Closed-loop Identification of an Industrial Extrusion Process

This paper deals with the challenging problem of closed-loop identification for multivariable chemical processes and particularly the estimation of an open-loop plant model for a lab-scale industrial twin-screw extruder used in a powder coatings manufacturing line. The aim is to produce a low order efficient model in order to assist the scaling-up and the model-based control design of the manufacturing process. To achieve this goal, a two-stage indirect approach has been deployed which relies on the a-priori knowledge of the controller parameters in order to extract good estimates of the open-loop dynamics of the underlying process. As input excitation signals we have used multiple single variable step tests at various operating conditions (current industrial practice) carried out manually in order to generate the data-set which captures the dynamics of the extrusion process. In order to increase the efforts for obtaining a suitable plant model, we have employed various identification techniques, such as Prediction Error Methods (PEM) and Subspace Identification Methods (SIM) in order to generate candidate closed-loop models that fit to the original input-output process data. Then, a comparison of the estimated models was performed by means of the mean square error and data fitting criteria in order to select the model that best describes the dynamic behaviour of the extrusion process. Model validation based on closed-loop step responses also used as verification of the results

Why are decisions in flood disaster management so poorly supported by information from flood models?

Flood simulation models can provide practitioners of Flood Disaster Management with sophisticated estimates of floods. Despite the advantages that flood simulation modeling may provide, experiences have proven that these models are of limited use. Until now, this problem has mainly been investigated by evaluations of which information is demanded by decision-makers versus what models can actually offer. However, the goal of this study is to investigate how model information is exchanged among participants in flood disaster organizations and how this exchange affects the use of modeling information. Our findings indicate that the extent to which a model is useful not only depends on the type and quality of its output, but also on how fast and flexible a model can be. In addition, methods of model use are required that support a fast exchange of model information between participants in the flood disaster organization

From Pilot Projects to Transformative Infrastructures, Exploring Market Receptivity for Permeable Pavement in The Netherlands

Climate change and changing land use challenge the livability and flood safety of Dutch cities. One option cities have to become more climate-proof is to increase infiltration of stormwater into soil through permeable pavement and thus reduce discharge of stormwater into sewer systems. To analyze the market receptivity for permeable pavements in the Netherlands, this article focuses on the perception of end-users towards key transition factors in the infrastructure transformation processes. Market receptivity was studied on two levels: (1) on the system level, by analyzing 20 key factors in the Dutch urban water sector that enable wider application of permeable pavements; and (2) on the technology level, by analyzing 12 key factors that explain why decision makers select permeable pavements or not. Results show that trust between cooperating partners was perceived as the system level key factor that needs to be improved most to facilitate the wider uptake of permeable pavements. Additionally, the association of end-users with permeable pavement, particularly their willingness to apply these technologies and their understanding of what kinds of benefits these technologies could bring, was regarded the most important receptivity attribute. On the technology level, the reliability of permeable pavement was regarded as the most important end-user consideration for selecting this technolog

Appropriate model use for predicting elevations and inundation extent for extreme flood events

Flood risk assessment is generally studied using flood simulation models; however, flood risk managers often simplify the computational process; this is called a “simplification strategy”. This study investigates the appropriateness of the “simplification strategy” when used as a flood risk assessment tool for areas prone to flash flooding. The 2004 Boscastle, UK, flash flood was selected as a case study. Three different model structures were considered in this study, including: (1) a shock-capturing model, (2) a regular ADI-type flood model and (3) a diffusion wave model, i.e. a zero-inertia approach. The key findings from this paper strongly suggest that applying the “simplification strategy” is only appropriate for flood simulations with a mild slope and over relatively smooth terrains, whereas in areas susceptible to flash flooding (i.e. steep catchments), following this strategy can lead to significantly erroneous predictions of the main parameters—particularly the peak water levels and the inundation extent. For flood risk assessment of urban areas, where the emergence of flash flooding is possible, it is shown to be necessary to incorporate shock-capturing algorithms in the solution procedure, since these algorithms prevent the formation of spurious oscillations and provide a more realistic simulation of the flood levels