Abstract
Reliability-based design optimization (RBDO) of a mechanism is normally based on the non-probabilistic model, which is viewed as failure possibility constraints in each optimization loop. It leads to a double-loop nested problem that causes a computationally expensive evaluation. Several methods have been developed to solve the problem, which are expected to increase the realization of optimum results and computational efficiency. The purpose of this paper was to develop a new technique of RBDO that can reduce the complexity of the double-loop nested problem to a single-loop. This involves using a multi-objective evolutionary technique combined with the worst-case scenario and fuzzy sets, known as a multi-objective, reliability-based design optimization (MORBDO). The optimization test problem and a steering linkage design were used to validate the performance of the proposed technique. The proposed technique can reduce the complexity of the design problem, producing results that are more conservative and realizable.
Highlights
Uncertainties such as tolerance, backlash, and clearance can affect kinematic and dynamic characteristics of a mechanism, especially for a steering linkage [1]
To solve the torsion bar spring optimization problem, we calculated the results, which are shown in Figure 6 and Table 1 at various α-cuts
The torsion bar problem demonstrates the validity of the present technique
Summary
Uncertainties such as tolerance, backlash, and clearance can affect kinematic and dynamic characteristics of a mechanism, especially for a steering linkage [1]. The uncertain parameters affecting steering linkages have been quantified [1], while the robust design was an alternative for synthesis of the mechanism [2]. The first study presented an effective surrogate model for reliability analysis wherein it was extended to time-dependent reliability analysis [1]. Kinematic reliability analysis of steering mechanisms has been proposed for sensitivity analysis and optimization design [2]. An alternative method of reliability analysis is MonteCarlo simulation (MCS), which is computationally time-consuming. This kind of technique is called the probabilistic analysis. Research in the field of topology optimization has been presented in [8], which depends on uncertainty of material properties, external loads, and other parameters
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