We examined the physical, chemical, and biological attributes of temporary and permanent lake outlets situated above treeline in the Swiss Alps. Surface f10w in the temporary outlet streams ceased by mid-September. High discharge in spring asso ciated with snowmelt was an order of magnitude greater in the temporary outlets than in the permanent outlets. Periphyton biomass attained 5-9 x higher levels in the tem porary sites than in the permanent sites by midsummer. Although macroinvertebrate densities were similar between temporary and permanent sites, taxon richness was 2 x greater in the permanent outlets. Macroinvertebrate groups absent from temporary out lets incIuded Ephemeroptera, Plecoptera, Trichoptera, and long-lived dipterans such as Limoniidae and Tipulidae. The semi-terrestrial gastropod Galba truncatula colonized the temporary lake outlets via the lake. Chironomidae, Oligochaeta and Simuliidae also were common and able to complete development in the temporary lake outlets. Cladocera and Copepoda originating from the lakes attained high abundances in some outlets regardless of being temporary or permanent. The harsh Alpine environment in concert with intermittency were strong determinants of ecosystem properties in the temporary outlets. Regardless of f10w permanency, the lakes directly affected commu nity dynamics of outlets by influencing physical and chemical properties, and provid ing colonists to outlet streams.

Modern material handling systems (MHS) are complex systems which are controlled by various control units on different automation levels. The design of the MHS facility layout and the development of the control units require the application of different CAE tools but simulation and virtual commissioning does currently not play a significant role because there is no integrated simulation-based verification environment for all project stages and control levels available. This paper presents an approach towards an integrated simulation-based verification tool for all stages of an MHS project. During the first stage a material flow simulation of the plant model is conducted to analyze key performance indicators. This model is reused to test and verify the function of control units such as material flow controllers or programmable logic controllers. An automatic equivalence checking tool identifies differences between simulation runs. An important benefit: One common simulation model is used for all project stages

No abstract

For covering the real-time characteristics of an automation system during model-based design it is essential to model not only the function but also the behaviour of the control programs running on a real-time controller. This paper introduces an approach to the modelling and evaluation of the functional and time behaviour of Programmable Logic Controllers (PLC) on model level. The control algorithm consisting of UML statecharts is extended with an execution model of the controller which is also given as a statechart. The approach is integrated into a model-based design system for industrial control systems focusing on the field of production systems. An example will be employed to illustrate the benefits of a model-based design system which does incorporate realtime aspects of the controller

Modern material handling systems (MHS) are complex systems which are controlled by various control units on different automation levels. The design of the MHS facility layout and the development of the control units require many different CAE tools but simulation and virtual commissioning does currently not play a significant role. This paper presents an approach towards an integrated simulation-based verification and virtual commissioning environment for all phases of an MHS project. During the first phase a material flow simulation of the plant model is conducted to analyse and confirm the planned performance indicators. The model is reused for testing and verification of the control units such as material flow controller or programmable logic controllers. An automatic equivalence inspector identifies differences between simulation results