Simultaneous Multi-Objective Optimal Sizing of Energy Dissipative Steel Cushions for Transversal Loading

2021 ◽  
Author(s):  
Ahmet Güllü ◽  
Seda Göktepe Körpeoğlu
Keyword(s):  
Structural Engineering ◽  
Mathematical Problem ◽  
Seismic Energy ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Element Analysis ◽  
Optimal Sizing ◽  
Displacement Capacity ◽  
Constraint Method

Current practice in structural engineering requires dissipating some part of seismic energy by sacrificial elements rather than structural members and/or joints. As an easy-to-produce and plug-and-play damper with stable hysteretic loops and large displacement capacity, steel cushion (SC) is a significant device to improve the seismic performance of the structures. It was stated in the previous studies that SC is less effective in the transversal direction. Hence, the efficiency of the damper is improved by optimal sizing through intelligent optimization techniques in this study. The complex optimization problem could be converted to a relatively simple mathematical problem since closed-form equations of the damper are exist in the literature. The optimal sizing problem was solved using two distinct methods namely the [Formula: see text]-constraint method and the elitist non-dominated sorting genetic algorithm (NSGA-II). The employed optimization methods were verified by each other as almost similar geometric ratios were obtained. The efficiency of the optimization is evaluated through finite element analysis (FEA). It is shown that the optimally sized SC is superior in terms of energy dissipation.

Estimation of Thermal Boundary Conditions by Gradient Based and Genetic Algorythms

2012 ◽  
Vol 729 ◽  
pp. 144-149 ◽  
Author(s):  
Imre Felde
Keyword(s):  
Heat Transfer ◽  
Boundary Conditions ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Thermal Boundary Conditions ◽  
Treatment Processes ◽  
Gradient Based ◽  
Type Boundary

The prediction of third type boundary conditions occurring during heat treatment processes is an essential requirement for characterization of heat transfer phenomena. In this work, the performance of four optimization techniques is studied. These models are the Conjugate Gradient Method, the Levenberg-Marquardt Method, the Simplex method and the NSGA II algorithm. The models are used to estimate the heat transfer coefficient during transient heat transfer. The performance of the optimization methods is demonstrated using numerical techniques.

Estimation of Thermal Boundary Conditions by Using Hybrid Inverse Approach

2015 ◽  
Vol 812 ◽  
pp. 419-424
Author(s):  
Imre Felde
Keyword(s):  
Heat Transfer ◽  
Boundary Conditions ◽  
Hybrid Approach ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Nsga Ii ◽  
Inverse Approach ◽  
Marquardt Method ◽  
Thermal Boundary Conditions ◽  
Levenberg Marquardt

The estimation of thermal boundary conditions occurring during heat treatment processes is an essential requirement for characterization of heat transfer phenomena. In this work, the performance of five optimization techniques is studied. These models are the Conjugate Gradient Method, the Levenberg-Marquardt Method, the Simplex method, the NSGA II algorithm and a hybrid approach based on the NSGA II and Levenberg-Marquardt Method sequence. The models are used to estimate the heat transfer coefficient in 2D axis symmetrical case during transient heat transfer. The performance of the optimization methods is demonstrated using numerical experiments.

Application of Computational Mechanics to Tire Design—Yesterday, Today, and Tomorrow

2011 ◽  
Vol 39 (4) ◽  
pp. 223-244 ◽  
Author(s):  
Y. Nakajima
Keyword(s):  
Finite Element ◽  
New Technologies ◽  
Computational Mechanics ◽  
Design Procedure ◽  
Side Wall ◽  
Rolling Resistance ◽  
Optimization Techniques ◽  
Stress Strain ◽  
Element Analysis ◽  
Crown Shape

Abstract The tire technology related with the computational mechanics is reviewed from the standpoint of yesterday, today, and tomorrow. Yesterday: A finite element method was developed in the 1950s as a tool of computational mechanics. In the tire manufacturers, finite element analysis (FEA) was started applying to a tire analysis in the beginning of 1970s and this was much earlier than the vehicle industry, electric industry, and others. The main reason was that construction and configurations of a tire were so complicated that analytical approach could not solve many problems related with tire mechanics. Since commercial software was not so popular in 1970s, in-house axisymmetric codes were developed for three kinds of application such as stress/strain, heat conduction, and modal analysis. Since FEA could make the stress/strain visible in a tire, the application area was mainly tire durability. Today: combining FEA with optimization techniques, the tire design procedure is drastically changed in side wall shape, tire crown shape, pitch variation, tire pattern, etc. So the computational mechanics becomes an indispensable tool for tire industry. Furthermore, an insight to improve tire performance is obtained from the optimized solution and the new technologies were created from the insight. Then, FEA is applied to various areas such as hydroplaning and snow traction based on the formulation of fluid–tire interaction. Since the computational mechanics enables us to see what we could not see, new tire patterns were developed by seeing the streamline in tire contact area and shear stress in snow in traction.Tomorrow: The computational mechanics will be applied in multidisciplinary areas and nano-scale areas to create new technologies. The environmental subjects will be more important such as rolling resistance, noise and wear.

Experimental Research and Finite Element Analysis on Behavior of Steel Frame with Semi-Rigid Connections

2010 ◽  
Vol 168-170 ◽  
pp. 553-558
Author(s):  
Feng Xia Li ◽  
Bu Xin
Keyword(s):  
Architectural Design ◽  
Plastic Hinge ◽  
Steel Frames ◽  
Seismic Energy ◽  
Internal Force ◽  
Steel Frame ◽  
Frame Structure ◽  
Element Analysis ◽  
Rigid Deformation ◽  
Steel Frame Structure

Most steel beam-column connections actually show semi-rigid deformation behavior that can contribute substantially to overall displacements of the structure and to the distribution of member forces. Steel frame structure with semi-rigid connections are becoming more and more popular due to their many advantages such as the better satisfaction with the flexible architectural design, low inclusive cost and environmental protect as well. So it is very necessary that studying the behavior of those steel frame under cyclic reversal loading. On the basics of connections experiments the experiment research on the lateral resistance system of steel frame structure has been completed. Two one-second scale, one-bay, two-story steel frames with semi-rigid connections under cyclic reversal loading. The seismic behavior of the steel frames with semi-rigid connections, including the failure pattern, occurrence order of plastic hinge, hysteretic property and energy dissipation, etc, was investigated in this paper. Some conclusions were obtained that by employing top-mounted and two web angles connections, the higher distortion occurred in the frames, and the internal force distributing of beams and columns was changed, and the ductility and the absorbs seismic energy capability of steel frames can be improved effectively.

scholarly journals Multiobjective Optimization Methods for Congestion Management in Deregulated Power Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
K. Vijayakumar
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Electricity Market ◽  
Optimization Methods ◽  
Evolutionary Programming ◽  
Congestion Management ◽  
Transmission Congestion ◽  
Nsga Ii ◽  
Line Overload ◽  
Nondominated Sorting

Congestion management is one of the important functions performed by system operator in deregulated electricity market to ensure secure operation of transmission system. This paper proposes two effective methods for transmission congestion alleviation in deregulated power system. Congestion or overload in transmission networks is alleviated by rescheduling of generators and/or load shedding. The two objectives conflicting in nature (1) transmission line over load and (2) congestion cost are optimized in this paper. The multiobjective fuzzy evolutionary programming (FEP) and nondominated sorting genetic algorithm II methods are used to solve this problem. FEP uses the combined advantages of fuzzy and evolutionary programming (EP) techniques and gives better unique solution satisfying both objectives, whereas nondominated sorting genetic algorithm (NSGA) II gives a set of Pareto-optimal solutions. The methods propose an efficient and reliable algorithm for line overload alleviation due to critical line outages in a deregulated power markets. The quality and usefulness of the algorithm is tested on IEEE 30 bus system.

scholarly journals Multi-Objective Optimization of Switched Reluctance Machine Design Using Jaya Algorithm (MO-Jaya)

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1107
Author(s):  
Mohamed Afifi ◽  
Hegazy Rezk ◽  
Mohamed Ibrahim ◽  
Mohamed El-Nemr
Keyword(s):  
Optimization Techniques ◽  
Design Parameters ◽  
Jaya Algorithm ◽  
Switched Reluctance Machine ◽  
Nsga Ii ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Reluctance Machine ◽  
Linear Relationships ◽  
Forward Equations

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions.

Static and Dynamic Crush Testing and Analysis of a Rail Vehicle Corner Structural Element

1999 ◽  
Author(s):  
Ronald A. Mayville ◽  
Randolph P. Hammond ◽  
Kent N. Johnson
Keyword(s):  
Structural Engineering ◽  
Current Strength ◽  
Test Element ◽  
Structural Element ◽  
Element Analysis ◽  
Explicit Finite Element ◽  
Rail Vehicle ◽  
Explicit Finite Element Analysis ◽  
Deformation And Fracture ◽  
Baseline State

Abstract This paper presents the results of an experimental study to establish the strength and energy absorption capability of cab car rail vehicle corner structures built to current strength requirements and for structures modified to carry higher loads and absorb more energy. We reviewed current structures and designed an end beam test element — the most common way of meeting current requirements — whose strength in the baseline state was at least 150,000 lbf. This design was then modified to provide a strength of over 400,000 lbf. The designs, which included consideration of the deformation and fracture response under impact loading, were carried out using conventional structural engineering methods and explicit finite element analysis.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

Design Optimization Method for MR-Brake Actuators

2011 ◽  
Author(s):  
Ozan G. Erol ◽  
Hakan Gurocak ◽  
Berk Gonenc
Keyword(s):  
Optimal Solution ◽  
Volume Ratio ◽  
Optimization Methods ◽  
Search Space ◽  
Optimization Method ◽  
Friction Torque ◽  
Element Analysis ◽  
Taguchi Design Of Experiments ◽  
Variable Friction ◽  
Electronically Controllable

MR-brakes work by varying viscosity of a magnetorheological (MR) fluid inside the brake. This electronically controllable viscosity leads to variable friction torque generated by the actuator. A properly designed MR-brake can have a high torque-to-volume ratio which is quite desirable for an actuator. However, designing an MR-brake is a complex process as there are many parameters involved in the design which can affect the size and torque output significantly. The contribution of this study is a new design approach that combines the Taguchi design of experiments method with parameterized finite element analysis for optimization. Unlike the typical multivariate optimization methods, this approach can identify the dominant parameters of the design and allows the designer to only explore their interactions during the optimization process. This unique feature reduces the size of the search space and the time it takes to find an optimal solution. It normally takes about a week to design an MR-brake manually. Our interactive method allows the designer to finish the design in about two minutes. In this paper, we first present the details of the MR-brake design problem. This is followed by the details of our new approach. Next, we show how to design an MR-brake using this method. Prototype of a new brake was fabricated. Results of experiments with the prototype brake are very encouraging and are in close agreement with the theoretical performance predictions.

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