This review covers the new developments in machine learning (ML) that are impacting the
multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics …

Quantitative analysis and optimal design under uncertainty are active research areas in
modern engineering structures and systems. A metamodel, as an effective mathematical …

Dual-mode ramjet/scramjet engines promise extended flight speed range and are the
commonly preferred air-breathing propulsion system from within the family of hypersonic …

We describe the integration of Bayesian decision theory in a digital twin framework to
provide a process optimization tool for a biomass boiler. Our application is the Atikokan …

In uncertainty analysis, surrogate modeling techniques demonstrate high efficiency and
reliable precision in estimating the uncertainty for the finite difference time domain (FDTD) …

Reduced order models (ROMs) are constructed by proper orthogonal decomposition (POD)
and regression by Kriging and Radial Basis Neural Network (RBFN) for a 500 MWe …

The use of polynomial chaos expansion (PCE) has gained a lot of attention due to its ability
to efficiently estimate the effects of parameter uncertainty on model outputs. The traditional …

Over the last century, computational modeling in geoscience, especially in porous media
research, has witnessed tremendous improvement. After decades of development, the state …

The growing share of wind and solar power in the total energy mix has caused severe
problems in balancing the electrical power production. Consequently, in the future, all fossil …

基于无监督学**的多参数储层评价:以蒲包山地区下三叠统飞仙关组礁滩储层为例 logo CSCD来源
期刊 北大中文核心期刊 **科技核心期刊 地学领域高质量科技期刊分级T2区(2023) 世界期刊 …