Genetic Algorithm for Optimizing the Gust Loads for Predicting Aircraft Loads and Dynamic Response

2001 ◽  
pp. 241-267 ◽  
Author(s):  
R. Mehrotra ◽  
C. L. Karr ◽  
T. A. Zeiler
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Gust Loads ◽  
Aircraft Loads

Multiobjective Optimization of a Railway Vehicle Dampers Using Genetic Algorithm

2013 ◽  
Author(s):  
Seyed Milad Mousavi Bideleh ◽  
Viktor Berbyuk
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Dynamic Response ◽  
Ride Comfort ◽  
Lateral Displacement ◽  
Contact Forces ◽  
Design Parameters ◽  
Railway Vehicle ◽  
Level Shift ◽  
Vehicle Speed

Ride comfort, safety, wear and vehicle speed are the most important factors in evaluating the efficiency of railway transportation. In order to decrease the track access charges it is often desirable to run the vehicle at maximum allowed speed, while keeping an admissible amount of wear in system. This usually deteriorates the ride comfort and safety level during the operation. Therefore, an optimization problem to find a tradeoff value for vehicle speed and design parameters is inevitable. Since, ride comfort, safety and wear values are sensitive to primary and secondary suspensions’ damping parameters it is desirable to find the optimum values of such design variables. In this regard, the multiobjective optimization of railway vehicle dampers is considered to increase the cost-efficiency of railway operation. One car vehicle model with 26 degrees of freedom (DOF) along with a set of initial states, design parameters and operational conditions is explored here. All bodies are assumed to be rigid. Vehicle carbody and bogie frames supposed to have the full set of DOF in space. While, only lateral and yaw motions are considered for each wheelset. It is also assumed that wheelset roll angle is a function of the lateral displacement. Primary and secondary suspensions compromised of parallel linear springs and dampers in longitudinal, vertical and lateral directions which connect wheelsets to bogie frames, and bogie frames to carbody, respectively. Lagrange formalism is employed to obtain the system’s equations of motion. The nonlinear heuristic theory is chosen to relate creepages and the corresponding creep contact forces. The dynamic response of the system is obtained for different operational scenarios including ideal and imperfect tangent and curved tracks. Series-based functions are chosen to approximate the harmonic lateral track irregularities. Accelerations at carbody level, shift forces and wear number are used to evaluate the ride comfort, safety and wear, respectively. MATLAB genetic algorithm optimization routine is applied to perform the optimization. The Pareto sets and Pareto fronts obtained from this study provide the vectors of optimal design parameters corresponding to maximum admissible vehicle speed and guarantee the best tradeoff values for safety and comfort with threshold on wear for each operational scenario. Analysis of the obtained results gives insight into multiobjective optimized dynamic response of a railway vehicle and useful hints for designing adaptive bogie systems with the possibility to switch between optimal damping parameters value and provide the best operational efficiency.

Dynamic Response Surface Method Combined with Genetic Algorithm to Optimize Extraction Process Problem

2021 ◽  
pp. 3-14
Author(s):  
Laires A. Lima ◽  
Ana I. Pereira ◽  
Clara B. Vaz ◽  
Olga Ferreira ◽  
Márcio Carocho ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Response Surface ◽  
Response Surface Method ◽  
Extraction Process ◽  
Surface Method

Lift generation with optimal elastic pitching for a flapping plate

2013 ◽  
Vol 717 ◽  
Author(s):  
Diing-wen Peng ◽  
Michele Milano
Keyword(s):  
Genetic Algorithm ◽  
Particle Image Velocimetry ◽  
Dynamic Response ◽  
Rectangular Plate ◽  
Particle Image ◽  
Digital Particle Image Velocimetry ◽  
Driving Frequency ◽  
Stroke Length ◽  
Rotational Spring ◽  
Image Velocimetry

AbstractThe lift-generating capabilities of a translating and passively pitching rectangular plate are assessed experimentally. The plate pitch dynamics are generated by a rotational spring, and a genetic algorithm isolates a set of spring parameters maximizing the average lift. Our experiments identified a range of parameters that produce kinematic trajectories associated with optimal lift production. The stroke length and the dynamic response of the spring at the driving frequency are revealed to play crucial roles in the generation of such trajectories. Measurements taken with digital particle image velocimetry are used to analyse the results.

scholarly journals Connection Damage Detection of Double Beam System under Moving Load with Genetic Algorithm

Mechanika ◽  
2021 ◽  
Vol 27 (1) ◽  
pp. 80-87
Author(s):  
Hougui ZHANG ◽  
Ruixiang SONG ◽  
Jie YANG ◽  
Dan WU ◽  
Yingjie WANG
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Damage Detection ◽  
Moving Load ◽  
Acceleration Response ◽  
Damage Pattern ◽  
Load Model ◽  
Beam System ◽  
Detection Approach ◽  
Double Beam

In this paper, a novel damage detection approach for the spring connection of the double beam system using the dynamic response of the beam and genetic algorithm is presented. The double beam system is regarded as both Bernoulli-Euler beams with simply supported ends, the upper and lower beams are connected by a series of linear springs with certain intervals. With the genetic algorithm, the dynamic acceleration response of double beam system under moving load, which can be solved by the Newmark-β integration procedure, is used as the input data to detect the connection damage. Thus the dynamic response of the double beam system with a certain damage pattern can be calculated employing the moving load model. If the calculated result is quite close to the recorded response of the damaged bridge, this damage pattern will be the solution. The connection damage detection process of the proposed approach is presented herein, and its feasibility is studied from the numerical investigation with simple and multiple damages detection. It is concluded that the sophisticated damage conditions need much longer time to detect successfully.

Dynamic response of a front end accessory drive system and parameter optimization for vibration reduction via a genetic algorithm

2016 ◽  
Vol 24 (11) ◽  
pp. 2201-2220 ◽  
Author(s):  
Hao Zhu ◽  
Yumei Hu ◽  
WD Zhu
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Flexural Rigidity ◽  
Optimization Method ◽  
Drive System ◽  
Dynamic Responses ◽  
Response Analysis ◽  
Front End ◽  
Space Technique ◽  
External Forces

A typical engine front end accessory drive system (FEADS) is mathematically modeled through Hamilton’s principle and Newton’s second law. In this model, the belt’s flexural rigidity and pulley’s eccentricity are considered. Eccentricities of the pulleys are introduced into governing motion equations of the belt spans through the boundary conditions and then transformed to external forces acting on the belt spans. Vibration modes and natural frequencies of the FEADS are calculated by the state-space technique of the complex mode theory. Dynamic responses of the FEADS at different rotational rates of the crankshaft are calculated by solving the spatially discretized governing equations obtained by Galerkin method. The modeling and solution methods are formulated and programmed in a general purposed code. The study shows that the typical resonance and beat phenomenon happen in a certain portion of the belt spans at a certain rotational rate by the excitations of the pulley’s eccentricity. According to the modal analysis and dynamic response analysis, an optimization method based on a genetic algorithm is proposed. By comparing the vibration amplitudes of belt spans before and after optimization at different rotational rates, this optimization method is verified to be effective in reducing transverse vibrations of the belt spans.

Structural Physical Parameter Identification Based on Empirical Genetic-Simplex Algorithm and Structural Dynamic Response

2011 ◽  
Vol 94-96 ◽  
pp. 1998-2004
Author(s):  
Li Ping Jiang ◽  
Wei Liu ◽  
Lei Shi ◽  
Yan Liu
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Response ◽  
Parameter Identification ◽  
Physical Parameter ◽  
Degrees Of Freedom ◽  
Simplex Algorithm ◽  
Physical Parameters ◽  
Running Speed ◽  
Structural Dynamic ◽  
Calculation Step

In the complex conversion analysis of multi-degrees of freedom，large calculation count needed in each calculation step of Genetic Algorithm limits the running speed of genetic algorithm. So the positive calculation count to be reduced is an effective method to enlarge the range of GA’s application. Empirical Genetic-Simplex Algorithm (EGSA) proposed in this paper is one of the effective methods to solve the problem. This method is applied to structural physical parameters identification based on the structural dynamic response. The result shows that EGSA has many advantages on precision, efficiency in searching, strong to resist the noise, and good adaptation to the incomplete information.

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