1 citations · 2 across the 9 of their papers we have counts for
9 papers
Efficient Bayesian calibration of many-parameter system models
Promit Chakroborty, Sankaran Mahadevan
Computer models of complex engineering systems rely on proper tuning of their model parameters to ensure accurate predictions of the system behavior. The challenge of effectively c…
SuSIE: Subset Simulation with Intrepid Exploration
Adwait Sharma, Promit Chakroborty, Michael D. Shields
This work explores the challenges associated with the subset simulation framework - a well-established algorithm for estimating structural reliability - in settings involving multi…
The tail wags the distribution: Only sample the tails for efficient reliability analysis
Promit Chakroborty, Michael D. Shields
To ensure that real-world infrastructure is safe and durable, systems are designed to not fail for any but the most rarely occurring parameter values. By only happening deep in the…
Intrepid MCMC: Metropolis-Hastings with Exploration
Promit Chakroborty, Michael D. Shields
In engineering examples, one often encounters the need to sample from unnormalized distributions with complex shapes that may also be implicitly defined through a physical or numer…
Covariance-free Bi-fidelity Control Variates Importance Sampling for Rare Event Reliability Analysis
Promit Chakroborty, Somayajulu L. N. Dhulipala, Michael D. Shields
Multifidelity modeling has been steadily gaining attention as a tool to address the problem of exorbitant model evaluation costs that makes the estimation of failure probabilities…
UQpy v4.1: Uncertainty Quantification with Python
Dimitrios Tsapetis, Michael D. Shields, Dimitris G. Giovanis +9
This paper presents the latest improvements introduced in Version 4 of the UQpy, Uncertainty Quantification with Python, library. In the latest version, the code was restructured t…
General multi-fidelity surrogate models: Framework and active learning strategies for efficient rare event simulation
Promit Chakroborty, Somayajulu L. N. Dhulipala, Yifeng Che +4
Estimating the probability of failure for complex real-world systems using high-fidelity computational models is often prohibitively expensive, especially when the probability is s…
Multifidelity Active Learning for Failure Estimation of TRISO Nuclear Fuel
Somayajulu L. N. Dhulipala, Promit Chakroborty, Michael D. Shields +3
The Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel proposed to be used for multiple modern nuclear technologies. Therefore, characterizing its safety…
Reliability Estimation of an Advanced Nuclear Fuel using Coupled Active Learning, Multifidelity Modeling, and Subset Simulation
Somayajulu L. N. Dhulipala, Michael D. Shields, Promit Chakroborty +7
Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However,…