Probabilistic and Robust Engineering Design

This cluster of papers focuses on uncertainty quantification and sensitivity analysis in complex mathematical and computational models. It explores methods such as polynomial chaos, Monte Carlo simulation, and sparse grids to assess and manage uncertainties in various engineering and scientific applications. The research also delves into topics like global sensitivity indices, reliability analysis, stochastic differential equations, and probabilistic design optimization.

How has Probabilistic and Robust Engineering Design's publication output changed over time?

Output grew100% over the shown period — from 1 works in 1975 to 2 in 2022.

What are the most-cited papers on Probabilistic and Robust Engineering Design?

Where is Probabilistic and Robust Engineering Design research published, and who funds it?

How much of the research on Probabilistic and Robust Engineering Design is open access?