Data assimilation for Navier-Stokes using the least-squares finite-element method

We investigate theoretically and numerically the use of the least-squares finite-element method (LSFEM) to approach data-assimilation problems for the steady-state, incompressible Navier-Stokes equations. Our LSFEM discretization is based on a stress-velocity-pressure (S-V-P) first-order formulation, using discrete counterparts of the Sobolev...

Bayesian and Dempster–Shafer reasoning for knowledge-based fault diagnosis: A comparative study

Even though various frameworks exist for reasoning under uncertainty, a realistic fault diagnosis task does not fit into any of them in a straightforward way. For each framework, only part of the available data and knowledge is in the desired format. Moreover, additional criteria, like clarity of inference and computational efficiency,...

Bayesian Inference of Aircraft Initial Mass

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other ATM topics. However, it is a common challenge for researchers who have no access to this proprietary information. Previously, several studies have proposed methods to estimates aircraft weight, most of which are focused on...

A toolbox to find the best mechanistic model to predict the behavior of environmental systems

Reliable prediction of the long-term behavior of environmental systems such as Municipal Solid Waste (MSW) landfills is challenging. While many driving forces influence this behavior, characterization of them is limited by measurement techniques. Therefore, a model structure for reliable prediction needs to optimally combine all measured...

Monitoring and statistical modelling of sedimentation in gully pots

Gully pots are essential assets designed to relief the downstream system by trapping solids and attached pollutants suspended in runoff. This study applied a methodology to develop a quantitative gully pot sedimentation and blockage model. To this end, sediment bed level time series from 300 gully pots, spanning 15 months, were collected. A...

Model-data integration for predictive assessment of groundwater reactive transport systems

Predicting the evolution of groundwater contamination is a major concern for society, in particular when investments are made to remediate the contamination. Groundwater reactive transport models are valuable tools to integrate the available measurements in a consistent framework, improving our understanding of the physical system and...

Reliability-Based Design and Quality Control of Bored Piles

Bored piles are a type of deep foundations which have been and are being widely used in construction engineering such as high-rise buildings, bridges, jetties, and so on. Although bored piles have remarkable advantages over driven piles, the quality of bored piles is frequently affected by many causes of imperfection, which mainly come from the...

Inference of reactive transport model parameters using a Bayesian multivariate approach

Parameter estimation of subsurface transport models from multispecies data requires the definition of an objective function that includes different types of measurements. Common approaches are weighted least squares (WLS), where weights are specified a priori for each measurement, and weighted least squares with weight estimation (WLS(we)) where...

Bayesian Data Assimilation for Improved Modeling of Road Traffic

This thesis deals with the optimal use of existing models that predict certain phenomena of the road traffic system. Such models are extensively used in Advanced Traffic Information Systems (ATIS), Dynamic Traffic Management (DTM) or Model Predictive Control (MPC) approaches in order to improve the traffic system. As road traffic is the result...

A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non?Gaussian errors

Estimation of parameter and predictive uncertainty of hydrologic models has traditionally relied on several simplifying assumptions. Residual errors are often assumed to be independent and to be adequately described by a Gaussian probability distribution with a mean of zero and a constant variance. Here we investigate to what extent estimates of...