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Noise and vibration performance of automotive disk brakes with laser-machined M-shaped grooves

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2023年第5期237卷 978-990页

作者： Zhu, Dapeng Yu, Xinke Sai, Qingyi wang, shuwen Barton, David Fieldhouse, John Kosarieh, Shahriar Univ Shanghai Sci & Technol Coll Mech Engn 516 Jungong Rd Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Coll Energy & Power Engn 516 Jungong Rd Shanghai 200093 Peoples R China Univ Leeds Sch Mech Engn Leeds W Yorkshire England

This work makes use of experimental and numerical studies to investigate the reduction of braking noise and vibrations of brake disks by introducing various M-shaped grooves on the brake disk frictional surfaces. Experiments with a brake test dynamometer have been carried out to compare the braking vibrations and noise of the grooved disks with that of the un-grooved disk. The experimental results demonstrate that disks with grooves significantly reduced braking vibrations and noise at both low and high frequencies, and as the initial braking temperature and braking pressure increased, the reduction effect is further enhanced. The investigation also shows the wear rates of both the grooved disks and brake pads are also significantly reduced. Thermo-mechanical coupled finite element models of the brake pads and disks with and without grooves are developed to investigate the mechanisms of the reduction of braking noise and vibrations by the introduction of grooves on the disk frictional surfaces. The numerical results show that the number of grooves plays an important role in reducing the interface surface temperatures, enhancing heat flux, reducing thermal deformation, changing the contact pressure distribution, and stabilizing the coefficients of friction of the braking sliding contacts. The thermal effects contribute to the wear reduction of both the braking disks and pads, and the reduction of braking noise and vibrations. In addition, both the finite element modal analysis and the experimental modal testing results show that surface grooves increase the modal damping ratio of the disks, which certainly plays a role on the reduction of braking noise and vibrations. This study has significance to the surface modification of brake disks in order to reduce braking noise and vibrations, as well as the wear resistance of brake disks and pads.

关键词： Surface modification finite element modeling thermal deformation braking surface temperature vibration and noise

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Optimization of Ball Valve Housing Based on Xgboost Regression Model 21

Optimization of Ball Valve Housing Based on Xgboost Regressi...

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21st International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Wenyi, Xu Jiawei, Dai Shun, Gao Xiaoqin, Liang shuwen, wang School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331519254

Ball valves play a pivotal role in industrial piping systems, with their design directly influencing system safety, stability, and fluid control efficiency. The thickness of the shell is a crucial parameter for ensuring structural strength and safety. Traditionally, this parameter has been determined using empirical formulas or standard specifications based on nominal pressure, diameter, and material properties. However, these methods are based on idealized assumptions that do not account for complex working conditions such as high pressure and temperature. This can result in reduced accuracy and potential safety risks. To address this issue, this study employs the Extreme Gradient Boosting (XGBoost) regression algorithm, utilizing historical data to train a machine learning model for precise ball valve design predictions. © 2024 IEEE.

关键词： Safety valves

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Short-Term Forecasting Of Evaporation Ducts Based On GraphCastGFS 14

Short-Term Forecasting Of Evaporation Ducts Based On GraphCa...

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14th International Symposium on Antennas Propagation and EM Theory

作者： Feng, Chongyang wang, shuwen Yang, Fan Yang, Kunde Chunlong, Huang Harbin Engn Univ Yantai Res Inst Yantai Peoples R China Northwestern Polytech Univ Ocean Inst Taicang Peoples R China

ISBN: (纸本)9798350353129;9798350353136

Evaporation ducts have an important impact on the propagation of electromagnetic waves near the sea surface. The short-term forecasting of regional evaporation ducts has important practical significance for radar, communication, etc. The development of machine learning technology has resulted in a wide range of applications in the field of meteorological forecasting. Recently, the National Centers for Environmental Prediction (NCEP) released the GraphCast Global Forecast System (GraphCastGFS), which is a new meteorological forecasting product based on the machine learning algorithm GraphCast. This study carried out a 168 h short-term forecast for the northern part of the South China Sea (SCS), based on the GraphCastGFS forecasting product and the NAVSLaM model. Taking ERA5 data as the benchmark value, a root-mean-square error (RMSE) analysis of the evaporation duct height (EDH) forecast results based on GraphCastGFS, and those of GFS, was performed. The results showed that the RMSE of the EDH forecast result based on GraphCastGFS was 3.0 m, and that of GFS was 3.4 m. The short-term forecasting accuracy of evaporation ducts based on GraphCastGFS was found to be marginally better than that of GFS, and the rapid data generation speed of GraphCastGFS further suggests its substantial potential in the field of evaporation duct forecasting.

关键词： EDH short-term forecasting machine learning

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Ni-Co PBA nanocubes for efficient capture and incorporation of Cs and Tl ions: Mechanism and techno-economic analysis

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JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2025年第3期13卷

作者： Su, Minhua Han, Weixing wang, shuwen Lai, Yanrong Chen, Miaoling Chen, Diyun Song, Gang Xu, Junhua Tang, Jinfeng Guangzhou Univ Sch Environm Sci & Engn Guangzhou 510006 Peoples R China Geol Survey Finland POB 96 FI-02151 Espoo Finland Chalmers Univ Technol Dept Chem & Chem Engn Nucl Chem & Ind Mat Recycling S-41296 Gothenburg Sweden

Toxic Cs+ and Tl+ ions are highly soluble and environmentally mobile;the effective and selective elimination of both elements from waste streams is of great significance. Herein, Ni-Co PBA (NCP) nanocubes were tailored through a facile coprecipitation process and found to have excellent adsorption performance. The pseudo-secondorder kinetic and Langmuir models fit the observed adsorption of Cs+ and Tl+ on NCP nanocubes. The Langmuir model indicated that the maximum capacity of NCP nanocubes to adsorb Cs+ and Tl+ was 201.09 and 39.26 mg/ g, respectively. NCP nanocubes exhibited excellent stability and was efficient for adsorption in a wide pH range (pH = 2-11) and in the presence of high concentrations of interfering cations, and even after strong irradiation. The mechanism of Cs+ and Tl+ adsorption was found to primarily be ion exchange of Cs+ and Tl+ with K+ in the cubic skeleton;on the other hand, surface complexation and electrostatic interactions also occurred during Tl capture. NCP nanocubes holds great potential for Cs+ and Tl+ removal from contaminated media due to its costeffectiveness, high adsorption capacity, irradiation resistance, and selectivity. This work thoroughly examined an economic and efficient materials for Cs and Tl removal, providing theoretical support for the facile fabrication and utilization of low-cost NCP nanocubes as sustainable and emergency materials for Cs or Tl contamination accident. This study also provides a preliminary discussion on the potential impacts on these stakeholders.

关键词： Nanocubes Cs and Tl removal Ion-exchange Adsorption capacity Radiation resistance Sustainable wastewater treatment

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Evolution of Research on funding inequality in science: a bibliometric analysis

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Procedia Computer Science 2023年 221卷 1200-1207页

作者： shuwen wang Dengsheng Wu Institutes of Science and Development Chinese Academy of Sciences Beijing 100190 P. R. China School of Public Policy and Management University of Chinese Academy of Sciences Beijing 100049 P. R. China

Funding inequality in the research community is a topic of widespread research interest. Research on funding inequality has evolved rapidly over time, yet there is a lack of comprehensive understanding of current research on this topic. We obtained 911 scientific papers published in 1990 – 2023 from the Web of Science core dataset and used bibliometric analysis to examine the evolution of the important issue of funding equality in the scientific research community. Specifically, we find that the number of papers about funding inequality has increased significantly in recent years. Among them, Scientometrics has published 29 papers related to funding inequality during the years. In addition, the results showed that Research Libraries UK ranked first in the number of outputs with a total of 77 publications related to funding inequality. Our research also goes a step further by identifying research experts in the field of funding inequality. Finally, the results of thematic clustering show that existing research related to funding inequality mainly revolves around issues such as gender differences, peer review, and productivity.

关键词： Research funding Grant Funding inequality Bibliometric Analysis

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Prediction of frictional braking noise based on brake dynamometer test and artificial intelligent algorithms

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2022年第12期236卷 2681-2695页

作者： wang, shuwen Zhong, Liangwei Niu, Yayun Liu, Shuangxia wang, Shaofan Li, Ke wang, Lijing Barton, David Univ Shanghai Sci & Technol Coll Mech Engn 516 Jungong Rd Shanghai 200093 Peoples R China Beihang Univ Inst Artificial Intelligence Beijing Peoples R China Univ Leeds Coll Mech Engn Leeds W Yorkshire England

Based on brake noise dynamometer test data, combined with the artificial intelligent algorithms, frictional braking noise is quantitatively analyzed and predicted in this study. To achieve this goal, a frictional braking noise prediction method is indicatively proposed, which consists of two main parts: first, based on the experimental data obtained from the brake noise dynamometer tests, and combining with the improved Long-Short-Term Memory (LSTM) algorithm, the coefficients of friction (COFs) are predicted under various braking test conditions. Then, based on the predicted braking COFs and other selected critical braking parameters, the quantitative prediction of frictional braking noise is obtained by means of the optimized eXtreme Gradient Boosting (XGBoost) algorithm. Finally, the inherent features of the XGBoost algorithm are employed to qualitatively analyze the importance of the main factors affecting the frictional braking noise. The prediction algorithms of COFs and frictional braking noise are validated by the brake dynamomter test data, and the R-2 (R square) scores of both the LSTM and XGBoost prediction algorithms are 0.9, which verifies the feasibility of both algorithms. The main contribution of this work is to predict the braking noise based on a large set of test data and combined with the LSTM and XGBoost artificial intelligent algorithms, which can significantly save time for the brake system development and braking performance testing, and has significance to the rapid prediction of braking frictional noise and fast NVH (noise, vibration, and harshness) optimal design of frictional braking systems.

关键词： Braking noise friction coefficient long-short-term memory algorithm XGBoost model noise prediction

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Evaluation of enrofloxacin in the Chinese soft-shelled turtle (Pelodiscus sinensis) based on the biochemical, histopathological and intestinal microbiota responses

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AQUACULTURE 2024年 590卷

作者： Zhang, Yonggang Liu, Ying Li, Zhaoxin Li, Xianguo Xing, Lihong wang, shuwen Sun, Xiaojie Zhang, Dahai Ocean Univ China Coll Chem & Chem Engn Qingdao 266100 Peoples R China Chinese Acad Fishery Sci Yellow Sea Fisheries Res Inst Key Lab Testing & Evaluat Aquat Prod Safety & Qual Lab Qual & Safety Risk Assessment Aquat ProdMinis Qingdao 266071 Peoples R China Qingdao Fishery Technol Serv Stn Qingdao 266071 Peoples R China Qingdao Marine Management Support Ctr Qingdao 266071 Peoples R China

Enrofloxacin (ENR) is a veterinary medicine extensively used in aquatic farming, the abuses of antibacterials can lead to drug residues and toxicity to aquatic animals. Nevertheless, its toxicological effects on the Pelodiscus sinensis remain unclear. The objective of this work was to study the toxic effects of ENR on male P. sinensis following multiple oral administration. For hematological, antioxidant status, histological and ultrastructural analyzed, male P. sinensis were orally administrated with ENR for 5 consecutive days, each at the dose of 15 (recommended dose, 1x), 45 (3 times the recommended dose, 3x), and 75 (5 times the recommended dose, 5x) mg/kg body weight (BW) daily. The effect of ENR on P. sinensis by changes in the intestinal microbiota using high-throughput sequencing technology was also investigated. Samples of blood and fresh tissue (liver, spleen, intestine, muscle, spermary, testes, heart, lung, and kidney) were collected after 24 h of drug withdrawal. The results showed that multiple oral administration of ENR induced immunosuppression (lowered total proteins, alkaline phosphatase, and albumin), hepatic-renal dysfunction (elevated aspartate transaminase, alanine aminotransferase, urea nitrogen, K+ and Ca2+), and lowering the hepatic and splenic antioxidant functions (higher MDA, and declines in the activities of SOD, CAT, and NOS) in 3x ENR-dosed or 5x ENR-dosed groups. Noteworthy, histopathological and ultrastructural examination of tissue samples revealed adverse effects with increasing oral dosage of ENR. The 16S sequencing analysis showed that the ENR treatment can greatly change the intestinal microbial diversity and abundance in P. sinensis, but more probiotics such as Cetobacterium, Lactococcus, and Paraclostridium were retained in the short-term period. The findings may provide new insights into the toxicity of ENR to P. sinensis, and help to determine the dose to ensure the safety of aquatic food products.

关键词： Enrofloxacin Pelodiscus sinensis Hematological variables Antioxidant status Histopathology Intestinal microbiota

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Trends of ischemic heart disease mortality attributable to household air pollution during 1990-2019 in China and India: an age-period-cohort analysis

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第58期29卷 87478-87489页

作者： wang, Tong Ma, Yudiyang Li, Ruiqing Sun, Jinyi Huang, Lihong wang, shuwen Yu, Chuanhua Wuhan Univ Sch Publ Hlth Dept Epidemiol & Biostat Wuhan 430071 Peoples R China Wuhan Univ Global Hlth Inst Wuhan 430071 Peoples R China

Cardiovascular diseases (CVD) caused by household air pollution (HAP) have sparked widespread concern globally in the recent decade. Meanwhile, increased ischemic heart disease (IHD) mortality has been the leading cause of worldwide CVD deaths. Both China and India experienced a high IHD burden and high exposure to HAP. The present study aimed to estimate and compare the long-term trends of HAP-attributable IHD mortality in the two countries. The data of this study were extracted from the Global Burden of Diseases (GBD) Study 2019. The age-period-cohort (APC) analysis was utilized to estimate the independent trends of the age, period, and cohort effects from 1990 to 2019. The age-standardized mortality rates (ASMRs) of HAP-attributable IHD have fallen faster in China than in India for both sexes. The local drift and net drift values were < 0 for all age groups in both countries. The age effects in both countries and sexes increased with time, suggesting age is a risk factor for IHD;conversely, period and cohort effects in China demonstrated a faster decline in both genders than in India. It indicated that China has been more successful than India in decreasing HAP-attributable IHD mortality.

关键词： Ischemic heart disease Household air pollution Age-period-cohort analysis China India

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Total saponins from Panax Japonicus regulate the ferritin heavy chain to reduce inflammation in aging adipose tissue by mediating iron metabolism

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JOURNAL OF GINSENG RESEARCH 2025年第2期49卷 134-144页

作者： Zhu, Leiqi Zhang, Jihong Hu, Yaqi Zhang, Yifan wang, shuwen wang, Rui Yuan, Qi Luo, Yiyang Yuan, Ding He, Yumin Yuan, Chengfu China Three Gorges Univ Grade Pharmacol Lab Tradit Chinese Med 3 State Adm Tradit Chinese Med Yichang Peoples R China China Three Gorges Univ Coll Basic Med Sci Yichang Peoples R China China Three Gorges Univ Hubei Clin Res Ctr Funct Digest Dis Tradit Chinese Yichang Peoples R China China Three Gorges Univ Tradit Chinese Med Hosp Yichang Peoples R China China Three Gorges Univ Coll Med & Hlth Sci Yichang Peoples R China

Background: Inflammation is a key factor contributing to aging-related morbidities. Inflammation is intimately linked to the iron metabolism in macrophages, and ferritin heavy chain (Fth) is the basis of iron metabolism in macrophages. Regulating Fth to control iron metabolism may help to reduce inflammation in macrophages, which can ultimately help to alleviate certain aging-related diseases. Methods: The effects of total saponins from Panax Japonicus (TSPJs) in the intervention of aging-related obesity were explored. The in vitro and in vivo models were established using RAW264.7 macrophage cells and naturally aging rats and mice. The inflammation, iron content, and gene expressions of the models were analyzed. Senescence was induced in RAW264.7 cells with adriamycin (ADR), and Fth knockdown was introduced to the models to investigate related mechanisms. Results: TSPJs reduced the iron content in the macrophages and prompted M2 polarization, which affected the JNK signaling pathway (p < 0.05) and reduced the expression of inflammatory cytokines in adipose tissue. Conclusion: TSPJs mediate the iron metabolism of macrophages via Fth to reduce aging-related inflammation of the adipose tissue.

关键词： TSPJs Aging Inflammation Ferritin heavy chain Iron metabolism

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LG-FAL: Locality-customized GSA Federated Active Learning

LG-FAL: Locality-customized GSA Federated Active Learning

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IEEE International Conference on Big Knowledge (ICBK)

作者： shuwen wang Xingquan Zhu Department of Computer Science Portland State University Portland USA Dept. of Electrical Engineering & Computer Science Florida Atlantic University Boca Raton USA

ISBN: (数字)9798331508821

ISBN: (纸本)9798331508838

Federated Learning (FL) is a learning paradigm which constructs machine learning models using decentralized datasets, with the goal of training a globally optimized model while preserving data privacy. In practice, annotating training data for FL is expensive and time-consuming. To solve this problem, researchers proposed to integrate active Learning (AL) strategy as Federated Active Learning (FAL) framework. However, existing research on FAL has two main limitations: (1) In the active learning part, more attention is paid to the global model, while ignoring the local information; (2) In the federated learning part, the popular Federated averaging (FedAvg) method relies on the assumption that the corresponding nodes in distributed neural networks share the same importance when averaging. In this paper, in order to tackle the two limitations, we propose a locality-customized GSA federated active learning (LG-FAL) method. Specifically, (i) both local and global information are taken into consideration to evaluate and select informative data samples to annotate for active learning; (ii) we integrate Gravitational Search Algorithm (GSA) to dynamically average local network parameters into the global parameter, by mimicking the principles of gravity and motion in the universe, for effective federated learning. As a result, LG-FAL can select a small subset of informative samples considering both local and global information, and at the same time, provide an improved trade-off between communication cost and learning accuracy. Experimental results show that LG-FAL significantly outperforms the current state-of-the-art baselines in terms of performance and effectiveness.

关键词： Adaptation models Accuracy Uncertainty Federated learning Annotations Active learning Training data Predictive models Entropy Data models

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