Zum Beulverhalten kaltgeformter und geschweißter Rechteckhohlprofile aus hochfestem Stahl

Local Buckling Behaviour of Cold‐formed and Welded Rectangular Hollow Sections made from Extra High Strength Steel (EHSS). New structural steels, such as (liquid) quenched and tempered (QT) steels, with extra high strength, good toughness and weldability have been developed in Europe in recent years and are included in Eurocode 3 Part 1‐12 for strengths up to S 700. However, extra high strength steels (EHSS) with a yield strength of 1100 N/mm² so far have not been taken into account in the present version of Eurocode 3 due to insufficient knowledge on their buckling behaviour and fatigue strength and lack of associated experimental data. In this article results of experimental and numerical investigations concerning the local buckling behaviour of cold‐formed and welded hollow sections made of EHSS are summarised. The investigations have been carried out within the scope of an European research project. Results have been used to check the applicability of existing design rules for local buckling to EHSS. As a consequence the scope of Eurocode 3, Part 1.12 could be expanded to cover stability rules also for such steels.     

Accelerating column generation for aircraft scheduling using constraint propagation

We discuss how constraint programming can improve the performance of a column generation solution process for the NP-hard Tail Assignment problem in aircraft scheduling. Combining a constraint model of a relaxed Tail Assignment problem with column generation, we achieve substantially improved performance. A generalized preprocessing technique based on constraint propagation is presented that can dramatically reduce the size of the flight network. We also present a heuristic preprocessing method based on the costs of connections, and show how constraint propagation can be used to improve fixing heuristics. Proof of concept is provided using real world Tail Assignment instances.     

Assessing the Potential of Predictive Control for Hybrid Vehicle Powertrains Using Stochastic Dynamic Programming

The potential for reduced fuel consumption of hybrid electric vehicles by the use of predictive powertrain control was assessed on measured-drive data from an urban route with varying topography. The assessment was done by evaluating the fuel consumption using three optimal controllers, each with a different level of information access to the driven route. The lowest information case represents that the vehicle knows that it is being driven in a certain environment, e.g., city driving, and that the controller has been optimized for that type of environment. The second highest information level represents a vehicle equipped with a GPS combined with a traffic-flow information system. In the highest information level, the future power demand is completely known to the control system, hence, the corresponding optimal controller results in the minimal attainable fuel consumption. This paper showed that good performance (1%-3% from the minimal attainable fuel consumption) can be achieved with the lowest information case, with a time-invariant controller that is optimized to the environment. The second highest information level results in less than 0.2% higher consumption than the minimal attainable on the studied route. This means that it is possible to design a predictive controller based on information supplied by the vehicle-navigation system and traffic-flow-information systems that can come very close to the minimal attainable fuel consumption. A novel algorithm that uses information supplied by the vehicle-navigation system was presented. The proposed algorithm results in a consumption only 0.3% from the minimal attainable consumption on the studied route     

Fractional Bayesian Lag Length Inference in Multivariate Autoregressive Processes

The posterior distribution of the number of lags in a multivariate autoregression is derived under an improper prior for the model parameters. The fractional Bayes approach is used to handle the indeterminacy in the model selection caused by the improper prior. An asymptotic equivalence between the fractional approach and the Schwarz Bayesian Criterion (SBC) is proved. Several priors and three loss functions are entertained in a simulation study which focuses on the choice of lag length. The fractional Bayes approach performs very well compared to the three most widely used information criteria, and it seems to be reasonably robust to changes in the prior distribution for the lag length, especially under the zero-one loss.     

FlexDx: A reconfigurable diagnosis framework

Detecting and isolating multiple faults is a computationally expensive task. It typically consists of computing a set of tests and then computing the diagnoses based on the test results. This paper describes FlexDx, a reconfigurable diagnosis framework which reduces the computational burden while retaining the isolation performance by only running a subset of all tests that is sufficient to find new conflicts. Tests in FlexDx are thresholded residuals used to indicate conflicts in the monitored system. Special attention is given to the issues introduced by a reconfigurable diagnosis framework. For example, tests are added and removed dynamically, tests are partially performed on historic data, and synchronous and asynchronous processing are combined. To handle these issues FlexDx has been implemented using DyKnow, a stream-based knowledge processing middleware framework. Concrete methods for each component in the FlexDx framework are presented. The complete approach is exemplified on a dynamic system which clearly illustrates the complexity of the problem and the computational gain of the proposed approach.     

Mixed C60/C70 based fullerene acceptors in polymer bulk-heterojunction solar cells

Different mixtures of identically substituted C60 and C70 based fullerens have been used as acceptors in three polymer:fullerene systems that strongly express various performance limiting aspects of bulk heterojunction solar cells. Results are correlated with, and discussed in terms of e.g. morphology, charge separation, and charge transport. In these systems, there appears to be no relevant differences in either mobility or energy level positions between the identically substituted C60 and C70 based fullerenes tested. Examples of how fullerene mixtures influence the nano-morphology of the active layer are given. An upper limit to the open circuit voltage that can be obtained with fullerenes is also suggested.     

Composition–structure–property relationships of transparent Ca–Al–Si–O–N oxynitride glasses: The roles of nitrogen and aluminum

We explore the formation and composition–structure–property correlations of transparent Ca–Al–Si–O–N glasses, which were prepared by a standard melt-quenching technique using AlN as the nitrogen source and incorporating up to 8 at.% of N. Their measured physical properties of density, molar volume, compactness, refractive index, and hardness—along with the Young, shear, and bulk elastic moduli—depended roughly linearly on the N content. These effects are attributed primarily to the improved glass-network cross-linking from N compared to O, rather than the formation of higher-coordination AlO₅ and AlO₆ groups, where ²⁷Al magic-angle-spinning nuclear magnetic resonance experimentation revealed that aluminum is predominately present in tetrahedral coordination as AlO₄ units. Yet, several physical properties, such as the refractive index along with the bulk, shear, and Young's elastic moduli, increase concomitantly with the Al content of the glass. We discuss the incompletely understood mechanical–property boosting role of Al as observed both herein and in previous reports on oxynitride glasses, moreover suggesting glass-composition domains that are likely to offer optimal mechanical properties.     

Global Optimization of Costly Nonconvex Functions Using Radial Basis Functions

The paper considers global optimization of costly objective functions, i.e. the problem of finding the global minimum when there are several local minima and each function value takes considerable CPU time to compute. Such problems often arise in industrial and financial applications, where a function value could be a result of a time-consuming computer simulation or optimization. Derivatives are most often hard to obtain, and the algorithms presented make no use of such information.Several algorithms to handle the global optimization problem are described, but the emphasis is on a new method by Gutmann and Powell, A radial basis function method for global optimization. This method is a response surface method, similar to the Efficient Global Optimization (EGO) method of Jones. Our Matlab implementation of the Radial Basis Function (RBF) method is described in detail and we analyze its efficiency on the standard test problem set of Dixon-Szegö, as well as its applicability on a real life industrial problem from train design optimization. The results show that our implementation of the RBF algorithm is very efficient on the standard test problems compared to other known solvers, but even more interesting, it performs extremely well on the train design optimization problem.     

Erosion of a model rosin-based marine antifouling paint binder as studied with quartz crystal microbalance with dissipation monitoring (QCM-D) and ellipsometry

In this study two surface sensitive methods, i.e. quartz crystal microbalance with dissipation monitoring (QCM-D) and ellipsometry, were used for erosion measurements of a rosin-based marine antifouling paint binder. Thin films of the binder were applied on sensor surfaces by the means of spin-coating and the effect of water velocity over the paint film, water temperature or ionic strength on erosion was investigated. Both the acoustic QCM-D model and the optical ellipsometry model gave comparable erosion results. The initial 2–50 nm rapid erosion of the top layer was followed by steady-state erosion rate until end of experiment. For example, the steady-state erosion rate was 12 nm/24 h in artificial seawater at 23 °C and with a flow of 200 μl/min over the paint surface as measured with QCM-D. The erosion rate increased with increased velocity and increased temperature. Ionic strength had no effect on the erosion rate of this model binder. At low water velocities the surface layer was highly dissipative indicating a water filled surface top layer or the formation of deposits on the surface. New characterization techniques that are able to study the erosion mechanisms on the nanometre scale are sought for as the binders get more technically complex containing, for example, nanoparticles or enzymes. Surface sensitive methods could be used to rapidly screen the effect of different binder chemistries or paint additives on the erosion during the paint development process.