Predicting the unexpected

Dagstuhl seminar no. 10102 on discrete event logistic systems recognized a network of persistent models to be a “Grand Challenge.” Such on-line model network will offer an infrastructure that facilitates the management of logistic operations. This ambition to create a network of persistent models implies a radical shift for model design activities as the objective is an infrastructure rather than application-specific solutions. In particular, model developers can no longer assume that they know what their model will be used for. It is no longer possible to design for the expected.This paper presents insights in model development and design in the absence of precise knowledge concerning a model's usage. Basically, model developers may solely rely on the presence of the real-world counterpart mirrored by their model and a general idea about the nature of the application (e.g. coordination of logistic operations). When the invariants of their real-world counterpart suffice for models to be valid, these models become reusable and integrate-able. As these models remain valid under a wide range of situations, they become multi-purpose and durable resources rather than single-purpose short-lived components or legacy, which is even worse.Moreover and more specifically, the paper describes how to build models that allow their users to generate predictions in unexpected situations and atypical conditions. Referring to previous work, the paper concisely discusses how these predictions can be generated starting from the models. This prediction-generating technology is currently being transferred into an industrial MES.     

Autonomic information flow improves prognostic impact of task force HRV monitoring

Heart rate variability (HRV) represents the cardiovascular control mediated by the autonomic nervous system and other mechanisms. In the established task force HRV monitoring different cardiovascular control mechanisms can approximately be identified at typical frequencies of heart rate oscillations by power spectral analysis. HRV measures assessing complex and fractal behavior partly improved clinical risk stratification. However, their relationship to (patho-)physiology is not sufficiently explored. Objective of the present work is the introduction of complexity measures of different physiologically relevant time scales. This is achieved by a new concept of the autonomic information flow (AIF) analysis which was designed according to task force HRV. First applications show that different time scales of AIF improve the risk stratification of patients with multiple organ dysfunction syndrome and cardiac arrest patients in comparison to standard HRV. Each group's significant time scales correspond to their respective pathomechanisms.     

Theoretical and Experimental Damage Prediction in Cold and Semi‐Hot Bulk Forming of Ductile Steels

Bulk forging is among the most important manufacturing methods in metal forming, due to its wide applicability from some ounces to several tons of steel in a high diversity of shapes and forming conditions. Economical constraints demand for further optimisation and cost‐effective production. This requires the application of suitable finite elements simulation software, in order to support the already digitalised construction processes. Ductile damage is one of the most severe problems to arise during the production sequences, not only in cold but also in semi‐hot forging operations. Mathematical approaches exist for the modelling and simulation of ductile fracture in steel. In this paper some widespread used damage models are introduced and discussed. Their damage prediction quality has been verified by experiments, the tensile test and the collar specimen upsetting with several different steels under cold and semi‐hot forging conditions. The methods for the experimental fracture detection are introduced as well. In cold forging the passive ultrasonic testing with integrated statistical filtering algorithms is used. As this method is not applicable to semi‐hot forging experiments, optical fracture detection by means of a high‐speed camera is used instead. A very interesting material behaviour of the steels tested has been identified in the semi‐hot upsetting of collar specimen. For every steel a distinct temperature crossover interval exists, in which the forging process abruptly changes from damaged to undamaged state. This interval amounts to some degrees Celsius only for each of the seven materials investigated. Among the damage models proposed, the Model of Effective Stresses by Lemaitre is chosen for the application to a cold and a semi‐hot forging operation. These industrial processes of an axle end (cold) and a journal bearing (semi‐hot) are susceptible to damage for reasons to be discussed in this paper. It will be shown that the internal fracture of the axle end (chevrons) and the surface fissures of the journal bearing can be predicted with high accuracy. Moreover, the application of the damage model in the finite element software MSC.SuperForm 2004 offers a promising approach for process optimisation. Several possibilities could be tested for their suitability of reducing the calculated damage: geometry variation of the forming tools, process annealing, different materials. The use of damage models in finite element simulation can be regarded as a further step towards an optimal process design.     

Lithium-Ion Desolvation Induced by Nitrate Additives Reveals New Insights into High Performance Lithium Batteries

Electrolyte additives have been widely used to address critical issues in current metal (ion) battery technologies. While their functions as solid electrolyte interface forming agents are reasonably well-understood, their interactions in the liquid electrolyte environment remain rather elusive. This lack of knowledge represents a significant bottleneck that hinders the development of improved electrolyte systems. Here, the key role of additives in promoting cation (e.g., Li⁺) desolvation is unraveled. In particular, nitrate anions (NO₃⁻) are found to incorporate into the solvation shells, change the local environment of cations (e.g., Li⁺) as well as their coordination in the electrolytes. The combination of these effects leads to effective Li⁺ desolvation and enhanced battery performance. Remarkably, the inexpensive NaNO₃ can successfully substitute the widely used LiNO₃ offering superior long-term stability of Li⁺ (de-)intercalation at the graphite anode and suppressed polysulfide shuttle effect at the sulfur cathode, while enhancing the performance of lithium–sulfur full batteries (initial capacity of 1153 mAh g⁻¹ at 0.25C) with Coulombic efficiency of ≈100% over 300 cycles. This work provides important new insights into the unexplored effects of additives and paves the way to developing improved electrolytes for electrochemical energy storage applications.     

On the optimum mass transfer of flat absorbing falling films

The coupled heat- and mass-transfer of the absorbing falling film is considered in the flat-film approximation. We study the influence of the operating conditions on the absorption efficiency in a fully non-dimensional framework and find an optimal Reynolds number, which can be interpreted as an optimal film thickness. We also test various thermal wall boundary conditions to select the best approximation compared to a realistic test case.     

Peanut varieties with reduced Ara h 1 content indicating no reduced allergenicity

Peanut allergy is a major cause of food‐induced severe anaphylactic reactions. To date, no medical care is available to prevent and treat peanut allergy and therefore hypoallergenic peanut varieties are of considerable health political and economic interest. Major allergens that induce IgE‐responses in peanut‐sensitive patients are Ara h 1, Ara h 2 and Ara h 3/4. In order to identify hypoallergenic peanuts, commercially locally available peanut varieties were screened for their allergen content. Ara h 1‐deficient peanuts from Southeast Asia were identified by SDS‐PAGE, immunoblotting, inhibition assays and ELISA. 2‐D PAGE analyses demonstrated the different compositions of the tested extracts and revealed a number of variations of the allergen patterns of peanuts from different varieties. Mediator release experiments of these peanut extracts demonstrated similar allergenicities as compared with standard peanut extract. These results indicate that the allergenicity of peanuts with reduced Ara h 1 content might be compensated by the other allergens, and thus do not necessarily cause a reduction of allergenicity.