scholarly journals Vibro-Acoustical Sensitivities of Stiffened Aircraft Structures Due to Attached Mass-Spring-Dampers with Uncertain Parameters

Aerospace ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 174
Author(s):  
Johannes Seidel ◽  
Stephan Lippert ◽  
Otto von Estorff
Keyword(s):  
System Response ◽  
Fuzzy Arithmetic ◽  
Parameter Uncertainties ◽  
Excitation Spectra ◽  
Radiated Noise ◽  
Linking Elements ◽  
Manufacturing Tolerances ◽  
Suitable Framework ◽  
Mass Spring ◽  
The Impact

The slightest manufacturing tolerances and variances of material properties can indeed have a significant impact on structural modes. An unintentional shift of eigenfrequencies towards dominant excitation frequencies may lead to increased vibration amplitudes of the structure resulting in radiated noise, e.g., reducing passenger comfort inside an aircraft’s cabin. This paper focuses on so-called non-structural masses of an aircraft, also known as the secondary structure that are attached to the primary structure via clips, brackets, and shock mounts and constitute a significant part of the overall mass of an aircraft’s structure. Using the example of a simplified fuselage panel, the vibro-acoustical consequences of parameter uncertainties in linking elements are studied. Here, the fuzzy arithmetic provides a suitable framework to describe uncertainties, create combination matrices, and evaluate the simulation results regarding target quantities and the impact of each parameter on the overall system response. To assess the vibrations of the fuzzy structure and by taking into account the excitation spectra of engine noise, modal and frequency response analyses are conducted.

A general theory of fuzzy arithmetic

1990 ◽  
Vol 36 (3) ◽  
pp. 339-363 ◽  
Author(s):  
Divyendu Sinha
Keyword(s):  
General Theory ◽  
Fuzzy Arithmetic

scholarly journals DUAL HESITANT FUZZY AGGREGATION OPERATORS

2015 ◽  
Vol 22 (2) ◽  
pp. 194-209 ◽  
Author(s):  
Dejian YU ◽  
Wenyu ZHANG ◽  
George HUANG
Keyword(s):  
Human Resources ◽  
Fuzzy Sets ◽  
Geometric Mean ◽  
Arithmetic Mean ◽  
Aggregation Operators ◽  
Fuzzy Arithmetic ◽  
Hesitant Fuzzy Sets ◽  
Numerical Example ◽  
Fuzzy Environment ◽  
Fuzzy Aggregation

Dual hesitant fuzzy sets (DHFSs) is a generalization of fuzzy sets (FSs) and it is typical of membership and non-membership degrees described by some discrete numerical. In this article we chiefly concerned with introducing the aggregation operators for aggregating dual hesitant fuzzy elements (DHFEs), including the dual hesitant fuzzy arithmetic mean and geometric mean. We laid emphasis on discussion of properties of newly introduced operators, and give a numerical example to describe the function of them. Finally, we used the proposed operators to select human resources outsourcing suppliers in a dual hesitant fuzzy environment.

scholarly journals Soil water management problems using fuzzy arithmetic

2013 ◽  
Vol 11 (4) ◽  
pp. 556-565
Keyword(s):  
Hydraulic Conductivity ◽  
Uncertain Data ◽  
Triangular Fuzzy Number ◽  
Effective Porosity ◽  
Specific Yield ◽  
Fuzzy Arithmetic ◽  
Two Dimensional ◽  
Fuzzy Analysis ◽  
Management Problems ◽  
Α Level

Drainage management problems are usually very hard to simulate due to the uncertainty of the hydraulic parameters involved. Fuzzy analysis is one of the available tools that can be used for such problems, involving uncertain data. A fuzzy analysis approach usually involves the consideration of several α-level cuts and an analytical approach or an explicit scheme approach for the PDE's discretization. Several application examples of this approach are listed in the literature, including uncertainty in hydraulic conductivity, specific yield, transmissivities, porosities, dispersivities, and deoxygenation rate coefficient. A methodology for the simulation of drainage problem having vague values of hydraulic parameters is introduced in this paper, and an analytical solution for a two-dimensional drainage application is presented. The two-dimensional problem of drainage is handled using fuzzy analysis by defining the hydraulic conductivity K as a triangular fuzzy number (TFN). The method of interval analysis is used in all the α-level cut examples. A solution is obtained using eleven α-level cuts and also solutions for two, three, and five α-level cuts are presented. Trials for different values of effective porosity are also performed. Finally conclusions on the necessary number of α-cuts utilized for drainage problems are drawn.

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