bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantitative damage imaging in plates based on SH0 mode tomographic approach
Authors: Ahmad Mubarak , Liu Zenghua , Basit Abdul , Bin Wu , He Cunfu 
Published: February 2021

Abstract
Exploring the non-dispersive property, the fundamental shear horizontal mode SH0 can be widely used in the detection and monitoring of defects in plate like structures. To combine an approach of ultrasonic guided waves and a tomographic technique by adapting a reconstruction algorithm for the probabilistic inspection of damage (RAPID) using a double-turn coil omnidirectional shear horizontal wave magnetostrictive patch transducer (OSH-MPT) with three different kinds of array arrangements is presented here for imaging. SH0 can propagate in a composite material through bonding double-turn coil OSH-MPT. To get the information about a damage, RAPID can be utilized based on direct wave of SH0 mode. It is advantageous to monitor a composite plate where the velocity of direct waves depends on the propagation direction. In this paper, a surface simulated defect, using a small cylinder, in a composite material is quantitatively evaluated by using shear horizontal mode tomographic approach. Using modified approaches, to eliminate the effect of uneven probability distribution of the array (UPDA) in RAPID, imaging is obtained. Three different array setups of transducers have been tested to monitor the influence on the images. It has been presented that the image generated by the proposed approach with the optimal transducer array and shape factor, β, calculation method has great influence on the real defect shape. To improve the imaging results threshold is selected based on the receiver operating characteristic (ROC) curve. The proposed approach can be used to detect, locate and image the surface defects in plate like structures.
Ergonomic Reliability Assessment for Operation Process of Medical Device Interface Design Based on OAT and CREAM
Authors: Liu Xin , Liu Zheng , Xie Ziyu , Chen Pengqing 
Published: February 2021

Abstract
This paper uses OAT (Operator Action Tree) and CREAM (Cognitive Reliability and Error Analysis Method) to analyze the interface design of medical equipment according to human error, discuss how to accurately describe the operator’s failure behavior, determine the development sequence of important human factors events and the feasible calculation method according to the system response, establish a complete ergonomic reliability assessment modeling by example demonstrations. This study can better describe the relationship between software interface reliability and ergonomic reliability. In addition, this paper makes improvement on the cognitive reliability and error analysis. In this paper, based on the basic concept and core idea of CREAM method, MADM (Multi-attribute Decision-making) is used to improve the weighting factor value of CPCs (Common Performance Conditions) provided by CREAM method. After the OAT model building based on the operation process of medical device interface design, the adjusted failure probability prediction analysis method is applied to obtain the failure probability of OAT basic events, which makes CREAM method more suitable for the medical device accident analysis and risk assessment in complex environment.
Prediction of fatigue crack growth life based on a new fusion model
Authors: Chen G L , Cheng J M , Jin H 
Published: February 2021

Abstract
A novel method based on filtering algorithm is proposed to predict fatigue crack growth life of metal structures under repeated loading. Three parts, including improvement of the two-parameter exponential formula, the improved two-parameter exponential formula parameter estimation and residual life prediction, are involved in the proposed method. The improved two-parameter exponential formula is discretized to establish a parameter estimation physical model of state space. Then, the uncertainty parameters α, β and crack length a in the state space physical model are determined according to the crack propagation data obtained by monitoring/detection and the filtering algorithm, to reduce the influence of uncertain factors such as environment and operation conditions on the prediction of fatigue crack growth life of in-service metal structures. Finally, the discretized improved two- parameter exponential formula are employed to predict the growth life of fatigue crack. An example is presented to test the validity of the proposed method. The result demonstrates that the proposed method is available to well deal with the uncertainty of fatigue parameters in the process of fatigue crack growth with the improved two-parameter exponential formula, and the particle filter algorithm can accurately predict the growth residual life of fatigue short crack.
Storage Life Evaluation and Aging Mechanism Analysis of Epoxy Resin Potting Materials
Authors: Zhao Q C , Li C , She Z X , Li Q , Sun Y M , Zhao F C , He J X 
Published: February 2021

Abstract
The tensile shear samples of potting epoxy resin materials were accelerated under 90°C, 100°C and 110°C temperature conditions. The tensile shear strength was used as the aging characteristic index during the aging test. After normalizing the data in the descending section, the storage life evaluation and analysis is performed based on the Arrhenius model. The retention rate of tensile shear strength is 50% as the critical failure condition. The storage life at 25°C is predicted to be 21.7 years. During the thermal oxygen aging process, the epoxy bonding material’s adhesive interface first undergoes post-curing reaction under the action of heat, and then undergoes oxidative degradation under the action of thermal oxygen. The sample interface is more susceptible to oxidative degradation than the interior. In the oxidative degradation stage, the part of the epoxy resin connected to the hydroxyl group is oxidized to the aldehyde group, and the methylene group connected to the N in the curing agent is oxidized to C=O, forming C=O in the amide, and the molecular backbone is broken And produce low molecular weight polymers.
Research on Prediction of Middle-frequency Ship Cabin Noise Based on Improved Statistical Energy Method
Authors: Ming Zhi-mao , Zhang Bo , Zhao Ke-lun , Xia Xue-bao 
Published: February 2021

Abstract
The ship vibration and noise calculation in middle-frequency region has always been a difficult point in engineering. The statistical energy method assumes that the coupling between structures is weakly coupled, which in turn limits its application in the calculation of ship’s middle frequency vibration and noise. In order to improve the vibration and noise calculation accuracy of statistical energy method in middle-frequency region, the equivalent coupling loss factors (ECLFs) between ship sub-structures were calculated based on the energy flow method (EFM), and the ECLFs were substituted into the statistics energy balance equation. The ship’s middle frequency cabin noise was calculated by the improved statistical energy method and compared with the measured values. The results show that the predicted values of the cabin noise are in good agreement with the measured values, which extends the application of the statistical energy method in the ship’s middle frequency cabin noise prediction.
A Framework to Integrate Prognostics and Health Management into Performance-Based Logistics
Authors: Zhu Xi , Hu Qiwei , Bai Yongsheng 
Published: February 2021

Abstract
Performance-based logistics (PBL) has achieved widespread success as a new logistics strategy, but not all PBL projects have been successful. This article summarizes the reasons for the failure of PBL and the advantages of Prognostics and Health Management (PHM), furthermore, analyses the necessity of integrating PHM into PBL. The innovation of this article lies in the establishment of a process framework to integrate PHM into PBL, and a specific evaluation method is given to evaluate the effect of PBL after using PHM, which make PBL gain more benefits or turn into a victory.
Response of the interface between the ball and the raceway of rolling bearing under starved lubrication
Authors: Bian Z , Song C , Meng L H , Zhou Q H 
Published: February 2021

Abstract
The interface state of the rolling bearing contact pair often directly determined the service performance of the bearing for the aviation equipment, the ball-raceway contact interface would develop from the homogeneous lubrication to starved lubrication when used for a while, the plasto-elastohydrodanamic lubrication analysis model was used to describe the ball-raceway contact interface lubrication condition. The influence of the normal pressure, the rolling speed and the service time to the ball-raceway contact interface wear behavior was investigated by the gearbox and rolling bearing on condition of starved lubrication, it was found that the centre region of the raceway generated concave residual deformation, while the convex residual deformation occurred at the lubrication region’s edge and its surrounding region, the groove and scratch marks were emerged on the contact surface of ball and raceway, which were accelerated produced by the normal load and rolling speed of rolling bearing, besides that the ball-raceway contact interface assumed adhesive wear behavior and the wear width became gradually larger over the time.
Improving the risk Assessment of FMEA in Foamed Asphalt preparation Plant based on Intuitionistic Fuzzy
Authors: Luo Zhun , Cheng Hai-Ying 
Published: February 2021

Abstract
Taking foamed bitumen preparation equipment as the research object, aiming at the shortcomings and shortcomings of traditional failure mode and effect analysis (FMEA) method, this paper proposes a method to improve FMEA based on intuitionistic fuzzy. This method converts N expert language variables into corresponding intuitionistic fuzzy numbers to represent the failure mode and risk factor weight evaluation information. Combined with intuitionistic fuzzy weighted geometric operators and improved Hamming distance, the traditional FMEA method is improved to determine the bubble Risk order of failure mode of asphalt preparation plant. The results show that: asphalt pipe blockage, asphalt tank cracking and tapered rod end fracture are the three highest failure modes for foamed asphalt preparation equipment.
Precise reliability analysis base on static pose error of 6 degree of freedom serial robot
Authors: Hu Ming , Wu Mei , Zhou Xuwu , Yang Jing , Wang Bingxu , Li Jian 
Published: February 2021

Abstract
Taking the JLRB20 industrial robot as the object, the improved D-H modelling method is used to establish the positioning error model of the robot, the reliability of the static pose error of the robot is analysed, and the reliability evaluation index of the static pose error of the robot is established. By analysing the precise reliability base on static pose error of the robot, it is determined that the joint rotation angle has the greatest influence on the accuracy of the static attitude error of the robot end, which provides a basis for improving the reliability of the static pose error of the robot.
A Monte Carlo Expectation Maximization Algorithm for Statistical Inference of Weibull Process with Left Censored Data
Authors: Hu Jun-Ming , Huang Hong-Zhong 
Published: February 2021

AbstractThe Weibull process plays an important role in the failure analysis of repairable systems. In practice, there exists a situation that the data collected are incomplete. Some of the failure data are missing due to various reasons. Statistical inferences of a Weibull process with incomplete data using Monte Carlo expectation maximization algorithm is proposed. The estimation procedures are derived. A case study is performed to illustrate and compare the performances of this algorithm. It is observed that this method is effective and can simplify the estimation.
Vibration indicator-based graph convolutional network for semi-supervised bearing fault diagnosis
Authors: Wang S H , Xing S B , Lei Y G , Lu N , Li N P 
Published: February 2021

Abstract
Since fault diagnosis has entered the big data era, deep learning has been more and more widely studied to diagnose faults of rolling element bearings. Generally, existing methods require labeled data for training before they can be used to recognize faults. However, in real scenarios, massive data are usually unlabeled data rather than labeled ones, because labeling data is always a tough issue and consumes much human labor. In order to fully take advantage of the massive unlabeled data, this paper proposes a vibration indicator-based graph convolutional neural network (VI-GCN) for fault diagnosis. The VI-GCN is applied to a benchmark dataset of bearing faults. Experimental results indicate that it is promising for bearing fault diagnosis when there are few labeled data.
Reliability analysis of ballast cleaning device based on fuzzy FTA and FMEA
Authors: Wang J , Cui Z X , Li S D , Yang T , Cheng H Y , Na R S 
Published: February 2021

Abstract
On the basis of analyzing the fault tree diagram of the ballast cleaning device of railway switch ballast cleaning machine, the fuzzy fault tree of the ballast cleaning device is established by blurring the probability of bottom event. Introducing grey fuzzy analysis correlation method, using the normal fuzzy comprehensive evaluation method of combining the theory and experts, quantitative and qualitative analysis, the fuzzy fault tree based on fault tree’s minimum cut sets, the fuzzy importance degree of the basic events, calculation of each failure mode and the top event correlation, figure out the influence of the top event to occur to the larger events and failure mode. Then FMEA method is used to analyze the key parts of ballast cleaning device such as gripper and sprocket, and corresponding compensation measures are put forward according to the specific failure reasons.
Research on Quality Surveillance in Digital Design Environment
Authors: Duan Bo , Yuan Shuo 
Published: February 2021

Abstract
This paper studies the definition of product quality surveillance in a digital design environment, analyzes the characteristics and new requirements of quality surveillance, and proposes the main contents of quality surveillance in these aspects, including digital design process in the aspects of quality information management, quality problem handling, digital prototype management, technical status management, data exchange and conversion. Finally,we put forward the methods of quality surveillance in digital design process.
Roughness and mechanical properties of electron-beam surface modified and TiN/TiO2-coated Ti6Al4V alloy
Authors: Nikolova M P , Ormanova M , Tonev D , Petrov P 
Published: February 2021

Abstract
In this study, we used PVD deposition of TiN/TiO2 coatings on polished and electron-beam-treated Ti6Al4V alloy to explore the changes in the surface roughness and mechanical properties of the coated systems. After the electron-beam treatment (EBT), the average surface hardness and roughness (R

a
) increased from 323±5.62 HV0.2 and 0.14±0.004 μm up to 387.5±9.33 HV0.2 and 1.58±0.05 μm, respectively. After coating with 3.7-μm thick TiN/TiO2, the average S

a
roughness and nanohardness of the film on the polished substrate reached 0.87±0.1 μm and 13.05±2.07 GPa while that on the EBT was equal to 1.57±0.2 μm and 9.02±2.15 GPa, respectively. However, the comparison of the coefficient of friction (COF) evolution of the substrates and the coated specimens indicated a COF decrease by about 0.18±0.03 for the coated EBT alloy as compared with the polished and EBT substrates, whose average COF were 0.45±0.04 and 0.38±0.06, respectively. A high average COF (0.68±0.16) was registered for the coated as-received alloy because of the gradual and complete wearing off of the film during the test. These results indicate that the combination of initial EBT of the Ti6Al4V alloy with PVD deposition of a TiN/TiO2 coating could substantially improve the roughness and tribological properties of the coated systems.
Surface modification of Co-Cr-Mo alloys by electron-beam treatment
Authors: Valkov S , Parshorov S , Andreeva A , Nikolova M , Petrov P 
Published: February 2021

Abstract
We present a study on the possibility of modifying the structure and properties of Co-Cr-Mo alloys by using the electron-beam surface modification technique. The technological parameters were optimized in order to obtain the highest cooling rate without melting the surface. The samples were characterized in terms of their phase composition and microstructure by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The surface roughness was evaluated by atomic force microscopy (AFM). The corrosion properties were investigated by electrochemical tests. It was found that the treatment process leads to a transition in the phase composition, from ε + γ to a single-phase γ structure. The electron-beam surface modification process causes an increase in the surface roughness and a significant improvement of the corrosion resistance.
Biogenic ferroxides derived from Leptothrix bacteria for applications in electronics, biomedicine and biotechnology
Authors: Angelova R , Slavov L , Blagoev B , Ghelev Ch , Iliev M , Groudeva V , Nedkov I 
Published: February 2021

Abstract
The present work is focused on studying by-products derived from the metabolism of bacteria of the Leptothrix genus, which are among the first described microorganisms associated with the iron cycle in nature. The products of their metabolism are nanostructured biogenic iron oxides in the form of precipitating powders and sheath structures. The sheath structures can be considered as an organic matrix in which inorganic crystallites are discretely dispersed. We used X-ray diffraction, magnetic measurements, light microscopy and scanning electron microscopy to characterize biogenic products formed in a silicon iron glucose peptone medium under laboratory conditions. The studies showed a lack of significant differences between the naturally obtained and the artificially synthesized biogenic sheaths, i.e., an adequate laboratory technological process had been developed. From the point of view of nanoelectronics application, these biogenic by-products are unique because they are biocompatible, have specific electromagnetic properties and are potential candidates for various applications in biomedicine and electronics.
Structural and mechanical properties of Ta-based coatings deposited on polymers for biomedical applications
Authors: Donkov N , Zykova A , Safonov V , Dudin S , Yakovin S , Petrov P , Rabadzhiyska S 
Published: February 2021

Abstract
The polypropylene meshes currently used for hernioplasty induce severe chronic inflammatory reactions over a long-term period of use. These processes lead to scarring and have a negative effect on the connective tissue and the abdominal walls. It is well-known that the biocompatibility of polymer surfaces might be improved by surface modification. We report on the structure and composition of nanostructured Ta, Ta2O5 and TaON coatings deposited on polypropylene in correlation with their mechanical properties. The elemental distribution and chemical composition of the coatings were analyzed by energy dispersive X-ray spectroscopy. The coatings cross-sectional structure and morphology were observed by electron scanning microscopy. Mechanical tests were performed of the polypropylene and of the samples with Ta-based coatings to evaluate the Vickers hardness and the elastic modulus. The coated samples exhibited higher nano-hardness and elasticity values, significantly exceeding the values of untreated polypropylene samples. The Ta-based coatings deposited by magnetron sputtering improve the mechanical characteristics and biocompatibility of the polypropylene materials in view of, e.g., hernia repair.
Atmospheric particulate matter pollution over residential urban areas during COVID-19 quarantine
Authors: Ilieva R , Angelova B , Iliev M , Stoyanov D , Groudeva V , Cherkezova-Zheleva Z , Nedkov I 
Published: February 2021

Abstract
This study of particulate matter (PM) pollution was conducted in May and June 2020 during the COVID-19 lockdown in residential areas of the Bulgarian capital Sofia. Its methodology was based on lidar monitoring of the ground layer of the atmosphere and focused on the sampling procedure. The sampling was performed with portable instruments in situ in the areas with air pollution fixed on the city’s map during the lidar monitoring. The collected PM was examined by a set of physical methods (XRD, SEM, EDAX) and PCR tests for viral contamination). A wide range of data on the nature of PM were obtained. Data on the number of COVID-19 positive individuals in the town for the period was also summarized.
Algorithms for fusion systems with applications to 𝑝-groups of small order
Authors: Parker Chris , Semeraro Jason 
Published: February 2021

For a prime

p
p

, we describe a protocol for handling a specific type of fusion system on a

p
p

-group by computer. These fusion systems contain all saturated fusion systems. This framework allows us to computationally determine whether or not two subgroups are conjugate in the fusion system for example. We describe a generation procedure for automizers of every subgroup of the

p
p

-group. This allows a computational check of saturation. These procedures have been implemented using Magma. We describe a computer program which searches for saturated fusion systems

F

\mathcal {F}

on

p
p

-groups with

O
p

(

F

)
=
1

O_p(\mathcal {F})=1

and

O
p

(

F

)
=

F

O^p(\mathcal {F})=\mathcal {F}

. Employing these computational methods we determine all such fusion systems on groups of order

p
n

p^n

where

(
p
,
n
)
∈
{
(
3
,
4
)
,
(
3
,
5
)
,
(
3
,
6
)
,
(
3
,
7
)
,
(
5
,
4
)
,
(
5
,
5
)
,
(
5
,
6
)
,
(
7
,
4
)
,
(
7
,
5
)
}

(p,n) \in \{(3,4),(3,5),(3,6),(3,7),(5,4),(5,5),(5,6),(7,4),(7,5)\}

. This gives the first complete picture of which groups can support saturated fusion systems with

O
p

(

F

)
=
1

O_p(\mathcal {F})=1

and

O
p

(

F

)
=

F

O^p(\mathcal {F})=\mathcal {F}

on small

p
p

-groups of odd order.
Knowledge-based classification of fine-grained immune cell types in single-cell RNA-Seq data
Authors: Liu Xuan , Gosline Sara J C , Pflieger Lance T , Wallet Pierre , Iyer Archana , Guinney Justin , Bild Andrea H , Chang Jeffrey T 
Published: February 2021

AbstractSingle-cell RNA sequencing (scRNA-Seq) is an emerging strategy for characterizing immune cell populations. Compared to flow or mass cytometry, scRNA-Seq could potentially identify cell types and activation states that lack precise cell surface markers. However, scRNA-Seq is currently limited due to the need to manually classify each immune cell from its transcriptional profile. While recently developed algorithms accurately annotate coarse cell types (e.g. T cells versus macrophages), making fine distinctions (e.g. CD8+ effector memory T cells) remains a difficult challenge. To address this, we developed a machine learning classifier called ImmClassifier that leverages a hierarchical ontology of cell type. We demonstrate that its predictions are highly concordant with flow-based markers from CITE-seq and outperforms other tools (+15% recall, +14% precision) in distinguishing fine-grained cell types with comparable performance on coarse ones. Thus, ImmClassifier can be used to explore more deeply the heterogeneity of the immune system in scRNA-Seq experiments.