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Wyświetlanie 1-10 z 12
Tytuł:
An efficient method for calculating system non-probabilistic reliability index
Autorzy:
Liu, Hui
Xiao, Ning-Cong
Tematy:
non-probabilistic model
non-probabilistic reliability index
system reliability
implicit function
Kriging model
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:
https://bibliotekanauki.pl/articles/2038190.pdf  Link otwiera się w nowym oknie
Opis:
Collecting enough samples is difficult in real applications. Several interval-based non-probabilistic reliability methods have been reported. The key of these methods is to estimate system non-probabilistic reliability index. In this paper, a new method is proposed to calculate system non-probabilistic reliability index. Kriging model is used to replace time-consuming simulations, and the efficient global optimization is used to determine the new training samples. A refinement learning function is proposed to determine the best component (or performance function) during the iterative process. The proposed refinement learning function has considered two important factors: (1) the contributions of components to system nonprobabilistic reliability index, and (2) the accuracy of the Kriging model at current iteration. Two stopping criteria are given to terminate the algorithm. The system non-probabilistic index is finally calculated based on the Kriging model and Monte Carlo simulation. Two numerical examples are given to show the applicability of the proposed method.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Global non-probabilistic reliability sensitivity analysis based on surrogate model
Autorzy:
Liu, Hui
Xiao, Ning-Cong
Tematy:
structural reliability
non-probabilistic reliability sensitivity
adaptive Kriging
surrogates
models
interval variables
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Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:
https://bibliotekanauki.pl/articles/2200925.pdf  Link otwiera się w nowym oknie
Opis:
Sensitivity analysis is used to find the key variables which have significant effect on system reliability. For a product in early design stage, it is impossible to collect sufficient samples. Thus, the probabilistic-based reliability sensitivity analysis methods are difficult to use due to the requirement of probability distribution. As an alternative, interval can be used because it only requires few samples. In this study, an effective global non-probabilistic sensitivity analysis based on adaptive Kriging model is proposed. The global accuracy Kriging model is constructed to reduce overall computational cost. Subsequently, the global non-probabilistic sensitivity analysis method is developed. Compared to existing non-probabilistic sensitivity analysis methods, the proposed method is a global non-probabilistic reliability sensitivity analysis method. The proposed method is easy to use and does not require probability distribution of the input variables. The applicability of proposed method is demonstrated via two examples.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Research on the modified echo highlight model for underwater vehicles with combined structures
Autorzy:
Xie, Xin
Liu, Fanghua
Jin, Guangwen
Liu, Jinwei
Xu, Cong
Peng, Zilong
Tematy:
modified highlight model
wedge-shaped convex structure
piecewise synthesis method
acoustic scattering calculation software
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Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Powiązania:
https://bibliotekanauki.pl/articles/34609383.pdf  Link otwiera się w nowym oknie
Opis:
The highlight model is widely used as a simple and convenient method in the radar field but its accuracy is not high. Based on the traditional highlight model, the algorithm has been improved to address the acoustic scattering problems of underwater vehicles with more complex line shapes. The basic idea is to partition the model into micro-bodies to calculate the scattered sound pressure, consider the phase interference of each part, and then synthesise the scattered sound pressure to approximate the target’s actual shape. A computational model of the wedge-shaped convex structure on the back of the underwater vehicles is developed using a highlight model of a trapezoidal plate. The results of the calculations using the highlight model approach are consistent with those of the planar element method. Utilising the modified highlight model method, the accuracy of acoustic scattering characteristics calculations for the stern and overall structures of underwater vehicles has proven satisfactory. Finally, fast acoustic scattering prediction software is developed for underwater vehicles, enabling the calculation of the acoustic scattering characteristics for individual structures, combined structures, and coated silent tiles. This software provides algorithmic support for the fast prediction of the acoustic stealth performance of underwater vehicles.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling and Identification Method of Bolt Loosening of Joint Surface under Axial Tension of Multistage Disk-Drum Rotor
Autorzy:
Yue, Cong
Zheng, Xiangmin
Wang, Chaoge
Liu, Hao
Chen, Hu
Tematy:
multistage drum rotor
bolt loosening
equivalent joint stiffness
structural health monitoring
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Powiązania:
https://bibliotekanauki.pl/articles/24200822.pdf  Link otwiera się w nowym oknie
Opis:
Individual bolt at key connection positions is prone to loose when the engine is cycle-operating under complex loads. A joint surface equivalent stiffness model is derived and developed based on the connection characteristics of bolt screwing in the multi-exciting environment of the high-pressure rotor. The model is used to analyse the effect of bolt missing at circumferential positions with the equivalent stiffness loss. Vibration experiments under both axial force and lateral impact were carried out to obtain the dynamic response feature of the multistage disk-drum simulated rotor with missing one bolt at different positions. The Spearman correlation coefficient was applied to evaluate the identification effect of different measuring points on the bolt loosening position. The study shows that the eigenfrequencies of experimental results have a consistent trend with the equivalent stiffness variation caused by single bolt missing model. This method also provides a theoretical basis for the detection of bolt deviation position with multi-exciting vibration detection.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation of ammonium citrate tribasic as a leaching reagent for lead-bearing ore
Autorzy:
Liu, Junbo
Li, Shimei
Zhao, Biao
Deng, Jianying
Huang, Lingyun
Zhou, Yuanyuan
Chen, Cong
Liu, Quanjun
Tematy:
lead
cerussite
ammonium citrate tribasic
leaching
kinetics
Pokaż więcej
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/109649.pdf  Link otwiera się w nowym oknie
Opis:
In this study, the leaching process of a lead-bearing ore, consisting mainly of cerussite, in an ammonium citrate tribasic medium was investigated. The parameters including temperature, reagent concentration, particle size, and stirring speed were examined. During leaching process, the lead conversion rate increased with an increase in reagent concentration, reaction temperature, and stirring speed, and a decrease in particle size. The results show that about 95% of lead content was extracted from the samples with particle size range of +75-96 μm after 21 min leaching in 1.25 mol/L ammonium citrate tribasic solution at 800 r/min and 40°C. It was found that the leaching reaction followed the shrinking core model. The results indicated that ammonium citrate tribasic could be used as an effective leaching reagent for extracting lead from lead oxide ore.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fungal diversity notes 2017-2122 : taxonomic and phylogenetic contributions to freshwater fungi and other fungal taxa
Autorzy:
Bandini, Ditte
Usman, Muhammad
Xiao, Yuanpin
Porcu, Giuseppe
Abeywickrama, Pranami D.
Liu, Jian-Wei
Armand, Alireza
Danteswari, Chalasani
Subramani, Priyadarshini
Casula, Marco
Zhang, Huang
Chen, Li-Jia
Dai, Dong-Qin
Liang, Yu-Shan
Zhao, Hai-Jun
Miller, Steven L.
Dissanayake, Asha J.
Rinaldi, Andrea C.
Wu, Na
Kumar, Shambhu
Martín, María P.
Svantesson, Sten
Kumla, Jaturong
Abdollahzadeh, Jafar
Tennakoon, Danushka S.
Yang, Chun-Lin
Kiss, Levente
Piri Kakihai, Sodabeh
Condé, Thiago O.
Suwannarach, Nakarin
Leonardi, Marco
Cheng, Song-Qi
Kezo, Kezhocuyi
Yu, Fu-Qiang
Shivas, Roger G.
Wang, Fei-Hu
Kabdraisova, Aisulu
Ronikier, Anna
Henkel, Terry W.
Khalid, Abdul Nasir
Yang, Yan-Yan
Gafforov, Yusufjon
Gao, Ying
de Silva, Nimali I.
Mleczko, Piotr
Du, Tian-Ye
Oset, Magdalena
Hyde, Kevin D.
Wen, Ting-Chi
Karunarathna, Samantha C.
Zhang, Jing-Yi
Ren, Guang-Cong
Ma, Jian
Gomdola, Deecksha
Ossowska, Emilia Anna
Yang, Yunhui
Suduri, Leila
Mahadevakumar, Shivannegowda
Mua, Alberto
Mohammadi Hamidi, Leila
Manawasinghe, Ishara Sandeepani
Ronikier, Michał
Li, Yan-Xia
Ferreira, Renato Juciano
Abdel-Wahab, Mohamed A.
Hernandez-Monroy, Abril
Podile, Appa Rao
Liao, Chun-Fang
Aime, M. Catherine
Rossi, Walter
Hashemlou, Esmaeil
Javan-Nikkhah, Mohammad
Lu, Yong-Zhong
Ghosta, Youbert
Jeewon, Rajesh
Gasca-Pineda, Jaime
Senanayake, Indunil Chinthani
Maharachchikumbura, Sajeewa S. N.
Rutkowski, Ryszard
Baseia, Iuri Goulart
Lumyong, Saisamorn
Bundhun, Digvijayini
Liu, Feng
Tian, Xing-Guo
Senwanna, Chanokned
Vaghefi, Niloofar
Gui, Heng
Sun, Ya-Ru
Wei, De-Ping
Chellapan, Naveenkumar
Bashiri, Samaneh
Xu, Rong-Ju
Karpowicz, Filip
Piepenbring, Meike
Chandranayaka, Siddaiah
Kunca, Vladimir
Kukwa, Martin
Han, Li-Su
Shu, Yong-Xin
Chen, Yanpeng
Chaiwan, Napalai
Acharya, Krishnendu
He, Shu-Cheng
Arumugam, Elangovan
de Farias, Antonio Roberto Gomes
Jayawardena, Ruvishika S.
Tan, Yu Pei
Pereira, Olinto L.
Zhao, Qi
Rajwar, Soumyadeep
Leão, Ana F.
Tarafder, Entaj
Velez, Patricia
Murugadoss, Ramesh
Tibpromma, Saowaluck
Sarma, Pullabhotla V. S. R. N.
Sanna, Massimo
Ahmadpour, Abdollah
Kaygusuz, Oğuzhan
Custódio, Fábio A.
Doilom, Mingkwan
Calabon, Mark S.
Singh, Raghvendra
Afshari, Naghmeh
Kosecka, Magdalena
Luo, Zong-Long
Shen, Hong-Wei
Glejdura, Stanislav
Kaliyaperumal, Malarvizhi
Dong, Wei
Vasan, Vigneshwari
Guzow-Krzemińska, Beata
Yang, Yu
Li, Hua
Amirashayeri, Pezhman
Chen, Liu-Huan
Monkai, Jutamart
Tang, Xia
Dostawca treści:
Repozytorium Uniwersytetu Jagiellońskiego
Artykuł
Wyświetlanie 1-10 z 12

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