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Inhaltlich beschäftigt sich die Arbeit, die im Rahmen des Promotionsstudiengangs Kunst und Gestaltung an der Bauhaus-Universität entstand, mit der Erforschung sozio-interaktiver Potentiale der Videotelefonie im Kontext von Nähe und Verbundenheit mit Fokus auf Eigenbild, Embodiment sowie den Rederechtswechsel.
Die Videotelefonie als Kommunikationsform hat sich – und darauf deuten die Erfahrungen der Co- vid-19-Pandemie hin – im lebensweltlichen Alltag der Menschen etabliert und wird dort in naher Zukunft nicht mehr wegzudenken sein. Auf Basis ihrer Möglichkeiten und Errungenschaften ist es inzwischen Realität und Lebenswirklichkeit, dass die Kommunikation sowohl im privaten als auch im geschäftlichen Kontext mittels verschiedenster Kanäle stattfindet. Der Videotelefonie kommt hierbei als solche nicht nur eine tragende Funktion, sondern auch eine herausragende Rolle bei der vermeintlichen Reproduktion der Face-to-Face-Kommunikation im digitalen Raum zu und wird wie selbstverständlich zum zwischenmenschlichen Austausch genutzt. Just an diesem Punkt knüpft die Forschungsarbeit an. Zentral stand dabei das Vorhaben einer dezidierte Untersuchung des Forschungsgegenstandes Videotelefonie, sowohl aus Kultur- als auch Technikhistorischer, aber auch Medien-, Wahrnehmungs- wie Kommunikations- theoretischer Perspektive, indem analytische und phänosemiotische Perspektiven miteinander in Beziehung gesetzt werden (z.B. Wahrnehmungsbedingungen, Interaktionsmerkmale, realisierte Kommunikationsprozesse etc.). Damit verbundenes, wünschenswertes Ziel war es, eine möglichst zeitgemäße wie relevante Forschungsfrage zu adressieren, die neben den kulturellen Technisierungs- und Mediatisierungstendenzen in institutionellen und privaten Milieus ebenfalls eine conditio sine qua non der pandemischen (Massen-)Kommunikation entwirft.
Die Arbeit ist damit vor allem im Bereich des Produkt- und Interactiondesigns zu verorten. Darüber hinaus hatte sie das Ziel der Darlegung und Begründung der Videotelefonie als eigenständige Kommunikationsform, welche durch eigene, kommunikative Besonderheiten, die sich in ihrer jeweiligen Ingebrauchnahme sowie durch spezielle Wahrnehmungsbedingungen äußern, und die die Videotelefonie als »Rederechtswechselmedium« avant la lettre konsolidieren, gekennzeichnet ist. Dabei sollte der Beweis erbracht werden, dass die Videotelefonie nicht als Schwundstufe einer Kommunikation Face-to-Face, sondern als ein eigenständiges Mediatisierungs- und Kommunikationsereignis zu verstehen sei. Und eben nicht als eine beliebige – sich linear vom Telefon ausgehende – entwickelte Form der audio-visuellen Fernkommunikation darstellt, sondern die gestalterische (Bewegtbild-)Technizität ein eigenständiges Funktionsmaß offeriert, welches wiederum ein innovatives Kommunikationsmilieu im Kontext einer Rederechtswechsel-Medialität stabilisiert.
The computational costs of newly developed numerical simulation play a critical role in their acceptance within both academic use and industrial employment. Normally, the refinement of a method in the area of interest reduces the computational cost. This is unfortunately not true for most nonlocal simulation, since refinement typically increases the size of the material point neighborhood. Reducing the discretization size while keep- ing the neighborhood size will often require extra consideration. Peridy- namic (PD) is a newly developed numerical method with nonlocal nature. Its straightforward integral form equation of motion allows simulating dy- namic problems without any extra consideration required. The formation of crack and its propagation is known as natural to peridynamic. This means that discontinuity is a result of the simulation and does not demand any post-processing. As with other nonlocal methods, PD is considered an expensive method. The refinement of the nodal spacing while keeping the neighborhood size (i.e., horizon radius) constant, emerges to several nonphysical phenomena.
This research aims to reduce the peridynamic computational and imple- mentation costs. A novel refinement approach is introduced. The pro- posed approach takes advantage of the PD flexibility in choosing the shape of the horizon by introducing multiple domains (with no intersections) to the nodes of the refinement zone. It will be shown that no ghost forces will be created when changing the horizon sizes in both subdomains. The approach is applied to both bond-based and state-based peridynamic and verified for a simple wave propagation refinement problem illustrating the efficiency of the method. Further development of the method for higher dimensions proves to have a direct relationship with the mesh sensitivity of the PD. A method for solving the mesh sensitivity of the PD is intro- duced. The application of the method will be examined by solving a crack propagation problem similar to those reported in the literature.
New software architecture is proposed considering both academic and in- dustrial use. The available simulation tools for employing PD will be collected, and their advantages and drawbacks will be addressed. The challenges of implementing any node base nonlocal methods while max- imizing the software flexibility to further development and modification
will be discussed and addressed. A software named Relation-Based Sim- ulator (RBS) is developed for examining the proposed architecture. The exceptional capabilities of RBS will be explored by simulating three dis- tinguished models. RBS is available publicly and open to further develop- ment. The industrial acceptance of the RBS will be tested by targeting its performance on one Mac and two Linux distributions.
The computational costs of newly developed numerical simulation play a critical role in their acceptance within both academic use and industrial employment. Normally, the refinement of a method in the area of interest reduces the computational cost. This is unfortunately not true for most nonlocal simulation, since refinement typically increases the size of the material point neighborhood. Reducing the discretization size while keep- ing the neighborhood size will often require extra consideration. Peridynamic (PD) is a newly developed numerical method with nonlocal nature. Its straightforward integral form equation of motion allows simulating dynamic problems without any extra consideration required. The formation of crack and its propagation is known as natural to peridynamic. This means that discontinuity is a result of the simulation and does not demand any post-processing. As with other nonlocal methods, PD is considered an expensive method. The refinement of the nodal spacing while keeping the neighborhood size (i.e., horizon radius) constant, emerges to several nonphysical phenomena.
This research aims to reduce the peridynamic computational and imple- mentation costs. A novel refinement approach is introduced. The pro- posed approach takes advantage of the PD flexibility in choosing the shape of the horizon by introducing multiple domains (with no intersections) to the nodes of the refinement zone. It will be shown that no ghost forces will be created when changing the horizon sizes in both subdomains. The approach is applied to both bond-based and state-based peridynamic and verified for a simple wave propagation refinement problem illustrating the efficiency of the method. Further development of the method for higher dimensions proves to have a direct relationship with the mesh sensitivity of the PD. A method for solving the mesh sensitivity of the PD is intro- duced. The application of the method will be examined by solving a crack propagation problem similar to those reported in the literature.
New software architecture is proposed considering both academic and in- dustrial use. The available simulation tools for employing PD will be collected, and their advantages and drawbacks will be addressed. The challenges of implementing any node base nonlocal methods while max- imizing the software flexibility to further development and modification will be discussed and addressed. A software named Relation-Based Sim- ulator (RBS) is developed for examining the proposed architecture. The exceptional capabilities of RBS will be explored by simulating three distinguished models. RBS is available publicly and open to further develop- ment. The industrial acceptance of the RBS will be tested by targeting its performance on one Mac and two Linux distributions.
With the growing importance of the World Wide Web, the major challenges our society faces are also increasingly affecting the digital areas of our lives. Some of the associated problems can be addressed by computer science, and some of these specifically by data-driven research. To do so, however, requires to solve open issues related to archive quality and the large volume and variety of the data contained.
This dissertation contributes data, algorithms, and concepts towards leveraging the big data and temporal provenance capabilities of web archives to tackle societal challenges. We selected three such challenges that highlight the central issues of archive quality, data volume, and data variety, respectively:
(1) For the preservation of digital culture, this thesis investigates and improves the automatic quality assurance of the web page archiving process, as well as the further processing of the resulting archive data for automatic analysis.
(2) For the critical assessment of information, this thesis examines large datasets of Wikipedia and news articles and presents new methods for automatically determining quality and bias.
(3) For digital security and privacy, this thesis exploits the variety of content on the web to quantify the security of mnemonic passwords and analyzes the privacy-aware re-finding of the various seen content through private web archives.
The growing complexity of modern engineering problems necessitates development of advanced numerical methods. In particular, methods working directly with discrete structures, and thus, representing exactly some important properties of the solution on a lattice and not just approximating the continuous properties, become more and more popular nowadays. Among others, discrete potential theory and discrete function theory provide a variety of methods, which are discrete counterparts of the classical continuous methods for solving boundary value problems. A lot of results related to the discrete potential and function theories have been presented in recent years. However, these results are related to the discrete theories constructed on square lattices, and, thus, limiting their practical applicability and
potentially leading to higher computational costs while discretising realistic domains.
This thesis presents an extension of the discrete potential theory and discrete function theory to rectangular lattices. As usual in the discrete theories, construction of discrete operators is strongly influenced by a definition of discrete geometric setting. For providing consistent constructions throughout the whole thesis, a detailed discussion on the discrete geometric setting is presented in the beginning. After that, the discrete fundamental solution of the discrete Laplace operator on a rectangular lattice, which is the core of the discrete potential theory, its numerical analysis, and practical calculations are presented. By using the discrete fundamental solution of the discrete Laplace operator on a rectangular lattice, the discrete potential theory is then constructed for interior and exterior settings. Several discrete interior and exterior boundary value problems are then solved. Moreover, discrete transmission problems are introduced and several numerical examples of these problems are discussed. Finally, a discrete fundamental solution of the discrete Cauchy-Riemann operator on a rectangular lattice is constructed, and basics of the discrete function theory on a rectangular lattice are provided. This work indicates that the discrete theories provide
solution methods with very good numerical properties to tackle various boundary value problems, as well as transmission problems coupling interior and exterior problems. The results presented in this thesis provide a basis for further development of discrete theories on irregular lattices.
In recent years, lightweight materials, such as polymer composite materials (PNCs) have been studied and developed due to their excellent physical and chemical properties. Structures composed of these composite materials are widely used in aerospace engineering structures, automotive components, and electrical devices. The excellent and outstanding mechanical, thermal, and electrical properties of Carbon nanotube (CNT) make it an ideal filler to strengthen polymer materials’ comparable properties. The heat transfer of composite materials has very promising engineering applications in many fields, especially in electronic devices and energy storage equipment. It is essential in high-energy density systems since electronic components need heat dissipation functionality. Or in other words, in electronic devices the generated heat should ideally be dissipated by light and small heat sinks.
Polymeric composites consist of fillers embedded in a polymer matrix, the first ones will significantly affect the overall (macroscopic) performance of the material. There are many common carbon-based fillers such as single-walled carbon nanotubes (SWCNT), multi-walled carbon nanotubes (MWCNT), carbon nanobuds (CNB), fullerene, and graphene. Additives inside the matrix have become a popular subject for researchers. Some extraordinary characters, such as high-performance load, lightweight design, excellent chemical resistance, easy processing, and heat transfer, make the design of polymeric nanotube composites (PNCs) flexible. Due to the reinforcing effects with different fillers on composite materials, it has a higher degree of freedom and can be designed for the structure according to specific applications’ needs. As already stated, our research focus will be on SWCNT enhanced PNCs. Since experiments are timeconsuming, sometimes expensive and cannot shed light into phenomena taking place for instance at the interfaces/interphases of composites, they are often complemented through theoretical and computational analysis.
While most studies are based on deterministic approaches, there is a comparatively lower number of stochastic methods accounting for uncertainties in the input parameters. In deterministic models, the output of the model is fully determined by the parameter values and the initial conditions. However, uncertainties in the input parameters such as aspect ratio, volume fraction, thermal properties of fiber and matrix need to be taken into account for reliable predictions. In this research, a stochastic multiscale method is provided to study the influence of numerous uncertain input parameters on the thermal conductivity of the composite. Therefore, a hierarchical multi-scale method based on computational homogenization is presented in to predict the macroscopic thermal conductivity based on the fine-scale structure. In order to study the inner mechanism, we use the finite element method and employ surrogate models to conduct a Global Sensitivity Analysis (GSA). The SA is performed in order to quantify the influence of the conductivity of the fiber, matrix, Kapitza resistance, volume fraction and aspect ratio on the macroscopic conductivity. Therefore, we compute first-order and total-effect sensitivity indices with different surrogate models.
As stochastic multiscale models are computational expensive, surrogate approaches are commonly exploited. With the emergence of high performance computing and artificial intelligence, machine learning has become a popular modeling tool for numerous applications. Machine learning (ML) is commonly used in regression and maps data through specific rules with algorithms to build input and output models. They are particularly useful for nonlinear input-output relationships when sufficient data is available. ML has also been used in the design of new materials and multiscale analysis. For instance, Artificial neural networks and integrated learning seem to be ideally for such a task. They can theoretically simulate any non-linear relationship through the connection of neurons. Mapping relationships are employed to carry out data-driven simulations of inputs and outputs in stochastic modeling.
This research aims to develop a stochastic multi-scale computational models of PNCs in heat transfer. Multi-scale stochastic modeling with uncertainty analysis and machine learning methods consist of the following components:
-Uncertainty Analysis. A surrogate based global sensitivity analysis is coupled with a hierarchical multi-scale method employing computational homogenization. The effect of the conductivity of the fibers and the matrix, the Kapitza resistance, volume fraction and aspect ratio on the ’macroscopic’ conductivity of the composite is systematically studied. All selected surrogate models yield consistently the conclusions that the most influential input parameters are the aspect ratio followed by the volume fraction. The Kapitza Resistance has no significant effect on the thermal conductivity of the PNCs. The most accurate surrogate model in terms of the R2 value is the moving least square (MLS).
-Hybrid Machine Learning Algorithms. A combination of artificial neural network (ANN) and particle swarm optimization (PSO) is applied to estimate the relationship between variable input and output parameters. The ANN is used for modeling the composite while PSO improves the prediction performance through an optimized global minimum search. The thermal conductivity of the fibers and the matrix, the kapitza resistance, volume fraction and aspect ratio are selected as input parameters. The output is the macroscopic (homogenized) thermal conductivity of the composite. The results show that the PSO significantly improves the predictive ability of this hybrid intelligent algorithm, which outperforms traditional neural networks.
-Stochastic Integrated Machine Learning. A stochastic integrated machine learning based multiscale approach for the prediction of the macroscopic thermal conductivity in PNCs is developed. Seven types of machine learning models are exploited in this research, namely Multivariate Adaptive Regression Splines (MARS), Support Vector Machine (SVM), Regression Tree (RT), Bagging Tree (Bag), Random Forest (RF), Gradient Boosting Machine (GBM) and Cubist. They are used as components of stochastic modeling to construct the relationship between the variable of the inputs’ uncertainty and the macroscopic thermal conductivity of PNCs. Particle Swarm Optimization (PSO) is used for hyper-parameter tuning to find the global optimal values leading to a significant reduction in the computational cost. The advantages and disadvantages of various methods are also analyzed in terms of computing time and model complexity to finally give a recommendation for the applicability of different models.
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.
Numerical simulation of physical phenomena, like electro-magnetics, structural and fluid mechanics is essential for the cost- and time-efficient development of mechanical products at high quality. It allows to investigate the behavior of a product or a system far before the first prototype of a product is manufactured.
This thesis addresses the simulation of contact mechanics. Mechanical contacts appear in nearly every product of mechanical engineering. Gearboxes, roller bearings, valves and pumps are only some examples. Simulating these systems not only for the maximal/minimal stresses and strains but for the stress-distribution in case of tribo-contacts is a challenging task from a numerical point of view.
Classical procedures like the Finite Element Method suffer from the nonsmooth representation of contact surfaces with discrete Lagrange elements. On the one hand, an error due to the approximate description of the surface is introduced. On the other hand it is difficult to attain a robust contact search because surface normals can not be described in a unique form at element edges.
This thesis introduces therefore a novel approach, the adaptive isogeometric contact formulation based on polynomial Splines over hierarchical T-meshes (PHT-Splines), for the approximate solution of the non-linear contact problem. It provides a more accurate, robust and efficient solution compared to conventional methods. During the development of this method the focus was laid on the solution of static contact problems without friction in 2D and 3D in which the structures undergo small deformations.
The mathematical description of the problem entails a system of partial differential equations and boundary conditions which model the linear elastic behaviour of continua. Additionally, it comprises side conditions, the Karush-Kuhn-Tuckerconditions, to prevent the contacting structures from non-physical penetration. The mathematical model must be transformed into its integral form for approximation of the solution. Employing a penalty method, contact constraints are incorporated by adding the resulting equations in weak form to the overall set of equations. For an efficient space discretization of the bulk and especially the contact boundary of the structures, the principle of Isogeometric Analysis (IGA) is applied. Isogeometric Finite Element Methods provide several advantages over conventional Finite Element discretization. Surface approximation with Non-Uniform Rational B-Splines (NURBS) allow a robust numerical solution of the contact problem with high accuracy in terms of an exact geometry description including the surface smoothness.
The numerical evaluation of the contact integral is challenging due to generally non-conforming meshes of the contacting structures. In this work the highly accurate Mortar Method is applied in the isogeometric setting for the evaluation of contact contributions. This leads to an algebraic system of equations that is linearized and solved in sequential steps. This procedure is known as the Newton Raphson Method. Based on numerical examples, the advantages of the isogeometric approach
with classical refinement strategies, like the p- and h-refinement, are shown and the influence of relevant algorithmic parameters on the approximate solution of the contact problem is verified. One drawback of the Spline approximations of stresses though is that they lack accuracy at the contact edge where the structures change their boundary from contact to no contact and where the solution features a kink. The approximation with smooth Spline functions yields numerical artefacts in the form of non-physical oscillations.
This property of the numerical solution is not only a drawback for the
simulation of e.g. tribological contacts, it also influences the convergence properties of iterative solution procedures negatively. Hence, the NURBS discretized geometries are transformed to Polynomial Splines over Hierarchical T-meshes (PHT-Splines), for the local refinement along contact edges to reduce the artefact of pressure oscillations. NURBS have a tensor product structure which does not allow to refine only certain parts of the geometrical domain while leaving other parts unchanged. Due to the Bézier Extraction, lying behind the transformation from NURBS to PHT-Splines, the connected mesh structure is broken up into separate elements. This allows an efficient local refinement along the contact edge.
Before single elements are refined in a hierarchical form with cross-insertion, existing basis functions must be modified or eliminated. This process of truncation assures local and global linear independence of the refined basis which is needed for a unique approximate solution. The contact boundary is a priori unknown. Local refinement along the contact edge, especially for 3D problems, is for this reason not straight forward. In this work the use of an a posteriori error estimation procedure, the Super Convergent Recovery Solution Based Error Estimation Scheme, together with the Dörfler Marking Method is suggested for the spatial search of the contact edge.
Numerical examples show that the developed method improves the quality of solutions along the contact edge significantly compared to NURBS based approximate solutions. Also, the error in maximum contact pressures, which correlates with the pressure artefacts, is minimized by the adaptive local refinement.
In a final step the practicability of the developed solution algorithm is verified by an industrial application: The highly loaded mechanical contact between roller and cam in the drive train of a high-pressure fuel pump is considered.
The objective of this thesis was to understand the 20th-century history of informal urbanisation in Europe and its origins in Madrid and Paris. The concept of informal urbanisation was employed to refer to the process of developing shacks and precarious single-family housing areas that were not planned by the public powers and were considered to be substandard because of their below-average materials and social characteristics. Our main hypothesis was that despite being a phenomenon with ancient roots, informal urbanisation emerged as a public problem and was subsequently prohibited in connection with another historical process occurred: the birth of contemporary urban planning. Therefore, its transformation into a deviant and illegal urban growth mechanism would have been a pan-European process occurring at the same pace that urban planning developed during the first decades of the 20th century.
Analysing the 20th-century history of informal urbanisation in Europe was an ambitious task that required using a large number of sources. To contend with this issue, this thesis combined two main methods: historiographical research about informal urbanisation in Europe and archival research of two case studies, Madrid and Paris, to make the account more precise by analysing primary sources of the subject.
Our research of these informal areas, which were produced mainly through poor private allotments and housing developed on land squats, revealed two key moments of explosive growth across Europe: the 1920s and 1960s. The near disappearance of informal urbanisation throughout the continent seemed to be a consequence not of the historical development of urban planning—which was commonly transgressed and bypassed—but of the exacerbation of global economic inequalities, permitting the development of a geography of privilege in Europe.
Concerning the cases of Paris and Madrid, the origins of informal urbanisation—that is, the moment the issue started to be problematised—seemed to occur in the second half of the 19th century, when a number of hygienic norms and surveillance devices began to control housing characteristics. From that moment onwards, informal urbanisation areas formed peripheral belts in both cities. This growth became the object of an illegalisation process of which we have identified three phases: (i) the unregulated development of the phenomenon during the second half of the 20th century, (ii) the institutional production of “exception regulations” to permit a controlled development of substandard housing in the peripheral fringes of both cities, and (iii) the synchronic prohibition of informal urbanisation in the 1920s and its illegal reproduction.
Analysis of Functionally Graded Porous Materials Using Deep Energy Method and Analytical Solution
(2022)
Porous materials are an emerging branch of engineering materials that are composed of two elements: One element is a solid (matrix), and the other element is either liquid or gas. Pores can be distributed within the solid matrix of porous materials with different shapes and sizes. In addition, porous materials are lightweight, and flexible, and have higher resistance to crack propagation and specific thermal, mechanical, and magnetic properties. These properties are necessary for manufacturing engineering structures such as beams and other engineering structures. These materials are widely used in solid mechanics and are considered a good replacement for classical materials by many researchers recently. Producing lightweight materials has been developed because of the possibility of exploiting the properties of these materials. Various types of porous material are generated naturally or artificially for a specific application such as bones and foams. Like functionally graded materials, pore distribution patterns can be uniform or non-uniform. Biot’s theory is a well-developed theory to study the behavior of poroelastic materials which investigates the interaction between fluid and solid phases of a fluid-saturated porous medium.
Functionally graded porous materials (FGPM) are widely used in modern industries, such as aerospace, automotive, and biomechanics. These advanced materials have some specific properties compared to materials with a classic structure. They are extremely light, while they have specific strength in mechanical and high-temperature environments. FGPMs are characterized by a gradual variation of material parameters over the volume. Although these materials can be made naturally, it is possible to design and manufacture them for a specific application. Therefore, many studies have been done to analyze the mechanical and thermal properties of FGPM structures, especially beams.
Biot was the pioneer in formulating the linear elasticity and thermoelasticity equations of porous material. Since then, Biot's formulation has been developed in continuum mechanics which is named poroelasticity. There are obstacles to analyzing the behavior of these materials accurately like the shape of the pores, the distribution of pores in the material, and the behavior of the fluid (or gas) that saturated pores. Indeed, most of the engineering structures made of FGPM have nonlinear governing equations. Therefore, it is difficult to study engineering structures by solving these complicated equations.
The main purpose of this dissertation is to analyze porous materials in engineering structures. For this purpose, the complex equations of porous materials have been simplified and applied to engineering problems so that the effect of all parameters of porous materials on the behavior of engineering structure has been investigated.
The effect of important parameters of porous materials on beam behavior including pores compressibility, porosity distribution, thermal expansion of fluid within pores, the interaction of stresses between pores and material matrix due to temperature increase, effects of pore size, material thickness, and saturated pores with fluid and unsaturated conditions are investigated.
Two methods, the deep energy method, and the exact solution have been used to reduce the problem hypotheses, increase accuracy, increase processing speed, and apply these in engineering structures. In both methods, they are analyzed nonlinear and complex equations of porous materials.
To increase the accuracy of analysis and study of the effect of shear forces, Timoshenko and Reddy's beam theories have been used. Also, neural networks such as residual and fully connected networks are designed to have high accuracy and less processing time than other computational methods.