Unravelling decision making about the future developments of Amsterdam Airport Schiphol

The time that airports were merely infrastructural works for supporting air transportation is no more. Over the years, especially the major airports have developed from airfields into multi-modal transportation nodes and cities of their own. Amsterdam Airport Schiphol is a perfect example of this. The airport has developed into an attractive pool for urban and economic development, known as an AirportCity. Airports like Amsterdam Airport Schiphol, took up their newfound position in the emerging network society and implemented new business strategies to cope with the increasing volatility of future transport volumes. The search for additional finances has lead to further commercialization of the airport and gave rise to Airport-city like concepts. However, this evolving form of airports did not find its way into Dutch national planning policy. An analysis of Dutch national spatial strategies shows an increased interest for Amsterdam Airport Schiphol as being of major importance for the national economy, but the emphasis is still mainly on the airport as an important piece of physical infrastructure. With fierce competition of cities like Barcelona and Dublin in mind, the Amsterdam region needs a strong, widely supported, development strategy to maintain and strengthen its concurrence position. A strategy that acknowledges the new airport day-to-day realities and that goes beyond the narrow definition of the airport as merely infrastructural. Such a widely accepted strategy does not exist at this moment, which causes serious problems if policies are willing to strengthen the role of Schiphol for the national economy in the future. This paper explores the newfound position of airports in the network society. It links this position to an analysis of the processes of policy making to identify reasons why there is currently no strong development strategy for Amsterdam Airport Schiphol (region). A comparison is made between the policy development process in the late 80’s and early 90’s, which did result in a widely accepted development policy for the airport, and the policy development process that currently takes place. Interviews with primary stakeholders and analyses of policy documents shed light on the success factors that made the reach of an agreement possible in the early 90’s as well as the reasons for not being able to reach such agreement today.

Darcian permeability constant as indicator for shear stresses in regular scaffold systems for tissue engineering

The shear stresses in printed scaffold systems for tissue engineering depend on the flow properties and void volume in the scaffold. In this work, computational fluid dynamics (CFD) is used to simulate flow fields within porous scaffolds used for cell growth. From these models the shear stresses acting on the scaffold fibres are calculated. The results led to the conclusion that the Darcian (k 1) permeability constant is a good predictor for the shear stresses in scaffold systems for tissue engineering. This permeability constant is easy to calculate from the distance between and thickness of the fibres used in a 3D printed scaffold. As a consequence computational effort and specialists for CFD can be circumvented by using this permeability constant to predict the shear stresses. If the permeability constant is below a critical value, cell growth within the specific scaffold design may cause a significant increase in shear stress. Such a design should therefore be avoided when the shear stress experienced by the cells should remain in the same order of magnitud

Control vector parameterization with sensitivity based refinement applied to baking optimization

In bakery production, product quality attributes as crispness, brownness, crumb and water content are developed by the transformations that occur during baking and which are initiated by heating. A quality driven procedure requires process optimization to improve bakery production and to find operational procedures for new products. Control vector parameterization (CVP) is an effective method for the optimization procedure. However, for accurate optimization with a large number of parameters CVP optimization takes a long computation time. In this work, an improved method for direct dynamic optimization using CVP is presented. The method uses a sensitivity based step size refinement for the selection of control input parameters. The optimization starts with a coarse discretization level for the control input in time. In successive iterations the step size was refined for the parameters for which the performance index has a sensitivity value above a threshold value.With this selection, optimization is continued for a selected group of input parameters while the other nonsensitive parameters (below threshold) are kept constant. Increasing the threshold value lowers the computation time, however the obtained performance index becomes less. A threshold value in the range of 10–20% of the mean sensitivity satisfies well. The method gives a better solution for a lower computation effort than single run optimization with a large number of parameters or refinement procedures without selection