Guocheng Lv, Dawei Jia, Changyou Li, Chunyu Zhao, Xiulu Zhang, Feng Yan, Hongzhuang Zhang and Bing Li
This study aims to investigate the effect of countersunk rivet head dimensions on the fatigue performance of the riveted specimens of 2024-T3 alloy.
Abstract
Purpose
This study aims to investigate the effect of countersunk rivet head dimensions on the fatigue performance of the riveted specimens of 2024-T3 alloy.
Design/methodology/approach
The relationship between rivet head dimensions and fatigue behavior was investigated by finite element method and fatigue test. The fatigue fracture of the specimens was analyzed by scanning electron microscopy.
Findings
A change of the rivet head dimensions will cause a change in the stress concentration and residual normal stress, the stress concentration near the rivet hole causes the fatigue crack source to be located on the straight section of the countersunk rivet hole and the residual normal stress can effectively restrain the initiation and expansion of fatigue cracks. The fatigue cycle will cause the rivet holes to produce different degrees of surface wear.
Originality/value
The fatigue life of the specimens with the height of the rivet head of 2.28 mm and 2.00 mm are similar, but the specimens with the height of the rivet head of 1.72 mm were far higher than the other specimens.
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Keywords
LanHao Zhao, Kailong Mu, Jia Mao, Khuc Hongvan and Dawei Peng
Moving interface problems exist commonly in nature and industry, and the main difficulty is to represent the interface. The purpose of this paper is to capture the accurate…
Abstract
Purpose
Moving interface problems exist commonly in nature and industry, and the main difficulty is to represent the interface. The purpose of this paper is to capture the accurate interface, a novel three-dimensional one-layer particle level set (OPLS) method is presented by introducing Lagrangian particles to reconstruct the seriously distorted level set function.
Design/methodology/approach
First, the interface is captured by the level set method. Then, the interface is corrected with only one-layer particles advected with the flow to ensure that the level set function value of the particle is equal to 0. When interfaces are merged, all particles in merged regions are deleted, while the added particles near the generated interface are used to determine the interface as the interface is separated.
Findings
The OPLS method is validated with well-known benchmark examples, such as the long-term advection of a sphere, the rotation of a three-dimensional slotted disk and sphere, single vortex in a box, sphere merging and separation, deformation of a sphere. The simulation results indicate that the proposed method is found to be highly reliable and accurate.
Originality/value
This method exhibits excellent conservation of the area bounded by the interface. The extraordinary performance is also shown in dealing with complex interface topological changes.
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Mingxia Jia, Yuxiang Chris Zhao, Xiaoyu Zhang and Dawei Wu
In the era of digital intelligence, individuals are increasingly interacting with digital information in their daily lives and work, and a growing phenomenon known as digital…
Abstract
Purpose
In the era of digital intelligence, individuals are increasingly interacting with digital information in their daily lives and work, and a growing phenomenon known as digital hoarding is becoming more prevalent. Prior research suggests that humanities researchers have unique and longstanding information interaction and management practices in the digital scholarship context. This study therefore aims to understand how digital hoarding manifests in humanities researchers’ behavior, identify the influencing factors associated with it, and explore how they perceive and respond to digital hoarding behavior.
Design/methodology/approach
Qualitative research methods enable us to acquire a rich insight and nuanced understanding of digital hoarding practices. In this study, semi-structured interviews were conducted with 20 humanities researchers who were pre-screened for a high propensity for digital hoarding. Thematic analyses were then used to analyze the interview data.
Findings
Three main characteristics of digital hoarding were identified. Further, the research paradigm, digital affordance, and personality traits and habits, collectively influencing the emergence and development of digital hoarding behaviors, were examined. The subtle influence of traditional Chinese culture was encountered. Interestingly, this study found that humanists perceive digital hoarding as a positive expectation (associated with inspiration, aesthetic pursuit, and uncertainty avoidance). Meanwhile, humanists' problematic perception of this behavior is more widely observed — they experience what we conceptualize as an “expectation-perception” gap. Three specific information behaviors related to avoidance were identified as aggravating factors for digital hoarding.
Originality/value
The findings deepen the understanding of digital hoarding behaviors and personal information management among humanities researchers within the LIS field, and implications for humanities researchers, digital scholarship service providers, and digital tool developers are discussed.
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Keywords
Hu Luo, Haobin Ruan and Dawei Tu
The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images…
Abstract
Purpose
The purpose of this paper is to propose a whole set of methods for underwater target detection, because most underwater objects have small samples, low quality underwater images problems such as detail loss, low contrast and color distortion, and verify the feasibility of the proposed methods through experiments.
Design/methodology/approach
The improved RGHS algorithm to enhance the original underwater target image is proposed, and then the YOLOv4 deep learning network for underwater small sample targets detection is improved based on the combination of traditional data expansion method and Mosaic algorithm, expanding the feature extraction capability with SPP (Spatial Pyramid Pooling) module after each feature extraction layer to extract richer feature information.
Findings
The experimental results, using the official dataset, reveal a 3.5% increase in average detection accuracy for three types of underwater biological targets compared to the traditional YOLOv4 algorithm. In underwater robot application testing, the proposed method achieves an impressive 94.73% average detection accuracy for the three types of underwater biological targets.
Originality/value
Underwater target detection is an important task for underwater robot application. However, most underwater targets have the characteristics of small samples, and the detection of small sample targets is a comprehensive problem because it is affected by the quality of underwater images. This paper provides a whole set of methods to solve the problems, which is of great significance to the application of underwater robot.
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Dawei Zhang, Haiyang Li, Hongchang Qian, Luntao Wang and Xiaogang Li
This study aims to construct a double layer heat insulation coating based on hollow glass microspheres (HGMs) and to investigate the effect of particle size on barrier property…
Abstract
Purpose
This study aims to construct a double layer heat insulation coating based on hollow glass microspheres (HGMs) and to investigate the effect of particle size on barrier property and heat insulation performance.
Design/methodology/approach
The waterborne double layer coating was composed of an anticorrosive epoxy ester primer and an HGM-containing silicone acrylic topcoat. With varied HGM sizes (20 μm, 40 μm, 60 μm and a 1:3 w/w mixture of 20 and 60 μm particles), the coating was immersed in 3.5 wt% NaCl solution for 28 days and was then subjected to a salt spray test for 450 h. The barrier properties of the coating were evaluated through electrochemical impedance spectroscopy. Heat insulation performance was examined using a self-made device.
Findings
The addition of HGMs decreased the barrier properties of the coating by creating particle/resin interfaces for water penetration. In the HGMs-containing coatings, the use of larger HGMs showed relatively good barrier properties because of the lower particle density. The coating with smaller particles yielded a higher heat insulating capacity as indicated by lower equilibrium temperatures.
Research limitations/implications
Future work will be focused on improving the barrier properties of the coating. Field exposure tests should also be performed to assess the long-term performance of the coating.
Practical implications
The mechanical properties of the coatings in this study also implied that HGMs can be used to develop scratch-resistant and impact-resistant coatings. Other potential applications for further studies include the uses of HGMs for coatings with improved fire retardancy and electromagnetic interference shielding.
Originality/value
A double layer coating was developed to provide balanced performance on both anticorrosion and heat insulation. The effects of HGM size were particularly highlighted.
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Yuanjie Zhi, Dongmei Fu, Tao Yang, Dawei Zhang, Xiaogang Li and Zibo Pei
This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.
Abstract
Purpose
This study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.
Design/methodology/approach
This paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.
Findings
Results of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.
Originality/value
Corrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.
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Hossein Dehdarirad, Javad Ghazimirsaeid and Ammar Jalalimanesh
The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the…
Abstract
Purpose
The purpose of this investigation is to identify, evaluate, integrate and summarize relevant and qualified papers through conducting a systematic literature review (SLR) on the application of recommender systems (RSs) to suggest a scholarly publication venue for researcher's paper.
Design/methodology/approach
To identify the relevant papers published up to August 11, 2018, an SLR study on four databases (Scopus, Web of Science, IEEE Xplore and ScienceDirect) was conducted. We pursued the guidelines presented by Kitchenham and Charters (2007) for performing SLRs in software engineering. The papers were analyzed based on data sources, RSs classes, techniques/methods/algorithms, datasets, evaluation methodologies and metrics, as well as future directions.
Findings
A total of 32 papers were identified. The most data sources exploited in these papers were textual (title/abstract/keywords) and co-authorship data. The RS classes in the selected papers were almost equally used. DBLP was the main dataset utilized. Cosine similarity, social network analysis (SNA) and term frequency–inverse document frequency (TF–IDF) algorithm were frequently used. In terms of evaluation methodologies, 24 papers applied only offline evaluations. Furthermore, precision, accuracy and recall metrics were the popular performance metrics. In the reviewed papers, “use more datasets” and “new algorithms” were frequently mentioned in the future work part as well as conclusions.
Originality/value
Given that a review study has not been conducted in this area, this paper can provide an insight into the current status in this area and may also contribute to future research in this field.
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Keywords
Abstract
Purpose
As a common form of failure in industry, corrosion causes huge economic losses. At present, with the development of computational techniques, artificial intelligence (AI) is playing a more and more important role in the field of scientific research. This paper aims to review the application of AI in corrosion protection research.
Design/methodology/approach
In this paper, the role of AI in corrosion protection is systematically described in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction.
Findings
With efficient and in-depth data processing methods, AI can rapidly advance the research process in terms of anticorrosion materials and methods, corrosion image recognition and corrosion life prediction and save on costs.
Originality/value
This paper summarizes the application of AI in corrosion protection research and provides the basis for corrosion engineers to quickly and comprehensively understand the role of AI and improve production processes.