The driftless gas scintillation proportional counter

Wetensch. publicatieFaculteit der Wiskunde en Natuurwetenschappe

Dynamic density functional study of a driven colloidal particle in polymer solutions

The Dynamic Density Functional (DDF) theory and standard Brownian dynamics simulations (BDS) are used to study the drifting effects of a colloidal particle in a polymer solution, both for ideal and interacting polymers. The structure of the stationary density distributions and the total induced current are analyzed for different drifting rates. We find good agreement with the BDS, which gives support to the assumptions of the DDF theory. The qualitative aspect of the density distribution are discussed and compared to recent results for driven colloids in one-dimensional channels and to analytical expansions for the ideal solution limit

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity

Achtergrondverlaging en grondwateraanvulling in Noord-Brabant

Achtergrondverlaging is dat deel van de gemeten grondwaterstandsdaling, dat niet door hydrologische berekeningen wordt verklaard. In het Nederlandse zandlandschap bedraagt dit deel, gemeten vanaf de jaren vijftig van de vorige eeuw, gemiddeld enkele decimeters. In dit artikel laten we zien dat de achtergrondverlaging in de provincie Noord-Brabant waarschijnlijk grotendeels is veroorzaakt door de afname van de grondwateraanvulling. Die afname hangt samen met veranderingen in het landgebruik en met een stijging van gewasopbrengsten in de landbouw

Structure, stability, and formation pathways of colloidal gels in systems with short-range attraction and long-range repulsion

We study colloidal gels formed upon centrifugation of dilute suspensions of spherical colloids (radius 446 nm) that interact through a long-range electrostatic repulsion (Debye length ≈ 850 nm) and a short-range depletion attraction (∼12.5 nm), by means of confocal scanning laser microscopy (CSLM). In these systems, at low colloid densities, colloidal clusters are stable. Upon increasing the density by centrifugation, at different stages of cluster formation, we show that colloidal gels are formed that significantly differ in structure. While significant single-particle displacements do not occur on the hour time scale, the different gels slowly evolve within several weeks to a similar structure that is at least stable for over a year. Furthermore, while reference systems without long-range repulsion collapse into dense glassy states, the repulsive colloidal gels are able to support external stress in the form of a centrifugal field of at least 9g

Simulated Annealing with Asymptotic Convergence for Nonlinear Constrained Global Optimization

. In this paper, we present constrained simulated annealing (CSA), a global minimization algorithm that converges to constrained global minima with probability one, for solving nonlinear discrete nonconvex constrained minimization problems. The algorithm is based on the necessary and sufficient condition for constrained local minima in the theory of discrete Lagrange multipliers we developed earlier. The condition states that the set of discrete saddle points is the same as the set of constrained local minima when all constraint functions are non-negative. To find the discrete saddle point with the minimum objective value, we model the search by a finite inhomogeneous Markov chain that carries out (in an annealing fashion) both probabilistic descents of the discrete Lagrangian function in the original-variable space and probabilistic ascents in the Lagrange-multiplier space. We then prove the asymptotic convergence of the algorithm to constrained global minima with probability one. Fi..