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Porvoo, Finland

Torkkeli J.,Neste Jacobs Oy | Saukkonen T.,Aalto University | Hanninen H.,Aalto University
Materials and Corrosion | Year: 2014

Stress corrosion cracking of carbon steel in aerated ethanol-gasoline blend was studied using notched slow strain rate testing. Characterization of the fracture surface was made using SEM and SEM-EDS. Intergranular stress corrosion cracking (SCC) was produced in ethanol-gasoline blend with 15.5 wt% ethanol that was produced by evaporation of light C4 and C5 fractions from the ethanol-gasoline blend with 10.4 wt% of ethanol. Chloride concentration of 2 mg/L was found to cause transition from intergranular SCC to fully transgranular SCC in ethanol-gasoline blend with 85 wt% of ethanol. Transgranular SCC was found to initiate mainly at the pearlite phase and intergranular SCC initiated equally on the pearlite and ferrite phases. Chloride caused localized crystallographic pitting on the transgranular SCC fracture surfaces near the lamellar cementite left on the steel surface due to selective dissolution of ferrite from pearlite. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Natural gas pipeline systems are not commonly discussed as target systems for Model Predictive Control (MPC). Over decades, complex, non-linear dynamic system models have been developed and trials to directly use these complex models as a part of a real-time (optimal) control or real-time optimization solution have been presented. Quite few are those approaches known from power systems and process industries: just pick the relevant dynamics and try to linarize, if possible. This paper describes how MPC can be applied on a natural gas pipeline system. The dynamic models required for MPC are assumed linear, which turns out to be a good approximation of reality. Natural Gas Pipeline Systems offer, because of their physical properties, an opportunity to use a'priori information in the model identification phase, which we make full use of. A demonstration example, though simplified, shows that significant improvement in pipeline operations can be achieved with MPC. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Liiri M.,Aalto University | Hatakka H.,Lappeenranta University of Technology | Kallas J.,Lappeenranta University of Technology | Aittamaa J.,Neste Jacobs Oy | Alopaeus V.,Aalto University
Chemical Engineering Research and Design | Year: 2010

In this study a combination of computational fluid dynamics (CFD) and multiblock model is used for modelling crystal growth in a 100dm3 suspension crystallizer equipped with two turbine impellers. Local hydrodynamics and crystal suspension densities were modelled using CFD. Simulation results were compared with experimental results to verify flow profile and slip velocities (Hatakka et al., 2008, 2009), and classification of crystals. Results from CFD simulations were then translated to a proper form and used as input data for the multiblock model. The same multiblock model has previously been used successfully for modelling gas-liquid systems (Laakkonen, 2006). For this study a growth model for potassium dihydrogen phosphate (KDP) was imported into the multiblock model. We used the power-law growth model including activity-based driving force. The growth model was developed based on single crystal experiments of KDP (Liiri et al., 2006). Growth of KDP crystals in the 100dm3 suspension crystallizer was simulated with the multiblock model. Verification was done by comparing the simulated results with results from crystal growth experiments. © 2009 The Institution of Chemical Engineers.

Aalto H.,Neste Jacobs Oy
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2013

Full-order filters which are optimal with respective to the H2 norm may be formulated as convex optimization problems with Linear Matrix Inequality (LMI) constraints. Reduced-order filter design problems are non-convex, but various elegant relaxations resulting in suboptimal filters are reported in the literature. In this paper, a very simple approach is taken, where the original system is first reduced to a smaller dimension, and then a suboptimal, reduced-order filter with respect to the H2 norm is obtained through straightforward numerical optimization. The smoothing stabilization task following this problem formulation is solved by simply adding a penalty function to the cost function of the optimization problem. Finally, for large-scale filter design problems, acceleration of the H2 norm minimization utilizing another reduced-order model is used. The method shows good performance when applied on a benchmark 5-state filtering problem and on a larger 150-state filtering problem. © IFAC.

Aalto H.,Neste Jacobs Oy
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2010

Many methods exist for model reduction of dynamical systems. However, only in a few cases a method can be picked from the literature and applied just like pushing a button. The structure and properties of the target system need to be investigated prior to model reduction. Natural gas pipeline systems are complex, large-scale systems with a special structure which must be recognized. Model reduction methods suitable for interconnected systems are tested on a true natural gas pipeline system with 600 state variables and almost 200 input variables.

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