Robustness of Design Through Minimum Sensitivity

1992 ◽  
Vol 114 (2) ◽  
pp. 213-217 ◽  
Author(s):  
A. D. Belegundu ◽  
Shenghua Zhang
Keyword(s):  
Optimization Problem ◽  
Probability Distributions ◽  
Uncertain Variable ◽  
Design Stage ◽  
Cross Sectional ◽  
Uncertain Variables ◽  
Design Variables ◽  
Variable Reduction ◽  
Minimum Sensitivity ◽  
Selection Of

The problem of designing mechanical systems or components under uncertainty is considered. The basic idea is to ensure quality control at the design stage by minimizing sensitivity of the response to uncertain variables by proper selection of design variables. The formulation does not involve probability distributions. It is proved, however, that when the response is linear in the uncertain variable, reduction in sensitivity implies lesser probability of failure. The proof is generalized to the non-linear case under certain restrictions. In one example, the design of a three-bar truss is considered. The length of one of the bars is considered to be the uncertain variable while cross-sectional areas are the design variables. The sensitivity of the x-displacement is minimized. The constrained optimization problem is solved using a nonlinear programming code. A criterion which can help identify some of the problems where robustness in design is critical is discussed.

Robust Mechanical Design Through Minimum Sensitivity

1989 ◽  
Author(s):  
A. D. Belegundu ◽  
S. Zhang
Keyword(s):  
Contact Pressure ◽  
Thermal Environment ◽  
Mechanical Design ◽  
Operating Temperature ◽  
Design Stage ◽  
Element Analysis ◽  
Uncertain Variables ◽  
Design Variables ◽  
Minimum Sensitivity ◽  
Selection Of

Abstract The problem of designing mechanical systems or components under uncertainty is considered. The basic idea is to ensure quality control at the design stage by minimizing sensitivity of the response to uncertain variables by proper selection of design variables. This formulation is applied to the design of a brass sleeve which is press fitted over a steel shaft in an uncertain thermal environment. The contact pressure is determined using finite element analysis. By optimizing the shape of the sleeve, the sensitivity of contact pressure with respect to operating temperature is reduced. The minimum sensitivity approach offers a straightforward procedure for robust design and can be implemented in a general manner. It is shown that reduction in sensitivity leads to increase in probability of safety.

Vehicle Handling Dynamics Optimization Based in Passive Suspension Settings in Target Cascading Framework

2014 ◽  
Author(s):  
Juan C. Blanco ◽  
Luis E. Muñoz
Keyword(s):  
Optimal Design ◽  
Optimization Problem ◽  
Suspension System ◽  
Dynamics Simulation ◽  
Design Stage ◽  
Partial Geometry ◽  
Embodiment Design ◽  
Design Variables ◽  
Target Cascading

The vehicle optimal design is a multi-objective multi-domain optimization problem. Each design aspect must be analyzed by taking into account the interactions present with other design aspects. Given the size and complexity of the problem, the application of global optimization methodologies is not suitable; hierarchical problem decomposition is beneficial for the problem analysis. This paper studies the handling dynamics optimization problem as a sub-problem of the vehicle optimal design. This sub-problem is an important part of the overall vehicle design decomposition. It is proposed that the embodiment design stage can be performed in an optimal viewpoint with the application of the analytical target cascading (ATC) optimization strategy. It is also proposed that the design variables should have sufficient physical significance, but also give the overall design enough design degrees of freedom. In this way, other optimization sub-problems can be managed with a reduced variable redundancy and sub-problem couplings. Given that the ATC strategy is an objective-driven methodology, it is proposed that the objectives of the handling dynamics, which is a sub-problem in the general ATC problem, can be defined from a Pareto optimal set at a higher optimization level. This optimal generation of objectives would lead to an optimal solution as seen at the upper-level hierarchy. The use of a lumped mass handling dynamics model is proposed in order to manage an efficient optimization process based in handling dynamics simulations. This model contains detailed information of the tire properties modeled by the Pacejka tire model, as well as linear characteristics of the suspension system. The performance of this model is verified with a complete multi-body simulation program such as ADAMS/car. The handling optimization problem is presented including the proposed design variables, the handling dynamics simulation model and a case study in which a double wishbone suspension system of an off-road vehicle is analyzed. In the case study, the handling optimization problem is solved by taking into account couplings with the suspension kinematics optimization problem. The solution of this coupled problem leads to the partial geometry definition of the suspension system mechanism.

scholarly journals Optimization of Single-Layer Braced Domes

2017 ◽  
Vol 17 (1) ◽  
pp. 45-50 ◽  
Author(s):  
Maksym Grzywiński
Keyword(s):  
Design Of Experiments ◽  
Optimization Problem ◽  
Limit State ◽  
Single Layer ◽  
Mass Reduction ◽  
Cross Sectional ◽  
Space Design ◽  
Design Variables ◽  
Structural Space ◽  
Ansys Workbench

Abstract The paper deals with discussion of optimization problem in civil engineering structural space design. Minimization of mass should satisfy the limit state capacity and serviceability conditions. The cross-sectional areas of bars and structural dimensions are taken as design variables. Variables are used in the form of continuous and discrete. The analysis is done using the Structural and Design of Experiments modules of Ansys Workbench v17.2. As result of the method a mass reduction of 46,6 % is achieved.

Implementation of Design Sensitivity Analysis with Existing Finite Element Codes

1987 ◽  
Vol 109 (3) ◽  
pp. 385-391 ◽  
Author(s):  
K. K. Choi ◽  
J. L. T. Santos ◽  
M. C. Frederick
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Cross Sectional ◽  
Design Variables ◽  
Accurate Design ◽  
Analysis Theory ◽  
Problem Design ◽  
Selection Of

A numerical method is presented to implement structural design sensitivity analysis theory, using the versatility and convenience of existing finite element structural analysis programs. Design variables such as thickness and cross-sectional areas of components of individual members and built-up structures are considered. Structural performance functionals considered include displacement and stress. The method is also applicable for eigenvalue problem design sensitivity analysis. It is shown that calculations can be carried out outside existing finite element codes, using postprocessing data only. Thus design sensitivity analysis software does not have to be imbedded in an existing finite element code. Feasibility of the method is shown through analysis of several problems, including a built-up structure. Accurate design sensitivity results are obtained without the uncertainty of numerical accuracy associated with selection of finite difference perturbations.

Unified Synthesis of Compact Planar Path-Generating Linkages With Rigid and Deformable Members

2009 ◽  
Author(s):  
Ashok Kumar Rai ◽  
A. Saxena ◽  
Nilesh D. Mankame
Keyword(s):  
Genetic Algorithm ◽  
Rigid Body ◽  
Optimization Problem ◽  
Compliant Mechanisms ◽  
Cross Sectional ◽  
The Cross ◽  
The Individual ◽  
Planar Linkages ◽  
Selection Of ◽  
Compact Planar

A unified procedure for the synthesis of planar linkages that may take the form of rigid body, fully compliant or partially compliant mechanisms is presented. The procedure automates the selection of mechanism topology as characterized by the number and connectivity of the links as well as the nature of the connections between the links, the mechanism shape as characterized by the shapes of the individual links, and the mechanism dimensions which include the locations of the joints and the cross-sectional dimensions of the links. The synthesis task is posed as an optimization problem and is solved by a hybrid, elite-preserving genetic algorithm. Three examples of compact mechanisms that trace different non-smooth paths in response to a single, monotonic and bounded force input are used to illustrate the synthesis capability of the procedure. Prototypes of the designs are built and tested to verify their performance.

Unified Approach to Optimization of Tread Pattern Shape and Cross-Sectional Contour of Tires

2010 ◽  
Vol 38 (4) ◽  
pp. 276-285 ◽  
Author(s):  
Yoshihiro Tanaka ◽  
Katsutoshi Ohishi
Keyword(s):  
Structure Design ◽  
Design Stage ◽  
Trial And Error ◽  
Cross Sectional ◽  
Pattern Design ◽  
Optimization System ◽  
Performance Requirements ◽  
Design Variables ◽  
Pattern Shape ◽  
Design Factors

Abstract During the design stage, tire designers have to use trial and error to decide on the design factors in order to satisfy performance requirements, and this involves a great deal of time and expense. Optimization is one of the methods which can be used effectively and efficiently to improve tire performance. There is a lot of literature available about optimal tire contour and structure design. On the other hand, there is little published information available about optimal tread pattern design. In particular, there is little information available about the interaction between optimal tire contour and tread pattern design. In this study, we constructed a tire optimization system in which the design factors of cross-sectional contour and tread pattern shape could both be dealt with as design variables at the same time. This optimization system was then applied to and verified for an actual tire design problem.

scholarly journals Multi-Objective Optimisation of Biodiesel Synthesis in Simulated Moving Bed Reactor

Separations ◽  
2021 ◽  
Vol 8 (8) ◽  
pp. 127
Author(s):  
Nillohit Mitra Ray ◽  
Ajay K. Ray
Keyword(s):  
Design Stage ◽  
Simulated Moving Bed ◽  
Moving Bed ◽  
Multi Objective ◽  
Design Variables ◽  
Biodiesel Synthesis ◽  
Single Column ◽  
Set Up ◽  
Yield And Purity ◽  
Selection Of

In this work, multi-objective optimisation study was performed to determine the performance improvement in a simulated moving bed reactor (SMBR) for biodiesel synthesis. The selection of the operating parameters such as switching time, liquid flow rates in various sections, as well as the length and number of columns is not straightforward in an SMBR. In most cases, conflicting requirements and constraints influence the optimal selection of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified and verified experimentally for multiple-column SMBR system. In this article, a few multi-objective optimisation problems were carried out for both existing set-up as well as at the design stage. A non-dominated sorting genetic algorithm (NSGA) was used as the optimisation tool for the optimisation study. Due to conflicting effect of process parameters, the multi-objective optimisation study resulted in non-dominated Pareto optimal solutions. It was shown that significant increase in yield and purity of biodiesel in SMBR was possible both for operating and at design stage.

scholarly journals Optimization Of Double-Layer Braced Barrel Vaults

2015 ◽  
Vol 15 (2) ◽  
Author(s):  
Maksym Grzywiński
Keyword(s):  
Double Layer ◽  
Discrete Optimization ◽  
Optimization Problem ◽  
Limit State ◽  
Discrete Optimization Problem ◽  
Cross Sectional ◽  
Optimization Constraints ◽  
Space Design ◽  
Design Variables ◽  
Structural Space

Abstract The paper deals with discussion of discrete optimization problem in civil engineering structural space design. Minimization of mass should satisfy the limit state capacity and serviceability conditions. The cross-sectional areas of truss bars are taken as design variables. Optimization constraints concern stresses, displacements and stability, as well as technological and computational requirements.

Research on Mechanical Engineering with Lightweight Design for a Car Body Frame

2014 ◽  
Vol 952 ◽  
pp. 334-337
Author(s):  
Da Feng Jin ◽  
Duo Zeng
Keyword(s):  
Sequential Quadratic Programming ◽  
Optimization Problem ◽  
Lightweight Design ◽  
Latin Hypercube Sampling ◽  
Body Frame ◽  
Cross Sectional ◽  
Car Body ◽  
Novel Approach ◽  
Design Variables ◽  
Sampling Points

This paper develops a novel approach for the lightweight design of a car body frame. In this approach, the cross-sectional dimensions of a car body frame are treated as design variables. First, sampling points are created based on Latin Hypercube Sampling (LHS), and then Design of Experiment (DOE) is conducted. After that, an analysis is done to obtain those design variables affect the results most. Finally, Sequential Quadratic Programming (SQP) is utilized to solve the optimization problem while the amount of design variables is reduced according to the former analysis. The advantage of this method is that it reduces the burden of optimization algorithms and offers a practical way for the lightweight design of a car body frame.

scholarly journals Prediction of Optimal Design and Deflection of Space Structures Using Neural Networks

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Reza Kamyab Moghadas ◽  
Kok Keong Choong ◽  
Sabarudin Bin Mohd
Keyword(s):  
Neural Networks ◽  
Optimal Design ◽  
Double Layer ◽  
Optimization Problem ◽  
Computational Cost ◽  
Space Structures ◽  
Maximum Deflection ◽  
Cross Sectional ◽  
Design Variables ◽  
Low Computational Cost

The main aim of the present work is to determine the optimal design and maximum deflection of double layer grids spending low computational cost using neural networks. The design variables of the optimization problem are cross-sectional area of the elements as well as the length of the span and height of the structures. In this paper, a number of double layer grids with various random values of length and height are selected and optimized by simultaneous perturbation stochastic approximation algorithm. Then, radial basis function (RBF) and generalized regression (GR) neural networks are trained to predict the optimal design and maximum deflection of the structures. The numerical results demonstrate the efficiency of the proposed methodology.

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