Uncertainty quantification of squeal instability under two fuzzy-interval cases

Lü, Hui; Shangguan, Wen‐Bin; Yu, Dejie

doi:10.1016/j.fss.2017.07.006

Cited by 23 publications

(14 citation statements)

References 43 publications

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“…In the future, a comparative study based on several cases should be developed. A comparison between the approaches and results with the works of the diode theory [19] or the interval theory [20,21] should also be considered.…”

Section: Resultsmentioning

confidence: 99%

Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

Mhalla

Gaied

2018

Journal of Engineering

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The importance of public transport systems continues to grow. These systems must respond to an increasing demand for population mobility and traffic disturbances. Rail transport networks can be considered as Discrete Event Systems (DES) with time constraints. The time factor is a critical parameter, since it includes dates to be respected in order to avoid overlaps, delays, and collisions between trains. P-time Petri Nets have been recognized as powerful modeling and analysis tools for railway transport systems. Temporal disturbances in these systems include railway infrastructure, traffic management, and disturbances (weather, obstacles on the tracks, malice, social movement, etc.). The developments presented in this paper are devoted to the modeling and the study of the robustness of the railway transport systems in order to evaluate the stability and the efficiency of these networks. In this study two robust control strategies towards time disturbances are presented. The first one consists of compensating the disturbance as soon as it is observed in order to avoid constraints violation. The second one allows generating, by the control, a temporal lag identical to the disturbance in order to avoid the death of marks on the levels of synchronization transitions of the P-time Petri net model.

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Section: Resultsmentioning

confidence: 99%

Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

Mhalla

Gaied

2018

Journal of Engineering

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“…This proposition is not an equivalence, as can be observed by taking [A, 7,9) , (10, 13,16)] T . It is the case that [(1, 2, 3) , (7, 9,11)] T ≤ [(5, 7,9) , (10, 13,16)…”

Section: Inequality Relationship: the Lattice (Ifs ≤)mentioning

confidence: 97%

“…In some studies, we can also find the concept of fuzzy-boundary interval [4][5][6][7]. In this case, the uncertain parameters of structures are treated as interval variables, but the intervals, instead of having two real (determined) bounds, the lower and upper bounds are considered to be fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

Interval Fuzzy Segments

Jorba

Adillon

2018

Symmetry

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In this paper, we bring together two concepts related to uncertainty and vagueness: fuzzy numbers and intervals. With them, we build a new structure whose elements we call interval fuzzy segments. We have undertaken this based on the conviction that the fuzzy numbers are a correct representation of the real numbers under situations of indeterminacy. We also believe that if it makes sense to consider the set of real numbers between two real bounds, then it also makes sense to consider the set of all the fuzzy numbers between two fuzzy number bounds. In this way, we extend the concept of real interval to the concept of interval fuzzy segment defined by two fuzzy bounds and a transition mapping that leads from the lower fuzzy bound to the upper fuzzy bound and this transition mapping generates the set of all the fuzzy numbers comprised between those fuzzy bounds. At the same time, this transition mapping brings the concept of interval fuzzy segment closer to the concept of line segment.

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“…The membership function is utilized to describe the uncertain parameters using fuzzy theory [13]. A unified method was developed for the uncertainty quantification of dis brake squeal for two fuzzy-interval cases, while the unified uncertain response was computed with the aid of the combination of level-cut strategy, Taylor series expansion, subinterval analysis and Monte Carlo simulation [14]. Both probability distribution function and membership function need a lot of data, however, the engineering problems have finite data [15].…”

Section: Introductionmentioning

confidence: 99%

Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

Liu

Xiao

et al. 2019

Applied Sciences

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With respect to heavy carrying tasks and uneven road surface in open pit mine, the mechanical performances of electric wheel dump truck frame regarded as the main bearing component are extremely important for its safe operation. For the problem of insufficient strength and stiffness, an interval multi-objectives optimization design method based on blind number theory is presented in this paper, taking into account uncertain factors caused by manufacturing process. The allowable interval strength of welding material and permissible interval bending and torsional stiffness are obtained by means of experiments and simulations, using the blind number theory. Based on Latin hypercube sampling technique, the strength and stiffness of frame under different conditions is estimated. It shows that in the case of braking interference between interval strength and interval dynamic stress appears. Strength and stiffness are considered as optimization objectives, while the thicknesses of top longitudinal beam, stiffener, lateral longitudinal beam and hanging ear in the frame are deeded as design variables, and Young’s modulus and Poisson’s ratio are taken as uncertain variables. The optimized results show that the stress and deformation of the frame due to dynamic loading decreased. This result enables to formulate the following sentence: the mechanical performance of frame is improved.

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Uncertainty quantification of squeal instability under two fuzzy-interval cases

Cited by 23 publications

References 43 publications

Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

Interval Fuzzy Segments

Interval Multi-Objectives Optimization of Electric Wheel Dump Truck Frame Based on Blind Number Theory

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