artisanal, and road as aggregates in the raw material. As part of the methodology, modern design theories were considered to select the materials for the different elements of the crushing machine; for this purpose, the SolidWorks design software was used to obtain a conceptual design model of the prototype. The mathematical and numerical results indicate that the prototype of the crushing machine will work in good conditions, always guaranteeing high levels of safety and performance based on the mechanical and physical properties of the materials selected through the design theories. Likewise, this machine will be low-cost to promote growth and competitive capacity for studies of different products with rubber aggregates to solve global environmental problems. Finally, the physical behavior of the new materials can be obtained with rubber particles aggregate will allow evaluating and optimizing a different kind of products that can be used in different sectors aiding sustainability sources.
Numerical simulation to analyze the physical behavior of centrifugal pumps as a turbine
Authors: Prada Botia G C , Pabón León J A , Orjuela Abril M S 
Published: December 2021

Abstract
In this research, a methodology based on the development of numerical simulations is proposed to analyze the physical behavior of centrifugal pumps such as a turbine. Numerical simulations were carried out using OpenFOAM software. For the validation of the numerical model, the construction of an experimental test bench was carried out. The analysis carried out involves the evaluation of performance parameters of the pump as a turbine, such as head, power, and efficiency. Additionally, the effect of the rotation speed on the previous parameters is evaluated. From the results obtained, it was shown that the maximum relative error was 4%, 3.4%, and 3.8% for the head, power, and efficiency parameters, respectively. In general, it was evidenced that the proposed numerical simulation has the ability to describe the real trends of the pump as a turbine for different flow conditions. In addition, an 11% increase in rotational speed was shown to cause a 12%, 1.9%, and 3% increase in head, power, and maximum efficiency. The proposed methodology is considered an adequate tool to analyze performance and identify the best efficiency point of pump systems such as a turbine. In this way, greater energy use is guaranteed.
Effect of a regenerator on hybrid solar gas turbine performance in Barranquilla, Colombia
Authors: Moreno-Gamboa F , Acevedo-Paéz J C , Sanin-Villa D 
Published: December 2021

Abstract
A thermodynamic analysis of a hybrid gas turbine solar plant, represented in three basic subsystems related to the power cycle, the combustion chamber subsystem, and the solar concentrator subsystem, allows evaluating the performance of a hybrid cycle from a reduced number of parameters, which include energy losses in each of its components. The solar radiation values are estimated with an evaluated and validated theoretical model, the combustion chamber uses natural gas as fuel and the numerical values of the system are taken from the Solugas experimental plant in Spain. This work presents an integrated model that allows to estimate the operation of a hybrid solar Brayton power plant in any place and day of the year. The evaluation of the plant in Barranquilla, Colombia is shown from the influence of the regenerator has on the plant performance and solar concentrating system. The results show that the regenerator can increase the overall efficiency of the plant by 29% and allows reaching a maximum temperature of the central receiver of the concentrator of 1044 K at noon, when solar radiation is maximum.
Strength of the flexural joint of mortar joints and solid fired clay brick prisms
Authors: Afanador García N , Guerrero Gómez G , Nolasco Serna C 
Published: December 2021

Abstract
Masonry constructions built with mortar and solid fired clay bricks are subject to: high cement content, excessive water-cement ratio causing problems of mortar shrinkage during curing and differential movements between the brick and mortar caused by movements due to wind or seismic events. Earth movements generate some failures in simple masonry walls and confined masonry in solid brick joints, mainly with failure inclination angles varying from 45 degrees to 50 degrees. The objective of this research work was to estimate the flexural bond strength of the mortar joint and the solid fired clay brick and thus establish design parameters for non-structural masonry in the municipality of Ocanña, Colombia. From the fired clay brick manufacturers, 18 in total, simple random sampling was used to determine the sample size, 4 manufacturers were randomly selected. In addition, the characterization of the solid fired clay brick units was carried out with respect to their compressive strength, initial absorption rate and final absorption, as well as the mortar with respect to its compressive strength at 28 days, according to the Colombian standard for earthquake resistant constructions; for the determination of the flexural strength of the bonding mortar and solid brick units, a semiautomatic machine for flexural strength testing of masonry units, Pinzuar model PC-13, with a force measurement of 1000 N and an accuracy of 0.1 N, was designed. The flexural strength at the masonry joint was obtained for mortar type M with a value of 0.26 MPa, with a standard deviation of 0.01 MPa and a coefficient of variation of 4.72%. As for mortars type N and S, the average strength value was equal to 0.24 MPa for the two types of mortar, with standard deviation of 0.03 MPa and 0.01 MPa respectively, and coefficient of variation of 11.4% and 3.18% respectively. Given the importance of the variables, an interpretation of physical of the relationship between the properties was made: compressive strength of the solid fired clay brick and flexural strength at the masonry joint, since their average values were similar.
Vernier time-to-digital converter with ring oscillators for in-pixel time-of-arrival and time-over-threshold measurement in 28 nm CMOS
Authors: Kadlubowski L.A. , Kmon P. 
Published: December 2021

Abstract
The paper describes a design of a prototype chip in 28 nm CMOS technology, consisting of 8 × 4 pixels with 50 μm pitch, dedicated for the precise measurement of Time-of-Arrival (ToA) and Time-over-Threshold (ToT) with a resolution within the picosecond range. To address this requirement, in-pixel Vernier time-to-digital converter (TDC) has been implemented, which utilizes two ring oscillators per pixel. Overall chip architecture is introduced as well as pixel architecture and selected simulation results. The pixel consists of a recording channel and TDC part. The recording channel is composed of an inverter-based front-end amplifier with Zimmerman feedback, a discriminator, a calibration block and a threshold setting block. TDC part includes two ring oscillators together with their calibration blocks and additional logic with counters/shift registers that allow for precise ToA measurement (using Vernier method) as well as ToT measurement (using one of the oscillators). Alternatively, single photon counting (SPC) mode can be used. Frequency of oscillators is set in three steps. First, two global 8-bit digital-to-analog converters (DACs) are used for initial setting of all ring oscillators. Then, per-oscillator capacitance bank and 6-bit DAC are used for fine setting. Simulation results of core blocks suggest that the ToA resolution on the order of tens of picoseconds may be achieved. The chips are already fabricated and are currently being prepared for measurements.