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Engineering Architecture: Advances of a technological practice
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... Due to this, Finite Element (FE) methods are now necessary tools for all engineering design projects. Numerous optimization algorithms are available in the literature, depending on the optimization problem, that can provide a general approach to automate the structural design process [6][7][8][9][10]. Many of them fall into one of two categories: gradient and heuristic methods. ...
The structural performance of any building design is often dependent on the geometrical shape, which affects its behavior and stability. Structural consideration and optimization in the conceptual stage of the design process can lead to better solutions and design exploration. In this paper, a design approach for generating and structurally optimizing the geometrical form in the conceptual design phase is presented. The method is applied to a canopy of an ecological island (waste collection center in Rome, Italy). We demonstrate how parametric structural design can facilitate the decision-maker to generate and analyze the optimal design solutions rapidly in the conceptual stage of the design process. Fully parametric models are created in a Rhinoceros3D® environment and interfaced with in-house built algorithms, and Finite Element simulations are performed in DubalRFEM. An ecological island’s canopy has been completely redesigned with a Genetic Algorithm and a Dynamic Relaxation Algorithm, resulting in a free-form shape-resistant structure. Finally, the shape-optimized canopy meets various requirements (structural, functional, formal) that improve structural efficiency and design collaboration, such as in the role of the architect and engineer in the design process and in the relationship between the designer and design tools.
... The roof structure is described by the means of the third degree NURBS surface (i.e. a rational polynomial continuous function, defined by a set of control points) with a grid of 10x10 control points in a plan projection restricted to the boundary presented in Fig. 4. Fig. 3. Boundary conditions in plan and elevation. Source: [31]. ...
Engineers and architects are now turning to use computational aids in order to analyze and solve complex design problems. Most of these problems can be handled by techniques that exploit Evolutionary Computation (EC). However existing EC techniques are slow [8] and hard to understand, thus disengaging the user. Swarm Intelligence (SI) relies on social interaction, of which humans have a natural understanding, as opposed to the more abstract concept of evolutionary change. The main aim of this research is to introduce a new solver Silvereye, which implements Particle Swarm Optimization (PSO) in the Grasshopper framework, as the algorithm is hypothesized to be fast and intuitive. The second objective is to test if SI is able to solve complex design problems faster than EC-based solvers. Experimental results on a complex, single-objective high-dimensional benchmark problem of roof geometry optimization provide statistically significant evidence of computational inexpensiveness of the introduced tool.
The paper presents an architectural concept and design method that investigates the use of dynamic factors in evolutionary form finding processes. The architectural construct, phenotype, is based on a brick assembly and how this can be organized based upon material properties and environmental aspects selected from the factors used in the Fanger equations to determine perceived comfort. The work finds that the developed method can be applied as performance oriented driver, while at the same time allowing diversity and variation in the architectural design space.
For my final thesis I decided to study the vast potential of surface structures in the field of architecture. I had the idea to create a surface that would not only act as a load bearing roof of a concert hall with a large clear span, but also, this surface was to serve as the main acoustic ceiling in this concert hall. This was the main idea, to have a concrete shell structure not only define the architectural space, but to properly function as a mayor structural and acoustic element in the building. In order to achieve this, important research had to be made on the form this surface was to take. Although the general type of surface was chosen firsthand for architectural reasons (folded concrete shell structure with hyperbolic paraboloid segments), the specific geometry of the shell structure had to be defined by a complex form-finding method. After some preliminary work it became clear that traditional methods of acoustic design and existing acoustic simulation software where insufficient. Special computational acoustic design tools were therefore created inside existing cad software using evolutionary algorithms and acoustic simulation. The final result of the thesis was not only a concert hall complete with the innovative acoustic and structural surface, but also a set of acoustic design tools that can be used in many different projects. This paper reports the process and the methods that gave way to the design of the surface and the tools that created it.
In the paper the application of a GA evolutionary algorithm to the structural optimisation of free-form architectural shell structures, as large concrete roofs, is shown. The attention is focused on the need of different computational tools and on the problems involved in multidisciplinary design, as the communication and information exchange. The procedure herein described can be applied to more general problems, involving not only the structural performance, but even functional and constructive requirements. The proposed implementation of the algorithm is efficient, robust and particularly capable to avoid local minimum convergence.
In this paper a constructional problem related to grid-shells design is approached as an optimisation problem and an evolutionary solution technique is proposed. The construction of glass grid-shells, when only four sides cladding elements are used, requires to check the planarity of each element, it means that the four corner points have to belong to the same plane. This requirement can be satisfied by generating the grid surface in specific ways (Schlaich and Bergermann [2]), but when the design involves truly free form shapes, a procedure of optimisation able to reduce the non planarity of each element can be applied. The proposed one is based on the use of a genetic algorithm and has been applied to a benchmark and to a real case, in order to evaluate the efficiency of the procedure and the goodness of the solution.
In optimization, multiple objectives and constraints cannot be handled independently of the underlying optimizer. Requirements such as continuity and differentiability of the cost surface and yet another conflicting element to the decision process. While "better" solutions should be rated higher than "worse" ones, the resulting cost landscape must also comply with such requirements.
Evolutionary algorithms (EA'S), which have found application in many areas not amenable to optimization by other methods, possess many characteristics desirable in a multiobjective optimizer, most notably at the concerted handling of multiple candidate solutions. However, EA's are essentially unconstrained search techniques which require the assignment of a scalar measure of quality or fitness to such candidate solutions.
After reviewing current evolutionary approaches to multiobjective constrained optimization, the paper proposes that fitness assignment be interpreted as, or at least related to, a multicriterion decision process. A suitable decision making framework based on goals and priorities is subsequently formulated in terms of a relational operator, characterized and shown to encompass a number of simpler decision strategies. Finally, the ranking of an arbitrary number of candidates is considered. The effect of preference changes on the cost surface seen by an EA is illustrated graphically for a simple problem. The paper concludes with the formulation of a multiobjective genetic algorithm based on the proposed decision strategy. Niche formation techniques are used to promote diversity among preferable candidates and progressive articulation of preferences is shown to be possible as long as the genetic algorithm can recover from abrupt changes in the cost landscape.
Evolutionary Structural Optimization (ESO) method is one of the powerful and promising techniques for pursuing the optimal structural form. Although it is easy to carry out the calculation of ESO, there have been remained some weak points in its evolutionary process, by which inefficiency of calculation is caused or unreasonable solutions are generated. The authors have already proposed a new method through the usage of the contour lines, which is named Extended ESO method, in order to remove such defects of the original ESO as well as to enable the structures to not only be scraped off but also grow up toward the final optimal structures. In this paper, extension for 3-dimensional structures of the Extended ESO method is proposed and the effectiveness of the proposed scheme is shown through some numerical examples as well as the application to the actual structural design project.