Ian R. Grosse - US grants

The project deals with a novel approach to conceptual design with the potential for decreasing the design and manufacturing costs at the same time increasing design productivity. Traditionally, products are designed for functionality without much regard for the manufacturability. By providing manufacturability information up front, it may be possible to develop better designs which would result in decreasing manufacturing costs. Comparative initial designs will be developed using functionality and functionability/manufacturability respectively, as inputs to access the relative cost and effectiveness of these methods to produce products. The problem under consideration will be restricted to the design of injection molded structural parts. The approach if successful, would provide the road to concurrent product and process design.

Residual stresses are the main cause of unwanted warpage observed in injection molded parts. The objective of this research is to develop new technology for eliminating flow induced birefringence and minimizing thermally induced stresses due to cooling. This objective will be accomplished by rapidly heating the mold surface so that the melt can fill the cavity isothermally and yet be processed within the normal injection molding cycle time. The outcome of this research could eliminate the flow induced stresses in injection molded parts. The inverse design optimization technique is very promising technique to obtain an optimally prescribed temporal profile of the mold surface temperature and provide better knowledge about the residual stress. This project will greatly enhance applications in molding high-precision parts requiring absolute dimensional stability. The results of these studies are expected to ultimately lead to the development of an innovative cost-effective method of producing injection molded parts.

This grant provides funding for the development of a trade-off based robust modeling and design methodology for identification of statistically optimal product specifications. This research will exploit concepts from utility theory into a robust design paradigm to quantitatively incorporate qualitative knowledge and preferences of different attributes without loss of generality and accuracy. Statistical exploration based design of experiment techniques will be developed to explore and generate system behavioral information, and to identify optimal product specifications from this quantitative representation of attribute data. By incorporating explicit representation of higher level modeling and design knowledge in the design process, an interactive design system will be developed to enable designers make intelligent decisions during the design process. Industry-driven design problems will be used as case studies to test and evaluate the proposed methodology. If successful, this research will result in a unified methodology that offers a rigorous treatment of design process from an overall design perspective under conditions of uncertainty in data. The primary goal of this research involves the determination of a trade-off based decision model formulation for direct and simultaneous treatment of multiple objectives and constraints in the design process, and its integration with a statistical exploration based robust optimal design generation strategy. This research could lead to a better understanding of the engineering modeling process, and advance the state of knowledge by which the inherent complexities arising from representing physical design problems using idealized computer-based abstractions can be addressed. Results of this research will also contribute towards the identification of a consistent body of synergistic, integrated engineering design methods based on design of experiments, utility theory, computer-based simulation models, finite element methods, and design optimization principles.

Visualization and spatial reasoning are integral components of intelligent systems. They form the basis for understanding a wide variety of topics across science, mathematics and engineering, including molecular structures, topologies, motion and forces, and manufacturing processes. Historically, many students, especially female students, have had difficulty acquiring visualization and spatial reasoning skills, creating potential barriers to advancement in science, mathematics and engineering. Within engineering, faculty have found it both challenging and time consuming to teach topics that require strong visualization and spatial reasoning skills, topics such as product design, manufacturing, and engineering modeling and analysis. Similarly, engineering students have found these topics unmotivating and difficult to comprehend. With the advent of sophisticated computer graphics and animation, one might expect that the need for human visualization skills has been eliminated. But this is not the case. Computers cannot replace the need for these skills in science and engineering just as calculators have not replaced the need for quantitative skills. Thus this project has three goals: l) to advance our understanding of human visualization and spatial reasoning; 2) to use this knowledge to develop computer-based visualization instruction; and 3) to incorporate this instruction into intelligent multimedia tutors in ways that maximize their effectiveness for a broad mix of students while minimizing the development time and cost for the faculty involved. The achievement of such goals has required that we put together a team of researchers with backgrounds in psychology, education, engineering and computer science.

Although visualization and spatial reasoning are fundamental cognitive skills, the cognitive processes that govern them are poorly understood. Thus, as our first goal, we will undertake during year l a series of experiments in our Eye Movement Laboratories designed to test alternative theories of how individuals represent mentally and reason spatially about 3-D objects and their transformations. We will use the detailed eye movement data as a window on the underlying cognitive processes. We have made similar use of such data in reading, visual search and scene perception (Rayner, l992, l998; Rayner & Pollatsek, l992). We expect these data to reveal large, stable differences among individuals, not only between low and high spatial ability participants, but also within groups of participants of similar spatial abilities.

Visualization and spatial reasoning skills are critical to the understanding of many concepts within science and engineering. Yet, we have little understanding of how we can best teach these skills. Thus, as our second goal, we will develop during year 2 computer-based visualization skills instruction modules based on what we have learned during the first year about the problems that individuals have and the strategies that work successfully, modules that will take advantage of current advances in instructional theories and technologies. Having developed the modules, we will then conduct a series of experiments in the second year designed to test theoretically motivated methods for delivering visualization instruction that improve the content of the instruction delivered to high and low spatial ability learners, optimize the mix of part- and whole-task training, and maximize the number of individuals that develop expertise.

The University of Pittsburgh and the University of Massachusetts at Amherst have joined to establish an Industry/University Cooperative Research Center (I/UCRC) for e-Design and Realization of Engineered Products and Systems. The Center will serve as a center of excellence in IT enabled design and realization of discrete manufactured products by envisioning that information is the lifeblood of an enterprise and collaboration is the hallmark that seamlessly integrated design, development, testing, manufacturing, and servicing of products around the world.

Biting Style and the Biomechanics of Feeding in Mammals
Elizabeth R. Dumont (PI), Ian R. Grosse (Co-PI)
University of Massachusetts, Amherst

The evolutionary history of mammals is largely a story about exploiting an ever broader array of food resources. While the first mammals were insect-eaters, modern mammals specialize in diets ranging from insects to fruits, foliage, meat, and plankton. This diversity in diet is reflected in the shape of the skull - the primary 'tool' that mammals use to bite and chew food. Importantly, however, the underlying mechanism driving the evolution of this diversity is unknown. This study explores the importance of the biomechanical link between the forces generated during biting and the anatomy of mammal skulls that safely and optimally bear and disperse these forces. Further, this study investigates the role of this relationship in the evolution of diversity in skull shape.
Previous analyses of mammalian feeding have taken one of two approaches, each of which has inherent limitations. Broad comparative studies document correlations between skull shape and diet, but fall short of testing the causal mechanisms underlying the correlations. On the other hand, detailed experimental studies document how bones and muscles behave during feeding, but the experimental conditions are often far from natural. This study will be the first to combine data on biting behavior and bite force gathered in the field with biomechanical experiments carried out in the laboratory.
The first aim is to investigate how different biting styles apply loads to the skull and how those loads are dispersed. Causal links between routine biting behaviors and morphology will be identified by comparing the loading regimes imposed by different biting styles within species. The second aim is to address two other unresolved issues regarding feeding in mammals: the extent to which skull shape is limited by other sensory systems (in this case, vision), and the strength of the facial skeleton relative to forces generated during feeding. Answers to these issues may explain why some lineages of mammals exhibit a wider variety of skull shapes than do others.
Initially, the forces generated by biting will be measured and the feeding behavior of mammals will be documented in the field. Next, the mechanical implications of these behaviors will be investigated in the laboratory using finite element (FE) modeling and analysis, a physics-based numerical technique widely used by engineers to assess the mechanical behavior of physical systems. FE analysis (FEA) provides a truly novel perspective on form-function relationships, but is not yet accessible to most biologists. An objective is to make FEA more accessible by accomplishing two specific methodological aims: 1) determine the extent to which FE models of mammal skulls can be simplified and still yield sufficiently accurate results, and 2) develop protocols for efficiently translating CT-scans into three dimensional FE models. These results will be communicated to the biology community through peer-reviewed scientific publications, presentations, and workshops.
This collaboration between a functional anatomist and a mechanical engineer offers an excellent opportunity to train graduate students and to expose undergraduates to collaborative, interdisciplinary research in biomechanics, comparative anatomy, and mechanical engineering. Graduate Research Assistants will conduct their own original research, and help the PIs to mentor 4-6 undergraduate research projects. These projects will serve as a springboard to graduate studies in biology and/or engineering.

Understanding the forces that shaped the appearance and development of modern humans has been a leading goal of biological anthropology for decades. As technology has improved, our capability to investigate key questions about the factors affecting the shape of our anatomy have advanced significantly. Here, an interdisciplinary team of anthropologists and engineers will use engineering and experimental methods to examine how the shape of the skull has evolved in order to adapt to the forces associated with feeding on different types of food items. Specifically, the researchers will take a highly interdisciplinary approach to examining whether the skulls of these early humans were well designed to crack open and chew such hard, brittle objects. Dietary adaptations are thought to have been critical factors influencing the course of early human evolution, so this research project will provide valuable insights into the functional anatomy, diet, ecology and behavior of the earliest human ancestors.

With respect to intellectual merit, this project will: (a) examine the functional and evolutionary relationships between diet and skull form, (b) test a leading hypothesis explaining the evolution of the earliest humans, (c) collect and integrate multiple types of raw data critical to an understanding of feeding biomechanics, (d) develop methods for the rapid construction of engineering models that can be applied to research questions in a wide range of disciplines, (e) integrate ecological, comparative, experimental, and engineering techniques for the investigation of evolutionary questions, and (f) rapidly disseminate data, models and findings to the scientific community.

With respect to broader impacts, this study will: (a) promote interdisciplinarity, diversity and internationalism in science, (b) collect data about skull biomechanics that are relevant to dentistry and craniofacial medicine, (c) support the research of three junior investigators each in the first year of their academic appointments, (d) support female graduate students at several universities, (e) provide support to undergraduates at a university whose student body has a high proportion of minorities, (f) provide training for international students in developing nations (Brazil, Suriname), which will ultimately support the development of scientific infrastructure and institutions in those countries, (g) provide content to an exhibit focusing on human biology and evolution at the Georgia Children?s Museum, (h) using engineering models, limit the need for, or at least increase the analytical power of, future experimental studies requiring the use of live animals, (i) generate data relevant to conservation efforts by documenting the relationship between ecology and adaptation in certain primates, (j) strengthen collaborations between anthropologists and engineers in ten universities and two countries, (k) heighten awareness in the engineering community about how their methods are applicable to evolutionary questions.

The University of Massachusetts Amherst is awarded a grant to develop a shared digital resource collection of finite element models of biological systems. Finite element analysis (FEA) is a computer-based technique for predicting the physical behavior of engineered products based on fundamental principles of mechanics. FEA has revolutionized engineering by allowing the design and optimization of high quality, complex products to occur completely within a digital environment. Now biologists are beginning to use FEA to understand the biomechanical behavior of biological organs, tissues and even cells. FEA has the ability to transform the way that biologists approach problems in areas ranging from functional morphology to paleobiology, developmental biology and cellular mechanics. In addition to finite element models, this resource collection will include an integrated set of web-enabled ontologies for sharing finite element modeling metadata, knowledge and mechanical property values of biological materials, interactive software tools for visualizing FEA models and results, FEA utilities supporting the development of biological finite element models, and a threaded discussion. On a broader scale, this project will capitalize on the visual appeal of FEA to inform the public's perception and understanding of the fundamental integration of biological and engineering sciences. This will be accomplished by developing fresh and exciting educational resources for use in the K-12 classroom and by contributing to college-level courses that use computational tools to teach abstract biological concepts.