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Enregistrement W4210975483 · doi:10.1115/1.4024746

Biologically Inspired Design

2013· article· en· W4210975483 sur OpenAlexaff

Notice bibliographique

RevueJournal of Mechanical Design · 2013
Typearticle
Langueen
DomaineEngineering
ThématiqueDesign Education and Practice
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésComputer scienceEngineeringComputer graphics (images)

Résumé

récupéré en direct d'OpenAlex

Biologically inspired design is the use of designs found in nature for analogy and inspiration in designing technological systems. Biological systems, processes, and strategies provide insights into sustainable and adaptable design that can inspire technological innovation. Thus, using nature for inspiration and emulating nature is a research field growing in scope, activity, and importance.We recently organized two workshops on “Charting a Course for Computer-Aided Bio-Inspired Design” sponsored by the United States National Science Foundation (NSF). These workshops brought together a few dozen leading researchers in computational methods and tools for biologically inspired design (http://designengineeringlab.org/BID-workshop/NSF_BID_Workshops.html). An edited volume based on the workshops and containing a dozen chapters describing the state of the art is forthcoming. Here, we briefly summarize some of the main findings from the two workshops.Biologically inspired design seeks to exploit biology for several different kinds of design such as sustainable design, creative design, and complex system design. Although these different kinds of design are mutually compatible and consistent—one can have complex systems that are sustainable, for example—the three design types have different emphases and foci. Some of the discussion at the first workshop focused on sustainable design and complex system design.The goal of biologically inspired sustainable design is to use biology as an inspiration for designing technological products that are ecologically sustainable. Although biological systems are not always optimal, they typically use only local and abundant resources, and often are very efficient in the use of resources such as energy and water. Of course, this does not guarantee that biologically inspired designs will be necessarily sustainable, but it promises that they may be more sustainable than equivalent products available in the market today. Consider the following specific cases:The goal of biologically inspired complex systems design is to use the characteristically complex interactions found in nature as a design guide to technological systems that are complex and integrated among their constituent components. Although biologists often welcome complexity, engineers typically attempt to avoid it. Approaching complex system design from a biologist’s perspective, such as using complexity to allow for mechanisms for coping with design failures appears a promising avenue with the following observations:Some of the discussion at the second workshop focused on the development of a potential research program at NSF. Here is one possible design for the program: NSF would invite proposals for research on biologically inspired design that has much potential to solve urgent and critical challenges faced by the United States and the world as a whole, including ecological sustainability, design innovation and complex system design. Proposals must be from suitable multidisciplinary teams (i.e., members might include biologists, cognitive scientists, computer scientists, designers, and engineers), addressing small to medium scale designs (such as household products or automotive systems), have demonstrated computational and educational components, and have a well-formed evaluation plan. Suitable research topics include but are not limited to the following:The proposed research should be extensible, and must be shared in order to promote community building.In summary, it is clear that recent research efforts across the disciplines of biology, computing, design, and engineering have attempted to address the various problems associated with not only developing biologically inspired designs, but also teaching students how to develop biologically inspired designs. It is also evident that there is a need for much additional work on refining the proposed methods and tools as well as developing new methods to address current limitations. We recommend that NSF establish a new crosscutting program in biologically inspired design that seeks to fund transformative research as briefly summarized above. Such a program can support high risk-high reward research that otherwise has no home in NSF.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,034
Score d'incertitude au seuil0,112

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,005
Communication savante0,0050,004
Science ouverte0,0020,003
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,0340,011

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,061
Tête enseignante GPT0,259
Écart entre enseignants0,198 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations27
Publié2013
Routes d'admission1
Résumé présentoui

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