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Guest Editorial

J. Mech. Des. 2014;136(11):110301-110301-3. doi:10.1115/1.4028572.

In 2011 and 2012, we organized two workshops on 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,1 and led to an edited volume [1]. The first chapter of the volume reports on the discussions at the two workshops. The success of the two workshops also led to this JMD special issue.

Topics: Design , Biomimetics
Commentary by Dr. Valentin Fuster

Research Papers: Survey

J. Mech. Des. 2014;136(11):111101-111101-10. doi:10.1115/1.4028171.

We present the BioM Innovation Database, the first of its kind containing detailed information about global biomimetic activity. We present a quantitative and qualitative analysis of the database to address the following questions: (1) Are products, which are identified as being the result of biologically inspired design (BID), actually BID and to what extent do they use biomimicry terminology in their descriptions by the designers? (2) To what extent do BID products mimic the forms, processes and interactions of biological systems? (3) To what extent do BID products exploit the scale and range of biological systems? (4) What patterns of design practice can we learn from successful BID practitioners?

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111102-111102-18. doi:10.1115/1.4028289.

Bio-inspired design and the broader field of design-by-analogy have been the basis of numerous innovative designs throughout history; yet there remains much to be understood about these practices of design, their underlying cognitive mechanisms, and preferred ways in which to teach and support them. In this paper, we work to unify the broader design-by-analogy research literature with that of the bio-inspired design field, reviewing the current knowledge of designer cognition, the seminal supporting tools and methods for bio-inspired design, and postulating the future of bio-inspired design research from the larger design-by-analogy perspective. We examine seminal methods for supporting bio-inspired design, highlighting the areas well aligned with current findings in design-by-analogy cognition work and noting important areas for future research identified by the investigators responsible for these seminal tools and methods. Supplemental to the visions of these experts in bio-inspired design, we suggest additional projections for the future of the field, posing intriguing research questions to further unify the field of bio-inspired design with its broader resident field of design-by-analogy.

Topics: Design , Biomimetics
Commentary by Dr. Valentin Fuster

Research Papers: Design Informatics

J. Mech. Des. 2014;136(11):111103-111103-12. doi:10.1115/1.4028167.

Bioinspired design is the adaptation of methods, strategies, or principles found in nature to solve engineering problems. One formalized approach to bioinspired solution seeking is the abstraction of the engineering problem into a functional need and then seeking solutions to this function using a keyword type search method on text based biological knowledge. These function keyword search approaches have shown potential for success, but as with many text based search methods, they produce a large number of results, many of little relevance to the problem in question. In this paper, we develop a method to train a computer to identify text passages more likely to suggest a solution to a human designer. The work presented examines the possibility of filtering biological keyword search results by using text mining algorithms to automatically identify which results are likely to be useful to a designer. The text mining algorithms are trained on a pair of surveys administered to human subjects to empirically identify a large number of sentences that are, or are not, helpful for idea generation. We develop and evaluate three text classification algorithms, namely, a Naïve Bayes (NB) classifier, a k nearest neighbors (kNN) classifier, and a support vector machine (SVM) classifier. Of these methods, the NB classifier generally had the best performance. Based on the analysis of 60 word stems, a NB classifier's precision is 0.87, recall is 0.52, and F score is 0.65. We find that word stem features that describe a physical action or process are correlated with helpful sentences. Similarly, we find biological jargon feature words are correlated with unhelpful sentences.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111104-111104-8. doi:10.1115/1.4028278.

More and more approaches for systematic biologically inspired design (BID) aim to scalably leverage large biological databases. To support the scalable systematic BID process, an automated method for mention and focus organism (FO) detection in biological strategy documents is proposed and validated to perform with 85% precision and 81% recall. Furthermore, a number of potential applications of mention and FO detection are presented, and the biodiversity of two corpora is measured.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111105-111105-13. doi:10.1115/1.4028348.

Locating relevant biological analogies is a challenge that lies at the heart of practicing biologically inspired design. Current computer-assisted biologically inspired design tools require human-in-the-loop synthesis of biology knowledge. Either a biology expert must synthesize information into a standard form, or a designer must interpret and assess biological strategies. These approaches limit knowledge breadth and tool usefulness, respectively. The work presented in this paper applies the technique of human computation, a historically successful approach for information retrieval problems where both breadth and accuracy are required, to address a similar problem in biologically inspired design. The broad goals of this work are to distribute the knowledge synthesis step to a large number of nonexpert humans, and to capture that synthesized knowledge in a format that can support analogical reasoning between designed systems and biological systems. To that end, this paper presents a novel human computation game and accompanying information model for collecting computable descriptions of biological strategies, an assessment of the quality of these descriptions gathered from experimental data, and a brief evaluation of the game's entertainment value. Two successive prototypes of the biology phenomenon categorizer (BioP-C); a cooperative, asymmetric, online game; were each deployed in a small engineering graduate class in order to collect assertions about the biological phenomenon of cell division. Through the act of playing, students formed assertions describing key concepts within textual passages. These assertions are assessed for their correctness, and these assessments are used to identify directly measurable correctness indicators. The results show that the number of hints in a game session is negatively correlated with assertion correctness. Further, BioP-C assertions are rated as significantly more correct than randomly generated assertions in both prototype tests, demonstrating the method's potential for gathering accurate information. Tests on these two different BioP-C prototypes produce average assertion correctness assessments of 3.19 and 2.98 on a five-point Likert scale. Filtering assertions on the optimal number of game session hints within each prototype test increases these mean values to 3.64 and 3.36. The median assertion correctness scores are similarly increased from 3.00 and 3.00 in both datasets to 4.08 and 3.50. Players of the game expressed that the fundamental anonymous interactions were enjoyable, but the difficulty of the game can harm the experience. These results indicate that a human computation approach has the potential to solve the problem of low information breadth currently faced by biologically inspired design databases.

Commentary by Dr. Valentin Fuster

Research Papers: Analogy Evaluation

J. Mech. Des. 2014;136(11):111106-111106-12. doi:10.1115/1.4028172.

Searching for biological analogies appropriate for design problems is a core process of biologically inspired design (BID). Through in situ observations of student BIDs, we discovered that student designers struggle with two issues that bookend the problem of search: design problem formulation, which generates the set of conditions to be used for search; and evaluation of the appropriateness of the retrieved analogies, which depends both on problem formulation and the retrieved analogy. We describe a method for problem formulation and analogy evaluation in BID that we call the Four-Box method. We show that the Four-Box method can be rapidly and accurately used by designers for both problem formulation and analogy evaluation, and that designers find the method valuable for the intended tasks.

Topics: Design , Students
Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111107-111107-7. doi:10.1115/1.4028170.

Inherent in biologically inspired design (BID) is the selection of one or more analogs from which one or more strategies are extracted and transferred into the engineering domain. The selection of an analog is a fundamental step in biomimetic process, but locating relevant biological analogies can be challenging. Often, designers may fixate on an analogy or choose an established analogy without rigorous examination of alternatives. This practice is problematic—as basing a new design on an invalid assumption can lead to suboptimal results. This paper makes contribution to evaluation of analogy utility. The contribution is made by combining stochastic multicriteria acceptability analysis (SMAA) with a set of criteria, derived from BID, to assist multidisciplinary decision makers (DMs) in evaluating candidate design analogs. The resulting framework, which we call the biotransferability framework, is being developed to assist multidisciplinary teams to choose, rank, or sort candidate design analogs by assessing biology-to-engineering transfer risk.

Topics: Design , Biology , Risk , Teams , Shells
Commentary by Dr. Valentin Fuster

Research Papers: Empirical Studies

J. Mech. Des. 2014;136(11):111108-111108-11. doi:10.1115/1.4028169.

Understanding the relationships between structures and functions is important for engineering design in general and for biomimetic design specifically. In nature, different structures provide a wide range of functions efficiently and with minimal costs. Based on the analyses of 140 biological systems that are derived from biomimetic sources by a TRIZ based method, we provide a list and examples of structure–function patterns that repeat in biomimetic applications. These patterns are presented through a technical lens and a complete system model, serving as engines or brakes of the biological system, exploiting energy sources or blocking them, respectively. This list of patterns serves as an index of clues that open doors for further investigation of the complexity of these relations. Understanding the mechanisms behind these meta-level patterns is required for a successful biomimetic design process. The list provides both keywords for biological databases search and clues for abstraction of biological texts. The TRIZ based method that has been used for this study can be further used for modeling other biological systems during the abstraction stage of the biomimetic design process. Thus, we offer a bridge between biology and technology and set a foundation for a new biomimetic design method.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111109-111109-13. doi:10.1115/1.4028100.

Design-by-analogy, including bioinspired design, is a powerful tool for innovation. Engineers need better tools to enhance ideation. To support tool creation, an exploratory cross-sectional empirical product study of 70 analogy-inspired products is conducted to report trends and associations among factors in the analogy-inspired design process, giving a general account of real-world practices. Products are randomly sampled from three technology magazines and a bioinspired design database. Seven variables are developed and used to classify each example according to design team composition, analogy mapping approach, analogies used, and design outcomes. Results do not suggest significant differences between problem-driven approaches, which start from a design problem and find solutions in analogous domains, and solution-driven approaches, which begin with knowledge in an analog domain and find design problems to solve. For instance, results suggest that both approaches yield products at about the same frequency, and both yield products with improved performance at statistically indistinguishable rates—thus, neither approach can be concluded to be advantageous over the other for improving product performance at this time. Overall, few associations are detected between design outcome variables and other variables, thus precluding recommendations for how to compose design teams, what approaches to promote, and what number and source of analogies to support in order to achieve the outcomes measured in this study.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111110-111110-11. doi:10.1115/1.4028303.

Fundamental characteristics identified via observation of the inherently sustainable biosphere can inform and guide environmentally benign design and manufacturing (EBDM). In support of this premise, this paper identifies characteristics, extracts biological principles, translates them into guidelines for EBDM, and briefly reports on their application in situations of engineering interest. It outlines and illustrates the use of constant comparative method (CCM) to identify and extract fundamental biosphere characteristics from biology and ecology literature. Then, it translates these biological principles into general guidelines with associated metrics. To illustrate the efficacy of this approach, bio-inspired metrics are used for the purposes of assessing micro/nanoscale self-cleaning surfaces and designing a carpet tile recycling network. These efforts suggest that learning the phenomena responsible for the biosphere's inherent sustainability can yield insight into EBDM.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):111111-111111-10. doi:10.1115/1.4028173.

The natural-language approach to identifying biological analogies exploits the existing format of much biological knowledge, beyond databases created for biomimetic design. However, designers may need to select analogies from search results, during which biases may exist toward: specific words in descriptions of biological phenomena, familiar organisms and scales, and strategies that match preconceived solutions. Therefore, we conducted two experiments to study the effect of abstraction on overcoming these biases and selecting biological phenomena based on analogical similarities. Abstraction in our experiments involved replacing biological nouns with hypernyms. The first experiment asked novice designers to choose between a phenomenon suggesting a highly useful strategy for solving a given problem, and another suggesting a less-useful strategy, but featuring bias elements. The second experiment asked novice designers to evaluate the relevance of two biological phenomena that suggest similarly useful strategies to solve a given problem. Neither experiment demonstrated the anticipated benefits of abstraction. Instead, our abstraction led to: (1) participants associating nonabstracted words to design problems and (2) increased difficulty in understanding descriptions of biological phenomena. We recommend investigating other ways to implement abstraction when developing similar tools or techniques that aim to support biomimetic design.

Topics: Design , Biomimetics
Commentary by Dr. Valentin Fuster

Design Innovation Paper

J. Mech. Des. 2014;136(11):115001-115001-8. doi:10.1115/1.4028094.

This paper describes the AmBot, a centipede-inspired amphibious robot for monitoring the Swan-Canning River, the most important estuary system in Western Australia. The major challenge in developing such a robot lies in that the limited physical size of the robot allows only one type of propulsion system to be used both on land and on water. This is in contrast to large amphibious robots that use wheels or track systems when on land and switch to propellers when on water. The focus of this paper is on the design of a single propulsion method suited to a small-sized amphibious robot. To achieve this, centipede-inspired tracks were engineered with each track-piece consisting of an aluminum base and a polystyrene-block float. It was hypothesized that tracks fixed with floats might be able to provide effective actuation both on land and on water for small-sized robots. When on water, the tracks provide propulsion force and buoyancy so that the waterline is well controlled. When on land, the tracks effectively spread the contact force across multiblocks, leading to effective actuation and low pressure on the sandy terrain, hence protecting the beach ecosystem. Finite element analysis (FEA) was applied to optimize the main components of the AmBot for weight reduction without sacrificing functionality and safety. The AmBot uses an Android-based remote-control system via the Internet, where the accelerometer, gyroscope, global positioning system (GPS), and camera on the Android device provide integrated navigation and monitoring sensing. A prototype was developed to validate the proposed design by conducting empirical studies.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2014;136(11):115002-115002-7. doi:10.1115/1.4028168.

This paper presents performance charts that map the design space of a bio-inspired robotic condylar hinge joint. The joint mimics the design of the human knee joint by copying the condylar surfaces of the femur and tibia and by copying the four-bar motion of the cruciate ligaments. Four aspects of performance are modeled: peak mechanical advantage, RMS (root mean square) mechanical advantage, RMS sliding ratio, and range of movement. The performance of the joint is dependent on the shape of the condylar surfaces and the geometry of the four-bar mechanism. The design space for the condylar hinge joint is large because the four-bar mechanism has a very large number of possible configurations. Also, it is not intuitive what values of design parameters give the best design. Performance graphs are presented that cover over 12,000 different geometries of the four-bar mechanism. The maps are presented on three-dimensional graphs that help designers visualize the limits of performance of the joint and visualize tradeoffs between individual aspects of performance. The maps show that each aspect of performance of the joint is very sensitive to the geometry of the four-bar mechanism. The trends in performance can be understood by analyzing the kinematics of the four-bar mechanism and the shape of the condylar surfaces.

Commentary by Dr. Valentin Fuster

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