Objective Function for Sensitivity-Based Shape Optimization

The objective function describes the optimization target. In general, one scalar value (sometimes combined from other scalars) is to be maximized or minimized.

This page discusses:

See Also
Objective Function
Design Responses
Remarks for Sensitivity-Based Optimizations
In Other Guides
OBJ_FUNC
Allowed Optimization Strategy for Design Responses

Overview

The OBJECTIVE FUNCTION is the function, which value can be maximized or minimized during the optimization. This function depends on the results of the FE analysis. Therefore, the values of interest must be derived from the FE results to define an objective function and functional constraints. The results of the FE analysis (total displacement, energy, etc.) for determining the objective function and functional constraints are called ’design responses’. A single value from the design response must be specified for the definition of the objective function using the command DRESP(Design Response).

Objective Function Terms

Tosca Structure.shape controller allows optimization on different stress hypotheses, strain formulations, and damage results. The most used equivalent stress is von Mises (SIG_MISES).

The supported types of design responses usable in an objective function for sensitivity-based shape optimization are listed in the table below.

Static analysis Description

CENTER_GRAVITY_X

CENTER_GRAVITY_Y

CENTER_GRAVITY_Z

Center of gravity design responses

DISP_ABS

DISP_X

DISP_Y

DISP_Z

DISP_X_ABS

DISP_Y_ABS

DISP_Z_ABS

Displacement design responses

INERTIA_XX

INERTIA_XY

INERTIA_XZ

INERTIA_YY

INERTIA_YZ

INERTIA_ZZ

Moment of inertia design responses

INTERNAL_FORCE_ABS

INTERNAL_FORCE_X

INTERNAL_FORCE_Y

INTERNAL_FORCE_Z

INTERNAL_FORCE_X_ABS

INTERNAL_FORCE_Y_ABS

INTERNAL_FORCE_Z_ABS

Internal force design responses

INTERNAL_MOMENT_X

INTERNAL_MOMENT_Y

INTERNAL_MOMENT_Z

INTERNAL_MOMENT_X_ABS

INTERNAL_MOMENT_Y_ABS

INTERNAL_MOMENT_Z_ABS

Internal moment design responses

PEMAG

Plastic strain magnitude design response**

REACTION_FORCE_ABS

REACTION_FORCE_X

REACTION_FORCE_Y

REACTION_FORCE_Z

REACTION_FORCE_X_ABS

REACTION_FORCE_Y_ABS

REACTION_FORCE_Z_ABS

Reaction force design responses

REACTION_MOMENT_X

REACTION_MOMENT_Y

REACTION_MOMENT_Z

REACTION_MOMENT_X_ABS

REACTION_MOMENT_Y_ABS

REACTION_MOMENT_Z_ABS

Reaction moment design responses

ROT_ABS

ROT_X

ROT_Y

ROT_Z

ROT_X_ABS

ROT_Y_ABS

ROT_Z_ABS

Rotation design responses

STRAIN_ENERGY

SIG_1

Maximum principal stress.

SIG_3

Minimum principal stress.

SIG_MISES

SIG_SENS_MISES

Von Mises Stress design responses

For SIG_MISES, SIG_SENS_MISES is used for sensitivity calculation.

SIG_SIGNED_MISES

Signed von Mises stress failure criteria.

SIG_GLINKA_EEQ

SIG_GLINKA_PEEQ

SIG_GLINKA_SEQ

SIG_NEUBER_EEQ

SIG_NEUBER_PEEQ

SIG_NEUBER_SEQ

Glinka and Neuber formulations for equivalent strain (_EEQ), stress (_SEQ) and plastic strain (_PEEQ) using the plastic correction factor, respectively**.

STRAIN_ENERGY

Strain energy design responses

WEIGHT

Weight design response

Modal analysis Description

DYN_FREQ

Dynamic frequency design response

Analysis independent Description

VOLUME

Volume design response

Additional design response types

Modal analysis Description

DYN_FREQ_KREISSEL

Dynamic frequency design response

Note:

  • Stress responses (*SIG*) are only supported by Tetrahedron 4 and 10 as well as Hexahedron 8. This does not hold if solver sensitivities are used. Refer the related topics.
  • GBL_SIG_MISES_SENS responses are based on element groups.
  • SIG_* generates a pseudo load for EACH element.
  • Design responses marked with ** are only allowed using Abaqus sensitivities.

Differences in Objective Target Formulation

The objective formulation for the optimization varies depending on the objective target such as minimization/ maximization or a Min-Max/ Max-Min definition. For further details and formulas, see Minimization or Maximization of an Objective Function and Multidisciplinary Objectives (Minmax and Maxmin Formulations).