20,970 research outputs found
Break Up Variations: An Annotated Score
Get PDFBreak Up Variations is an annotated score by means of which we consider the document as a break-up from — and with — the thinking of performance. We explore the formal categories of page-based and stage-based scores and documentations of performance, asserting the simultaneity of the document and its performance in their mutual departures, theorising the break-up as a form of relation, not as its absence. As a committee of interdisciplinary researchers and practitioners, we consider annotation in terms of affective and theoretical responses to each other’s subject positions.
Break Up Variations relates to the problems particular to working in groups: the challenges of collaboration, the disagreements and community-led conflict resolutions, the difficulties with acting professionally, and the desires to keep working together, despite it all. We ask the following questions of each other and ourselves: What are the strategies that art, science, politics and theory might offer each other for navigating — possibly circumventing — the demise of relationships? If the working relationship breaks down, could the end of the group be considered a constitutive aspect of that group? We consider these questions to be about institutions as much as they are about interdependence on personal and planetary scales. Riffing on ideas about romantic break-ups, political dissolutions and ecological collapse, Break Up Variations considers the possibility that an end to a dream of symbiotic life is exactly what makes that dream possible and important
Generative feature-based design-by-constraints as a means of integration within the manufacturing industry
No full textThe article examines the development of computer aids within manufacturing industry and proposes an alternative approach to the way we design and the designer's role within manufacturing. A feature-based generative design-by-constraints approach is applied, which requires the designer to specify solutions in terms of manufacturing data, which is captured by means of an interactive simulation of machining processes, in which the constraints of equipment, materials and tools are displayed to the designer. The effect of this approach on the integration of all areas within a manufacturing environment is explored, as is the simultaneous design nature of this approach
The Designers' Workbench: Using Ontologies and Constraints for Configuration.
No full textTypically, complex engineering artifacts are designed by teams who may not all be located in the same building or even city. Additionally, besides having to design a part of an artifact to be consistent with the specification, it must also be consistent with the company's design standards. The Designers' Workbench supports designers by checking that their configurations satisfy both physical and organisational constraints. The system uses an ontology to describe the available elements in a configuration task. Configurations are composed of features, which can be geometric or nongeometric, physical or abstract. Designers can select a class of feature (e.g. Bolt) from the ontology, and add an instance of that class (e.g. a particular bolt) to their configuration. Properties of the instance can express the parameters of the feature (e.g. the size of the bolt), and also describe connections to other features (e.g. what parts the bolt is used to hold together)
Generative Agent-Based Design Computation
No full textAgent-based systems have been widely investigated in simulation and modeling. In this paper, it is proposed that agent-based systems can also be developed as generative systems, in which different aspects of performative design can be defined as separate drivers in a proper computational framework. In this manner constrained generating procedures (CGP’s) are studied to integrate the discrete design processes into one system. Subsequently, this generative agent-based design tool is accompanied with generating and constraining mechanism which are informed by material characteristics and fabrication constraints, bringing to the forefront emergent complexity
Weighted constraints in Generative Linguistics
Get PDFHarmonic Grammar (HG) and Optimality Theory (OT) are closely related formal frameworks for the study of language. In both, the structure of a given language is determined by the relative strengths of a set of constraints. They differ in how these strengths are represented: as numerical weights (HG) or as ranks (OT). Weighted constraints have advantages for the construction of accounts of language learning and other cognitive processes, partly because they allow for the adap-tation of connectionist and statistical models. HG has been little studied in generative linguistics, however, largely due to influential claims that weighted constraints make incorrect predictions about the typology of natural languages, predictions that are not shared by the more popular OT. This paper makes the case that HG is in fact a promising framework for typological research, and reviews and extends the existing arguments for weighted over ranked constraints
Generative design of a jet engine bracket using solidedge
No full textThis thesis investigates the application of generative design techniques in the field of jet engine bracket design using Solid Edge software. The project, especially emphasizes the use of computational methods towards structural optimization, aims to add to the growing environment of the aerospace field by using new design technology.
The investigation starts with an in-depth review of generative design principles and their application inside the Solid Edge software. The study explores into the generation of different design iterations using an iterative approach, considering different kinds of parameters such as material properties, geometric limitations, and performance measurements. The optimization techniques included into Solid Edge are used systematically to repeatedly develop designs, with an emphasis on improving structural integrity, minimizing weight, and optimizing load distribution.
Structural simulations are carried out to evaluate the structural performance of produced designs under 4 of load scenarios, making sure that they meet 3D printing standards and safety requirements. At the same time, an analysis on the aesthetic and practical constraints associated in the generative design process is provided, acknowledging the close connection between imaginative perception and engineering precision.
Following the guidelines set out by academic articles and journals, the thesis compares jet engine brackets that are constructed conventionally with those that are created generatively. Comparative analyses include structural integrity, weight efficiency, and versatility, giving practical insights into the importance of generative design approaches in the aerospace sector and engineering field.
The thesis concludes with views on the potential benefits of generative design for the future of aerospace engineering, emphasizing the importance ofmaterials scientists for material selection, and manufacturing experts. As a result, the thesis emphasizes within the field of study as a thoughtful investigation of generative design applied to the important field of jet engine brackets, giving important details and methods to advance the continuous progress of aerospace and mechanical engineering practices.BSc/BAMechanical Engineerin
Generative Design, Characterization, and Testing for Additive Manufacturing of Lightweight Structures
Get PDFGenerative design has developed over the years through various CAD software’s and has changed the industry in new ways. Generative design has opened a new aspect of engineering that can change industries through design created with artificial intelligence technology. Through generative design, various components and characteristics of materials and objects can be reinvented to make them lighter weight and more cost effective within the industry. Within this thesis, the aspects of Fusion 360, a CAD software, has been reviewed and utilized when creating an I beam. The I beam has ran through various simulations to understand the forces and constraints applied on it to see the force the beam will break at. The safety factor allows for the understanding of when the beam will break and how the force can be withstood with a new design. With the known forces, the beam was placed in the generative design component of the software to redesign the beam based on the given information and requirements. The generative design portion of the software and artificial intelligence created a new object via iterations to be evaluated. Through additive manufacturing the beam was printed with PLA and resin materials. This thesis discusses the processes of 3D printing and testing of the I beam and generative designed I beam. Through testing, the analysis of the displacement, mass, and force of the I beams was evaluated with the Fusion 360 results to see if the requirements was met during the redesign
Job Loss, Credit Constraints and Consumption Growth
Get PDFWe use direct evidence on credit constraints to study their importance for household consumption growth and for welfare. We distentangle the direct effect on consumption growth of a currently binding credit constraints from the indirect effect of a potentially binding credit constraint which generates consumption risk. Our data is focused on job losers. We find that less than 5% of job losers experience a binding credit constraint, but for those that do, they experience significant welfare losses, and consumption growth is 24% higher than for the rest of the population. However, even among those who are currently unconstrained and who are able to borrow if needed, consumption responds to transitory income.Job Loss, Credit Constraints, Consumption
How much can the orientation of G's eigenvectors tell us about genetic constraints?
Get PDFA key goal in evolutionary quantitative genetics is to understand how evolutionary trajectories are constrained by pleiotropic coupling among multiple traits. Because studying pleiotropic constraints directly at the molecular genetic level remains very difficult, several analytical approaches attempt to draw conclusions about constraints by relating the orientation of the eigenvectors of the traits' (co)variance matrix to vectors of multivariate selection. On the basis of explicit models of genetic architecture, I here argue that the value of such approaches is greatly overestimated. The reason is that eigenvector orientation can be highly unstable and lack a biologically meaningful relationship with the underlying traits' genetic architecture. Genetic constraints are more profitably explored through experimental approaches avoiding the mathematical abstraction inherent in eigenanalysis
Shaping Realities: Enhancing 3D Generative AI with Fabrication Constraints
Get PDFGenerative AI tools are becoming more prevalent in 3D modeling, enabling
users to manipulate or create new models with text or images as inputs. This
makes it easier for users to rapidly customize and iterate on their 3D designs
and explore new creative ideas. These methods focus on the aesthetic quality of
the 3D models, refining them to look similar to the prompts provided by the
user. However, when creating 3D models intended for fabrication, designers need
to trade-off the aesthetic qualities of a 3D model with their intended physical
properties. To be functional post-fabrication, 3D models have to satisfy
structural constraints informed by physical principles. Currently, such
requirements are not enforced by generative AI tools. This leads to the
development of aesthetically appealing, but potentially non-functional 3D
geometry, that would be hard to fabricate and use in the real world. This
workshop paper highlights the limitations of generative AI tools in translating
digital creations into the physical world and proposes new augmentations to
generative AI tools for creating physically viable 3D models. We advocate for
the development of tools that manipulate or generate 3D models by considering
not only the aesthetic appearance but also using physical properties as
constraints. This exploration seeks to bridge the gap between digital
creativity and real-world applicability, extending the creative potential of
generative AI into the tangible domain
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