An optimization approach for material-constant determination for the endochronic constitutive model

Jao, S. Y.; Arora, Jasbir S.; Wu, Han

doi:10.1007/bf00370546

Cited by 11 publications

(2 citation statements)

References 15 publications

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“…A method to identify viscoelastic materials characterized by Volterra integral equations was presented by Distefano and Todeschini (1973). An optimization based approach was used by Jao et al (1991) to identify plastic, viscoelastic and viscoplastic materials modeled using the endochronic constitutive theory. The problem had several nonlinear constraints.…”

Section: Nonparametric System Identificationmentioning

confidence: 99%

Development of simplified models for design and optimization of automotive structures for crashworthiness

Kim¹,

Mijar²,

Arora³

2001

Struct Multidisc Optim

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Simplified models can be useful for up-front design of automotive structures for passenger safety during crash. Formulations based on the system identification approach are presented for development of simplified models for simulation and design for automotive crash environment. Numerical crash data available from experiments or simulations are used in the development of such models. Parametric as well as nonparametric formulations of the problem are investigated. Standard nonlinear programming optimality conditions and methods are used to solve the resulting nonlinear identification problem. Simple numerical examples are solved to illustrate the proposed formulations and methodologies. As a practical example, the front horn of an automotive structure is replaced by a single degree of freedom system (SDOF). Two basis functions that identify the given target data are studied: Hat functions (piecewise linear) and Chebyshev polynomials. Effects of the number of design variables on the final solution to the problem are investigated. In addition, using the identified SDOF model, redesign of the front horn to improve its performance is discussed.

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Section: Nonparametric System Identificationmentioning

confidence: 99%

Development of simplified models for design and optimization of automotive structures for crashworthiness

Kim¹,

Mijar²,

Arora³

2001

Struct Multidisc Optim

View full text Add to dashboard Cite

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“…However, there are some engineering problems, e.g. calibration of a model (Pint@r and Szab6 1985), material constant determination (Jao et al 1990), etc., for which it is essential to find the global minimum with absolute guarantee, irrespective of the computational effort needed. Since no other method gives absolute guarantee in finite number of steps, these methods are very important.…”

Section: II Ii Ii V Fix(t)] 1 Introductionmentioning

confidence: 99%

Global optimization methods for engineering applications: A review

Arora

Elwakeil

Chahande

et al. 1995

Structural Optimization

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138

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A review of the methods for global optimization rea¢ veals that most methods have been developed for unconstrained ~t problems. They need to be extended to general constrained c~ problems because most of the engineering applications have conAx(e) straints. Some of the methods can be easily extended while others need further work. It is also possible to transform a constrained D problem to an unconstrained one by using penalty or augmented det(°)Lagrangian methods and solve the problem that way. Some of the global optimization methods find all the local minimum points dj while others find only a few of them. In any case, all the methods require a very large number of calculations. Therefore, the dt computational effort to obtain a global solution is generally subdx stantial. The methods for global optimization can be divided into two broad categories: deterministic and stochastic. Some deter-~(t) ministic methods are based on certain assumptions on the cost e0 function that are not easy to check. These methods are not very exp (°)

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Design optimization of non‐linear structures with rate‐dependent and rate‐independent constitutive models

Jao

Arora

1993

Numerical Meth Engineering

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Optimal Design Luhorator), C'olleqe of Engrneerinq, The Unn,er\itc of lowu, l o w Cili. I A 52242-1527, U S A SUMMARY A design optimization process for non-linear structures with history-dependent materials modelled using the endochronic constitutive theory is described. This constitutive model does not use the concept of a yield surface and describes plastic, viscoplastic and viscoelastic behaviour with one set of equations. Therefore, development of the yield surface is not traced in numerical calculations, simplifying the implementation of response and sensitivity analyses. The total Lagrangian formulation incorporating both geometric and material non-linear effects is used. Shape, non-shape and material design parameters are treated simultaneously using the control volume concept, and static and dynamic problems are treated. A simple structure is optimized for several cases of static and impact loading conditions to demonstrate the procedure. Plastic and viscoplastic material behaviour as well as shape and non-shape design parameters are treated in the example problems.

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An optimization approach for material-constant determination for the endochronic constitutive model

Cited by 11 publications

References 15 publications

Development of simplified models for design and optimization of automotive structures for crashworthiness

Development of simplified models for design and optimization of automotive structures for crashworthiness

Global optimization methods for engineering applications: A review

Design optimization of non‐linear structures with rate‐dependent and rate‐independent constitutive models

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