Mechanism Simulation Based on ADAMS and Structure Optimization for Automobile Punching Parts On-Line Detector

2011 ◽  
Vol 211-212 ◽  
pp. 619-623
Author(s):  
Xi Xin Rao ◽  
Kang He ◽  
He Sheng Liu
Keyword(s):  
Objective Function ◽  
Dynamic Performance ◽  
Mathematic Model ◽  
Design Parameters ◽  
Work Piece ◽  
Simulation And Optimization ◽  
Design Variables ◽  
Simulation Based ◽  
On Line ◽  
Line Detector

Camera Device is crucial components of Automobile punching parts on-line detector and Its dynamic characteristics has a critical influence on the accuracy of Automobile punching parts on-line detector. To reduce the relative acceleration of Camera Device to the measured part, biaxial body of Automobile Punching Parts On-line Detector was optimized. On the basis of analyzing mechanism, simplifying the prototype, determining the design variables and the objective function and the constraint condition, this paper puts forward the parameter optimization mathematic model with the minimum of the acceleration of Camera Device relative to the point on the measured work piece as objective function and completes mechanism simulation and optimization by the ADAMS software. The results show that some design parameters gets more reasonable and dynamic performance of Automobile punching parts on-line detector is better.

The Effect of Different Optimization Methods on Robustness for Robust Optimization Design

2014 ◽  
Vol 721 ◽  
pp. 464-467
Author(s):  
Tao Fu ◽  
Qin Zhong Gong ◽  
Da Zhen Wang
Keyword(s):  
Robust Optimization ◽  
Objective Function ◽  
Robust Design ◽  
Optimization Design ◽  
Optimization Methods ◽  
Optimization Method ◽  
Design Parameters ◽  
Hybrid Particle Swarm Optimization ◽  
Design Variables ◽  
Robust Optimization Design

In view of robustness of objective function and constraints in robust design, the method of maximum variation analysis is adopted to improve the robust design. In this method, firstly, we analyses the effect of uncertain factors in design variables and design parameters on the objective function and constraints, then calculate maximum variations of objective function and constraints. A two-level optimum mathematical model is constructed by adding the maximum variations to the original constraints. Different solving methods are used to solve the model to study the influence to robustness. As a demonstration, we apply our robust optimization method to an engineering example, the design of a machine tool spindle. The results show that, compared with other methods, this method of HPSO(hybrid particle swarm optimization) algorithm is superior on solving efficiency and solving results, and the constraint robustness and the objective robustness completely satisfy the requirement, revealing that excellent solving method can improve robustness.

Shipboard Radar Servo System PID Parameters Turning Based on Simulink

2014 ◽  
Vol 536-537 ◽  
pp. 1121-1124
Author(s):  
Qiu Qi Ding ◽  
Min Tao ◽  
Xin Rong Wang
Keyword(s):  
Pid Control ◽  
Dynamic Performance ◽  
Servo System ◽  
Mathematic Model ◽  
Parameter Tuning ◽  
Fuzzy Pid Control ◽  
Simulation Experiments ◽  
Loop Bandwidth ◽  
Self Tuning ◽  
On Line

This paper expounds the structure and principle of shipboard radar servo system, according to traditional PID parameter tuning problem, the parameter self-tuning fuzzy PID control technology is applied to the servo system position loop, through the simulation experiments show that the method can 't depend on the mathematic model of the system, and according to the relation between input and output of the PID parameters on-line adjustment, automatic adjustment loop bandwidth, increase the system dynamic performance and steady performance, strong robustness and adaptability.

Design of composite helicopter rotor blades to meet given cross-sectional properties

2005 ◽  
Vol 109 (1100) ◽  
pp. 471-475 ◽  
Author(s):  
S. L. Lemanski ◽  
P. M. Weaver ◽  
G. F. J. Hill
Keyword(s):  
Finite Element ◽  
Objective Function ◽  
Helicopter Rotor ◽  
Design Parameters ◽  
Stochastic Methods ◽  
Element Analysis ◽  
Cross Sectional ◽  
Design Variables ◽  
Non Linear ◽  
Optimisation Methods

Abstract This paper examines the design of a composite helicopter rotor blade to meet given cross-sectional properties. As with many real-world problems, the choice of objective and design variables can lead to a problem with a non-linear and/or non-convex objective function, which would require the use of stochastic optimisation methods to find an optimum. Since the objective function is evaluated from the results of a finite element analysis of the cross section, the computational expense of using stochastic methods would be prohibitive. It is shown that by choosing appropriate simplified design variables, the problem becomes convex with respect to those design variables. This allows deterministic optimisation methods to be used, which is considerably more computationally efficient than stochastic methods. It is also shown that the design variables can be chosen such that the response of each individual cross-sectional property can be closely modelled by a linear approximation, even though the response of a single objective function to many design parameters is non-linear. The design problem may therefore be reformulated into a number of simultaneous linear equations that are easily solved by matrix methods, thus allowing an optimum to be located with the minimum number of computationally expensive finite element analyses.

Improving Emission and Blow-Out Characteristics of Novel Natural Gas Low NOx Burners for Heavy Duty Gas Turbine

2019 ◽  
Author(s):  
Matteo Cerutti ◽  
Michele Roma ◽  
Alessio Picchi ◽  
Riccardo Becchi ◽  
Bruno Facchini
Keyword(s):  
Objective Function ◽  
Gas Turbine ◽  
Mathematical Formulation ◽  
Flame Stabilization ◽  
Operating Conditions ◽  
Design Parameters ◽  
Design Variables ◽  
Geometrical Features ◽  
Heavy Duty Gas Turbine ◽  
Operating Window

Abstract The development and the optimization of a novel dry low NOx burner may require several steps of improvement. The first step of the overall development process has been documented by authors in a previous paper and included an exhaustive experimental characterization of a set of novel geometries. The in-depth results analysis allowed to correlate the investigated design parameters to burner performances, discovering possible two-fold optimization paths. Recurrent verifications of the assumptions made to define prototypes design are considered a mandatory step to avoid significant deviation from the correct optimization path, which strongly depends on both objective function definition and selection of design variables. Concerning the objective function, a proper mathematical formulation was proposed in the previous work, which represented a balance between two apparently conflicting aspect like flame stability and low emissions. Concerning design variables, outcomes of the first test campaign have been used in the present work to define new burner geometries. Starting from a new baseline who has showed the widest low NOx operating window, additional geometrical features have been considered in this survey as potentially affecting flame stabilization. Thanks to the degree of freedom offered by DMLM technology, rapid prototyping of alternative geometries allowed to easily setup a new experimental plan for the second optimization step. Exploiting the same approach used in the first test campaign, new geometries have been tested in a single-cup test rig at gas turbine relevant operating conditions, showing Stable low-NOx operating windows have been evaluated throughout dedicated objective functions for all geometries and results showed lower NOx and CO emissions as a consequence of the newly introduced geometrical modifications. Moreover, the comparison with the estimates of the previous campaign proved the existence of the identified optimization path. Indeed, it furnished valid elements for further using of the proposed methodology for the improvement of emission and blow-out characteristics of novel burners and, more in general, for the development of a novel dry low NOx technology.

A Multi-Variable Approach to Determine the “Best” Gear Design

2000 ◽  
Author(s):  
Donald R. Houser ◽  
Jonny Harianto ◽  
B. Chandrasekaran ◽  
John Josephson ◽  
Naresh Iyer
Keyword(s):  
Objective Function ◽  
Optimization Techniques ◽  
Response Variable ◽  
Gear Design ◽  
Variable Approach ◽  
Design Variables ◽  
Simulation Based ◽  
To Come ◽  
Selection Of ◽  
Response Variables

Abstract Gear design requires the designer to compromise many design variables in order to determine the best performance of a gear set. Unfortunately the designer has a multiplicity of goals including keeping both bending and pitting stresses under an allowable value, minimizing scoring, achieving minimum efficiency and trying to minimize noise. This latter response variable is rarely considered in the initial gear design. In this work, noise is considered to be one of the more important design considerations. One approach to multi-variable gear design that has been tried is design optimization. Usually optimization techniques are limited in the number of variables that can be handled and with so many response variables, it is difficult to come up with an objective function that reflects the considerations of a real gear designer. In this paper we present a simulation-based approach to gear design that allows the designer to essentially “run all of the cases”. The simulation accounts for the true load distribution of the gears when computing response variables. Also, such factors as manufacturing tolerances may be included in the simulation so that truly robust designs may be obtained. Rather than using an objective function approach, designs are analyzed with a dominance filter that assesses each response variable in a manner that results in the “best” design. After these “best” designs are found, an interactive viewer allows the selection of those designs that best meet the designer’s goals with regard to all design variables. Several examples are presented in this paper. In each case, over 65,000 designs are evaluated and the dominance filter results in from 200 to 900 successful designs, depending on the tolerances that are applied. After sorting with the viewer the designer usually ends up with from 5 to 20 designs whose features may vary significantly, but have similar performances.

Single Spur Gear Reducer Optimization Design Mathematical Modeling

2013 ◽  
Vol 273 ◽  
pp. 198-202
Author(s):  
Yu Xia Wang
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Optimal Design ◽  
Objective Function ◽  
Optimization Design ◽  
Spur Gear ◽  
Design Parameters ◽  
Constraint Function ◽  
Design Variables ◽  
The Mathematical Model

In a given power P, number of teeth than u, input speed and other technical conditions and requirements, find out a set of used a economic and technical indexes reach the optimal design parameters, realize the optimization design of the reducer, This paper determined unipolar standard spur gear reducer design optimization of the design variables, and then determine the objective function, determining constraint function, so as to establish the mathematical model.

Optimization of a Micro Gas Turbine Using Genetic Algorithm

2011 ◽  
Author(s):  
Maryam Pourhasanzadeh ◽  
Sajjad Bigham
Keyword(s):  
Genetic Algorithm ◽  
Combustion Chamber ◽  
Objective Function ◽  
Gas Turbine ◽  
Distributed Generation ◽  
Gas Turbines ◽  
Design Parameters ◽  
Micro Gas Turbine ◽  
Design Variables ◽  
Isentropic Efficiency

Distributed generation is an attractive way of producing energy, minimizing transport losses and enhancing energy efficiency. Micro gas turbines in distributed generation systems add other advantages such as low emissions and fuel flexibility. In the present work, a 100 kW micro gas turbine is considered. The optimization procedure is done by Genetic Algorithm method which is a new method in optimizing problems. The plant is comprised of an air compressor, recuperator, combustion chamber and gas turbine. The design Parameters of the plant, were chosen as: compressor pressure ratio, compressor isentropic efficiency, gas turbine isentropic efficiency, combustion chamber inlet temperature and the temperature of the combustion gas at the gas turbine inlet. In order to find the design parameters optimally, a thermo-economic approach has been followed. An objective function, representing the total cost of the plant in terms of dollar per second, was defined as the sum of the operating cost, related to the fuel consumption, the capital investment which stands for equipment purchase and maintenance cost. Subsequently, different parts of the objective function have been expressed in terms of design variables. Finally, the optimal values of design variables were obtained by minimizing the objective function using Genetic Algorithm code that is developed in Matlab software programming.

Simulation Model and Analysis of a Small Solar-Assisted Refrigeration System: Dynamic Simulation and Optimization

2008 ◽  
Author(s):  
F. Calise ◽  
M. Dentice d’Accadia ◽  
A. Palombo ◽  
L. Vanoli
Keyword(s):  
Simulation Model ◽  
Control Strategies ◽  
Point Of View ◽  
Design Parameters ◽  
Total System ◽  
Variable Speed ◽  
Simulation And Optimization ◽  
Design Variables ◽  
Hysteresis Controller ◽  
Energetic Point

In this paper, a complete zero-dimensional transient simulation model of a solar-assisted refrigeration plant is presented. In addition, a case study is discussed, aiming at determining the optimal configuration of the system, from the energetic point of view, in a specific application. The system under analysis consisted of several components: evacuated solar collectors, circulation pumps, variable speed pump, water storage tanks, auxiliary heater, single-stage H2O-LiBr absorption chiller, cooling tower, feedback controller, on/off hysteresis controller, single lumped capacitance building and controllers. The simulation was performed using the TRNSYS environment which is provided by a large component library. This software also includes a detailed database with weather parameters for several European cities. The system and the building were simulated using TRNSYS built in models. The system was simulated using specially designed control strategies and varying the main design variables. In particular, a variable speed pump on the solar collector was implemented in order to maximize the tank temperature and minimizing the heat losses. Finally a sensitivity analysis was also performed in order to calculate the set of synthesis/design parameters that maximize the total system efficiency.

A New Approach to Solving Reliability Optimization Design of Gear Box

2011 ◽  
Vol 295-297 ◽  
pp. 1326-1329
Author(s):  
Wen Hui Mo
Keyword(s):  
Objective Function ◽  
Material Properties ◽  
Optimization Design ◽  
Random Variables ◽  
Design Parameters ◽  
Reliability Optimization ◽  
New Approach ◽  
Reliability Calculation ◽  
Design Variables ◽  
Gear Box

Reliability optimization design of the gear box is proposed. It includes an objective function, 30 design variables and 52 constraints. It is important to note that material properties, geometry parameters and applied loads of the structure are assumed to be normal random variables. Reliability calculation adopts the HL-RF method. The comparison of design parameters demonstrates the proposed method.

Pretension Optimization Method for Complex Cablenet System

2014 ◽  
Vol 574 ◽  
pp. 143-146
Author(s):  
Guo Qiang You ◽  
Ying Bai Xie
Keyword(s):  
Objective Function ◽  
Axial Symmetry ◽  
Mathematic Model ◽  
Optimization Method ◽  
Gradient Algorithm ◽  
Matrix Analysis ◽  
Analysis Method ◽  
Design Variables ◽  
Reduced Gradient ◽  
Generalized Reduced Gradient

Based on balance matrix analysis method and considered the evenness of pretension distribution as objective function, a pretension optimization method is proposed for complex cablenet system of large span structure. In this method, the whole cablenet system is firstly divided into several groups according to its axial symmetry to simplify its balance matrix, and then balance matrix analysis method is used to analyze balance matrix of grouped cablenet system. Next, the corresponding optimum mathematic model for grouped cablenet system can be established with pretension solutions coefficients as design variables and evenness of pretension distribution as objective function. Finally, generalized reduced gradient algorithm is used to solve the optimum mathematic model of an example, and the result is satisfactory.

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