Computational Architecture: development, design and optimization. Case study of a glass and steel roof for the Scuola Normale Superiore's courtyard in Pisa

This thesis is built around the conception, development and optimization of complex architecture, also known as free form. The project consists in a steel and glass roof over the inner courtyard of the Scuola Normale Superiore, with the aim to make the living space accessible at every moment of day life. The shape was conceived such that it would suit well the architecture of the Scuola Normale and the spirit it emobdies, with a special regard to energetics and fabrication, true weakness of architectures of this kind. The structure was modelled entirely on Grasshopper, a Rhino3D plug-in which allows to parametrically design objects. This programming environment allowed to interface add-ons, both proprietary and made on purpose by the author. With those tools, the author was able to develop algorithms for structural and geometric optimization. The former consisted in the process at the end of which the best structural performance is found, at constant weight: in the case studym genetic algorithms and iterative processes were used. Geometric optimization consisted in seeking the fabricability of the architecture, in the reduction of overall panel curvatures and eventually in the panelization of the surface. Finally, thanks to the code so created, it was possible to easily export all data and run required analysis exploiting the software more suited for each needing

PTAF Polygon Tessellation to Approximate Frame. A Method for the Design and Analysis of Complex Frames

Complex frames are difficult to model because there are so many elements and redundant load paths. In order to explore the realm of complex frames, there needs to be a technique for approximate modelling to allow for rapid analysis with dependable accuracy. This thesis proposes the Polygon Tessellation to Approximate Frame (PTAF) method for rapid structural analysis of the Living Architecture Systems (LAS) group’s complex frames. The PTAF method uses the LAS composition design polygons as inputs for a parametric script that generates a simplified frame model. This model can be used for Finite Element Analysis (FEA) because it has perfect connectivity. By simplifying the model, the analysis can be run quickly on conventional computer hardware. In this way, structural performance can be evaluated without significant time investment. Especially in the early stages of the design process, it is important to quickly receive reasonably accurate predictions of performance because the design is constantly evolving. To simplify the model, each component of the frame are reduced to a few beam elements that closely approximate the behaviour of much more detailed models. The process of linear FEA relates the force exerted on a model to the displacement it will undergo by its stiffness. The detailed and coarse models were subjected to the same support and loading conditions so that the displacement could be measured, and a function of error between the two displacements could be made. By minimizing the error between detailed and course models, values for the equivalent stiffness of each component can be derived. By enforcing continuity, the behaviour at the component scale can be used to predict behaviour at the global scale. In this way, the global simplified model will approximate the behaviour of the frame. This research started through a collaboration with the LAS on the Amatria installation at Luddy Hall. The goal of the collaboration was to add value to the project through the addition of structural analysis in the design process. The frame of Amatria was immensely complex, full analysis of the frame would be prohibitively expensive, and add an unreasonable amount of time to the design process. This research was able to benefit the project by analyzing key components to ensure adequate strength and stiffness to facilitate ease of construction. Lessons learned from this projected helped inform this method’s development. This research provided the possibility of self-supporting LAS structures, based on the system of components currently being used in LAS testbeds. A pavilion study was used as a thought experiment of how the combination of parametric modeling and approximate analysis could be used to design a free standing pavilion with LAS component construction. Participation in future testbeds will undoubtedly provide invaluable information to refine this method

Designing efficient grid structures considering structural imperfection sensitivity

At the initial design stage of a grid structure, shape optimisation is an effective way to find the optimal structural form. However, most of the shape optimisation methods do not take into consideration the imperfections, thus the actual buckling load capacity of the optimised structure is usually low. In this paper, an improved shape optimisation method is proposed, one that is considering the effect of structural imperfection sensitivity. In this method, the bending strain energy ratio is taken as a constraint, and when the total strain energy decreases, yet there is a certain proportion of bending strain energy in the structure. Consequently, the resulted shape is not sensitive to the initial geometry imperfection, and therefore, an efficient structure with higher buckling load capacity and low imperfection sensitivity is obtained. In order to evaluate the redundancy performance of the optimised structure, an index called structural overall redundancy, based on damage model is proposed herein. The damage model is simulated by removing a key rod of the structure. The results demonstrate that the overall redundancy of the structure obtained by the proposed method is higher than that obtained by the traditional method, thus an optimal design of a grid structure is obtained

Performance Assessment Strategies

Using engineering performance evaluations to explore design alternatives during the conceptual phase of architectural design helps to understand the relationships between form and performance; and is crucial for developing well-performing final designs. Computer aided conceptual design has the potential to aid the design team in discovering and highlighting these relationships; especially by means of procedural and parametric geometry to support the generation of geometric design, and building performance simulation tools to support performance assessments. However, current tools and methods for computer aided conceptual design in architecture do not explicitly reveal nor allow for backtracking the relationships between performance and geometry of the design. They currently support post-engineering, rather than the early design decisions and the design exploration process. Focusing on large roofs, this research aims at developing a computational design approach to support designers in performance driven explorations. The approach is meant to facilitate the multidisciplinary integration and the learning process of the designer; and not to constrain the process in precompiled procedures or in hard engineering formulations, nor to automatize it by delegating the design creativity to computational procedures. PAS (Performance Assessment Strategies) as a method is the main output of the research. It consists of a framework including guidelines and an extensible library of procedures for parametric modelling. It is structured on three parts. Pre-PAS provides guidelines for a design strategy-definition, toward the parameterization process. Model-PAS provides guidelines, procedures and scripts for building the parametric models. Explore-PAS supports the solutions-assessment based on numeric evaluations and performance simulations, until the identification of a suitable design solution. PAS has been developed based on action research. Several case studies have focused on each step of PAS and on their interrelationships. The relations between the knowledge available in pre-PAS and the challenges of the solution space exploration in explore-PAS have been highlighted. In order to facilitate the explore-PAS phase in case of large solution spaces, the support of genetic algorithms has been investigated and the exiting method ParaGen has been further implemented. Final case studies have focused on the potentials of ParaGen to identify well performing solutions; to extract knowledge during explore-PAS; and to allow interventions of the designer as an alternative to generations driven solely by coded criteria. Both the use of PAS and its recommended future developments are addressed in the thesis

Performance Assessment Strategies:

Using engineering performance evaluations to explore design alternatives during the conceptual phase of architectural design helps to understand the relationships between form and performance; and is crucial for developing well-performing final designs. Computer aided conceptual design has the potential to aid the design team in discovering and highlighting these relationships; especially by means of procedural and parametric geometry to support the generation of geometric design, and building performance simulation tools to support performance assessments. However, current tools and methods for computer aided conceptual design in architecture do not explicitly reveal nor allow for backtracking the relationships between performance and geometry of the design. They currently support post-engineering, rather than the early design decisions and the design exploration process. Focusing on large roofs, this research aims at developing a computational design approach to support designers in performance driven explorations. The approach is meant to facilitate the multidisciplinary integration and the learning process of the designer; and not to constrain the process in precompiled procedures or in hard engineering formulations, nor to automatize it by delegating the design creativity to computational procedures. PAS (Performance Assessment Strategies) as a method is the main output of the research. It consists of a framework including guidelines and an extensible library of procedures for parametric modelling. It is structured on three parts. Pre-PAS provides guidelines for a design strategy-definition, toward the parameterization process. Model-PAS provides guidelines, procedures and scripts for building the parametric models. Explore-PAS supports the solutions-assessment based on numeric evaluations and performance simulations, until the identification of a suitable design solution. PAS has been developed based on action research. Several case studies have focused on each step of PAS and on their interrelationships. The relations between the knowledge available in pre-PAS and the challenges of the solution space exploration in explore-PAS have been highlighted. In order to facilitate the explore-PAS phase in case of large solution spaces, the support of genetic algorithms has been investigated and the exiting method ParaGen has been further implemented. Final case studies have focused on the potentials of ParaGen to identify well performing solutions; to extract knowledge during explore-PAS; and to allow interventions of the designer as an alternative to generations driven solely by coded criteria. Both the use of PAS and its recommended future developments are addressed in the thesis

Performance Assessment Strategies:

Using engineering performance evaluations to explore design alternatives during the conceptual phase of architectural design helps to understand the relationships between form and performance; and is crucial for developing well-performing final designs. Computer aided conceptual design has the potential to aid the design team in discovering and highlighting these relationships; especially by means of procedural and parametric geometry to support the generation of geometric design, and building performance simulation tools to support performance assessments. However, current tools and methods for computer aided conceptual design in architecture do not explicitly reveal nor allow for backtracking the relationships between performance and geometry of the design. They currently support post-engineering, rather than the early design decisions and the design exploration process. Focusing on large roofs, this research aims at developing a computational design approach to support designers in performance driven explorations. The approach is meant to facilitate the multidisciplinary integration and the learning process of the designer; and not to constrain the process in precompiled procedures or in hard engineering formulations, nor to automatize it by delegating the design creativity to computational procedures. PAS (Performance Assessment Strategies) as a method is the main output of the research. It consists of a framework including guidelines and an extensible library of procedures for parametric modelling. It is structured on three parts. Pre-PAS provides guidelines for a design strategy-definition, toward the parameterization process. Model-PAS provides guidelines, procedures and scripts for building the parametric models. Explore-PAS supports the solutions-assessment based on numeric evaluations and performance simulations, until the identification of a suitable design solution. PAS has been developed based on action research. Several case studies have focused on each step of PAS and on their interrelationships. The relations between the knowledge available in pre-PAS and the challenges of the solution space exploration in explore-PAS have been highlighted. In order to facilitate the explore-PAS phase in case of large solution spaces, the support of genetic algorithms has been investigated and the exiting method ParaGen has been further implemented. Final case studies have focused on the potentials of ParaGen to identify well performing solutions; to extract knowledge during explore-PAS; and to allow interventions of the designer as an alternative to generations driven solely by coded criteria. Both the use of PAS and its recommended future developments are addressed in the thesis

Development of space truss systems in timber

Space trusses are a valuable structural form for architects and structural engineers due mainly to their efficiency in providing large unobstructed areas, associated with faster erection speeds and low maintenance cost. Most space trusses are made of steel and aluminium whilst a few are of timber. Interest is now shifting from the traditional use of timber in plane trusses of relatively short span, to new structural forms for medium to long spans. In adopting such systems in timber for non-traditional roofing applications, the challenge lies in developing structurally sound, visually neat and economically reproducible connectors for 3-dimensional configurations of timber members. The research aimed at developing a new connector for double and triple-layer space grids in timber, intended for medium-span lightweight roofing applications. The origins of the connector date back to 1995, when it was first proposed by Zingoni as the 14FTC-U Timber Space-Truss Connector, and subsequently tested under laboratory conditions over the three years that followed. Unlike connectors for timber space grids proposed by earlier investigators, or the proprietary connector systems that are available for constructions in steel and aluminium, the 14FTC-U connector features a central core of wood in the form of a cuboctahedron or its variants, upon whose faces are attached U-shaped metal brackets that take the timber members. Thus the connector unit is predominantly wood, giving it considerable aesthetic advantages over its all-metal counterparts. While promising, the structural performance of the original connector was not adequate for practical application, hence a programme of further development was embarked upon. As reported in the thesis, the improvements of the connector have culminated in a structurally viable unit that has been successfully employed in a prototype double-layer timber grid

Recent advances and applications of machine learning in metal forming processes

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Recent Advances and Applications of Machine Learning in Metal Forming Processes

Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics

Responsive Architecture

This book is a collection of articles that have been published in the Special Issue “Responsive Architecture” of the MDPI journal Buildings. The eleven articles within cover various areas of sensitive architecture, including the design of packaging structures reacting to supporting components; structural efficiency of bent columns in indigenous houses; roof forms responsive to buildings depending on their resiliently transformed steel shell parts; creative design of building free shapes covered with transformed shells; artistic structural concepts of the architect and civil engineer; digitally designed airport terminal using wind analysis; rationalized shaping of sensitive curvilinear steel construction; interactive stories of responsive architecture; transformed shell roof constructions as the main determinant in the creative shaping of buildings without shapes that are sensitive to man-made and natural environments; thermally sensitive performances of a special shielding envelope on balconies; quantification of generality and adaptability of building layout using the SAGA method; and influence of initial conditions on the simulation of the transient temperature field inside a wall