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Schalung und Gerüste
(2019)
Die grundsätzliche Planung von Schalungsaufgaben wird heute in der Regel im Rahmen der Arbeitsvorbereitung von den entsprechenden Stabsabteilungen oder als Serviceleistung von den Schalungsherstellern mit Anwendung von spezieller Software und den technischen Unterlagen für die jeweiligen Schalungsgeräte durchgeführt. Diese Programme und technischen Unterlagen stehen in der Regel auch den Mitarbeitern in der Bauleitung zur Verfügung, werden dort aber eher seltener genutzt. Zur Anwendung auf der Baustelle stellen die Schalungshersteller neben den technischen Unterlagen Bemessungstabellen zur Verfügung, welche die Auswahl und Dimensionierung einzelner Schalungen wesentlich erleichtern.
Die nachfolgend aufgeführten Beispiele aus dem Bereich Schalung und Gerüste beschreiben Aufgaben, die im Baustellenbetrieb auf die Bauleitung zu kommen können und auch ohne Unterstützung einer Stabsabteilung gelöst werden können.
Betriebsorganisation
(2019)
Kalkulation
(2019)
Arbeitssicherheit
(2019)
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material.
Themen
(2019)