| 1. |
- Ahmad, Aftab, et al.
(författare)
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A deterministic and probabilistic approach for robust optimal design of a 6-DOF haptic device
- 2014
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Ingår i: Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference--2013. - : ASME Press. - 9780791855898 ; , s. V03BT03A032-
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Konferensbidrag (refereegranskat)abstract
- This work suggests a two-stage approach for robust optimal design of 6-DOF haptic devices based on a sequence of deterministic and probabilistic analyses with a multi-objective genetic algorithm and the Monte-Carlo method. The presented model-based design robust optimization approach consider simultaneously the kinematic, dynamic, and kinetostatic characteristics of the device in both a constant and a dexterous workspace in order to find a set of optimal design parameter values for structural configuration and dimensioning. Design evaluation is carried out based on local and global indices, like workspace volume, quasi-static torque requirements for the actuators, kinematic isotropy, dynamic isotropy, stiffness isotropy, and natural frequencies of the device. These indices were defined based on focused kinematic, dynamic, and stiffness models. A novel procedure to evaluate local indices at a singularity-free point in the dexterous workspace is presented. The deterministic optimization approach neglects the effects from variations of design variables, e.g. due to tolerances. A Monte-Carlo simulation was carried out to obtain the response variation of the design indices when independent design parameters are simultaneously regarded as uncertain variables. It has been observed that numerical evaluation of performance indices depends of the type of workspace used during optimization. To verify the effectiveness of the proposed procedure, the performance indices were evaluated and compared in constant orientation and in dexterous workspace.
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| 2. |
- Amouzgar, Kaveh, 1980-, et al.
(författare)
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Multi-objective optimization of a disc brake system by using SPEA2 and RBFN
- 2013
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Ingår i: ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. - New York : ASME Press. - 9780791855898
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Many engineering design optimization problems involve multiple conflicting objectives, which today often are obtained by computational expensive finite element simulations. Evolutionary multi-objective optimization (EMO) methods based on surrogate modeling is one approach of solving this class of problems. In this paper, multi-objective optimization of a disc brake system to a heavy truck by using EMO and radial basis function networks (RBFN) is presented. Three conflicting objectives are considered. These are: 1) minimizing the maximum temperature of the disc brake, 2) maximizing the brake energy of the system and 3) minimizing the mass of the back plate of the brake pad. An iterative Latin hypercube sampling method is used to construct the design of experiments (DoE) for the design variables. Next, thermo-mechanical finite element analysis of the disc brake, including frictional heating between the pad and the disc, is performed in order to determine the values of the first two objectives for the DoE. Surrogate models for the maximum temperature and the brake energy are created using RBFN with polynomial biases. Different radial basis functions are compared using statistical errors and cross validation errors (PRESS) to evaluate the accuracy of the surrogate models and to select the most accurate radial basis function. The multi-objective optimization problem is then solved by employing EMO using the strength Pareto evolutionary algorithm (SPEA2). Finally, the Pareto fronts generated by the proposed methodology are presented and discussed.
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| 3. |
- Söderberg, Rikard, 1963, et al.
(författare)
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Tolerance plugin module in integrated design
- 2014
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Ingår i: Proceedings of the ASME Design Engineering Technical Conference. - 9780791855898 ; 3 B, s. Article number V03BT03A009-
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Konferensbidrag (refereegranskat)abstract
- Increased use of recycled material in high-end structural components based on wrought alloys is the goal of the EC project Suplight. The project proposes a framework for multi objective optimization. In this paper, a tolerance plugin module used in this project is described. The tolerance plugin module aims at controlling if the geometrical variation requirements on part level are fulfilled. The variation in the part stems from variation in material and process parameters and the relationship between variation in process and material parameters is estimated using designed computer experiments. Moreover, the tolerance plugin module offers an automatically generated meta-model, based on principal component analysis, for handling part variation that allows for faster Monte Carlo simulations and a format that can be used in variation simulations in succeeding assembly steps. The functionality is illustrated using two cases studies; one for investigation of geometrical part variation due to a stamping process and one for investigation of geometrical part variation due to a sheet metal forming process.
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