A generic data assimilation framework for vehicle trajectory reconstruction on signalized urban arterials using particle filters

With trajectory data, a complete microscopic and macroscopic picture of traffic flow operations can be obtained. However, trajectory data are difficult to observe over large spatiotemporal regions—particularly in urban contexts—due to practical, technical and financial constraints. The next best thing is to estimate plausible trajectories from...

A Study of the Influence of Measurement Volume, Blending Ratios and Sensor Precision on Real-Time Reconciliation of Grade Control Models

The mining industry continuously struggles to keep produced tonnages and grades aligned with targets derived from model-based expectations. Deviations often result from the inability to characterise short-term production units accurately based on sparsely distributed exploration data. During operation, the characterisation of short-term...

Computing derivative information of sequentially coupled subsurface models

A generic framework for the computation of derivative information required for gradient-based optimization using sequentially coupled subsurface simulation models is presented. The proposed approach allows for the computation of any derivative information with no modification of the mathematical framework. It only requires the forward model...

A particle filter-based data assimilation framework for discrete event simulations

With the advent of new sensor technologies and communication solutions, the availability of data for discrete event systems has greatly increased. This motivates research on data assimilation for discrete event simulations that has not yet fully matured. This paper presents a particle filter-based data assimilation framework for discrete event...

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...

Non-intrusive subdomain POD-TPWL for reservoir history matching

This paper presents a non-intrusive subdomain POD-TPWL (SD POD-TPWL) for reservoir history matching through integrating domain decomposition (DD), proper orthogonal decomposition (POD), radial basis function (RBF) interpolation, and the trajectory piecewise linearization (TPWL). It is an efficient approach for model reduction and linearization...

Reduction of uncertainty in stability calculations for slopes under seepage

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Traffic state estimation based on Eulerian and Lagrangian observations in a mesoscopic modeling framework

The paper proposes a model-based framework for estimating traffic states from Eulerian (loop) and/or Lagrangian (probe) data. Lagrangian-Space formulation of the LWR model adopted as the underlying traffic model provides suitable properties for receiving both Eulerian and Lagrangian external information. Three independent methods are proposed...

Accelerating volcanic ash data assimilation using a mask-state algorithm based on an ensemble Kalman filter: A case study with the LOTOS-EUROS model (version 1.10)

In this study, we investigate a strategy to accelerate the data assimilation (DA) algorithm. Based on evaluations of the computational time, the analysis step of the assimilation turns out to be the most expensive part. After a study of the characteristics of the ensemble ash state, we propose a mask-state algorithm which records the sparsity...

Variational data assimilation of satellite observations to estimate volcanic ash emissions

Volcanic eruptions release a large amount of volcanic ash, which can pose hazard to human and animal health, land transportation, and aviation safety. Volcanic Ash Transport and Dispersion (VATD) models are critical tools to provide advisory information and timely volcanic ash forecasts. Due to the complexity and the uncertainty of many dynamic...

Improving volcanic ash forecasts with ensemble-based data assimilation

The 2010 Eyjafjallajökull volcano eruption had serious consequences to civil aviation. This has initiated a lot of research on volcanic ash forecasting in recent years. For forecasting the volcanic ash transport after eruption onset, a volcanic ash transport and diffusion model (VATDM) needs to be run with Eruption Source Parameters (ESPs) such...

Recent Developments in Closed-Loop Approaches for Real-Time Mining and Petroleum Extraction

Advanced data acquisition and process modelling technology provide ‘real-time’ data and decision support capacity for different aspects of the resource extraction process. Closed-loop approaches have recently been applied to utilize information extracted from these data in combination with advanced computing technology for improved production...

Seasonal dependence of northern high-latitude upper thermospheric winds: A quiet time climatological study based on ground-based and space-based measurements

This paper investigates the large-scale seasonal dependence of geomagnetically quiet time, northern high-latitude F region thermospheric winds by combining extensive observations from eight ground-based (optical remote sensing) and three space-based (optical remote sensing and in situ) instruments. To provide a comprehensive picture of the...

High resolution soil moisture mapping using distributed temperature sensing: A data assimilation framework

Estimation of volcanic ash emissions through assimilating satellite data and ground-based observations

In this paper, we reconstruct the vertical profile of volcanic ash emissions by assimilating satellite data and ground-based observations using a modified trajectory-based 4D-Var (Trj4DVar) approach. In our previous work, we found that the lack of vertical resolution in satellite ash column data can result in a poor estimation of the injection...

Ensemble-based data assimilation schemes for atmospheric chemistry models

The atmosphere is a complex system which includes physical, chemical and biological processes. Many of these processes affecting the atmosphere are subject to various interactions and can be highly nonlinear. This complexity makes it necessary to apply computer models in order to understand the natural behavior of the atmosphere. In addition to...