Fostering Diverse Analogical Transfer in Bio-Inspired Design

Author(s):  
Jacquelyn K. S. Nagel ◽  
Linda Schmidt ◽  
Werner Born

Nature is a powerful resource for engineering designers. The natural world provides numerous cases for analogy and inspiration in engineering design. Transferring the valuable knowledge and inspiration gained from the biology domain to the engineering domain during concept generation is a somewhat disorganized process and relies heavily on the designers’ insight and background knowledge of many fields to make the necessary leaps between the domains. Furthermore, the novice designer approaching biology for inspiration tends to focus heavily on copying the visual attributes of a biological system to develop a solution that looks like the biological system rather than explore at deeper levels to uncover relationships that lead to the development of true analogies. There are now well-known methods for teaching bioinspired design in engineering and the majority of methods prescribe the use of analogies in order to facilitate knowledge transfer, however, guidance in analogy formulation to foster the creative leaps is missing or ill defined. Thus little is known about how students use biological systems for design inspiration. This paper proposes categories for analogical knowledge transfer in bio-inspired design to foster and characterize diverse analogical knowledge transfer. The proposed analogy categories are used to describe the behavior seen in an engineering class. Results indicate that (1) single biological system provides multiple analogies that result in different engineering inspiration for design; (2) biological information from multiple categories is transferred during concept generation; and (3) non-physical characteristics may inspire more sophisticated engineering inspiration than those based on physical characteristics alone. Overall, the analogy data classification has resulted in a better understanding of analogical knowledge transfer during bio-inspired design and leads to best practices for teaching bio-inspired design to engineering students.

Author(s):  
Jacquelyn K.S. Nagel ◽  
Robert L. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams

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.


Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert B. Stone ◽  
Daniel A. McAdams

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.


Author(s):  
Jacquelyn K. S. Nagel ◽  
Robert L. Nagel ◽  
Marjan Eggermont

This paper presents research on the use of an engineering-to-biology thesaurus in an engineering classroom as an aid to teaching biomimicry. The leap from engineering to biological science has posed a challenge. Engineers often struggle with how to best use the vast amount of biological information available from the natural world around them. Often there is a knowledge gap, and terminology takes different meanings. Generally, the time required to learn and become fluent in biology poses too large a hurdle. The engineering-to-biology thesaurus was designed to allow engineers without advanced biological knowledge to leverage nature’s ingenuity during engineering design. The three key goals of this thesaurus are to (1) lessen the burden when working with knowledge from the biological domain by providing a link between engineering and biological terminology; (2) assist designers with establishing connections between the two domains; and (3) to facilitate biologically-inspired design. In this paper, the results of a pilot study as well as a second study are presented. The pilot study was used to craft instructional materials involving the engineering-to-biology thesaurus. In the second study, sophomore engineering students enrolled in a design course were given a design task to complete using the thesaurus. The task focused on biomimetic concept development for their course project — designing a human-powered vehicle for a person with cerebral palsy. Results of the design task are presented.


2019 ◽  
Vol 6 (1) ◽  
pp. 40-49
Author(s):  
Teresa Paiva

Background: The theoretical background of this article is on the model developed of knowledge transfer between universities and the industry in order to access the best practices and adapt to the study case in question regarding the model of promoting and manage innovation within the universities that best contribute with solution and projects to the business field. Objective: The development of a knowledge transfer model is the main goal of this article, supported in the best practices known and, also, to reflect in the main measurement definitions to evaluate the High Education Institution performance in this area. Methods: The method for this article development is the case study method because it allows the fully understanding of the dynamics present within a single setting, and the subject examined to comprehend what is being done and what the dynamics mean. The case study does not have a data collection method, as it is a research that may rely on multiple sources of evidence and data which should be converged. Results: Since it’s a case study this article present a fully description of the model proposed and implemented for the knowledge transfer process of the institution. Conclusion: Still in a discussion phase, this article presents as conclusions some questions and difficulties that could be pointed out, as well as some good perspectives of performed activity developed.


GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Neil Davies ◽  
John Deck ◽  
Eric C Kansa ◽  
Sarah Whitcher Kansa ◽  
John Kunze ◽  
...  

Abstract Sampling the natural world and built environment underpins much of science, yet systems for managing material samples and associated (meta)data are fragmented across institutional catalogs, practices for identification, and discipline-specific (meta)data standards. The Internet of Samples (iSamples) is a standards-based collaboration to uniquely, consistently, and conveniently identify material samples, record core metadata about them, and link them to other samples, data, and research products. iSamples extends existing resources and best practices in data stewardship to render a cross-domain cyberinfrastructure that enables transdisciplinary research, discovery, and reuse of material samples in 21st century natural science.


Author(s):  
K. Scott Marshall ◽  
Richard Crawford ◽  
Matthew Green ◽  
Daniel Jensen

Recent research has investigated methods based on design-by-analogy meant to enhance concept generation. This paper presents Analogy Seeded Mind-Maps, a new method to prompt generation of analogous solution principles drawn from multiple analogical domains. The method was evaluated in two separate design studies using senior engineering students. The method begins with identifying a primary functional design requirement such as “eject part.” We used this functional requirement “seed” to generate a WordTree of grammatically analogical words for each design team. We randomly selected a set of words from each WordTree list with varying lexical “distances” from the seed word, and used them to populate the first-level nodes of a mind-map, with the functional requirement seed as the central hub. Design team members first used the word list to individually generate solutions and then performed team concept generation using the analogically seeded mind-map. Quantity and uniqueness of the resulting verbal solution principles were evaluated. The solution principles were further analyzed to determine if the lexical “distance” from the seed word had an effect on the evaluated design metrics. The results of this study show Analogy Seeded Mind-Maps to be useful tool in generating analogous solutions for engineering design problems.


Author(s):  
David Wang ◽  
Adam Gomes

Abstract – A flipped classroom model is used to teach a 4th year multi-variable control systems course. This course is a technical elective and is not in the core curriculum. The capstone project is to model and control a nonlinear robot in simulation. The students are interdisciplinary Engineering students (Mechanical, Mechatronics, Computer and Electrical). Building upon accepted best practices for flipped classrooms, several additional enhancements are applied and evaluated. The results of student surveys as well as a comparison of the results of student performance in the capstone project between traditional and flipped lecturing techniques are presented. It is believed that the enhancements that were implemented can aid in future flipped classroom initiatives.  


2019 ◽  
Vol 14 (2) ◽  
pp. 184-206 ◽  
Author(s):  
Michelle C. Howell Smith ◽  
Wayne A. Babchuk ◽  
Jared Stevens ◽  
Amanda L. Garrett ◽  
Sherry C. Wang ◽  
...  

Mixed methods–grounded theory (MM–GT) has emerged as a promising methodology that intersects the value of mixed methods with rigorous qualitative design. However, recent reviews have found that MM–GT empirical studies tend to lack procedural details. The purpose of this article is to apply the “best practices” for conducting MM–GT in a study designed to develop and then test a theoretical model for how undergraduate engineering students develop interest in the engineering PhD. This study contributes to the field of mixed methods research by (a) illustrating best practices for MM–GT, (b) providing an MM–GT scale development example, (c) demonstrating how an MM-GT scale could potentially bypass exploratory factor analysis and proceed directly to confirmatory factor analysis for testing psychometric properties, and showing how a joint display for data collection planning can be used to strengthen integration in an instrument development study.


Author(s):  
Sooyeon Lee ◽  
Daniel A. McAdams ◽  
Elissa Morris

AbstractA function-based keyword search is a concept generation methodology studied in the bioinspired design area that conveys textual biological inspiration for engineering design. Current keyword search methods are inefficient primarily due to the knowledge gap between engineering and biology domains. To improve current keyword search methods, we propose an algorithm that extracts and organizes morphology-based solutions from biological text. WordNet is utilized to discover morphological solutions in biological text. The novel algorithm also adapts latent semantic analysis and the expectation–maximization algorithm to categorize morphological solutions and group biological text. We introduce a novel penalty function that reflects the distance between functions (problems) and morphologies (solutions). The penalty function allows the algorithm to extract morphological solutions directly related to a design problem. We compare the output of the algorithm to manually extracted solutions for validation. A case study is included to exemplify the utility of the developed algorithm. Upon implementation of the algorithm, engineering designers can discover innovative solutions in biological text in a straightforward, efficient manner.


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