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Civil-Comp Proceedings
ISSN 1759-3433
ISSN 1759-3433
CCP: 83
PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
PROCEEDINGS OF THE EIGHTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping, G. Montero and R. Montenegro
Paper 33
Efficient Reliability-Based Design Optimization of Structural-Acoustic Problems
A. Mohsine and A. El-Hami
INSA de Rouen, LMR, St Etienne du Rouvray, France
Full Bibliographic Reference for this paper
A. Mohsine, A. El-Hami, "Efficient Reliability-Based Design Optimization of Structural-Acoustic Problems", in B.H.V. Topping, G. Montero, R. Montenegro, (Editors), "Proceedings of the Eighth International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 33, 2006. doi:10.4203/ccp.83.33
Keywords: reliability-based design optimization, structural reliability, acoustic, probabilistic model.
Summary
The objective of reliability based design optimization (RBDO), it is to provide the
designer with structures that should be economic and reliable. The RBDO problem
is often formulated as a minimization of the initial structural cost under constraints
imposed on the values of elemental reliability indices corresponding to various limit
states. The classical RBDO leads to high computing time and weak convergence. To
overcome these two drawbacks, a hybrid method has been elaborated [1].
It has been demonstrated that the hybrid method successfully reduces the
computing time in static and dynamic cases [1]. The
formulation of the hybrid method is expressed by:
In this formulation,
is the distance in the hybrid space between the
optimum solution and the design point (the most probable failure point). The
minimization of the total function
is carried out in the hybrid design
space (HDS) of deterministic variables 
and random variables 
. In the above formulation
the deterministic variable vector is found in both functions: 
and
but the random vector is only located in the distance function
. Therefore, when minimizing the total objective function
, we
may obtain several optimum solutions verifying the different constraints of the
problem, especially the reliability index constraint. In order to obtain a global
solution, we propose in this paper, to multiply the objective function with the
random vector by the total objective function. So, the formulation of the
improved hybrid method can be expressed as:
Using the proposed formulation, we can improve our results (objective function) and we can control the optimal configuration of the studied structure to get global solution. A numerical application shows the importance of the improved hybrid method.
 |
In this formulation,
is the distance in the hybrid space between the
optimum solution and the design point (the most probable failure point). The
minimization of the total function
is carried out in the hybrid design
space (HDS) of deterministic variables and random variables . In the above formulation
the deterministic variable vector is found in both functions: and
but the random vector is only located in the distance function
. Therefore, when minimizing the total objective function
, we
may obtain several optimum solutions verifying the different constraints of the
problem, especially the reliability index constraint. In order to obtain a global
solution, we propose in this paper, to multiply the objective function with the
random vector by the total objective function. So, the formulation of the
improved hybrid method can be expressed as:
|
Using the proposed formulation, we can improve our results (objective function) and we can control the optimal configuration of the studied structure to get global solution. A numerical application shows the importance of the improved hybrid method.
In this paper, we apply the improved hybrid method as an efficient RBDO approach to the acoustic problem.
References
- 1
- Kharmanda, G., Mohamed, A. and Lemaire, M. "Efficient reliability-based design optimization using a hybrid space with application to finite element analysis", Struct. Multidisc. Optim 24 3, pp 233-245, 2002. doi:10.1007/s00158-002-0233-z
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