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modeling and prediction of Fatigue Properties of Additively Manufactured Metals

Acta Mechanica Solida Sinica 2023年第2期36卷 181-213页

作者： Wei Tang Ziming Tang Wenjun Lu Shuai Wang Min Yi State Key Lab of Mechanics and Control of Mechanical Structures&Institute for Frontier Science&Key Lab for Intelligent Nano Materials and Devices of Ministry of Education&College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics(NUAA)Nanjing 210016China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055China

Additive manufacturing(AM)has emerged as an advanced technique for the fabrication of complex near-net shaped and lightweight metallic parts with acceptable mechanical *** strength of AM metals has been confirmed comparable or even superior to that of metals manufactured by conventional processes,but the fatigue performance is still a knotty issue that may hinder the substitution of currently used metallic components by AM counterparts when the cyclic loading and thus fatigue failure *** essential complements to high-cost and time-consuming experimental fatigue tests of AM metals,models for fatigue performance prediction are highly *** this review,different models for predicting the fatigue properties of AM metals are summarized in terms of fatigue life,fatigue limit and fatigue crack growth,with a focus on the incorporation of AM characteristics such as AM defect and processing parameters into the *** predicting the fatigue life of AM metals,empirical models and theoretical models(including local characteristic model,continuum damage mechanics model and probabilistic method)are *** terms of fatigue limit,the introduced models involve the Kitagawa–Takahashi model,the Murakami model,the El-Haddad model,*** modeling the fatigue crack growth of AM metals,the summarized methodologies include the Paris equation,the Hartman-Schijve equation,the NASGRO equation,the small-crack growth model,and numerical *** of these models for AM metals are similar to those for conventionally processed materials,but are modified and pay more attention to the AM ***,an outlook for possible directions of the modeling and prediction of fatigue properties of AM metals is provided.

关键词： Additive manufacturing Fatigue properties Metals modeling and prediction Microstructure

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modeling and prediction research on wear of electroplated diamond micro-grinding tool in soda lime glass grinding

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2017年第9-12期91卷 3467-3479页

作者： Wen, Xuelong Gong, Yadong Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Liaoning Peoples R China

Micro-wear in micro-grinding process is very important to research the micro-tools wear and the service life prediction of the micro-tools. The wear mechanism of electroplated diamond micro-grinding tool is analyzed in this paper. The geometric and mathematical modeling is established in allusion to the composite mechanism in micro-grinding zone and the main characteristics of the wear forms. The prediction model of micro-wear is established by considering the size effect and the minimum chip thickness. Experiments with different grinding parameters in micro-grinding soda lime glass are carried out to confirm the validity of the model. The influence of the worn micro-grinding tools are proposed by analyzing the diameter of grinding head, the ratio of wear and fracture grains, the surface roughness of the specimens, and different grinding parameters. The test results show that the grinding head diameter decreases rapidly and sharply first and then decreases slowly and steadily. The wear is more slowly with better surface quality. The wear rate and the ratio of wear and fracture grains increase with the increasing of grinding and feed speeds, and the ratio has a linear trend integrally. It provides the experimental reference and the theoretical basis for improving the grinding performance and extending the service life of micro-grinding tools.

关键词： Micro-grinding Wear modeling and prediction Soda lime glass

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An Artificial Intelligence Approach for modeling and prediction of Water Diffusion Inside a Carbon Nanotube

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NANOSCALE RESEARCH LETTERS 2009年第9期4卷 1054-1058页

作者： Ahadian, Samad Kawazoe, Yoshiyuki Tohoku Univ Inst Mat Res Sendai Miyagi 9808577 Japan

modeling of water flow in carbon nanotubes is still a challenge for the classic models of fluid dynamics. In this investigation, an adaptive-network-based fuzzy inference system (ANFIS) is presented to solve this problem. The proposed ANFIS approach can construct an input-output mapping based on both human knowledge in the form of fuzzy if-then rules and stipulated input-output data pairs. Good performance of the designed ANFIS ensures its capability as a promising tool for modeling and prediction of fluid flow at nanoscale where the continuum models of fluid dynamics tend to break down.

关键词： Carbon nanotube Water diffusion Artificial intelligence modeling and prediction

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modeling and prediction for the Buoy motion characteristics

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OCEAN ENGINEERING 2021年 239卷

作者： Li, Xintian Bian, Yujian Hangzhou Appl Acoust Res Inst Hangzhou 310023 Peoples R China Hangzhou Ruili Marine Equipment Co LTD Hangzhou 310023 Peoples R China

To ensure the stability of buoy systems, it is necessary to predict the buoy motion characteristics in different environment conditions. Unfortunately, an accurate model is still not available for some unknown interaction between waves, currents and winds in oceans. modeling and designing a suitable buoy for further manufacture often encounters some challenges in practice. In this work, the least squares support vector regression (LSSVR) method is proposed to predict buoy motion characteristics. First, some modeling data are collected from the data processing system of a buoy. Additionally, an evaluation criterion is designed to automatically divide training data into two subsets, corresponding to the normal and extreme conditions. Moreover, two local LSSVR models are constructed using the subsets, respectively. Finally, a suitable model is automatically selected for each new sample. Consequently, with limited modeling samples, different property in the normal and extreme conditions can be effectively captured. Experimental results show the superiority of the proposed method.

关键词： Ocean environment Buoy motion characteristics Support vector regression modeling and prediction

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modeling and prediction of primary energy supply and electricity generation structures based on Markov chain: an insight with focus on the role of natural gas in Pakistan

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JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS 2021年第2期44卷 177-191页

作者： Ahmad, Hussaan Hayat, Nasir Univ Engn & Technol Dept Mech Engn Lahore Pakistan

This study aims to develop an alternative trended matrices approach of structural prediction as a counterpart to the classical Chapman-Kolmogorov approach. Methodological addition lies within the way of preservation of stochasticity of the transition matrices originated from the alternative approach for the case of initial non-stochasticity due to all negative row elements. Ten datasets (various case studies) of historic energy structures have been modeled, simulated, and extended as Markov chains followed by their respective error assessments. Linear regression-based alternative approach is found to be the nearest counterpart to the classical approach for the majority of datasets. This approach is subsequently applied for the prediction of primary energy supply and electricity generation structures in Pakistan in business as usual scenario for 2018-2030 period. Fossil fuels will share about 90% in the primary energy supply and electricity generation. Moreover, gas will prevail as the major fossil fuel for both primary energy supply and thermal-dominant electricity generation mixes. Gas share will be about 70% within the thermal electricity generation mix. Some results depict the hurdles in the development of a low carbon future. The alternative prediction approach may be used for comparable fields of resource allocation, planning, and management.

关键词： Markov chain modeling and prediction natural gas primary energy

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Neuro-fuzzy modeling and prediction of current total harmonic distortion for high power nonlinear loads

Neuro-fuzzy modeling and prediction of current total harmoni...

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IEEE (SMC) International Conference on Innovations in Intelligent Systems and Applications (INISTA)

作者： Panoiu, Manuela Panoiu, Caius Ghiormez, Loredana Polytech Univ Timisoara Elect Engn & Ind Informat Dept Timisoara Romania

ISBN: (纸本)9781538651506

The paper presents the results of the modeling and the prediction of the total harmonic distortion (THD) of the current and the voltage for a nonlinear high power load. modeling was performed using intelligent techniques based on neural networks and fuzzy inference. To achieve this, data were measured in the electrical installation of a non-linear electrical load, in this case a high-power electric arc furnace. These data were measured over the entire duration of a steel charge. The measured data was used to train a neuro fuzzy adaptive system. Following training, tests with different architectures have been performed with the neuro fuzzy adaptive system. The modeling and prediction results are useful in designing harmonic current Filters. The presence of these harmonic currents decreases productivity and affects the quality of power.

关键词： modeling and prediction total harmonic distortion ANFIS fuzzy

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modeling and prediction of Disturbing Force and Moment Based on Harmonic Analysis for Ship Cross Direction

Modeling and Prediction of Disturbing Force and Moment Based...

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第三届国际仪器科学技术学术研讨会

作者： TANG Hui-yan, ZHAO Xi-ren, ZHANG Jun, PENG Xiu-yan Automation College, Harbin Engineering University, Harbin 150001, China

In order to diminish the swing and improving the efficient of navigate,it was necessy to give the modeling and prediction of the wave disturbing force and moment and then give the compensate control o

关键词： modeling and prediction estimation for disturbing force and moment extended Kalman filtering harmonic analysis harmonic spectrum

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A critical review on modeling and prediction on properties of fresh and hardened geopolymer composites

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JOURNAL OF BUILDING ENGINEERING 2024年 88卷

作者： Zhang, Peng Mao, Yifan Yuan, Weisuo Zheng, Jie Hu, Shaowei Wang, Kexun Zhengzhou Univ Sch Water Conservancy & Transportat Zhengzhou 450001 Peoples R China Zhengzhou Dev Ctr Highway Ind Zhengzhou 450015 Peoples R China

Geopolymer is an environmentally friendly material that is recognized as a potential alternative binder to ordinary Portland cement. However, accurate prediction of the properties of geopolymer composites (GC) has been a concerned issue since there are few design codes for GC to guide their designs. The application of geopolymer has prompted scholars to seek reliable models for predicting their properties, which can save on research costs. With the development of computer science, an increasing number of algorithms are gradually applied to the prediction of GC in recent years. In the present paper, a comprehensive review of the modeling and prediction on GC properties is discussed and the common modeling and prediction methods are introduced in brief, including regression analysis, artificial neural network, adaptive network-based fuzzy inference system, and gene expression programming. Moreover, the advantages, weaknesses, and performance of various methods mentioned in this study are also critically discussed and analyzed. Most methods have presented success in a variety of property forecasts with reliable accuracy, even if the relationships between the properties and the inputs (such as mixture constituents and the curing conditions) are intricate. Nevertheless, these modeling and prediction methods still have some problems in large-scale applications. The effectiveness of these modeling and prediction methods is highly dependent on the database size and the choice of parameter. This review provides a basis for future research on the property modeling and prediction of GC, which could help the researchers and engineers choose the appropriate methods for modeling and prediction of the properties, and to design and optimize the formulations of GC.

关键词： Geopolymer composites modeling and prediction Machine learning Fresh properties Mechanical properties Durability

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Analyzing the prices of the most expensive sheet iron all over the world: modeling, prediction and regime change

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2010年第17期389卷 3538-3545页

作者： Song, Fu-Tie Zhou, Wei-Xing E China Univ Sci & Technol Sch Business Shanghai 200237 Peoples R China E China Univ Sci & Technol Res Ctr Econophys Shanghai 200237 Peoples R China E China Univ Sci & Technol Sch Sci Shanghai 200237 Peoples R China E China Univ Sci & Technol Minist Educ Engn Res Ctr Proc Syst Engn Shanghai 200237 Peoples R China Chinese Acad Sci Res Ctr Fictitious Econ & Data Sci Beijing 100080 Peoples R China

The private car license plates issued in Shanghai are bestowed the title of "the most expensive sheet iron all over the world", more expensive than gold. A citizen has to bid in a monthly auction to obtain a license plate for his new private car. We perform statistical analysis to investigate the influence of the minimal price P(min) of the bidding winners, the quota N(quota) of private car license plates, the number N(bidder) of bidders, as well as two external shocks including the legality debate of the auction in 2004 and the auction regime reform in January 2008 on the average price P(mean) of all bidding winners. It is found that the legality debate of the auction had marginal transient impact on the average price in a short time period. In contrast, the change of the auction rules has significant permanent influence on the average price, which reduces the price by about 3020 yuan Renminbi. It means that the average price exhibits nonlinear behaviors with a regime change. The evolution of the average price is independent of the number N(bidder) of bidders in both regimes. In the early regime before January 2008, the average price P(mean) was influenced only by the minimal price P(min) in the preceding month with a positive correlation. In the current regime since January 2008, the average price is positively correlated with the minimal price and the quota in the preceding month and negatively correlated with the quota in the same month. We test the predictive power of the two models using 2-year and 3-year moving windows and find that the latter outperforms the former. It seems that the auction market becomes more efficient after the auction reform since the prediction error increases. (C) Elsevier B.V. All rights reserved.

关键词： Econophysics Auction markets Private car license plate Regime change modeling and prediction

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Effects of TiO_(2)content on microstructure,thermal and mechanical properties of microwave sintered lunar regolith simulant

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Science China(Technological Sciences) 2025年第4期68卷 233-248页

作者： Zekai WANG Yan ZHOU Long XIAO Cheng ZHOU Lieyun DING National Center of Technology Innovation for Digital Construction School of Civil and Hydraulic EngineeringHuazhong University of Science and TechnologyWuhan430074China Planetary Science Institute China University of Geosciences(Wuhan)Wuhan430074China

Dense building components can be fabricated using lunar regolith simulants prepared via microwave *** this study,the microstructure and properties of such simulants containing high(14.72%),medium(6.71%),and low(1.7%)TiO_(2)contents prepared via microwave sintering at different temperatures(1030℃-1070℃)were *** sample sintered at 1060℃ with 14.72%TiO_(2)content exhibited the highest compressive strength of(125.2±22)*** was because high TiO_(2)content was more conducive to densification due to microwave *** influence of TiO_(2)content and sintering temperature on the strength of microwave-sintered samples was statistically analyzed,which revealed that sintering temperature was the main influencing factor(F value=187.3)and TiO_(2)content was the auxiliary influencing factor(F value=4.91).Using an enhanced multilayer perceptron model,a continuous surface diagram and prediction model were *** were then used to determine the influence of sintering temperature and TiO_(2)content on the compressive strength as well as to predict compressive strength with comparable *** study provides insights into microwave sintering of materials for future lunar construction.

关键词： lunar regolith simulant microwave sintering thermal property mechanical property modeling and prediction

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