scholarly journals Design optimization of an axial-field eddy-current magnetic coupling based on magneto-thermal analytical model

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Julien Fontchastagner ◽  
Thierry Lubin ◽  
Smaïl Mezani ◽  
Noureddine Takorabet
Keyword(s):  
Design Optimization ◽  
Analytical Model ◽  
Eddy Current ◽  
Convection Heat Transfer ◽  
Design Procedure ◽  
Magnetic Coupling ◽  
Optimization Procedure ◽  
Computationally Efficient ◽  
Transfer Coefficients ◽  
Good Efficiency

Abstract This paper presents a design optimization of an axial-flux eddy-current magnetic coupling. The design procedure is based on a torque formula derived from a 3D analytical model and a population algorithm method. The main objective of this paper is to determine the best design in terms of magnets volume in order to transmit a torque between two movers, while ensuring a low slip speed and a good efficiency. The torque formula is very accurate and computationally efficient, and is valid for any slip speed values. Nevertheless, in order to solve more realistic problems, and then, take into account the thermal effects on the torque value, a thermal model based on convection heat transfer coefficients is also established and used in the design optimization procedure. Results show the effectiveness of the proposed methodology.

Design Optimization of a Rocker-Joint Silent Chain and Sprocket Drive Based on the Mesh Performance Indices

2012 ◽  
Vol 197 ◽  
pp. 104-109 ◽  
Author(s):  
Wen Yi Su ◽  
Yu Ren Wu
Keyword(s):  
Design Optimization ◽  
Design Procedure ◽  
Optimization Procedure ◽  
Design Parameters ◽  
Chain Drive ◽  
Performance Indices ◽  
Tooth Contact Analysis ◽  
Noise Vibration ◽  
Chain Drives ◽  
Novel Design

Improvement on noise, vibration and wear in silent chain drives is always an important research subject. However, design methods revealed in public are few because the silent chain shapes are variable and complex. A feasible design procedure is extremely required for improving transmission performance of chain drives. Therefore, a novel design optimization procedure for the rocker-joint silent (RJS) chain and sprocket drive is proposed in this paper. The mathematical models of geometry generation, tooth contact analysis and impact velocities at different mesh stages and chain raise amount in the RJS chain drive have been established. Besides, impact velocities and raise amount which may produce ill effects in the chine drive are incorporated as a multi-objective function to carry out the global minimization trying to find out the optimal design parameters for RJS chain drives. The single-objective optimization trends have also been verified with the previous references.

Design Optimization of Magnetic Coupling Using Genetic Algorithm and 2D FEM Model

2004 ◽  
Author(s):  
Petr Krejci ◽  
Cestmir Ondrusek
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
Permanent Magnets ◽  
Magnetic Coupling ◽  
Optimization Procedure ◽  
Magnetic Characteristics ◽  
Fe Model ◽  
Fem Model ◽  
Additional Advantage ◽  
Torque Transmission

Magnetic couplings (Figure 1) are widely used to torque transmission between two shafts without any mechanical contact. They are especially well suited for used in hazardous environments, to transmit torque through a separation wall. An additional advantage of a magnetic coupling is that slipping occurs when excessive torque is applied, this can be used to prevent mechanical failure due to torque overloads. This paper deals with influence of temperature on behavior of magnetic coupling and magnetic coupling design optimization. The permanent magnets that are used for torque transmission cannot be used close to Currie point, which is a point of loss of magnetic characteristics. We intend to use the magnetic coupling for pump of radioactive liquid materials for transmutation devices, where the temperature is close to four hundred centigrade. Because of we suggest the design changes for elimination of temperature influence. This paper presents the finite element (FE) parametric model of magnetic coupling, experimental verification of FE model and optimization of the inner part of magnetic coupling in order to increase the maximal torque. The genetic algorithm method in connection with FEM model of magnetic coupling was used for the design optimization procedure.

scholarly journals Water distribution network optimization using maximum entropy under multiple loading patterns

2013 ◽  
Vol 13 (5) ◽  
pp. 1265-1271 ◽  
Author(s):  
Anna M. Czajkowska ◽  
Tiku T. Tanyimboh
Keyword(s):  
Design Optimization ◽  
Maximum Entropy ◽  
Water Distribution ◽  
Optimization Procedure ◽  
Water Distribution Network ◽  
Distribution Networks ◽  
Operating Conditions ◽  
Statistical Entropy ◽  
Computationally Efficient ◽  
Nsga Ii

This paper proposes a maximum entropy-based multi-objective genetic algorithm approach for the design optimization of water distribution networks (WDNs). The novelty is that in contrast to previous research involving statistical entropy the algorithm can handle multiple operating conditions. We used NSGA II and EPANET 2 and wrote a subroutine that calculates the entropy value for any given WDN configuration. The proposed algorithm is demonstrated by designing a six-loop network that is well known from previous entropy studies. We used statistical entropy to include reliability in the design optimization procedure in a computationally efficient way.

scholarly journals Optimized Design of a Novel Hydraulic Propeller Turbine for Low Heads

Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 20
Author(s):  
Dario Barsi ◽  
Marina Ubaldi ◽  
Pietro Zunino ◽  
Robert Fink
Keyword(s):  
Design Optimization ◽  
High Efficiency ◽  
Single Point ◽  
Design Procedure ◽  
Optimization Procedure ◽  
Design Parameters ◽  
Geometrical Parameters ◽  
Practical Case ◽  
Optimized Design ◽  
Starting Point

In the present paper, an optimized design procedure capable of providing the geometry of a high efficiency compact hydraulic propeller turbine for low head is proposed and developed. The turbine preliminary design is based on fundamental turbomachinery mean-line equations and on the employment of statistical correlations, which relate the main geometrical parameters to the fundamental design parameters. The first obtained geometry represents the starting point of an automated aerodynamic single point optimization procedure based on a genetic algorithm generating and updating a wide database of turbine geometries. The approach employs a three-dimensional (3D) Reynolds averaged Navier–Stokes (RANS) solver for the construction of the corresponding database of performance. A meta-model, such as an artificial neural network (ANN), is used to speed up the design optimization process. The procedure has been applied on the practical case of a novel simplified hydraulic propeller turbine prototype for very low heads. The adopted design optimization procedure is able to modify the turbine blade and vane geometries in order to achieve automatically the targeted net head and the maximum for the total to total internal efficiency once diameter, mass flow rate, and rotational speed are assigned.

A Novel Design Optimization Method for Obtaining Desired Deformation Behavior in Additively Manufactured Multi-Material Parts

2014 ◽  
Author(s):  
Ranjit Gopi ◽  
Sonjoy Das ◽  
Rahul Rai
Keyword(s):  
Design Optimization ◽  
Cross Sections ◽  
Deformation Behavior ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Full Scale ◽  
Scale Model ◽  
Fe Model ◽  
Computationally Efficient ◽  
Novel Design

This paper introduces a novel design optimization method to optimize models with multiple material layers and complex cross-sections, for desired behavior. The developed optimization procedure utilizes an upscaling approach to approximate a full scale finite element (FE) model, by only analyzing a small material volume element. This approach requires less modeling efforts and is computationally less expensive than the full scale model. The developed method helps in building computationally efficient models for obtaining desired deformation behavior. The efficacy of the proposed method is illustrated through a couple of example design problems.

Design optimization of hopper cars employing functionally graded honeycomb sandwich panels

2021 ◽  
pp. 095440972110496
Author(s):  
Ayman Al-Sukhon ◽  
Mostafa SA ElSayed
Keyword(s):  
Design Optimization ◽  
Sandwich Panels ◽  
Design Procedure ◽  
Functionally Graded ◽  
Sandwich Composite ◽  
Wall Structure ◽  
Concentrate Mass ◽  
Cross Sectional ◽  
Baseline Design ◽  
Honeycomb Sandwich

In this paper, a novel multiscale and multi-stage structural design optimization procedure is developed for the weight minimization of hopper cars. The procedure is tested under various loading conditions according to guidelines established by regulatory bodies, as well as a novel load case that considers fluid-structure interaction by means of explicit finite elements employing Smoothed Particle Hydrodynamics. The first stage in the design procedure involves topology optimization whereby optimal beam locations are determined within the design space of the hopper car wall structure. This is followed by cross-sectional sizing of the frame to concentrate mass in critical regions of the hopper car. In the second stage, hexagonal honeycomb sandwich panels are considered in lower load regions, and are optimized by means of Multiscale Design Optimization (MSDO). The MSDO drew upon the Kreisselmeier–Steinhausser equations to calculate a penalized cost function for the mass and compliance of a hopper car Finite Element Model (FEM) at the mesoscale. For each iteration in the MSDO, the FEM was updated with homogenized sandwich composite properties according to four design variables of interest at the microscale. A cost penalty is summed with the base cost by comparing results of the FEM with the imposed constraints. Efficacy of the novel design methodology is compared according to a baseline design employing conventional materials. By invoking the proposed methodology in a case study, it is demonstrated that a mass savings as high as 16.36% can be yielded for a single hopper car, which translates into a reduction in greenhouse gas emissions of 13.09% per car based on available literature.

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