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- CAD (184) (entfernen)
The Finite Element Method (FEM) is widely used in engineering for solving Partial Differential Equations (PDEs) over complex geometries. To this end, it is required to provide the FEM software with a geometric model that is typically constructed in a Computer-Aided Design (CAD) software. However, FEM and CAD use different approaches for the mathematical description of the geometry. Thus, it is required to generate a mesh, which is suitable for FEM, based on the CAD model. Nonetheless, this procedure is not a trivial task and it can be time consuming. This issue becomes more significant for solving shape and topology optimization problems, which consist in evolving the geometry iteratively. Therefore, the computational cost associated to the mesh generation process is increased exponentially for this type of applications.
The main goal of this work is to investigate the integration of CAD and CAE in shape and topology optimization. To this end, numerical tools that close the gap between design and analysis are presented. The specific objectives of this work are listed below:
• Automatize the sensitivity analysis in an isogeometric framework for applications in shape optimization. Applications for linear elasticity are considered.
• A methodology is developed for providing a direct link between the CAD model and the analysis mesh. In consequence, the sensitivity analysis can be performed in terms of the design variables located in the design model.
• The last objective is to develop an isogeometric method for shape and topological optimization. This method should take advantage of using Non-Uniform Rational B-Splines (NURBS) with higher continuity as basis functions.
Isogeometric Analysis (IGA) is a framework designed to integrate the design and analysis in engineering problems. The fundamental idea of IGA is to use the same basis functions for modeling the geometry, usually NURBS, for the approximation of the solution fields. The advantage of integrating design and analysis is two-fold. First, the analysis stage is more accurate since the system of PDEs is not solved using an approximated geometry, but the exact CAD model. Moreover, providing a direct link between the design and analysis discretizations makes possible the implementation of efficient sensitivity analysis methods. Second, the computational time is significantly reduced because the mesh generation process can be avoided.
Sensitivity analysis is essential for solving optimization problems when gradient-based optimization algorithms are employed. Automatic differentiation can compute exact gradients, automatically by tracking the algebraic operations performed on the design variables. For the automation of the sensitivity analysis, an isogeometric framework is used. Here, the analysis mesh is obtained after carrying out successive refinements, while retaining the coarse geometry for the domain design. An automatic differentiation (AD) toolbox is used to perform the sensitivity analysis. The AD toolbox takes the code for computing the objective and constraint functions as input. Then, using a source code transformation approach, it outputs a code for computing the objective and constraint functions, and their sensitivities as well. The sensitivities obtained from the sensitivity propagation method are compared with analytical sensitivities, which are computed using a full isogeometric approach.
The computational efficiency of AD is comparable to that of analytical sensitivities. However, the memory requirements are larger for AD. Therefore, AD is preferable if the memory requirements are satisfied. Automatic sensitivity analysis demonstrates its practicality since it simplifies the work of engineers and designers.
Complex geometries with sharp edges and/or holes cannot easily be described with NURBS. One solution is the use of unstructured meshes. Simplex-elements (triangles and tetrahedra for two and three dimensions respectively) are particularly useful since they can automatically parameterize a wide variety of domains. In this regard, unstructured Bézier elements, commonly used in CAD, can be employed for the exact modelling of CAD boundary representations. In two dimensions, the domain enclosed by NURBS curves is parameterized with Bézier triangles. To describe exactly the boundary of a two-dimensional CAD model, the continuity of a NURBS boundary representation is reduced to C^0. Then, the control points are used to generate a triangulation such that the boundary of the domain is identical to the initial CAD boundary representation. Thus, a direct link between the design and analysis discretizations is provided and the sensitivities can be propagated to the design domain.
In three dimensions, the initial CAD boundary representation is given as a collection of NURBS surfaces that enclose a volume. Using a mesh generator (Gmsh), a tetrahedral mesh is obtained. The original surface is reconstructed by modifying the location of the control points of the tetrahedral mesh using Bézier tetrahedral elements and a point inversion algorithm. This method offers the possibility of computing the sensitivity analysis using the analysis mesh. Then, the sensitivities can be propagated into the design discretization. To reuse the mesh originally generated, a moving Bézier tetrahedral mesh approach was implemented.
A gradient-based optimization algorithm is employed together with a sensitivity propagation procedure for the shape optimization cases. The proposed shape optimization approaches are used to solve some standard benchmark problems in structural mechanics. The results obtained show that the proposed approach can compute accurate gradients and evolve the geometry towards optimal solutions. In three dimensions, the moving mesh approach results in faster convergence in terms of computational time and avoids remeshing at each optimization step.
For considering topological changes in a CAD-based framework, an isogeometric phase-field based shape and topology optimization is developed. In this case, the diffuse interface of a phase-field variable over a design domain implicitly describes the boundaries of the geometry. The design variables are the local values of the phase-field variable. The descent direction to minimize the objective function is found by using the sensitivities of the objective function with respect to the design variables. The evolution of the phase-field is determined by solving the time dependent Allen-Cahn equation.
Especially for topology optimization problems that require C^1 continuity, such as for flexoelectric structures, the isogeometric phase field method is of great advantage. NURBS can achieve the desired continuity more efficiently than the traditional employed functions. The robustness of the method is demonstrated when applied to different geometries, boundary conditions, and material configurations. The applications illustrate that compared to piezoelectricity, the electrical performance of flexoelectric microbeams is larger under bending. In contrast, the electrical power for a structure under compression becomes larger with piezoelectricity.
In computer-aided design (CAD), industrial products are designed using a virtual 3D model. A CAD model typically consists of curves and surfaces in a parametric representation, in most cases, non-uniform rational B-splines (NURBS). The same representation is also used for the analysis, optimization and presentation of the model. In each phase of this process, different visualizations are required to provide an appropriate user feedback. Designers work with illustrative and realistic renderings, engineers need a
comprehensible visualization of the simulation results, and usability studies or product presentations benefit from using a 3D display. However, the interactive visualization of NURBS models and corresponding physical simulations is a challenging task because of the computational complexity and the limited graphics hardware support.
This thesis proposes four novel rendering approaches that improve the interactive visualization of CAD models and their analysis. The presented algorithms exploit latest graphics hardware capabilities to advance the state-of-the-art in terms of quality, efficiency and performance. In particular, two approaches describe the direct rendering of the parametric representation without precomputed approximations and timeconsuming pre-processing steps. New data structures and algorithms are presented for the efficient partition, classification, tessellation, and rendering of trimmed NURBS surfaces as well as the first direct isosurface ray-casting approach for NURBS-based isogeometric analysis. The other two approaches introduce the versatile concept of programmable order-independent semi-transparency for the illustrative and comprehensible visualization of depth-complex CAD models, and a novel method for the hybrid reprojection of opaque and semi-transparent image information to accelerate stereoscopic rendering. Both approaches are also applicable to standard polygonal geometry which contributes to the computer graphics and virtual reality research communities.
The evaluation is based on real-world NURBS-based models and simulation data. The results show that rendering can be performed directly on the underlying parametric representation with interactive frame rates and subpixel-precise image results. The computational costs of additional visualization effects, such as semi-transparency and stereoscopic rendering, are reduced to maintain interactive frame rates. The benefit of this performance gain was confirmed by quantitative measurements and a pilot user study.
It's not uncommon that analysis and simulation methods are used mainly to evaluate finished designs and to proof their quality. Whereas the potential of such methods is to lead or control a design process from the beginning on. Therefore, we introduce a design method that move away from a “what-if” forecasting philosophy and increase the focus on backcasting approaches. We use the power of computation by combining sophisticated methods to generate design with analysis methods to close the gap between analysis and synthesis of designs. For the development of a future-oriented computational design support we need to be aware of the human designer’s role. A productive combination of the excellence of human cognition with the power of modern computing technology is needed. We call this approach “cognitive design computing”. The computational part aim to mimic the way a designer’s brain works by combining state-of-the-art optimization and machine learning approaches with available simulation methods. The cognition part respects the complex nature of design problems by the provision of models for human-computation interaction. This means that a design problem is distributed between computer and designer. In the context of the conference slogan “back to command”, we ask how we may imagine the command over a cognitive design computing system. We expect that designers will need to let go control of some parts of the design process to machines, but in exchange they will get a new powerful command on complex computing processes. This means that designers have to explore the potentials of their role as commanders of partially automated design processes. In this contribution we describe an approach for the development of a future cognitive design computing system with the focus on urban design issues. The aim of this system is to enable an urban planner to treat a planning problem as a backcasting problem by defining what performance a design solution should achieve and to automatically query or generate a set of best possible solutions. This kind of computational planning process offers proof that the designer meets the original explicitly defined design requirements. A key way in which digital tools can support designers is by generating design proposals. Evolutionary multi-criteria optimization methods allow us to explore a multi-dimensional design space and provide a basis for the designer to evaluate contradicting requirements: a task urban planners are faced with frequently. We also reflect why designers will give more and more control to machines. Therefore, we investigate first approaches learn how designers use computational design support systems in combination with manual design strategies to deal with urban design problems by employing machine learning methods. By observing how designers work, it is possible to derive more complex artificial solution strategies that can help computers make better suggestions in the future.
Some caad packages offer additional support for the optimization of spatial configurations, but the possibilities for applying optimization are usually limited either by the complexity of the data model or by the constraints of the underlying caad system. Since we missed a system that allows to experiment with optimization techniques for the synthesis of spatial configurations, we developed a collection of methods over the past years. This collection is now combined in the presented open source library for computational planning synthesis, called CPlan. The aim of the library is to provide an easy to use programming framework with a flat learning curve for people with basic programming knowledge. It offers an extensible structure that allows to add new customized parts for various purposes. In this paper the existing functionality of the CPlan library is described.
Der vorliegende Text beschreibt ein computerbasiertes Verfahren zur Lösung von Layout-problemen in Architektur und Städtebau, welches mit möglichst wenig Problemwissen auskommt und schnell brauchbare Ergebnisse liefert, die durch schrittweises Hinzufügen von Problemwissen interaktiv weiter ausgearbeitet werden können. Für das generative Verfahren wurde eine Evolutions-Strategie verwendet, die mit Mechanismen zur Kollisionserkennung und virtuellen Federn zu einem hybriden Algorithmus kombiniert wurde. Dieser dient erstens der Lösung des Problems der Dichten Packung von Rechtecken sowie zweitens der Herstellung bestimmter topologischer Beziehungen zwischen diesen Rechtecken. Die Bearbeitung beider Probleme wird durch schrittweise Erweiterung grundlegender Verfahren untersucht, wobei die einzelnen Schritte anhand von Performancetests miteinander verglichen werden. Am Ende wird ein iterativer Algorithmus vorgestellt, der einerseits optimale Lösungen garantiert und andererseits diese Lösungen in einer für eine akzeptable Nutzerinteraktion ausreichenden Geschwindigkeit generiert.
Entwerfen Versionieren: Probleme und Lösungsansätze für die Organisation verteilter Entwurfsprozesse
(2011)
Entwerfen ist ein komplexer Vorgang. Soll dieser Vorgang nicht allein, sondern räumlich verteilt mit mehreren Beteiligten gemeinsam stattfinden, so sind digitale Werkzeuge zur Unterstützung dieses Prozesses unumgänglich. Die Verwendung von Werkzeugen für Ent-wurfsprozesse bedeutet jedoch immer auch eine Manipulation des zu unterstützenden Prozesses selbst. Im Falle von Werkzeugen zur Unterstützung der Kollaboration mehrerer Beteiligter stellen die implementierten Koordinationsmechanismen solche prozessbeeinflussenden Faktoren dar. Damit diese Mechanismen, entsprechend der Charakteristika kreativer Prozesse, so flexibel wie möglich gestaltet werden können, liegt die Anforderung auf technischer Ebene darin, ein geeignetes Konzept für eine nachvollziehbare Speicherung (Versionierung) der stattfindenden Entwurfshandlungen zu schaffen. Der vorliegende Artikel beschäftigt sich mit dem Thema der Entwurfsversionierung in computergestützten kollaborativen Arbeitsumgebungen. Vor dem Hintergrund, dass die Versionierung den kreativen Entwurfsprozess möglichst wenig manipulieren soll, werden technische sowie konzeptionelle Probleme der diskutiert und Lösungsansätze für diese vorgestellt.
This work is based on the concept that the structure of a city can be defined by six basic urban patterns. To enable more complex urban planning as a long-term objective I have developed a simulation method for generating these basic patterns and for combining them to form various structures. The generative process starts with the two-dimensional organisation of streets followed by the parceling of the remaining areas. An agent-based diffusion-contact model is the basis of these first two steps. Then, with the help of cellular automata, the sites for building on are defined and a three-dimensional building structure is derived. I illustrate the proposed method by showing how it can be applied to generate possible structures for an urban area in the city of Munich.
Nähert man sich der Frage nach den Zusammenhängen zwischen Strukturalismus und generativen algorithmischen Planungsmethoden, so ist zunächst zu klären, was man unter Strukturalismus in der Architektur versteht. Allerdings gibt es letztlich keinen verbindlichen terminologischen Rahmen, innerhalb dessen sich eine solche Klärung vollziehen könnte. Strukturalismus in der Architektur wird oftmals auf ein formales Phänomen und damit auf eine Stilfrage reduziert. Der vorliegende Text will sich nicht mit Stilen und Phänomenen strukturalistischer Architektur auseinandersetzen, sondern konzentriert sich auf die Betrachtung strukturalistischer Entwurfsmethoden und stellt Bezüge her zu algorithmischen Verfahren, wobei das Zusammenspiel zwischen regelgeleitetem und intuitivem Vorgehen beim Entwerfen herausgearbeitet wird.
Im vorliegenden Beitrag wird ein Framework für ein verteiltes dynamisches Produktmodell (FREAC) vorgestellt, welches der experimentellen Softwareentwicklung dient. Bei der Entwicklung von FREAC wurde versucht, folgende Eigenschaften umzusetzen, die bei herkömmlichen Systemen weitgehend fehlen: Erstens eine hohe Flexibilität, also eine möglichst hohe Anpassbarkeit für unterschiedliche Fachdisziplinen; Zweitens die Möglichkeit, verschiedene Tools nahtlos miteinander zu verknüpfen; Drittens die verteilte Modellbearbeitung in Echtzeit; Viertens das Abspeichern des gesamten Modell-Bearbeitungsprozesses; Fünftens eine dynamische Erweiterbarkeit sowohl für Softwareentwickler, als auch für die Nutzer der Tools. Die Bezeichnung FREAC umfasst sowohl das Framework zur Entwicklung und Pflege eines Produktmodells (FREAC-Development) als auch die entwickelten Tools selbst (FREAC-Tools).
Architektur wird vorwiegend über die den Raum begrenzenden Oberflächen wahrgenommen. Das Oberflächenmaterial kann daher mit seinen sinnlichen Eigenschaften die Entwurfsintention unterstützen, zugleich muss es aber auch zahlreiche technische, ökonomische und ökologische Anforderungen erfüllen. Materialwahl in der Architektur bedeutet somit das Abwägen einer Vielzahl von Parametern, die sich sowohl inhaltlich als auch hinsichtlich ihrer Relevanz stark unterscheiden. Die Entscheidung für ein Material kann dabei durch verschiedene analoge und digitale Ansätze unterstützt werden. Die vorhandenen Systeme sind jedoch allesamt begrenzt: in den von ihnen berücksichtigten Aspekten, den möglichen Suchwegen oder ihren Inhalten. Keines der in dieser Arbeit untersuchten Systeme berücksichtigt zudem die unterschiedliche Wichtigkeit oder gegenseitige Abhängigkeiten und Unschärfen der in die Materialwahl einfließenden Kriterien. Die vorliegende Arbeit formuliert daher eine Gesamtstrategie zur besseren Unterstützung der Entscheidung für ein Oberflächenmaterial. Im Wesentlichen wird dabei eine Methode vorgestellt, wie die inhaltlich höchst unterschiedlichen Kriterien, welche Einfluss auf die Materialwahl ausüben, mit ihrer jeweiligen Relevanz gegeneinander in Ansatz gebracht werden können, um eine umfassende Bewertung der Materialalternativen zu ermöglichen. In einem zweiten Schritt wird mit Multidimensional Scaling eine Technik der Informationsvisualisierung benutzt, die eine zusätzliche Unterstützung durch weitere Analysemöglichkeiten und andere Suchwege eröffnet. Das vorgeschlagene Verfahren ist in einem Software-Prototyp umgesetzt. Die Arbeit leistet damit einen Beitrag, die Auswahl eines geeigneten Materials in der Architektur zu erleichtern, diese Entscheidung plausibel begründen zu können und den Weg der Entscheidungsfindung nachvollziehbar werden zu lassen.