Simulation of arc models with the block modelling method

Simulation of current interruption is currently performed with non-ideal switching devices for large power systems. Nevertheless, for small networks, non-ideal switching devices can be substituted by arc models. However, this substitution has a negative impact on the computation time. At the same time, these simulations are useful to design...

Assimilating Aircraft-based measurements to improve the State of Distal Volcanic Ash Cloud

Estimation of volcanic ash emissions with satellite data: The inclusion of mass loading and plume height information in modified 4D-Var

The Copula Bayesian Network with mixed discrete and continuous nodes to forecast railway disruption lengths

The highly uncertain nature of a railway disruption complicates the tasks carried by the Dutch Operational Control Centre Rail (OCCR) in the Netherlands. A good prediction of disruption length is believed to help the decision making in dealing with the disruption. Zilko, et al. [Non-Parametric Bayesian Network to Forecast Railway Disruption...

An induced dimension reduction algorithm to approximate eigenpairs of large nonsymmetric matrices

This work presents an algorithm to approximate eigenpairs of large, sparse and nonsymmetric matrices based on the Induced Dimension Reduction method (IDR(s)) introduced in [1]. We obtain a Hessenberg relation from IDR(s) computations and in conjunction with Implicitly Restarting and shift-and-invert techniques [2] we created a short recurrence...

Experimental results about the assessments of conditional rank correlations by experts: Example with air pollution estimates

Science-based models often involve substantial uncertainty that must be quantified in a defendable way. Shortage of empirical data inevitably requires input from expert judgment. How this uncertainty is best elicited can be critical to a decision process, as differences in efficacy and robustness of the elicitation methods can be substantial....

Deep and shallow uncertainty in messaging climate change

Deep and shallow uncertainty are defined and contrasted with regard to messaging the uncertainty about climate change. Deep uncertainty is often traced back to the writings of Frank Knight, where in fact it simply meant subjective probability. Although Knight envisioned a scientifically grounded quantification of subjective uncertainty, deep...

A stochastic process model for life cycle cost analysis of nuclear power plant systems

The paper presents a general stochastic model to analyze the life cycle cost of an engineering system that is affected by minor but repairable failures interrupting the operation and a major failure that would require the replacement or renewal of the failed system. It is commonly observed that the frequency of minor failures increases with...

Interactive mathematical model of self-healing in carbonated cementitious materials

A mathematical model for the post-damage recovery of carbonated cement is described. The model is based on a two-dimensional initial-boundary value problem for a system of partial differential equations. The study is embedded within the framework of investigating the effect of using lightweight expanded clay aggregate, which is incorporated into...

Ensemble methods for large scale inverse problems

Variational data assimilation, also sometimes simply called the ‘adjoint method’, is used very often for large scale model calibration problems. Using the available data, the uncertain parameters in the model are identified by minimizing a certain cost function that measures the difference between the model results and the data. A variational...

A New Coastal Flood Forecasting System for the Netherlands

The North Sea is one of the busiest seas in the world with dense ship traffic, fisheries, wind farming, recreation and many other activities. All these activities depend on the ‘marine weather’. Accurate forecasts of waves, currents and sea level are crucial for operational management and for issuing warnings during extreme events. The current...

Least squares estimation of Generalized Space Time AutoRegressive (GSTAR) model and its properties

In this paper we studied a least squares estimation parameters of the Generalized Space Time AutoRegressive (GSTAR) model and its properties, especially in consistency and asymptotic normality. We use R software to estimate the GSTAR parameter and apply the model toward real phenomena of data, such as an oil production data at volcanic layer.

Non parametric continuous Bayesian belief nets in reliability of bridges under traffic load

Conditions for stochastic integrability in UMD Banach spaces

Continuous/discrete non parametric Bayesian belief nets with UNICORN and UNINET

Hanea et al. (2006) presented a method for quantifying and computing continuous/discrete non parametric Bayesian Belief Nets (BBN). Influences are represented as conditional rank correlations, and the joint normal copula enables rapid sampling and conditionalization. Further mathematical background is in Kurowicka and Cooke (2007). This article...

A suite of sharp interface models for solid-state transformations in alloys

The work deals in particular with dissolution and growth of particles in solid-state alloys. Several models are presented and numerical solution procedures are summarized briefly. Further, some analytic solutions are considered shortly, which are useful to validate the numerical solutions. One model, which incorporates surface energy effects is...

Domain decomposition methods and deflated Krylov subspace iterations

The balancing Neumann-Neumann (BNN) and the additive coarse grid correction (BPS) preconditioner are fast and successful preconditioners within domain decomposition methods for solving partial differential equations. For certain elliptic problems these preconditioners lead to condition numbers which are independent of the mesh sizes and are...

Entropy quotients and correct digits in number-theoretic expansions

Expansions that furnish increasingly good approximations to real numbers are usually related to dynamical systems. Although comparing dynamical systems seems difficult in general, Lochs was able in 1964 to relate the relative speed of approximation of decimal and regular continued fraction expansions (almost everywhere) to the quotient of the...