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Accepted Manuscripts

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research-article  
Tingli Xie, Ping Jiang, Qi Zhou, Leshi Shu, Yahui Zhang, Xiangzheng Meng and Hua Wei
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4040710
There are a large number of real-world engineering design problems with multi-objective, multi-constraint and having uncertainty in their inputs. Robust optimization is developed to obtain solutions that are optimal and less sensitive to uncertainty. Since most of complex engineering design problems rely on time-consuming simulations, the robust optimization approaches may become computationally intractable. To address this issue, an advanced multi-objective robust optimization approach based on Kriging and support vector machine (MORO-KS) is proposed in this work. Firstly, the main problem in MORO-KS is iteratively restricted by constraint cuts formed in the sub-problem. Secondly, a Support Vector Machine (SVM) model is constructed to replace all constraint functions classifying design alternatives into two categories: feasible and infeasible. Thirdly, each objective function is approximated by a Kriging model to predict the response value. The proposed MORO-KS approach is tested on two numerical examples and the design optimization of a micro-aerial vehicle fuselage. Compared with the results obtained from the MORO approach based on Constraint Cuts (MORO-CC), the effectiveness and efficiency of the proposed MORO-KS approach are illustrated.
TOPICS: Optimization, Support vector machines, Uncertainty, Engineering design, Design, Engineering simulation, Vehicles, Simulation
research-article  
Yanjun Zhang and Mian Li
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4040608
As the core component of an automobile, the internal combustion engine (ICE) nowadays is still a typical complex engineering system. Tolerance design for ICEs is of great importance since small changes in the dimensions and clearances of ICE components may result in large variations on the performance and cost of manufactured products. In addition, uncertainty in tolerance design has great impact on the engine performance. Although tolerance optimization for the key components of ICEs has been discussed, few of them takes uncertainty into consideration. In this regard, robust optimization (RO) for the tolerance of ICEs remains a critical issue. In this work, a novel RO approach is proposed to deal with the tolerance optimization problem for ICEs under parameter and model uncertainties, even considering metamodeling uncertainty from Gaussian processes (GP). A typical parameter uncertainty in ICEs exists in the rotation speed which can vary randomly due to the inherent randomness. AVL Excite is used to build the simulation models of ICE components, which brings in model uncertainty. GP models are used as the analysis model in order to combine the corresponding simulation and experimental data together, which introduces metamodeling uncertainty. The proposed RO approach provides a general and systematic procedure for determining robust optimal tolerances and has competitive advantages over traditional experience-based tolerance design. In addition to the ICE example, a numerical example is utilized to demonstrate the applicability and effectiveness of the proposed approach.
TOPICS: Internal combustion engines, Optimization, Uncertainty, Design, Engineering systems and industry applications, Automobiles, Chaos, Simulation models, Rotation, Engines, Dimensions, Simulation
research-article  
Nathan Kalish, Joseph K. Davidson, Satchit Ramnath, Payam Haghighi and Jami S. Shah
J. Comput. Inf. Sci. Eng   doi: 10.1115/1.4038821
Mathematical tools underlie a method that has strong potential to lower the cost of fixture-setup when finishing large castings that have machined surfaces where other components are attached. One math tool, the kinematic transformation, is used for the first time to construct Tolerance-Map (T-Map) models of geometric and size tolerances that are applied to planar faces and to the axes of round shapes, such as pins or holes. For any polygonal planar shape, a generic T-Map primitive is constructed at each vertex of its convex hull, and each is sheared uniquely with the kinematic transformation. All are then intersected to form the T-Map of the given shape in a single frame of reference. For an axis, the generic T-Map primitive represents each circular limit to its tolerance-zone. Both are transformed to a central frame of reference and are intersected to form the T-Map. The paper also contains the construction for the first 5D T-Map for controlling the minimum wall thickness between two concentric cylinders with a least-material-condition tolerance specification on position. It is formed by adding the dimension of size to the T-Map for an axis. The T-Maps described are consistent with geometric dimensioning and tolerancing standards and industry practice. Finally, transformations are presented to translate between small displacement torsor (SDT) coordinates and the classical coordinates for lines and planes used in T-Maps.
TOPICS: Kinematics, Dimensions, Finishing, Construction, Pins (Engineering), Space, Cylinders, Displacement, Shapes, Wall thickness, Hull, Geometric dimensioning and tolerancing, Mathematics

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