Effect of Suspension Parameter Uncertainty on the Dynamic Behaviour of Railway Vehicles

2011 ◽  
Vol 104 ◽  
pp. 177-185 ◽  
Author(s):  
Laura Mazzola ◽  
Stefano Bruni
Keyword(s):  
Parameter Uncertainty ◽  
Analytical Form ◽  
Computational Effort ◽  
Railway Vehicle ◽  
Vehicle Design ◽  
Vehicle Suspensions ◽  
Propagation Of Uncertainty ◽  
Vehicle Component ◽  
Component Manufacturing ◽  
And Performance

The paper describes a study carried out by Dipartimento di Meccanica Politecnico di Milano, aimed at investigating how uncertainty in railway vehicle suspension components can be treated in the framework of vehicle design and performance assessment in respect to vehicle dynamics. In railway vehicle suspensions, sources of parameter uncertainty may arise from inaccuracy in the modelling of a vehicle component or from a scatter in the behaviour of nominally identical components, on account of the variability implied by the component manufacturing process. The approach proposed in this paper, completely new to the railway field, is to use statistical methods having different complexity (and entailing a proportional computational effort), to analyse the propagation of uncertainty from the parameters input in the vehicle mathematical model to the results of running dynamics, in terms of the assessment quantities used for verification and evaluation of train performances. The problem is treated by numerical means, being the dependency of simulation outputs from the input parameters typically non-linear, and not defined in an analytical form.

Conceptual comparison of the ecogeography-based algorithm, equilibrium algorithm, marine predators algorithm and slime mold algorithm for optimal product design

2021 ◽  
Vol 63 (4) ◽  
pp. 336-340
Author(s):  
Betül Sultan Yıldız ◽  
Vivek Patel ◽  
Nantiwat Pholdee ◽  
Sadiq M. Sait ◽  
Sujin Bureerat ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Performance Enhancement ◽  
Slime Mold ◽  
Vehicle Design ◽  
Shape Design ◽  
Marine Predators ◽  
Component Design ◽  
Vehicle Component ◽  
Optimal Product Design ◽  
And Performance

Abstract Vehicle component design is crucial for developing a vehicle prototype, as optimum parts can lead to cost reduction and performance enhancement of the vehicle system. The use of metaheuristics for vehicle component optimization has been commonplace due to several advantages: robustness and simplicity. This paper aims to demonstrate the shape design of a vehicle bracket by using a newly invented metaheuristic. The new optimizer is termed the ecogeography-based optimization algorithm (EBO). This is arguably the first vehicle design application of the new optimizer. The optimization problem is posed while EBO is implemented to solve the problem. It is found that the design results obtained from EBO are better when compared to other optimizers such as the equilibrium optimization algorithm, marine predators algorithm, slime mold algorithm.

Simulation and Simulation Software Development of the Braking Process of a Subway Train

2014 ◽  
Vol 556-562 ◽  
pp. 294-301 ◽  
Author(s):  
Long Han ◽  
Chun Tian ◽  
Yan Wang ◽  
Meng Ling Wu ◽  
Zhuo Jun Luo
Keyword(s):  
Computational Effort ◽  
Simulation Software ◽  
System Model ◽  
Brake System ◽  
Railway Vehicle ◽  
Model Parameters ◽  
Modeling Process ◽  
Time Simulation ◽  
Subway Train ◽  
Braking Process

This paper deals with the problem of braking process modeling. A subway train braking process simulation software is built, which composes of a GUI and a underlying model. The underlying model consists of a train model and a brake system model. The train model is simplified and built by assembling subcomponent element models of a railway vehicle. The brake system model is simplified and built based on experimental data in order to reduce computational effort. The GUI of the software can be use to input model parameters, display simulation results, and store simulation data. As a result of the simplifications of the modeling process, the developed software can perform real time simulation.

scholarly journals A Novel Methodology for Hydrocarbon Depth Prediction in Seabed Logging: Gaussian Process-Based Inverse Modeling of Electromagnetic Data

2021 ◽  
Vol 11 (4) ◽  
pp. 1492
Author(s):  
Hanita Daud ◽  
Muhammad Naeim Mohd Aris ◽  
Khairul Arifin Mohd Noh ◽  
Sarat Chandra Dass
Keyword(s):  
Gaussian Process ◽  
Inverse Modeling ◽  
Mean Squared Error ◽  
Computational Effort ◽  
Percentage Error ◽  
Depth Prediction ◽  
Receiver System ◽  
Realistic Representation ◽  
And Performance ◽  
Gp Model

Seabed logging (SBL) is an application of electromagnetic (EM) waves for detecting potential marine hydrocarbon-saturated reservoirs reliant on a source–receiver system. One of the concerns in modeling and inversion of the EM data is associated with the need for realistic representation of complex geo-electrical models. Concurrently, the corresponding algorithms of forward modeling should be robustly efficient with low computational effort for repeated use of the inversion. This work proposes a new inversion methodology which consists of two frameworks, namely Gaussian process (GP), which allows a greater flexibility in modeling a variety of EM responses, and gradient descent (GD) for finding the best minimizer (i.e., hydrocarbon depth). Computer simulation technology (CST), which uses finite element (FE), was exploited to generate prior EM responses for the GP to evaluate EM profiles at “untried” depths. Then, GD was used to minimize the mean squared error (MSE) where GP acts as its forward model. Acquiring EM responses using mesh-based algorithms is a time-consuming task. Thus, this work compared the time taken by the CST and GP in evaluating the EM profiles. For the accuracy and performance, the GP model was compared with EM responses modeled by the FE, and percentage error between the estimate and “untried” computer input was calculated. The results indicate that GP-based inverse modeling can efficiently predict the hydrocarbon depth in the SBL.

Warm forming process for an AA5754 train window panel

2021 ◽  
pp. 1-32
Author(s):  
Antonio Piccininni ◽  
Andrea Lo Franco ◽  
Gianfranco Palumbo
Keyword(s):  
Material Characterization ◽  
Room Temperature ◽  
Warm Forming ◽  
Railway Vehicle ◽  
Fe Model ◽  
Forming Process ◽  
Vehicle Component ◽  
Mechanical Approach ◽  
Thermal Simulations ◽  
Critical Regions

Abstract A warm forming process is designed for AA5754 to overcome low room temperature formability. The solution includes increased working temperature and is demonstrated with a railway vehicle component. A Finite Element (FE) based methodology was adopted to design the process taking into account also the starting condition of the alloy. In fact, the component's dent resistance can be enhanced if the yield point is increased accordingly: the stamping process was thus designed considering the blank in both the H111 (annealed and slightly hardened) and H32 (strain-hardened and stabilized) conditions that were preliminarily characterized. Tensile and formability tests were carried out at different temperature and strain rate levels, thus providing the data to be implemented within the FE model (Abaqus/CAE): the stamping was at first simulated at room temperature to evaluate the blank critical regions. Subsequently, the warm forming process was designed by means of an uncoupled thermo-mechanical approach. Thermal simulations were run to properly design the heating strategy and achieve an optimal temperature distribution over the blank deformation zone (according to the results of the material characterization). Such a distribution was then imported as a boundary condition into the mechanical step (Abaqus/Explicit) to determine the optimal process parameters and obtain a sound component (strain severity was monitored implementing an FLD-based damage criterion). The simulation model was validated experimentally with stamping trials to fabricate a sound component using the optimized heating strategy and punch stroke profile.

scholarly journals A thick-walled sheet moulding compound automotive component: Manufacturing and performance

2020 ◽  
Vol 128 ◽  
pp. 105688 ◽  
Author(s):  
L.M. Martulli ◽  
Thomas Creemers ◽  
Erich Schöberl ◽  
Nicholas Hale ◽  
Martin Kerschbaum ◽  
...  
Keyword(s):  
Automotive Component ◽  
Moulding Compound ◽  
Component Manufacturing ◽  
And Performance ◽  
Sheet Moulding Compound

Loading and Design Parameter Uncertainty in the Dynamics and Performance of High-Speed-Parallel-Helical Stage of a Wind Turbine Gearbox

2013 ◽  
Author(s):  
Fisseha M. Alemayehu ◽  
Stephen Ekwaro-Osire
Keyword(s):  
Wind Turbine ◽  
Parameter Uncertainty ◽  
System Reliability ◽  
Design Parameter ◽  
High Speed ◽  
Probability Of Failure ◽  
Wind Turbine Gearbox ◽  
Input Shaft ◽  
Input Variables ◽  
And Performance

The Wind Turbine Gearboxes (WTGs) are highly subjected to variable torsional and non-torsional loads. In addition, the manufacturing and assembly process of these devices results in uncertainty in the system. These gearboxes are reported to fail in their early life of operation, within three to seven years as opposed to the expected twenty years of operation. Their downtime and maintenance process is the most costly of any failure of subassembly of wind turbines. The objective of this work is to perform a probabilistic multibody dynamic analysis (PMBDA) of the high-speed-parallel-helical stage of the gearbox of wind turbine that considers uncertainty of generator side torque loading and the input shaft speed, assembly errors and design parameter uncertainty. System reliability, probability of failure, and probabilistic sensitivities of all the input variables towards several performance functions have been measured and conclusions have been drawn. PMBDA has demonstrated a new dimension of design and installation of wind turbine gearboxes than traditional deterministic approach. In addition to revealing system reliability or under-performance through probability of failure, the method will also help designers to consider certain variables critically through the sensitivity results.

scholarly journals A Modification Artificial Bee Colony Algorithm for Optimization Problems

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Jun-Hao Liang ◽  
Ching-Hung Lee
Keyword(s):  
Mobile Robot ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Optimization Problems ◽  
Computational Effort ◽  
Function Optimization ◽  
Cooperative Strategy ◽  
Robot System ◽  
Bee Colony ◽  
And Performance

This paper presents a modified artificial bee colony algorithm (MABC) for solving function optimization problems and control of mobile robot system. Several strategies are adopted to enhance the performance and reduce the computational effort of traditional artificial bee colony algorithm, such as elite, solution sharing, instant update, cooperative strategy, and population manager. The elite individuals are selected as onlooker bees for preserving good evolution, and, then, onlooker bees, employed bees, and scout bees are operated. The solution sharing strategy provides a proper direction for searching, and the instant update strategy provides the newest information for other individuals; the cooperative strategy improves the performance for high-dimensional problems. In addition, the population manager is proposed to adjust population size adaptively according to the evolution situation. Finally, simulation results for optimization of test functions and tracking control of mobile robot system are introduced to show the effectiveness and performance of the proposed approach.

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