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- 2014 (8) (remove)
Structural optimization has gained considerable attention in the design of structural engineering structures, especially in the preliminary phase.
This study introduces an unconventional approach for structural optimization by utilizing the Energy method with Integral Material Behavior (EIM), based on the Lagrange’s principle of minimum potential energy. An automated two-level optimization search process is proposed, which integrates the EIM, as an alternative method for nonlinear
structural analysis, and the bilevel optimization. The proposed procedure secures the equilibrium through minimizing the potential energy on one level, and on a higher level, a design objective function. For this, the most robust strategy of bilevel optimization, the nested method is used. The function of the potential energy is investigated along with its instabilities for physical nonlinear analysis through principle examples, by which the advantages and limitations using this method are reviewed. Furthermore, optimization algorithms are discussed.
A numerical fully functional code is developed for nonlinear cross section,
element and 2D frame analysis, utilizing different finite elements and is verified
against existing EIM programs. As a proof of concept, the method is applied on selected
examples using this code on cross section and element level. For the former one a
comparison is made with standard procedure, by employing the equilibrium equations
within the constrains. The validation of the element level was proven by a theoretical
solution of an arch bridge and finally, a truss bridge is optimized. Most of the
principle examples are chosen to be adequate for the everyday engineering practice, to
demonstrate the effectiveness of the proposed method.
This study implies that with further development, this method could become just as
competitive as the conventional structural optimization techniques using the Finite
Element Method.
When working on urban planning projects there are usually multiple aspects to consider. Often these aspects are contradictory and it is not possible to choose one over the other; instead, they each need to be fulfilled as well as possible. Planners typically draw on past experience when subjectively prioritising which aspects to consider with which degree of importance for their planning concepts. This practice, although understandable, places power and authority in the hands of people who have varying degrees of expertise, which means that the best possible solution is not always found, because it is either not sought or the problem is regarded as being too complex for human capabilities. To improve this situation, the project presented here shows the potential of multi-criteria optimisation algorithms using the example of a new housing layout for an urban block. In addition it is shown, how Self-Organizing-Maps can be used to visualise multi-dimensional solution spaces in an easy analysable and comprehensible form.
The increasing success of BIM (Building Information Model) and the emergence of its implementation in 3D construction models have paved a way for improving scheduling process. The recent research on application of BIM in scheduling has focused on quantity take-off, duration estimation for individual trades, schedule visualization, and clash detection.
Several experiments indicated that the lack of detailed planning causes about 30% non-productive time and stacking of trades. However, detailed planning still has not been implemented in practice despite receiving a lot of interest from researchers. The reason is associated with the huge amount and complexity of input data. In order to create a detailed planning, it is time consuming to manually decompose activities, collect and calculate the detailed information in relevant. Moreover, the coordination of detailed activities requires much effort for dealing with their complex constraints.
This dissertation aims to support the generation of detailed schedules from a rough schedule. It proposes a model for automated detailing of 4D schedules by integrating BIM, simulation and Pareto-based optimization.
A fundamental characteristic of human beings is the desire to start learning at the moment of birth. The rather formal learning process that learners have to deal with in school, on vocational training or in university, is currently subject to fundamental changes. The increasing technologization, overall existing mobile devices, the ubiquitous access to digital information, and students being early adaptors of all these technological innovations require reactions on the part of the educational system.
This study examines such a reaction: The use of mobile learning in higher education.
Examining the subject m-learning first requires an investigation of the educational model e-learning. Many universities already established e-learning as one of their educational segments, providing a wide range of methods to support this kind of teaching.
This study includes an empirical acceptance analysis regarding the general learning behavior of students and their approval of e-learning methods. A survey on the approval of m-learning supplements the results.
Mobile learning is characterized by both the mobility of the communication devices and the users. Both factors lead to new correlations, demonstrate the potential of today's mobile devices and the probability to increase the learning performance.
The dissertation addresses these correlations and the use of mobile devices in the context of m-learning. M-learning and the usage of mobile devices not only require a reflection from a technological point of view. In addition to the technical features of such mobile devices, the usability of their applications plays an important role, especially with regard to the limited display size.
For the purpose of evaluating mobile apps and browser-based applications, various analytical methods are suitable.
The concluding heuristic evaluation points out the vulnerability of an established m-learning application, reveals the need for improvement, and shows an approach to rectify the shortcoming.