The Effect of Functional Modeling on Understanding Complex Biological Systems

2010 ◽  
Author(s):  
Michael Helms ◽  
Swaroop Vattam ◽  
Ashok Goel
Keyword(s):  
Engineering Design ◽  
Biological Systems ◽  
Functional Modeling ◽  
Biologically Inspired ◽  
Engineering Designs ◽  
Functional Representations ◽  
Diagrammatic Representations ◽  
Behavior Function

Biologically inspired engineering design requires understanding of complex biological systems for use as analogues in engineering designs. In this study we seek to understand how functional representations, in particular Structure-Behavior-Function (SBF) models, enable understanding complex biological systems. Results from this study indicate that SBF representations may enable more accurate inferences about biological systems for complex and abstract questions than purely textual, or textual and diagrammatic, representations. They also suggest that no one representation is best for all types of inferences.

Function-based, biologically inspired concept generation

2010 ◽  
Vol 24 (4) ◽  
pp. 521-535 ◽  
Author(s):  
Jacquelyn K.S. Nagel ◽  
Robert L. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Engineering Design ◽  
Biological Systems ◽  
Natural World ◽  
Biological Information ◽  
Biological Knowledge ◽  
Concept Generation ◽  
Biologically Inspired ◽  
Modeling Methodology ◽  
Functional Representation ◽  
Engineering Designs

AbstractThe natural world provides numerous cases for inspiration in engineering design. Biological organisms, phenomena, and strategies, which we refer to as biological systems, provide a rich set of analogies. These systems provide insight into sustainable and adaptable design and offer engineers billions of years of valuable experience, which can be used to inspire engineering innovation. This research presents a general method for functionally representing biological systems through systematic design techniques, leading to the conceptualization of biologically inspired engineering designs. Functional representation and abstraction techniques are used to translate biological systems into an engineering context. The goal is to make the biological information accessible to engineering designers who possess varying levels of biological knowledge but have a common understanding of engineering design. Creative or novel engineering designs may then be discovered through connections made between biology and engineering. To assist with making connections between the two domains concept generation techniques that use biological information, engineering knowledge, and automatic concept generation software are employed. Two concept generation approaches are presented that use a biological model to discover corresponding engineering components that mimic the biological system and use a repository of engineering and biological information to discover which biological components inspire functional solutions to fulfill engineering requirements. Discussion includes general guidelines for modeling biological systems at varying levels of fidelity, advantages, limitations, and applications of this research. The modeling methodology and the first approach for concept generation are illustrated by a continuous example of lichen.

An Engineering-to-Biology Thesaurus for Engineering Design

2010 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams
Keyword(s):  
Engineering Design ◽  
Design Process ◽  
Idea Generation ◽  
Natural World ◽  
Biological Information ◽  
Concept Generation ◽  
Functional Modeling ◽  
University Of Toronto ◽  
Engineering Designs ◽  
Design Activities

Engineering design is considered a creative field that involves many activities with the end goal of a new product that fulfills a purpose. Utilization of systematic methods or tools that aid in the design process is recognized as standard practice in industry and academia. The tools are used for a number of design activities (i.e., idea generation, concept generation, inspiration searches, functional modeling) and can span across engineering disciplines, the sciences (i.e., biology, chemistry) or a non-engineering domain (i.e., medicine), with an overall focus of encouraging creative engineering designs. Engineers, however, have struggled with utilizing the vast amount of biological information available from the natural world around them. Often it is because there is a knowledge gap or terminology is difficult, and the time needed to learn and understand the biology is not feasible. This paper presents an engineering-to-biology thesaurus, which we propose affords engineers, with limited biological background, a tool for leveraging nature’s ingenuity during many steps of the design process. Additionally, the tool could also increase the probability of designing biologically-inspired engineering solutions. Biological terms in the thesaurus are correlated to the engineering domain through pairing with a synonymous function or flow term of the Functional Basis lexicon, which supports functional modeling and abstract representation of any functioning system. The second version of the thesaurus presented in this paper represents an integration of three independent research efforts, which include research from Oregon State University, the University of Toronto, and the Indian Institute of Science, and their industrial partners. The overall approach for term integration and the final results are presented. Applications to the areas of design inspiration, comprehension of biological information, functional modeling, creative design and concept generation are discussed. An example of comprehension and functional modeling are presented.

A state–behavior–function model for functional modeling of multi-state systems

2018 ◽  
Vol 233 (7) ◽  
pp. 2302-2317 ◽  
Author(s):  
Meng Zhao ◽  
Yong Chen ◽  
Linfeng Chen ◽  
Youbai Xie
Keyword(s):  
Functional Analysis ◽  
Engineering Design ◽  
Conceptual Design ◽  
Functional Modeling ◽  
Function Model ◽  
State Behavior ◽  
Proposed Model ◽  
Functional Models ◽  
Behavior Function ◽  
Prototype Software

Since functional modeling can be very useful in conceptual design, it has received considerable attention from engineering design community. However, existing functional models still cannot effectively assist designers in analyzing the functionalities of multi-state systems during conceptual design. As a result, designers often have to manually carry out functionality analysis according to their experiences, which are not only tedious, but also error-prone. Therefore, this paper proposes a state–behavior–function model for functional modeling of multi-state systems, which can provide designers with automated functional analysis support. The approach involves not only a state–behavior–function model for representing components, but also a model for representing the functionalities of multi-state systems. A prototype software is then developed for demonstrating the proposed model, with the functional modeling of a peeler centrifuge as an example to illustrate the proposed functional modeling approach.

scholarly journals A 30-year case study and 15 principles: Implications of an artificial intelligence methodology for functional modeling

2013 ◽  
Vol 27 (3) ◽  
pp. 203-215 ◽  
Author(s):  
Ashok K. Goel
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Design Patterns ◽  
Human Cognition ◽  
Functional Modeling ◽  
The Core ◽  
Functional Representations ◽  
Behavior Function ◽  
Function Models

AbstractResearch on design and analysis of complex systems has led to many functional representations with several meanings of function. This work on conceptual design uses a family of representations called structure–behavior–function (SBF) models. The SBF family ranges from behavior–function models of abstract design patterns to drawing–shape–SBF models that couple SBF models with visuospatial knowledge of technological systems. Development of SBF modeling is an instance of cognitively oriented artificial intelligence research that seeks to understand human cognition and build intelligent agents for addressing complex tasks such as design. This paper first traces the development of SBF modeling as our perspective on design evolved from that of problem solving to that of memory and learning. Next, the development of SBF modeling as a case study is used to abstract some of the core principles of an artificial intelligence methodology for functional modeling. Finally, some implications of the artificial intelligence methodology for different meanings of function are examined.

A Systematic Approach to Biologically-Inspired Engineering Design

2011 ◽  
Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone
Keyword(s):  
Engineering Design ◽  
Systematic Approach ◽  
Biological Information ◽  
Biological Knowledge ◽  
Biologically Inspired ◽  
Design Methodologies ◽  
Functional Representation ◽  
Engineering Designs ◽  
Engineered Systems ◽  
Biologically Inspired Design

To facilitate systematic biologically-inspired design, a design methodology that integrates with function-based design methodologies has been formalized. The goals of this methodology are to go beyond the element of chance, reduce the amount of time and effort required for developing biologically-inspired engineering solutions, and bridge the seemingly immense disconnect between the engineering and biological domains. Using functional representation and abstraction to describe biological systems presents the natural designs in an engineering context and allows designers to make connections between biological and engineered systems. Thus, the biological information is accessible to engineering designers with varying biological knowledge, but a common understanding of engineering design methodologies. Two approaches to validation are presented. One examines current biologically-inspired products either in production or in literature to see if the systematic approach to biologically-inspired design can reproduce the existing designs. The second investigates needs-based design problems that lead to plausible biologically-inspired solutions. This work has demonstrated the feasibility of using systematic design for the discovery of innovative engineering designs without requiring expert-level knowledge, but rather broad knowledge of many fields.

Biologically Inspired Design: A Macrocognitive Account

2010 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael Helms ◽  
Ashok K. Goel
Keyword(s):  
Biological Sciences ◽  
Information Processing ◽  
Engineering Design ◽  
Design Patterns ◽  
Information Processing Model ◽  
Biologically Inspired ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Other Information ◽  
Biologically Inspired Design

Biologically inspired engineering design is an approach to design that espouses the adaptation of functions and mechanisms in biological sciences to solve engineering design problems. We have conducted an in situ study of designers engaged in biologically inspired design. Based on this study we develop here a macrocognitive information-processing model of biologically inspired design. We also compare and contrast the model with other information-processing models of analogical design such as TRIZ, case-based design, and design patterns.

Some Ontological Distinctions of Function Based on the Role Concept

2009 ◽  
Author(s):  
Yoshinobu Kitamura ◽  
Riichiro Mizoguchi
Keyword(s):  
Life Cycle ◽  
Engineering Design ◽  
Product Life Cycle ◽  
Functional Modeling ◽  
Ontological Engineering ◽  
Product Life ◽  
Functional Models ◽  
Role Concept ◽  
Essential Function ◽  
The Relationship

Function is an important aspect of artifacts in engineering design. Although many definitions of function have been proposed in the extensive research mainly in engineering design and philosophy, the relationship among them remains unclear. Aiming at a contribution to this problem, this paper investigates some ontological issues based on the role concept in ontological engineering. We discuss some ontological distinctions of function such as essentiality and actuality and then propose some fundamental kinds of function such as essential function and capacity function. Based on them, we categorize some existing definitions in the literature and clarify the relationship among them. Then, a model of function in a product life-cycle is proposed. It represents the changes of existence of the individuals of each kind of function, which are caused by designing, manufacturing and use. That model enables us to give answers to some ontological questions such as when and where a function exists and what a function depends on. The consideration on these issues provides engineers with some differentiated viewpoints for capturing functions and thus contributes to consistent functional modeling from a specific viewpoint. The clarified relationships among the kinds of function including the existing definitions in the literature will contribute to interoperability among functional models based on the different kinds and/or definitions.

Swarm Robotics

2011 ◽  
pp. 1537-1542 ◽  
Author(s):  
Amanda J.C. Sharkey
Keyword(s):  
Social Insects ◽  
Swarm Robotics ◽  
Biological Systems ◽  
Cooperative Behaviour ◽  
Biologically Inspired ◽  
Central Idea ◽  
Biological Inspiration ◽  
The Individual ◽  
And Control

Swarm Robotics is a biologically inspired approach to the organisation and control of groups of robots. Its biological inspiration is mainly drawn from social insects, but also from herding and flocking phenomena in mammals and fish. The promise of emulating some of the efficient organisational principles of biological swarms is an alluring one. In biological systems such as colonies of ants, sophisticated cooperative behaviour emerges despite the simplicity of the individual members, and the absence of centralised control and explicit directions. Such societies are able to maintain themselves as a collective, and to accomplish coordinated actions such as those required to construct and maintain nests, to find food, and to raise their young. The central idea behind swarm robotics is to find similar ways of coordinating and controlling collections of robots.

A content account of creative analogies in biologically inspired design

2010 ◽  
Vol 24 (4) ◽  
pp. 467-481 ◽  
Author(s):  
Swaroop S. Vattam ◽  
Michael E. Helms ◽  
Ashok K. Goel
Keyword(s):  
Sustainable Development ◽  
Engineering Design ◽  
Ad Hoc ◽  
Extended Period ◽  
Biological Knowledge ◽  
Biologically Inspired ◽  
Cross Domain ◽  
Engineering Problems ◽  
Biologically Inspired Design ◽  
Content Theory

AbstractThe growing movement of biologically inspired design is driven in part by the need for sustainable development and in part by the recognition that nature could be a source of innovation. Biologically inspired design by definition entails cross-domain analogies from biological systems to problems in engineering and other design domains. However, the practice of biologically inspired design at present typically isad hoc, with little systemization of either biological knowledge for the purposes of engineering design or the processes of transferring knowledge of biological designs to engineering problems. In this paper we present an intricate episode of biologically inspired engineering design that unfolded over an extended period of time. We then analyze our observations in terms ofwhy,what,how, andwhenquestions of analogy. This analysis contributes toward a content theory of creative analogies in the context of biologically inspired design.

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