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Wir betrachten im ÖPNV (Öffentlichen Personennahverkehr) diejenige Situation, daß zwei Bus- oder Straßenbahnlinien gemeinsame Haltestellen haben. Ziel unserer Untersuchungen ist es, für beide Linien einen solchen Fahrplan zu finden, der für die Fahrgäste möglichst viel Bequemlichkeit bietet. Die Bedarfsstruktur - die Anzahl von Personen, die die beiden Linien benutzen - setzt dabei gewisse Beschränkungen für die Taktzeiten der beiden Linien. Die verbleibenden Entscheidungsfreiheiten sollen im Sinne der Zielstellung ausgenutzt werden. Im Vortrag wird folgenden Fragen nachgegangen: - nach welchen Kriterien kann man die "Bequemlichkeit" oder die "Synchonisationsgüte" messen? - wie kann man die einzelnen "Synchronisationsmaße" berechnen ? - wie kann man die verbleibenden Entscheidungsfreiheiten nutzen, um eine möglichst gute Synchronisation zu erreichen ? Die Ergebnisse werden dann auf einige Beispiele angewandt und mit den bereitgestellten Methoden Lösungsvorschläge unterbreitet.
In civil engineering it is very difficult and often expensive to excite constructions such as bridges and buildings with an impulse hammer or shaker. This problem can be avoided with the output-only method as special feature of stochastic system identification. The permanently existing ambient noise (e.g. wind, traffic, waves) is sufficient to excite the structures in their operational conditions. The output-only method is able to estimate the observable part of a state-space-model which contains the dynamic characteristics of the measured mechanical system. Because of the assumption that the ambient excitation is white there is no requirement to measure the input. Another advantage of the output-only method is the possibility to get high detailed models by a special method, called polyreference setup. To pretend the availability of a much larger set of sensors the data from varying sensor locations will be collected. Several successive data sets are recorded with sensors at different locations (moving sensors) and fixed locations (reference sensors). The covariance functions of the reference sensors are bases to normalize the moving sensors. The result of the following subspace-based system identification is a high detailed black-box-model that contains the weighting function including the well-known dynamic parameters eigenfrequencies and mode shapes of the mechanical system. Emphasis of this lecture is the presentation of an extensive damage detection experiment. A 53-year old prestressed concrete tied-arch-bridge in Hünxe (Germany) was deconstructed in 2005. Preliminary numerous vibration measurements were accomplished. The first experiment for system modification was an additional support near the bridge bearing of one main girder. During a further experiment one hanger from one tied arch was cut through as an induced damage. Some first outcomes of the described experiments will be presented.
Due to the amount of flow simulation and measurement data, automatic detection, classification and visualization of features is necessary for an inspection. Therefore, many automated feature detection methods have been developed in recent years. However, only one feature class is visualized afterwards in most cases, and many algorithms have problems in the presence of noise or superposition effects. In contrast, image processing and computer vision have robust methods for feature extraction and computation of derivatives of scalar fields. Furthermore, interpolation and other filter can be analyzed in detail. An application of these methods to vector fields would provide a solid theoretical basis for feature extraction. The authors suggest Clifford algebra as a mathematical framework for this task. Clifford algebra provides a unified notation for scalars and vectors as well as a multiplication of all basis elements. The Clifford product of two vectors provides the complete geometric information of the relative positions of these vectors. Integration of this product results in Clifford correlation and convolution which can be used for template matching of vector fields. For frequency analysis of vector fields and the behavior of vector-valued filters, a Clifford Fourier transform has been derived for 2D and 3D. Convolution and other theorems have been proved, and fast algorithms for the computation of the Clifford Fourier transform exist. Therefore the computation of Clifford convolution can be accelerated by computing it in Clifford Fourier domain. Clifford convolution and Fourier transform can be used for a thorough analysis and subsequent visualization of flow fields.
Die Liquiditätsplanung von Bauunternehmen XE "Liquiditätsplanung" gilt als ein wesentliches Steuerungs-, Kontroll- sowie Informationsinstrument für interne und externe Adressaten und übt eine Entscheidungsunterstützungsfunktion aus. Da die einzelnen Bauprojekte einen wesentlichen Anteil an den Gesamtkosten des Unternehmens ausmachen, besitzen diese auch einen erheblichen Einfluß auf die Liquidität und die Zahlungsfähigkeit der Bauunternehmung. Dem folgend ist es in der Baupraxis eine übliche Verfahrensweise, die Liquiditätsplanung zuerst projektbezogen zu erstellen und anschließend auf Unternehmensebene zu verdichten. Ziel der Ausführungen ist es, die Zusammenhänge von Arbeitskalkulation XE "Arbeitskalkulation" , Ergebnisrechnung XE "Ergebnisrechnung" und Finanzrechnung XE "Finanzrechnung" in Form eines deterministischen XE "Erklärungsmodells" Planungsmodells auf Projektebene darzustellen. Hierbei soll das Verständnis und die Bedeutung der Verknüpfungen zwischen dem technisch-orientierten Bauablauf und dessen Darstellung im Rechnungs- und Finanzwesen herausgestellt werden. Die Vorgänge aus der Bauabwicklung, das heißt die Abarbeitung der Bauleistungsverzeichnispositionen und deren zeitliche Darstellung in einem Bauzeitenplan sind periodisiert in Größen der Betriebsbuchhaltung (Leistung, Kosten) zu transformieren und anschließend in der Finanzrechnung (Einzahlungen., Auszahlungen) nach Kreditoren und Debitoren aufzuschlüsseln.
We consider efficient numerical methods for the solution of partial differential equations with stochastic coefficients or right hand side. The discretization is performed by the stochastic finite element method (SFEM). Separation of spatial and stochastic variables in the random input data is achieved via a Karhunen-Loève expansion or Wiener's polynomial chaos expansion. We discuss solution strategies for the Galerkin system that take advantage of the special structure of the system matrix. For stochastic coefficients linear in a set of independent random variables we employ Krylov subspace recycling techniques after having decoupled the large SFEM stiffness matrix.
In many branches companies often lose the visibility of their human and technical resources of their field service. On the one hand the people in the fieldservice are often free like kings on the other hand they do not take part of the daily communication in the central office and suffer under the lacking involvement in the decisions inside the central office. The result is inefficiency. Reproaches in both directions follow. With the radio systems and then mobile phones the ditch began to dry up. But the solutions are far from being productive.
HYPERMONOGENIC POLYNOMIALS
(2006)
It is well know that the power function is not monogenic. There are basically two ways to include the power function into the set of solutions: The hypermonogenic functions or holomorphic Cliffordian functions. L. Pernas has found out the dimension of the space of homogenous holomorphic Cliffordian polynomials of degree m, but his approach did not include a basis. It is known that the hypermonogenic functions are included in the space of holomorphic Cliffordian functions. As our main result we show that we can construct a basis for the right module of homogeneous holomorphic Cliffordian polynomials of degree m using hypermonogenic polynomials and their derivatives. To that end we first recall the function spaces of monogenic, hypermonogenic and holomorphic Cliffordian functions and give the results needed in the proof of our main theorem. We list some basic polynomials and their properties for the various function spaces. In particular, we consider recursive formulas, rules of differentiation and properties of linear independency for the polynomials.
Traffic simulation is a valuable tool for the design and evaluation of road networks. Over the years, the level of detail to which urban and freeway traffic can be simulated has increased steadily, shifting from a merely qualitative macroscopic perspective to a very detailed microscopic view, where the behavior of individual vehicles is emulated realistically. With the improvement of behavioral models, however, the computational complexity has also steadily increased, as more and more aspects of real-life traffic have to be considered by the simulation environment. Despite the constant increase in computing power of modern personal computers, microscopic simulation stays computationally expensive, limiting the maximum network size than can be simulated on a single-processor computer in reasonable time. Parallelization can distribute the computing load from a single computer system to a cluster of several computing nodes. To this end, the exisiting simulation framework had to be adapted to allow for a distributed approach. As the simulation is ultimately targeted to be executed in real-time, incorporating real traffic data, only a spatial partition of the simulation was considered, meaning the road network has to be partitioned into subnets of comparable complexity, to ensure a homogenous load balancing. The partition process must also ensure, that the division between subnets does only occur in regions, where no strong interaction between the separated road segments occurs (i.e. not in the direct vicinity of junctions). In this paper, we describe a new microscopic reasoning voting strategy, and discuss in how far the increasing computational costs of these more complex behaviors lend themselves to a parallelized approach. We show the parallel architecture employed, the communication between computing units using MPIJava, and the benefits and pitfalls of adapting a single computer application to be used on a multi-node computing cluster.
The use of process models in the analysis, optimization and simulation of processes has proven to be extremely beneficial in the instances where they could be applied appropriately. However, the Architecture/Engineering/Construction (AEC) industries present unique challenges that complicate the modeling of their processes. A simple Engineering process model, based on the specification of Tasks, Datasets, Persons and Tools, and certain relations between them, have been developed, and its advantages over conventional techniques have been illustrated. Graph theory is used as the mathematical foundation mapping Tasks, Datasets, Persons and Tools to vertices and the relations between them to edges forming a directed graph. The acceptance of process modeling in AEC industries not only depends on the results it can provide, but the ease at which these results can be attained. Specifying a complex AEC process model is a dynamic exercise that is characterized by many modifications over the process model's lifespan. This article looks at reducing specification complexity, reducing the probability for erroneous input and allowing consistent model modification. Furthermore, the problem of resource leveling is discussed. Engineering projects are often executed with limited resources and determining the impact of such restrictions on the sequence of Tasks is important. Resource Leveling concerns itself with these restrictions caused by limited resources. This article looks at using Task shifting strategies to find a near-optimal sequence of Tasks that guarantees consistent Dataset evolution while resolving resource restrictions.
In this paper we consider three different methods for generating monogenic functions. The first one is related to Fueter's well known approach to the generation of monogenic quaternion-valued functions by means of holomorphic functions, the second one is based on the solution of hypercomplex differential equations and finally the third one is a direct series approach, based on the use of special homogeneous polynomials. We illustrate the theory by generating three different exponential functions and discuss some of their properties. Formula que se usa em preprints e artigos da nossa UI&D (acho demasiado completo): Partially supported by the R\&D unit \emph{Matem\'atica a Aplica\c\~es} (UIMA) of the University of Aveiro, through the Portuguese Foundation for Science and Technology (FCT), co-financed by the European Community fund FEDER.