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Partikelmesstechnik
(2012)
Der Schutz von Produkten vor der Kontamination durch Partikel gilt als eine zentrale Aufgabe der Reinraumtechnik. Da es dabei um Kontaminationseffekte weit unterhalb der visuellen Wahrnehmbarkeit geht, braucht es leistungsfähige Verfahren, um die Messgröße „Partikelkontamination“ über den gesamten Bereich, den Anwender fordern, präzise zu bestimmen. Neben der Partikelhäufigkeit ist dabei die Größe der Partikel, die sowohl das Transportverhalten wie auch die mögliche Wirkung auf das Produkt beeinflusst, von entscheidender Bedeutung. Ferner kann es für die Ermittlung von Kontaminationsquellen von Interesse sein, die Form und die chemische Natur der Partikel zu bestimmen (z. B. textile Fasern, Metallabrieb, flüssige Tröpfchen). Die Partikelhäufigkeit wird üblicherweise als Konzentration, d. h. bezogen auf das analysierte Gasvolumen angegeben. Bei den in reinen Technologien üblichen niedrigen Konzentrationen dient als Häufigkeitsmaß die Partikelanzahlkonzentration, also die Partikelanzahl pro Volumeneinheit des Trägermediums.
Partikelmesstechnik
(2002)
It has been observed that carcinogenic polycyclic aromatic hydrocarbons (PAH) are present in the atmosphere. Combustion processes are considered the most important sources for PAH. Among these, the burning of coal produces the highest emission, but in cities with high traffic density and low meteorological exchange activities, vehicle emissions determine the immission situation, especially in narrow streets. For estimating the potential health effects caused by PAH, it is sufficient to characterize the emission of PAH with respect to their physical state, concentrations, and, as far as the particulate phase is concerned, size distribution. The size distribution is important for transport phenomena, inhalation, and deposition in the respiratory tract. These parameters mainly depend on the combustion system, on system operating conditions, on the exhaust system, and on exhaust cooling conditions. At exhaust-gas temperatures in the range of ambient air temperatures, almost the whole emission of PAH is made up of particulate matter.
The fundamental modeling of energy systems through individual unit commitment decisions is crucial for energy system planning. However, current large-scale models are not capable of including uncertainties or even risk-averse behavior arising from forecasting errors of variable renewable energies. However, risks associated with uncertain forecasting errors have become increasingly relevant within the process of decarbonization. The intraday market serves to compensate for these forecasting errors. Thus, the uncertainty of forecasting errors results in uncertain intraday prices and quantities. Therefore, this paper proposes a two-stage risk-constrained stochastic optimization approach to fundamentally model unit commitment decisions facing an uncertain intraday market. By the nesting of Lagrangian relaxation and an extended Benders decomposition, this model can be applied to large-scale, e.g., pan-European, power systems. The approach is applied to scenarios for 2023—considering a full nuclear phase-out in Germany—and 2035—considering a full coal phase-out in Germany. First, the influence of the risk factors is evaluated. Furthermore, an evaluation of the market prices shows an increase in price levels as well as an increasing day-ahead-intraday spread in 2023 and in 2035. Finally, it is shown that intraday cross-border trading has a significant influence on trading volumes and prices and ensures a more efficient allocation of resources.
Masonry is used in many buildings not only for load-bearing walls, but also for non-load-bearing enclosure elements in the form of infill walls. Many studies confirmed that infill walls interact with the surrounding reinforced concrete frame, thus changing dynamic characteristics of the structure. Consequently, masonry infills cannot be neglected in the design process. However, although the relevant standards contain requirements for infill walls, they do not describe how these requirements are to be met concretely. This leads in practice to the fact that the infill walls are neither dimensioned nor constructed correctly. The evidence of this fact is confirmed by the recent earthquakes, which have led to enormous damages, sometimes followed by the total collapse of buildings and loss of human lives. Recently, the increasing effort has been dedicated to the approach of decoupling of masonry infills from the frame elements by introducing the gap in between. This helps in removing the interaction between infills and frame, but raises the question of out-of-plane stability of the panel. This paper presents the results of the experimental campaign showing the out-of-plane behavior of masonry infills decoupled with the system called INODIS (Innovative decoupled infill system), developed within the European project INSYSME (Innovative Systems for Earthquake Resistant Masonry Enclosures in Reinforced Concrete Buildings). Full scale specimens were subjected to the different loading conditions and combinations of in-plane and out-of-plane loading. Out-of-plane capacity of the masonry infills with the INODIS system is compared with traditionally constructed infills, showing that INODIS system provides reliable out-of-plane connection under various loading conditions. In contrast, traditional infills performed very poor in the case of combined and simultaneously applied in-plane and out-of-plane loading, experiencing brittle behavior under small in-plane drifts followed by high out-of-plane displacements. Decoupled infills with the INODIS system have remained stable under out-of-plane loads, even after reaching high in-plane drifts and being damaged.
Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.