Novel Performance-Oriented Tolerance Design Method Based on Locally Inferred Sensitivity Analysis and Improved Polynomial Chaos Expansion

2020 ◽  
Vol 143 (2) ◽  
Author(s):  
Guodong Sa ◽  
Zhenyu Liu ◽  
Chan Qiu ◽  
Xiang Peng ◽  
Jianrong Tan

Abstract Tolerance design is becoming increasingly important for electromechanical products. Reasonable tolerance design can reduce production costs and improve product performance. However, as the complexity of the coupling of tolerances and performance increases, it becomes difficult for designers to establish accurate tolerance design models, leading to experience-based design. This study proposes a novel performance-oriented tolerance design method. First, the main tolerance variables affecting the product performance are rapidly determined based on the proposed locally inferred sensitivity analysis method. Then, based on the improved approximate polynomial chaos expansion, a surrogate model of the product performance and main tolerance variables is established. Finally, the geometric tolerances of the electromechanical products are optimized based on the surrogate model with performance requirements. The proposed tolerance design method is computationally efficient and accurate, and it can be implemented with a small number of samples. To demonstrate its performance, the proposed method is validated with a spaceborne active-phased array antenna. The optimal tolerance design of the antenna for the electrical performance requirements is performed successfully.

2021 ◽  
Author(s):  
Gowtham Radhakrishnan ◽  
Xu Han ◽  
Svein Sævik ◽  
Zhen Gao ◽  
Bernt Johan Leira

Abstract From a mathematical viewpoint, the frequency domain analysis of vessel motion responses due to wave actions incorporates the integration of system dynamics idealized in terms of response amplitude operators (RAOs) for 6 DOF rigid body motions and an input wave spectrum to yield the response spectrum. Various quantities of interest can be deduced from the response spectrum and further used for decision support in marine operations, extreme value and fatigue analysis. The variation of such quantities, owing to the uncertainties associated with the vessel system parameters, can be quantified by performing uncertainty propagation (UP) and consequent sensitivity analysis (SA). This study, emphasizes and proposes a computational-efficient way of assessing the sensitivity of the system model output with respect to the uncertainties residing in the input parameters by operating on a surrogate model representation. In this respect, the global sensitivity analysis is effectively carried out by deploying an efficient non-intrusive polynomial chaos expansion (PCE) surrogate model built using a point collocation strategy. Successively, the coherent and effective Sobol’ indices are obtained from the analytical decomposition of the polynomial coefficients. The indices, eventually, are employed to quantitatively gauge the effects of input uncertainties on the output 6 DOF vessel responses.


2009 ◽  
Vol 94 (7) ◽  
pp. 1161-1172 ◽  
Author(s):  
Thierry Crestaux ◽  
Olivier Le Maıˆtre ◽  
Jean-Marc Martinez

2021 ◽  
Author(s):  
Giuseppe Abbiati ◽  
Stefano Marelli ◽  
Nikolaos Tsokanas ◽  
Bruno Sudret ◽  
Bozidar Stojadinovic

Hybrid Simulation is a dynamic response simulation paradigm that merges physical experiments and computational models into a hybrid model. In earthquake engineering, it is used to investigate the response of structures to earthquake excitation. In the context of response to extreme loads, the structure, its boundary conditions, damping, and the ground motion excitation itself are all subjected to large parameter variability. However, in current seismic response testing practice, Hybrid Simulation campaigns rely on a few prototype structures with fixed parameters subjected to one or two ground motions of different intensity. While this approach effectively reveals structural weaknesses, it does not reveal the sensitivity of structure's response. This thus far missing information could support the planning of further experiments as well as drive modeling choices in subsequent analysis and evaluation phases of the structural design process.This paper describes a Global Sensitivity Analysis framework for Hybrid Simulation. This framework, based on Sobol' sensitivity indices, is used to quantify the sensitivity of the response of a structure tested using the Hybrid Simulation approach due to the variability of the prototype structure and the excitation parameters. Polynomial Chaos Expansion is used to surrogate the hybrid model response. Thereafter, Sobol' sensitivity indices are obtained as a by-product of polynomial coefficients, entailing a reduced number of Hybrid Simulations compared to a crude Monte Carlo approach. An experimental verification example highlights the excellent performance of Polynomial Chaos Expansion surrogates in terms of stable estimates of Sobol' sensitivity indices in the presence of noise caused by random experimental errors.


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