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On the Adjoint Formulation of Design Sensitivity Analysis of Multibody Dynamics

Andrei Schaffer

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06 October 2008
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A modified Adjoint method is presented, in which computation can be distributed to 2d+2 processors, where d is the number of degrees of freedom of the multibody system, and the Adjoint backward initial value problem (IVP) is replaced by a boundary value problem (BVP), which is solved through a backward multiple shooting algorithm. In the equivalent BVP formulation, each time-step is solved in the backward direction, but time-steps advance in the forward direction. As a result, the memory load for storing generalized coordinates during integration of the DAE of motion, is minimized. The specific objectives are (...) to develop a new method, called the Piecewise Adjoint method, that (1) requires the integration of a number of DAE that does not depend on the number of design parameters; (2) has a parallel computational structure; (3) progresses forward in time; and (4) minimizes the memory load required by the backward integration of the Adjoint DAE.

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RRP: $126.87
$102.00
Ships in 3-5 business days
Hurry up! Current stock:

On the Adjoint Formulation of Design Sensitivity Analysis of Multibody Dynamics

RRP: $126.87
$102.00

Description

A modified Adjoint method is presented, in which computation can be distributed to 2d+2 processors, where d is the number of degrees of freedom of the multibody system, and the Adjoint backward initial value problem (IVP) is replaced by a boundary value problem (BVP), which is solved through a backward multiple shooting algorithm. In the equivalent BVP formulation, each time-step is solved in the backward direction, but time-steps advance in the forward direction. As a result, the memory load for storing generalized coordinates during integration of the DAE of motion, is minimized. The specific objectives are (...) to develop a new method, called the Piecewise Adjoint method, that (1) requires the integration of a number of DAE that does not depend on the number of design parameters; (2) has a parallel computational structure; (3) progresses forward in time; and (4) minimizes the memory load required by the backward integration of the Adjoint DAE.

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