Vibration Control of the Rail Grinding Vehicle with Abrasive Belt Based on Structural Optimization and Lightweight Design

As a new grinding and maintenance technology,rail belt grinding shows significant advantages in many applications The dynamic characteristics of the rail belt grinding vehicle largely determines its grinding performance and service life.In order to explore the vibration control method of the rail grinding vehicle with abrasive belt,the vibration response changes in structural optimization and lightweight design are respectively analyzed through transient response and random vibration simulations in this paper.Firstly,the transient response simulation analysis of the rail grinding vehicle with abrasive belt is carried out under operating conditions and non-operating conditions.Secondly,the vibration control of the grinding vehicle is implemented by setting vibration isolation elements,optimizing the structure,and increasing damping.Thirdly,in order to further explore the dynamic characteristics of the rail grinding vehicle,the random vibration simulation analysis of the grinding vehicle is carried out under the condition of the horizontal irregularity of the American AAR6 track.Finally,by replacing the Q235 steel frame material with 7075 aluminum alloy and LA43M magnesium alloy,both vibration control and lightweight design can be achieved simultaneously.The results of transient dynamic response analysis show that the acceleration of most positions in the two working conditions exceeds the standard value in GB/T 17426-1998 standard.By optimizing the structure of the grinding vehicle in three ways,the average vibration acceleration of the whole car is reduced by about 55.1%from 15.6 m/s^(2) to 7.0 m/s^(2).The results of random vibration analysis show that the grinding vehicle with Q235 steel frame does not meet the safety conditions of 3σ.By changing frame material,the maximum vibration stress of the vehicle can be reduced from 240.7 MPa to 160.0 MPa and the weight of the grinding vehicle is reduced by about 21.7%from 1500 kg to 1175 kg.The modal analysis results indicate that the vibration control of the grinding vehicle can be realized by optimizing the structure and replacing the materials with lower stiffness under the premise of ensuring the overall strength.The study provides the basis for the development of lightweight,diversified and efficient rail grinding equipment.

A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem

Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.

A Smooth Bidirectional Evolutionary Structural Optimization of Vibrational Structures for Natural Frequency and Dynamic Compliance

A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique.

Fluid-Dynamics Analysis and Structural Optimization of a 300 kW MicroGas Turbine Recuperator

Computational Fluid Dynamics(CFD)is used here to reduce pressure loss and improve heat exchange efficiency in the recuperator associated with a gas turbine.First,numerical simulations of the high-temperature and lowtemperature channels are performed and,the calculated results are compared with experimental data(to verify the reliability of the numerical method).Second,the flow field structure of the low-temperature side channel is critically analyzed,leading to the conclusion that the flow velocity distribution in the low-temperature side channel is uneven,and its resistance is significantly higher than that in the high-temperature side.Therefore,five alternate structural schemes are proposed for the optimization of the low-temperature side.In particular,to reduce the flow velocity in the upper channel,the rib length of each channel at the inlet of the low-temperature side region is adjusted.The performances of the 5 schemes are compared,leading to the identification of the configuration able to guarantee a uniform flow rate and minimize the pressure drop.Finally,the heat transfer performance of the optimized recuperator structure is evaluated,and it is shown that the effectiveness of the recuperator is increased by 1.5%.

A strategy for lightweight designing of a railway vehicle car body including composite material and dynamic structural optimization

Rolling stock manufacturers are finding structural solutions to reduce power required by the vehicles,and the lightweight design of the car body represents a possible solution.Optimization processes and innovative materials can be combined in order to achieve this goal.In this framework,we propose the redesign and optimization process of the car body roof for a light rail vehicle,introducing a sandwich structure.Bonded joint was used as a fastening system.The project was carried out on a single car of a modern tram platform.This preliminary numerical work was developed in two main steps:redesign of the car body structure and optimization of the innovated system.Objective of the process was the mass reduction of the whole metallic structure,while the constraint condition was imposed on the first frequency of vibration of the system.The effect of introducing a sandwich panel within the roof assembly was evaluated,focusing on the mechanical and dynamic performances of the whole car body.A mass saving of 63%on the optimized components was achieved,corresponding to a 7.6%if compared to the complete car body shell.In addition,a positive increasing of 17.7%on the first frequency of vibration was observed.Encouraging results have been achieved in terms of weight reduction and mechanical behaviour of the innovated car body.

APPROXIMATION TECHNIQUES FOR APPLICATION OF GENETIC ALGORITHMS TO STRUCTURAL OPTIMIZATION

Although the genetic algorithm (GA) has very powerful robustness and fitness, it needs a large size of population and a large number of iterations to reach the optimum result. Especially when GA is used in complex structural optimization problems, if the structural reanalysis technique is not adopted, the more the number of finite element analysis (FEA) is, the more the consuming time is. In the conventional structural optimization the number of FEA can be reduced by the structural reanalysis technique based on the approximation techniques and sensitivity analysis. With these techniques, this paper provides a new approximation model-segment approximation model, adopted for the GA application. This segment approximation model can decrease the number of FEA and increase the convergence rate of GA. So it can apparently decrease the computation time of GA. Two examples demonstrate the availability of the new segment approximation model.

Composite Structural Optimization by Genetic Algorithm and Neural Network Response Surface Modeling

Neural-Network Response Surfaces （NNRS） is applied to replace the actual expensive finite element analysis during the composite structural optimization process. The Orthotropic Experiment Method （OEM） is used to select the most appropriate design samples for network training. The trained response surfaces can either be objective function or constraint conditions. Together with other conven- tional constraints, an optimization model is then set up and can be solved by Genetic Algorithm （GA）. This allows the separation between design analysis modeling and optimization searching. Through an example of a hat-stiffened composite plate design, the weight response surface is constructed to be objective function, and strength and buckling response surfaces as constraints; and all of them are trained through NASTRAN finite element analysis. The results of optimization study illustrate that the cycles of structural analysis ean be remarkably reduced or even eliminated during the optimization, thus greatly raising the efficiency of optimization process. It also observed that NNRS approximation can achieve equal or even better accuracy than conventional functional response surfaces.

New Knowledge-based Genetic Algorithm for Excavator Boom Structural Optimization

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the conflgurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, arc taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Dynamic Analysis and Structural Optimization of a Novel Palletizing Robot

A novel palletizing robot is presented and developed.By using the Newton-Euler method and the principle that the instantaneous inertial force system could be transformed into a static system,the force equilibrium equations of the whole robot and its subsystem were derived and the robot＇s dynamic models were established.After that,an example simulation was performed by using Matlab software and the structural optimization of the robot＇s key parts were discussed and analyzed in ANSYS platform.The results show that the dynamic models are correct and can be helpful for the design,validation and kinetic control based on dynamics of this kind of palletizing robots.

Book Review “William R. Spillers and Keith M. MacBain. Structural Optimization,Springer Dordrecht Heidelberg London New York,2009”

This book presents general theories and applications of structural optimization methods. The first chapter of the book introduces various basic concepts of structural optimization through several illustrative examples. Chapter 2 is devoted to a comprehensive review of math- ematical programming methods, including classical methods such as the simplex method, the （SLP） method, the interior point method and relatively new approaches such as genetic algo- rithms. The third chapter presents the main topic of this book, the SLP methods based on the incremental equations of structures. Some useful techniques in implementation of SLP, including the move limit, scaling and active constraint identifying, are discussed. In chapter 4, classical optimality criterion approaches, including the fully stress approach for truss struc- tures and its extensions for membrane and plate structures, are presented with demonstrative examples. The remaining chapters develop an overview of structural optimization problems, among which are dynamic optimization, multi-criterion optimization, earlier work on the op- timal layouts of plates, as well as some practical issues in general size and shape optimization problems.

Topology Optimization with Aperiodic Load Fatigue Constraints Based on Bidirectional Evolutionary Structural Optimization

Because of descriptive nonlinearity and computational inefficiency,topology optimization with fatigue life under aperiodic loads has developed slowly.A fatigue constraint topology optimization method based on bidirectional evolutionary structural optimization(BESO)under an aperiodic load is proposed in this paper.In viewof the severe nonlinearity of fatigue damagewith respect to design variables,effective stress cycles are extracted through transient dynamic analysis.Based on the Miner cumulative damage theory and life requirements,a fatigue constraint is first quantified and then transformed into a stress problem.Then,a normalized termination criterion is proposed by approximatemaximum stress measured by global stress using a P-normaggregation function.Finally,optimization examples show that the proposed algorithm can not only meet the requirements of fatigue life but also obtain a reasonable configuration.

Stress Relaxation and Sensitivity Weight for Bi-Directional Evolutionary Structural Optimization to Improve the Computational Efficiency and Stabilization on Stress-Based Topology Optimization

Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimization,many schemes are added to the conventional bi-directional evolutionary structural optimization(BESO)method in the previous studies.However,these schemes degrade the generality of BESO and increase the computational cost.This study proposes an improved topology optimization method for the continuum structures considering stress minimization in the framework of the conventional BESO method.A global stress measure constructed by p-norm function is treated as the objective function.To stabilize the optimization process,both qp-relaxation and sensitivity weight scheme are introduced.Design variables are updated by the conventional BESO method.Several 2D and 3D examples are used to demonstrate the validity of the proposed method.The results show that the optimization process can be stabilized by qp-relaxation.The value of q and p are crucial to reasonable solutions.The proposed sensitivity weight scheme further stabilizes the optimization process and evenly distributes the stress field.The computational efficiency of the proposed method is higher than the previous methods because it keeps the generality of BESO and does not need additional schemes.

3D numerical simulation and structural optimization of the rod baffle heat exchanger

Because of the complexities of fluid dynamics equations and the structure of heat exchangers, few theoretical solutions have been acquired to specify the shell side characteristics of the rod baffle heat exchanger （RBHE）. Based on the platform of PHEONICS version 3.5.1, a three-dimensional numerical method for predicting the turbulent fluid flow behavior in the shell side of the rod baffle heat exchangers is developed in this paper. With this method, modeling of the tube bundle is carried out based on the porous media concept using volumetric porosities and applicable flow resistance correlations. Turbulence effects are modeled using a standard κ-ε model. It is shown that the simulation results and experimental results are in good agreement in the shell side. The maximum absolute deviation value of pressure drops is less than 5%, and that of the heat transfer coefficients is less than 8%. Furthermore, the numerical model is used to optimize the structure of the RBHE and improves its performance.

Parametric Structural Optimization of 2D Complex Shape Based on Isogeometric Analysis

The geometric model and the analysis model can be unified together through the isogeometric analysis method,which has potential to achieve seamless integration of CAD and CAE.Parametric design is a mainstream and successful method in CAD field.This method is not continued in simulation and optimization stage because of the model conversion in conventional optimization method based on the finite element analysis.So integration of the parametric modeling and the structural optimization by using isogeometric analysis is a natural and interesting issue.This paper proposed a method to realize a structural optimization of parametric complex shapes by using isogeometric analysis.By the given feature curves and the constraints,a feature frame model is built.Based on the feature frame model,a parametric representation of complex shape is obtained.After adding some auxiliary curves,the feature frame model is divided into many box-like patches in three dimension or four-sided patches in two dimension.These patches are built into parametric patches by using volume interpolation methods such as Coons method.Based on the parametric patches,isogeometic analysis is applied.Thus,the relationships are constructed among the size parameters,the control points and the physical performance parameters.Then the sensitivity matrix could be derived based on the relationships.The size optimization is carried out in the first stage by taking the size parameters as variables.Based on the result of size optimization,shape optimization with the constraints of stress is carried out in the second stage by taking the control points as variables.Serval planar complex shapes are taken as example to verify our method.The results verify that the parametric modeling and structural optimization can be united together without model conversion.Benefit from this,the optimization design can be executed as a dark box operation without considering the concrete modeling and analysis by input of the sizes,constraints and loads.

Failure Mechanisms and Structural Optimization of Shredder Hammer for Metal Scraps

Recycling retired cars can relieve the environmental pollution and resource waste efficiently.However,a few publications can be found on the failure mechanisms and optimization method of recycling equipment,shredders.Thus,the failure mechanisms and structural optimization of shredder hammers for retired cars are studied aiming improving shredding efficiency and reducing cost.Failure types of shredder hammer are studied theoretically,and it is found that wear failure and fatigue failure are the two main failure types of shredder hammer.The shredding process of metal scraps is analyzed by finite element method,and it can be divided into four stages based on the stress states：initial stage,collision stage,grinding stage and separation stage.It is proved that the shredding efficiency can be improved by increasing cutouts on the hammer head.Finally,it is determined that the hammer with two cutouts is the optimal structure for metal scraps,which can improve the shredding efficiency by 20% and lengthen the hammer life by 15%.This study provides scientific basis for the industry application and theoretical foundation for further research.

Finite Element Analysis and Structural Optimization of a Vibration Feeder Based on ANSYS

Based on ANSYS software, a finite element model is built for the fatigue break of a vibration feeder influenced by an exciting force alternate load. We first study the harmonic response of the feeder and discovers the weak links which is an angle steel junction of side plate, feed inlet and the junction panel between the no-feed side plate and the bottom plate. Then, we carry out structural optimization. A streamlined method for optimum design of a vibration feeder is presented.

APPLICATION OF WAVELET TRANSFORM IN STRUCTURAL OPTIMIZATION

It is very common in structural optimization that the optima lie at or in the vicinities of the singular points of feasible domain. Therefore it is very reasonable to introduce wavelet transform that is advantageous in singularity detection. The principle and algorithm of the application of wavelet transform in structural optimization are discussed The feasibility is demonstrated by some typical examples.

Structural Optimization of Metal and Polymer Ore Conveyor Belt Rollers

Ore conveyor belt rollers operate in harsh environments,making them prone to premature failure.Their service lives are highly dependent on the stress field and bearing misalignment angle,for which limit values are defined in a standard.In this work,an optimization methodology using metamodels based on radial basis functions is implemented to reduce themass of twomodels of rollers.From a structural point of view,one of the rollers ismade completely of metal,while the other also has some components made of polymeric material.The objective of this study is to develop and apply a parametric structural optimization methodology to minimize the mass of the two models of rollers.To represent the mechanical behavior of the rollers,simulations were performed using the finite element method.During the numerical optimization process,the variable parameters were the dimensions of the shaft and external tube.The geometric configuration that corresponded at the same time to the lowest mass and acceptable ranges for the stress and bearingmisalignment angle was determined.With the proposed methodology,a 32.3% reduction in mass was obtained for a metal roller design and an 18.9% reduction for a polymer roller.In both cases,the constraints were not violated.For the all-metal roller,the safety factors for the maximum stress and bearingmisalignment angle were 1.44 and 1.75,respectively,while for the polymer roller the corresponding figures were 1.50 and 2.23.This work describes a low-computational-cost optimization methodology for roller designs that have been little studied in the literature.Furthermore,the methodology could be adapted for use with other types of rollers and rollers made of different materials.

Application of a Machine Learning Algorithm for the Structural Optimization of Circular Arches with Different Cross-Sections

Arches are employed for bridges. This particular type of structures, characterized by a very old use tradition, is nowadays, widely exploited because of its strength, resilience, cost-effectiveness and charm. In recent years, a more conscious design approach that focuses on a more proper use of the building materials combined with the increasing of the computational capability of the modern computers, has led the research in the civil engineering field to the study of optimization algorithms applications aimed at the definition of the best design parameters. In this paper, a differential formulation and a MATLAB code for the calculation of the internal stresses in the arch structure are proposed. Then, the application of a machine learning algorithm, the genetic algorithm, for the calculation of the geometrical parameters, that allows to minimize the quantity of material that constitute the arch structures, is implemented. In this phase, the method used to calculate the stresses has been considered as a constraint function to reduce the range of the solutions to the only ones able to bear the design loads with the smallest volume. In particular, some case studies with different cross-sections are reported to prove the validity of the method and to compare the obtained results in terms of optimization effectiveness.

Structural Optimization of Concrete Slab Frame Bridges Considering Investment Cost

The present study investigates computer-antomated design and structural optimization of concrete slab frame bridges considering investment cost based on a complete 3D model. Thus, a computer code with several modules has been developed to produce parametric models of slab frame bridges. Design loads and load combinations are based on the Eurocode design standard and the Swedish design standard for bridges. The necessary reinforcement diagrams to satisfy the ultimate and serviceability limit states, including fatigue checks for the whole bridge, are calculated according to the aforementioned standards. Optimization techniques based on the genetic algorithm and the pattern search method are applied. A case study is presented to highlight the efficiency of the applied optimization algorithms. This methodology has been applied in the design process for the time-effective, material-efficient, and optimal design of concrete slab frame bridges.