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Bayesian model calibration and optimization of surfactant-polymer flooding

The physical models governing surfactant-polymer (SP) flooding process are subject to parametric uncertainties, accurate quantification of which is crucial for improved decision making. Moreover, history matching of SP flooding is an ill-posed …

Bayesian optimal design of experiments for inferring the statistical expectation of expensive black-box functions

Global sensitivity analysis for the design of nonlinear identification experiments

Bayesian inference techniques have been used extensively in recent years for parameter estimation in nonlinear systems. Despite the many advances made in the field, highly nonlinear systems can still be challenging to identify. Of key interest is the …

Model selection and uncertainty quantification of seismic fragility functions

Implementation of a self-tuned HVAC controller to satisfy occupant thermal preferences and optimize energy use

This paper presents the development of a self-tuned HVAC controller that provides customized thermal conditions to satisfy occupant preferences (i.e., online learning) while minimizing energy consumption, and the implementation of this controller in …

A personalized daylighting control approach to dynamically optimize visual satisfaction and lighting energy use

This paper presents a method to incorporate personalized visual preferences in real-time optimal daylighting control without using general discomfort-based assumptions. A personalized shading control framework is developed to maximize occupant …

Machine learning for high-dimensional dynamic stochastic economies

We present a novel computational framework that can compute global solutions to high-dimensional dynamic stochastic economic models on irregular state space geometries. This framework can also resolve value and policy functions’ local features and …

Predicting the effect of aging and defect size on the stress profiles of skin from advancement, rotation and transposition flap surgeries

Predicting mechanical stress contours on skin resulting from local tissue rearrangement surgeries is needed to design optimal treatment plans and avoid wound healing complications. Finite element (FE) simulations of skin tissues have been shown to be …

Inference of thermal preference profiles for personalized thermal environments with actual building occupants

In this paper we present a methodology to map individual occupants' thermal preference votes and indoor environmental variables into personalized preference models. Our modeling approach includes a new Bayesian classification and inference algorithm …

Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification

State-of-the-art computer codes for simulating real physical systems are often characterized by vast number of input parameters. Performing uncertainty quantification (UQ) tasks with Monte Carlo (MC) methods is almost always infeasible because of the …