Surrogate models are usually used to perform global sensitivity analysis （GSA） by avoiding a large ensemble of deterministic simulations of the Monte Carlo method to provide a reliable estimate of GSA indices. Howev...Surrogate models are usually used to perform global sensitivity analysis （GSA） by avoiding a large ensemble of deterministic simulations of the Monte Carlo method to provide a reliable estimate of GSA indices. However, most surrogate models such as polynomial chaos （PC） expansions suffer from the curse of dimensionality due to the high-dimensional input space. Thus, sparse surrogate models have been proposed to alleviate the curse of dimensionality. In this paper, three techniques of sparse reconstruc- tion are used to construct sparse PC expansions that are easily applicable to computing variance-based sensitivity indices （Sobol indices）. These are orthogonal matching pursuit （OMP）, spectral projected gradient for L1 minimization （SPGL1）, and Bayesian compressive sensing with Laplace priors. By computing Sobol indices for several benchmark response models including the Sobol function, the Morris function, and the Sod shock tube problem, effective implementations of high-dimensional sparse surrogate construction are exhibited for GSA.展开更多
Three-dimensional visualization technology converts engineering design drawings and data into graphics or images, realizes virtual reality perception of simulated users in future construction scene, enhances the inter...Three-dimensional visualization technology converts engineering design drawings and data into graphics or images, realizes virtual reality perception of simulated users in future construction scene, enhances the interaction between project management and technical personnel and engineering construction achievement, and provides intuitive, flexible and strong realistic experience for project management. It can effectively improve the level of project communication, and assist the needs of project construction planning management, training, exhibition, etc. As a tool to help improve project management skills, it has good application effect and prospects.展开更多
基金Project supported by the National Natural Science Foundation of China(Nos.11172049 and11472060)the Science Foundation of China Academy of Engineering Physics(Nos.2015B0201037and 2013A0101004)
文摘Surrogate models are usually used to perform global sensitivity analysis （GSA） by avoiding a large ensemble of deterministic simulations of the Monte Carlo method to provide a reliable estimate of GSA indices. However, most surrogate models such as polynomial chaos （PC） expansions suffer from the curse of dimensionality due to the high-dimensional input space. Thus, sparse surrogate models have been proposed to alleviate the curse of dimensionality. In this paper, three techniques of sparse reconstruc- tion are used to construct sparse PC expansions that are easily applicable to computing variance-based sensitivity indices （Sobol indices）. These are orthogonal matching pursuit （OMP）, spectral projected gradient for L1 minimization （SPGL1）, and Bayesian compressive sensing with Laplace priors. By computing Sobol indices for several benchmark response models including the Sobol function, the Morris function, and the Sod shock tube problem, effective implementations of high-dimensional sparse surrogate construction are exhibited for GSA.
文摘Three-dimensional visualization technology converts engineering design drawings and data into graphics or images, realizes virtual reality perception of simulated users in future construction scene, enhances the interaction between project management and technical personnel and engineering construction achievement, and provides intuitive, flexible and strong realistic experience for project management. It can effectively improve the level of project communication, and assist the needs of project construction planning management, training, exhibition, etc. As a tool to help improve project management skills, it has good application effect and prospects.
