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Design for Additive Manufacturing: A Method to Explore Unexplored Regions of the Design Space
Additive Manufacturing (AM) technologies enable the fabrication of parts and devices that
are geometrically complex, have graded material compositions, and can be customized. To take
advantage of these capabilities, it is important to assist designers in exploring unexplored regions
of design spaces. We present a Design for Additive Manufacturing (DFAM) method that
encompasses conceptual design, process selection, later design stages, and design for
manufacturing. The method is based on the process-structure-property-behavior model that is
common in the materials design literature. A prototype CAD system is presented that embodies
the method. Manufacturable ELements (MELs) are proposed as an intermediate representation
for supporting the manufacturing related aspects of the method. Examples of cellular materials
are used to illustrate the DFAM method.Mechanical Engineerin
Representing Concepts by Weighted Formulas
A concept is traditionally defined via the necessary and sufficient conditions
that clearly determine its extension. By contrast, cognitive views of concepts
intend to account for empirical data that show that categorisation under a concept
presents typicality effects and a certain degree of indeterminacy. We propose a formal
language to compactly represent concepts by leveraging on weighted logical
formulas. In this way, we can model the possible synergies among the qualities that
are relevant for categorising an object under a concept. We show that our proposal
can account for a number of views of concepts such as the prototype theory and the
exemplar theory. Moreover, we show how the proposed model can overcome some
limitations of cognitive views
Measuring Relations Between Concepts In Conceptual Spaces
The highly influential framework of conceptual spaces provides a geometric
way of representing knowledge. Instances are represented by points in a
high-dimensional space and concepts are represented by regions in this space.
Our recent mathematical formalization of this framework is capable of
representing correlations between different domains in a geometric way. In this
paper, we extend our formalization by providing quantitative mathematical
definitions for the notions of concept size, subsethood, implication,
similarity, and betweenness. This considerably increases the representational
power of our formalization by introducing measurable ways of describing
relations between concepts.Comment: Accepted at SGAI 2017 (http://www.bcs-sgai.org/ai2017/). The final
publication is available at Springer via
https://doi.org/10.1007/978-3-319-71078-5_7. arXiv admin note: substantial
text overlap with arXiv:1707.05165, arXiv:1706.0636
Social Sustainability: A design research approach to sustainable development
While issues such as clean production and energy efficiency are still central in sustainable development discourse, attention is increasingly on patterns of consumption at multiple levels in society. This opens new opportunities and responsibilities for design research, as we shift from a focus on product lifecycles to people’s lifestyles. It also requires further understanding the ‘social sustainability’ aspects of the environment and development, including the complexity of problematics characterized by uncertainties, contradictions and controversies. In response, we propose a programmatic approach, in which a tentative assemblage of theoretical and experimental strategies frame a common ground for a collaborative and practice-led inquiry. We present a design research program based on two propositions: socio-cultural practices are the basic unit for design, and; transitions, and transition management, are the basic points of design intervention. Rather than affirming the status quo or the prevailing discourse, we argue for design research as a ‘critical practice’, in which cultural diversity, non-humans and multiple futures are considered
Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...
There are indications that the current generation of simulation models in practical,
operational uses has reached the limits of its usefulness under existing specifications.
The relative stasis in operational urban modeling contrasts with simulation efforts in
other disciplines, where techniques, theories, and ideas drawn from computation and
complexity studies are revitalizing the ways in which we conceptualize, understand,
and model real-world phenomena. Many of these concepts and methodologies are
applicable to operational urban systems simulation. Indeed, in many cases, ideas from
computation and complexity studies—often clustered under the collective term of
geocomputation, as they apply to geography—are ideally suited to the simulation of
urban dynamics. However, there exist several obstructions to their successful use in
operational urban geographic simulation, particularly as regards the capacity of these
methodologies to handle top-down dynamics in urban systems.
This paper presents a framework for developing a hybrid model for urban geographic
simulation and discusses some of the imposing barriers against innovation in this
field. The framework infuses approaches derived from geocomputation and
complexity with standard techniques that have been tried and tested in operational
land-use and transport simulation. Macro-scale dynamics that operate from the topdown
are handled by traditional land-use and transport models, while micro-scale
dynamics that work from the bottom-up are delegated to agent-based models and
cellular automata. The two methodologies are fused in a modular fashion using a
system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of
residential location has been developed with a view to hybridization. The model
mixes cellular automata and multi-agent approaches and is formulated so as to
interface with meso-models at a higher scale
Understanding Predication in Conceptual Spaces
We argue that a cognitive semantics has to take into account the possibly
partial information that a cognitive agent has of the world. After discussing
Gärdenfors's view of objects in conceptual spaces, we offer a number of viable
treatments of partiality of information and we formalize them by means of alternative
predicative logics. Our analysis shows that understanding the nature of simple
predicative sentences is crucial for a cognitive semantics
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