Multi-Objective Optimization of Functionally Graded Hollow Cylinders

2011 ◽  
Author(s):  
M. Nabian ◽  
M. T. Ahmadian
Keyword(s):  
Natural Frequency ◽  
Volume Fraction ◽  
Optimization Method ◽  
Functionally Graded ◽  
Multi Objective Optimization ◽  
Algorithm Optimization ◽  
Multi Objective ◽  
Graded Material ◽  
Hollow Cylinders ◽  
Volume Fraction Function

In this study, two physical properties of simply supported hollow cylinders made of functionally graded materials are investigated. These two properties are mass and first natural frequency which is desirable to be minimized and maximized respectively in mechanical applications. The functionally graded material properties are assumed to vary continuously through the thickness of the cylinder. In this multi-objective optimization problem the first natural frequency of the FGM cylinders as well as its mass are formulated in terms of the volume fraction of the constituents, then by using Genetic algorithm optimization method the continuous volume fraction function of the constituents has been derived to minimize the mass and maximize the first natural frequency simultaneously.

scholarly journals Dynamics of axially functionally graded conical pipes conveying fluid

2021 ◽  
Vol 37 ◽  
pp. 318-326
Author(s):  
Yuzhen Zhao ◽  
Dike Hu ◽  
Song Wu ◽  
Xinjun Long ◽  
Yongshou Liu
Keyword(s):  
Natural Frequency ◽  
Critical Velocity ◽  
Volume Fraction ◽  
Differential Quadrature Method ◽  
Reduction Factor ◽  
Functionally Graded ◽  
Function Type ◽  
Pipes Conveying Fluid ◽  
Volume Fraction Function ◽  
Conveying Fluid

Abstract In this paper, the dynamics of axially functionally graded (AFG) conical pipes conveying fluid are analyzed. The materials are distributed along the conical pipe axis as a volume fraction function. Either the elastic modulus or the density of the AFG conical pipe is assumed to vary from the inlet to the outlet. The governing equation of the AFG conical pipe is derived using the Hamiltonian principle and solved by the differential quadrature method. The effects of the volume fraction index, volume fraction function type and reduction factor on the natural frequency and critical velocity are analyzed. It is found that for a power function volume fraction type, the natural frequency and critical velocity increase with increasing volume fraction index and clearly increase when the volume fraction index is within the range (0, 10). For an exponential function volume fraction type, the natural frequency and critical velocity change rapidly within the range (−10, 10), besides the above range the relationship between the natural frequency, critical velocity and volume fraction index is approximate of little change. The natural frequency and critical velocity decrease linearly with increasing reduction factor.

Wave propagation analysis of thermoelastic functionally graded nanotube conveying nanoflow

2020 ◽  
pp. 107754632097704
Author(s):  
Jiayin Dai ◽  
Yongshou Liu ◽  
Guojun Tong
Keyword(s):  
Wave Propagation ◽  
Temperature Variation ◽  
Volume Fraction ◽  
Functionally Graded ◽  
Nonuniform Temperature ◽  
Propagation Analysis ◽  
Graded Material ◽  
The Stability ◽  
Volume Fraction Function ◽  
Better Than

As a hollow cylindrical structure, a nanotube has potential to convey nanoflow, which has opened up a field of research. Functionally graded nanotube as a designable structure with continuous variation of material properties can perform better than uniform nanotube, especially in physical field without introducing large stress concentration. In this article, we take the thermal effect into account and investigated the wave propagation characteristics of functionally graded material nanotube conveying nanoflow. In particular, we compared the effects of different kinds of volume fraction function and also the cases of uniform and nonuniform temperature variation. According to the numerical results, we can conclude that as we decrease the exponent n of the volume fraction function, the system is enhanced and larger enhancement can be observed in the case of the power volume fraction function. In addition, there is a positive correlation between the stability and both the temperature variation and the nonuniformity of temperature variation.

scholarly journals Multi-Objective Optimization of Variable-Stiffness Composites Fabricated by Tailored Fiber Placement Machine

2019 ◽  
Vol 2 (1) ◽  
pp. 14-18
Author(s):  
Shinya Honda
Keyword(s):  
Mechanical Properties ◽  
Volume Fraction ◽  
Variable Stiffness ◽  
Optimization Method ◽  
Pareto Optimum ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Fiber Placement ◽  
Curvilinear Fibers ◽  
Placement Machine

A multi-objective optimization method for the laminated composite fabricated by a tailored fiber placement machine that is an application of embroidering machine is presented. The mechanical properties of composite with curvilinear fibers including stiffness, volume fraction, and density are variable depending on curvatures of fibers. The present study first measures the relation between curvatures and mechanical properties. The measured results indicate that the stiffness of composite decreases linearly as the curvature increases. Then, the obtained relation is applied to the multi-objective optimization where the maximum principal strain and magnitude of curvature are employed as objective functions. Obtained Pareto optimum solutions are widely distributed ranging from the solutions with curvilinear fibers to those with straight fibers, and the curvilinear fiber has still advantages over straight fiber even its weakened stiffness.

scholarly journals Multi-objective optimization of flexure hinge mechanism considering thermal–mechanical coupling deformation and natural frequency

2017 ◽  
Vol 9 (1) ◽  
pp. 168781401668791 ◽  
Author(s):  
Lufan Zhang ◽  
Xueli Li ◽  
Jiwen Fang ◽  
Zhili Long
Keyword(s):  
Finite Element ◽  
Natural Frequency ◽  
Element Model ◽  
Optimization Method ◽  
Design Parameters ◽  
Flexure Hinge ◽  
Multi Objective Optimization ◽  
Motion Platform ◽  
Mechanical Coupling ◽  
Multi Objective

Flexure hinge mechanism plays a key part in realization of terminal nano-positioning. The performance of flexure hinge mechanism is determined by its positioning design. Based on the actual working conditions, its finite element model is built and calculated in ANSYS. Moreover, change trends of deformation and natural frequency with positioning design parameters are revealed. And sensitivity analysis is performed for exploration response to these parameters. These parameters are used to build four objective functions. To solve it conveniently, the multi-objective optimization problem is transferred to the form of single-objective function with constraints. An optimal mechanism is obtained by an optimization method combining ANSYS with MATLAB. Finite element numerical simulation has been carried out to demonstrate the superiority of the optimal flexure hinge mechanism, and the superiority can be further verified by experiment. Measurements and tests have been conducted at varying accelerations, velocities, and displacements, to quantify and characterize the amount of acceleration responses obtained from flexure hinge mechanism before and after optimization. Both time- and frequency-domain analyses of experimental data show that the optimal flexure hinge mechanism has superior effectiveness. It will provide a basic for realizing high acceleration and high precision positioning of macro–micro motion platform.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

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